Abstracts

Most educational institutes have initiated various efforts to reduce energy consumption. In the case of big universities, the reduction of energy consumption is especially difficult because of the complexity of university systems.To tackle this problem, we constructed a visualization platform encouraging people to reduce electricity consumption. We implemented a website called the “energy consumption visualization portal site” as a pull-based visual presentation and developed a desktop gadget and a digital signage system as push-based visual presentations. This article describes the implementation and evaluation of the pull- and push-based visual presentations. In the evaluation, we focused on increasing the user’s motivation. We distributed questionnaires to survey the relationships between the user’s motivation and the presentations used. One of the results we obtained is that push-based methods were effective to increase the user’s motivation to save electricity, and digital signage was the best of the tested methods.

The concept of microgeneration can be extended into homes which use a variety of techniques to generate energy using green concepts. This paper examines one such experimental house that uses active and passive systems to generate energy for the home while putting surpluses back onto the grid. This house is a proving ground of building and energy concepts with a goal of demonstrating feasibilities in multiple green technologies.

Researchers at the Texas Sustainable Energy Research Institute are enhancing the capabilities of building performance simulation (BPS) tools by collecting real-time high fidelity energy data to validate and verify simulation capabilities used to predict building energy consumption and to better understand the impacts of building occupants on energy performance. Two case studies, a residential new construction project and an existing commercial building study, have adopted a systems approach toward evaluating the building sector, looking at the relationship between residential buildings, commercial buildings, their occupants, utilities, and local demographics. This paper assesses the important role of efficiency, conservation, and demand response capabilities in reducing energy consumption without requiring significant occupant sacrifices. The Institute is coupling simulation science (as well as its assumptions and processes), with technology that allows researchers to capture real-time energy information and identify more space-specific behavioral pattern assumptions which create an opportunity for better refinement of continuously-responsive building systems.

Energy remains one of the most important factors in both the global economy and ecology. Currently, there is a strong focus on the development of renewable energies. This is a laudable goal; however, every second of every day sees 10,000 gallons of petroleum burned in the United States. Combustion is now and will remain a predominant share of the world’s energy usage; the efficiency of combustion engines must be maximized. The cornerstone of engine efficiency lies in the fuel spray; more information on the fluid dynamics associated with spray breakup and atomization is certain to lead to increased combustion efficiency. This paper will discuss one of the most promising emerging technologies in fuel spray imaging — an ultrafast laser based technique known as ballistic imaging. Ballistic imaging, initially developed in the medical field, has provided the first high resolution images of both the liquid core and the primary breakup processes of a variety of atomizing fuel sprays. Transient ballistic imaging diagnostics have been used to reveal details of the primary breakup process in a LOX injector, a turbulent water jet, a water jet in cross-flow, a transient diesel fuel spray, a rocket fuel injector, and an aerated spray. This leading edge research project is currently underway at Chalmers University of Technology in Gothenberg, Sweden as well as a variety of research institutions and universities worldwide. The results provided by this relatively new imaging technique have been used by combustion engine modelers in their quest to design more efficient and cleaner combustion engines.

This paper presents a real-time algorithm to predict the energy consumption of the heating, ventilation, and air conditioning (HVAC) system at home. The autoregressive model with exogenous inputs (ARX model) is used to identify the house thermal model. The ARX model, with the thermostat controller, is simulated to obtain the future state of the HVAC system with the knowledge of the weather forecast data obtained from a weather server. The utility bill for the HVAC system can be estimated if a real-time price model is provided, thereafter. The proposed method is validated by experimentation in a particular home using GE Nucleus energy management system for data aggregation and algorithm implementation. The experimental results show that the energy prediction error is around 15% in both heating and cooling mode of the HVAC system.

Currently, biodiesel (BD) is produced mainly from various vegetable oils in South Korea. Our previous study has investigated high-quality BD synthesis from Pork lard. Therefore, the animal fats have a great potential to increase the BD production scale. This investigation presents the experimental results of Pork lard BD blends with commercial diesel fuel effects on the indirect injection (IDI) diesel engine and aimed at evaluating the overall performances, combustion characteristics and exhaust emissions. Engine torque and power were reduced slightly at high engine speed, while the brake specific fuel consumption was increased for lard BD blends. The lower calorific value of lard BD results in increased energy consumption but the engine thermal efficiency is not affected significantly. The in-cylinder pressure and heat release curves for lard BD blends were similar to those of diesel fuel. Moreover, the ignition delay was shorter for the lard BD blends. It was observed that the smoke and carbon oxides remarkably decreased. On the whole, the lard BD blends results in more complete and cleaner combustion than commercial diesel fuel in an IDI diesel engine.

Steam reforming of product gas produced by biomass gasification is regarded as a major route for the industrial production of hydrogen and synthesis gas, which can subsequently be converted to numerous valuable basic chemicals. This paper reports investigations of steam methane reforming process by means of mathematical modeling. A packed bed reactor filled with nickel catalyst is simulated numerically by state of the art Finite Element Method software (COMSOL Multiphysics). The process is highly endothermic and electrical heating is used to keep the outer wall of the reactor at constant temperature in order to provide heat into the reactor, therefore, reactor tube is exposed to significant axial and radial temperature gradients .The steady state pseudo-heterogeneous model represents the heat and mass transfer in the reactor tube. The obtained results are satisfactory when compared to the literature, giving similar profiles but slightly different temperature values and concentration profiles.

How to efficiently integrate and exploit flexible demand and distributed renewable generation in the Smart Grid is a question of high interest reflecting the societal need for energy efficiency and urge to lower carbon emissions. This question also provides strong motivation for honing the concept of a microgrid as an atomic cell of future active distribution networks as well as the smallest market entity. The microgrid locally balances demand and supply in a far more efficient way than in current practice. Complementary, the microgrid market offers basis for creating energy prices that stimulate investments in renewable generation, storage, and demand response. As similar to the current energy markets, the microgrid market can accommodate trading of the short term and the long term energy products, balancing energy and capacity. The foundation of trading is forecasting and optimization, and consequently each party involved in microgrid trading must be able to forecast its demand, supply, or flexibility. But how precise these forecasts must be? This paper focuses on the impact of forecasting errors on the economic effects of trading and balancing in the microgrid: while lower forecasting accuracy induces greater differences between forecasted and real consumption/generation, and hence higher need for balancing energy, higher forecasting precision may increase the cost of the system. We present results of an agent-based simulation study of a microgrid with a simple market integrating local suppliers and customers with flexible loads, renewable energy sources and storage capacity. These actors buy energy, sell demand reduction, and sell energy produced by their wind turbines and solar panels, or stored in their battery. The Microgrid System Operator (MSO) operates the local market and balances demand and supply. In our model MSO operates a dedicated storage capacity and interacts with the global grid markets to provide balancing energy and do clearing and settlement for the balancing energy costs. In an agent-based simulation study we implemented a model in which actors engage in trading, in tariff contracts, and in clearing and settlement relationships, and we compare the economic results of trading and balancing for different values of forecasting errors in scenarios characterized with different supply levels in the microgrid.

The smart grid introduces significant challenges for the reliability and economics of traditional power grids. Dynamic pricing is an important mechanism for improving effectiveness of the smart grid. Presently, the smart grid pricing research mainly focuses on the interactions between a single energy provider and multiple energy consumers. However, in a deregulated energy market, it is possible that there exist multiple energy suppliers who compete with each other. In this paper, we examine a microgrid consisting of multiple generators. We propose a generic pricing mechanism based on the QoS of the power supply inside the microgrid. In particular, a noncooperative game is formulated to capture the competitive market and to study the energy supply strategies of multiple energy suppliers. For solving the game, a distributed algorithm is proposed using which the energy suppliers can reach a Nash equilibrium point. Furthermore, we show that due to the inefficiency of distributed decisions, microgrids may cooperate and form a coalition. In this case, microgrids cooperate by jointly coordinating their energy supply in order to increase their aggregated utilities. As a result, their individual payoffs may increase substantially. Cooperative game theory is used to study the coalition formation process and the profit allocation inside the coalition. Numerical examples are presented to show the performance of the proposed pricing scheme.

The use of energy storage in conjunction with renewable energy sources such as wind and solar is receiving more attention to help mitigate the effects of the intermittent nature of these sources. One wishes to maximize the probability that there will be enough energy available to meet the residential load demand while minimizing the cost of both the renewable energy sources as well as the energy storage device(s). In this paper, the energy storage required to ensure high reliability of supply to an off-grid residence in the Midwest is determined iteratively based on the amount of installed solar power. A Markov is employed consisting of 288 state transition matrices to generate synthetic solar data for analysis. model By accounting for the costs of both the photovoltaic system and the energy required energy storage, an optimal cost solution is provided.

Self-funded energy efficiency programs have largely ignored the rural, low-income and non-profit segments of our population because of financial, accessibility, or other issues. With the most recent economic downturn, this market segment is growing, and market-based energy efficiency programs designed to address its needs are absent. The iCAST Energy Efficiency Program “ResourceSmart” is a turn-key plan that addresses the specific needs of this customer group and implements a program that achieves energy savings, creates jobs locally, improves the comfort and safety of the home or business, and can be scaled to meet the needs of a diverse range of communities small and large. In our sustainable, self-funded approach, energy conservation measures (ECMs) are prioritized by return on investment, and financing options are established so that monthly energy savings exceed loan payments. The program begins with a whole-building energy audit (that also covers water conservation and indoor air quality), and once appropriate measures are determined, iCAST hires the contractors, oversees the scope of work, and performs the final inspection. This market-based approach not only addresses an underserved market, but achieves considerable energy savings, job creation, and carbon footprint and pollution reduction where it otherwise might not occur.

In times of generation shortage relative to load demand, the only available way to ensure system stability is to shed load equivalent to the amount that demand exceeds supply. This load shedding procedure usually takes place in a series of 3 – 5 steps where each step has a quantity of load assigned to it. The process is carried out with each subsequent steps adding to the total load disconnected from supply until the amount of load/demand is less than the present supply capacity. Presently there is no method that gauges the percentage of load to be disconnected, then equitably allocates this loss of supply to the non-critical load on multiple feeders. We investigate using the game theory method of bargaining games for resources, within the setting where available supply needs to be allocated to the loading on feeders appropriately to their respective level of demand.

Load forecasting at the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process, or suitable reserves. An understanding of the load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves that are necessary to compensate the errors that occur. In this work we perform a statistical analysis of the day-ahead (and two day-ahead) load forecasting errors observed in two different independent system operators for a one year period. Comparisons are made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identifies time periods when the load is more likely to under- or over-forecast.

Unscheduled power flows cause inequitable compensation of transmission infrastructure usage as well as a less reliable system. Accordingly, an unspecified amount of dollars in the United States are lost annually to unscheduled flows. A comprehensive survey of the literature on methods used to handle unscheduled flow in the market and the system is provided in this paper. Advantages and disadvantages are discussed with specific regard to the system and operating considerations within the Western Interconnection of the United States bulk electric system. Operating challenges within the Western Interconnection are briefly introduced. An action plan for including any of the proposed unscheduled flow mitigation mechanisms within the Western Interconnection is recommended, which includes guidance from a regulatory agency, infrastructure enhancements, and modeling efforts to determine associated impacts of the most promising methods prior to implementation.

In recent years, energy consumption has become a major issue in terms of cost, infrastructure requirements and emissions. In deregulated markets electricity prices, renewable energy contribution and emissions can vary substantially from hour to hour. These temporal variations introduce significant opportunities for any flexible energy consumer. A granular analysis of the Irish electricity market for the first four months of 2012 showed the large variations characteristic of deregulated electricity markets – the spot price spiked up to 985% of the average price, marginal emissions varied by up to 55% and renewable energy generation had a standard deviation of 11.78%. Strong correlations are observed between renewable generation and market prices – market prices reduced significantly with increased wind generation. Utilising intelligence and awareness of these market and grid fluctuations allows the delivery of products/services at much more favorable conditions – reducing costs, reducing emissions and increasing renewable energy content are all possible. The aim of the research described in this paper is the development of algorithms which take advantage of variability observed in electricity markets to reduce the costs and emissions of services, and provide a way for service operators to insulate themselves against turbulent market conditions.

Due to the widely use of public networks in smart grid, the security risks are increasing. Therefore, cyber security becomes an important and urgent issue in the smart grid systems on the public networks. In this paper, the business functions and system architecture of the smart grid systems on public networks are analyzed, and the cyber security risks in main stations, communication networks and field devices are studied. Based on the analysis, technological requirements of information security for the smart grid systems on the public networks are proposed, including access control, integrity, confidentiality and other controls for communication and field devices. To meet the security requirements, the paper proposes a practical and reliable protection framework and some certification suggestions for typical systems.

This paper focuses on Radio-On-Demand (ROD) wireless LANs (WLANs) where the operating mode of Access Points (APs) is transited from ‘active’ to ‘sleep’ in case of no traffic to reduce wasteful power consumption. A sleep control strategy, which automatically decides the timing to transit AP’s mode, plays an important role in ROD WLANs. The frequent mode transitions are likely to increase waiting time or delay perceived by the user who attempts to communicate through ROD APs. In this paper, we investigate the tradeoff between power-saving effect and delay-reduction of an automatic sleep control by using trace data of WLAN traffic obtained in a real-world office environment. We also propose a cooperative sleep control method for large-scale WLANs, where the mode of APs is decided based on the deployment topology of APs and STAs. Numerical evaluation results show that, in a large-scale WLAN, significant amount of power can be saved by jointly employing the automatic and cooperative sleep control methods.

This paper explores the capability of the reduced model artificial neural networks (ANNs)-based power system state estimator to accurately identify single and multiple bad data. This state estimator uses fewer measurements than conventional state estimators and does not require network observability analysis. A comparison of the single bad data detection and identification between the proposed state estimator and the Weighted Least Squares (WLS) state estimator on GE 6-bus and IEEE 14-bus power systems is provided. The results show that the proposed state estimator is more accurate than the WLS state estimator.Furthermore, the proposed methodology is a great alternative to the conventional techniques and is therefore well suited for smart grid applications.

Phase Change Memory is an emerging technology for main memory design. It is denser, non-volatile and consumes lower idle energy compared to traditional DRAM.Yet its limited write endurance and inherent greater write latency and energy constrain its replacement of DRAM. Based on these observations, many studies combine DRAM and PCM in main memory system. However, DRAM’s idle energy is the bottleneck of energy reduction for the hybrid memory and no previous work paid attention to it. In this paper, we propose a memory power transition policy and two page migration strategies (inner-DRAM and PCM-DRAM) to reduce the DRAM idle energy as well as the overall energy consumption. We experimentally compare our design with other previous hybrid memory systems under cycle-accurate simulation. Experiments of various benchmark workloads show that our system achieves significantly better improvements over other techniques in terms of metrics Energy and Energy-Delay2.

This paper presents an energy-efficient hybrid storage system framework. An integer linear programming (ILP) approach is used to formulate power optimization frameworks for each individual storage system. ILP power optimization frameworks with appropriate system constants, binary decision variables, and associated constraints are separately developed for a four power level Mobile Random Access Memory (MRAM) and a three power level Phase Change Memory (PCM). Subsequently, a hybrid configuration of MRAM and PCM storage systems is used to describe corresponding integer system variables and associated constraints under predefined power-level operation conditions to quantify actual power usage for programs with plausible execution patterns. The numerical results illustrate the efficiency of the proposed hybrid storage power optimization framework with respect to individual memory devices.

Real-time control of a smart grid with renewable energy based generations requires accurate state estimates, that is typically based on measurements aggregated from smart meters. However, the amount of data/measurements increases with the scale of the physical grid, posing a significant stress on both the communication infrastructure as well as data processing control centers. This paper first investigates the effect of geographical footprint of distributed generation (DG) on the voltage states of a smart distribution system. We demonstrate that the strong coupling of the physical power system results in estimated voltage phasors exhibiting a correlation structure that allows for compressed measurements. Specifically, by exploiting principles of 1D and 2D compressed sensing, we illustrate the effectiveness of voltage estimation with significantly low number of random spatial, temporal as well as spatio-temporal power measurements. Results demonstrate the importance of accounting for correlation in information aggregation in smart grids.

For green networking, Sliced Router Architecture was proposed which controls power consumption of routers by adjusting routers’ performance based on the volume of traffic. In this architecture, any packet losses can be eliminated but it leads a significant increase of processing latency in some cases, which is also a serious performance degradation of routers. In this paper, we propose two extensions in Sliced Router Architecture to achieve both zero packet loss and low latency which satisfies the requirement in current common routers. We first propose parallelized prediction counters for improving accuracy of prediction. Moreover, we extend the prediction circuit to support multiple prediction functions which derive the number of active slices continuously or supplely to reduce traffic latency under the conditions of keeping no packet loss. We then perform the simulation to evaluate the improvements in prediction accuracy, and the trade-off in power-saving and worst traffic latency. Our results show that the power efficiency can increase up to 3.4% by introducing parallelized counters, and achieve 156 microseconds of the processing latency by accepting 21.1% increase of power consumption.

High penetrations of distribution connected photovoltaic (PV) systems are becoming more common. However, the impact of these variable generators on system voltage and automatic voltage regulation equipment is not well quantified. In contrast to load which generally has some diversity, PV systems are often non-diverse over small geographic areas. Variability caused by PV can range from relatively slow changes in system voltage to high frequency impacts on real and reactive power. These changes have the ability to impact the operation of a distribution circuit from a protection, voltage control and load prediction/modeling point of view. This paper will utilize information from high resolution data acquisition systems developed at the National Renewable Energy Laboratory and deployed on a high PV penetration distribution system to analyze the variability of different electrical parameters. High resolution solar irradiance data is also available in the same area which can be used to characterize the available resource and how it affects the electrical characteristics of the study circuit. The full paper will look at the variability caused by load and compare the results against times when significant PV production is present, effectively comparing the diversity of system load to the diversity of the integration PV generation. Additionally, the impact of high-penetration PV integration on substation equipment such as capacitor banks and load tap changers will be quantified.

Cloud computing have attracted a lot of attention recently due to increasing demand for high performance computing and storage. Resource allocation is one of the most important challenges in the cloud computing system especially when the clients have some Service Level Agreements (SLAs) and the total profit depends on how the system can meet these SLAs. Moreover, a data center typically hosts and manages a suite of application environments and a fixed number of servers that are allocated to these application environments in a way that maximizes a certain utility function. In this paper, we consider the problem of SLA-based joint optimization of application environment assignment, request dispatching from the clients to the servers, as well as resource allocation in a data center comprised of heterogeneous servers. The objective is to maximize the total profit, which is the total price gained from serving the clients subtracted by the operation cost of the data center. The total price depends on the average service request response time for each client as defined in their utility functions, while the operating cost is related to the total energy consumption. We propose a near-optimal solution of the joint optimization problem based on the Hungarian algorithm for the assignment problem, as well as convex optimization techniques, in a way that is similar to the constructive partitioning algorithm in VLSI computer-aided design (CAD). Experimental results demonstrate that the proposed near-optimal joint application environment assignment and resource allocation algorithm outperforms baseline algorithms by up to 65.7%.

In this paper, a topology is proposed to convert a single-phase power supply to independent three phases so that balanced or unbalanced, linear or non-linear three-phase loads can be operated. It can be used in places, e.g., rural areas, where only a single-phase power supply is available. The converter consists of four legs: i) one rectifier leg to generate a DC-bus voltage; ii) two phase legs to generate two independent phases to form balanced three-phase voltages together with the single-phase power supply and iii) one neutral leg to generate a neutral point, which is common to the single-phase supply and the two phases generated. Decoupled control strategies are developed to make sure that i) the current drawn from the single phase supply is sinusoidal and in phase with the supply voltage, ii) the generated phase voltages contain low voltage harmonics even when the load is non-linear and iii) the neutral point is maintained stable. Simulation results are provided to illustrate the excellent performance of the system.

The world’s energy paradigm continues to undergo a rapid shift towards an increased use of renewable energy sources. To support this shift, an advanced electric power system architecture is being implemented by many electric utilities and new distributed energy resources interconnected with it. As these new installations occur, it is essential to verify that their grid interconnection systems (ICSs) conform to the relevant grid interconnection standards and that they perform satisfactorily under a variety of variable resource input and grid output conditions. This paper describes a Grid Interconnection System Evaluator (GISE) that leverages hardware-in-the-loop (HIL) simulation techniques in order to rapidly evaluate the grid interconnection standard conformance of an ICS according to the procedures in IEEE Std 1547.1™. The architecture and test sequencing of this evaluation tool, along with a set of representative ICS test results from three different photovoltaic (PV) inverters, are presented. The GISE adds to NREL’s evaluation platform that now allows for rapid development of ICS control algorithms using controller HIL (CHIL) techniques, the ability to test the dc input characteristics of PV-based ICSs through the use of a PV simulator capable of simulating realworld dynamics using power HIL (PHIL), and evaluation of the grid interconnection conformance of an ICS.

The frequency droop response of conventional turbine driven synchronous generators with respect to load increases is normally used in order to have stable operating characteristics for multiple generators operating in parallel over large geographical regions. This presents a challenge for renewable energy sources that interface to the transmission grid through static inverters that do not exhibit an intrinsic frequency droop characteristic. This paper presents a method of designing optimal load frequency controllers for transmission line inverters fed from renewable energy sources that allows for fast dynamic response due to variable solar and wind conditions while maintaining stability to interconnected synchronous generators. A control technique based on H2 norm optimization theory is presented. Detailed analysis of a three-area system representative of a region of mixed wind and solar photovoltaic sources is modeled in order to confirm the effectiveness of the proposed load-frequency control method.

Pakistan, a developing country is facing immense problem in form of load shedding. This self-created issue has not only affected the residential sector but at the same time, seriously damaged the industrial as well as agriculture sector .One of the techniques to compensate for the issue is to use effective load management techniques in addition to commencing new power projects. Smart Grid is an effective option to minimize the severity of these problems, especially in form of smart distribution system. However, efficient implementation of smart distribution grid system in Pakistan needs certain challenges to be addressed which is the core theme of this research paper.

Several large scale offshore wind farms are planned to be built far from the shores in the future. High Voltage Direct Current (HVDC) Light by ABB is an effective and reliable way to integrate this large scale wind power production to the grid. An expensive component of offshore wind park HVDC Light technology is offshore AC collector platform. The AC collector platform in the offshore wind farm HVDC link contributes significantly to the cost of the overall project. This paper investigates the comparison between two different AC topologies of an offshore wind farm connection to offshore HVDC converter platforms with and without offshore AC collector platforms. The technical feasibility of the omission of an AC collector platform from offshore wind farms connection to HVDC converter platform is investigated for the first time. In the first topology, the offshore wind farms are connected to an HVDC converter platform through offshore AC collector platforms. An offshore AC collector platform is used to collect energy from the wind farm and step up the voltages for transmission to offshore HVDC converter platform. The offshore AC collector platforms contribute significantly to the total cost and technical complexity of the HVDC connection. In the second topology, the offshore AC collector platform is removed from the circuit and the offshore wind farms are connected directly to offshore HVDC converter platform. The topological alteration of an offshore wind farm HVDC link gives rise to some technical challenges. The short circuit analysis and annual energy loss analysis is performed for these two topologies. The type of wind turbine generators, internal wind farm voltages and the distance between the wind farms and offshore HVDC converter platform are quite important factors that are investigated in this study. The short circuit analysis and loss analysis is performed for two types of wind turbine generators i.e. doubly fed induction generators (DFIG) and full conversion (FC) generators. Two internal wind farm voltage levels i.e. 33 kV and 66 kV, and three different distances i.e. 1 km, 5 km, and 10 km between the wind farms and offshore HVDC converter platform are investigated.

In this paper, the connectivity issues related to linking two DC buses featuring different voltage characteristics, in terms of voltage level and ripple, in a DC microgrid are identified, analyzed and discussed. A controlled DC-DC converter was used as the main bidirectional energy transfer enabler between the two buses. The focus of this paper is on how to achieve the best controllability and performance levels of the bidirectional converter when it is linking a DC bus with a relatively high voltage ripple to another with small ripple. The operating fundamentals of a buck-boost converter and its current control algorithm are explained. Different operation and control schemes are also presented. An experimental test setup was devised to investigate and compare the performance of each configuration. A three-phase full wave diode rectifier was used to achieve the high voltage ripple bus, whereas a three-phase controllable IGBT based rectifier was used as a pure DC bus. The results of the various experiments run for bidirectional power flow show that depending on the configuration of the system, better controllability and lower current ripple can be achieved by the proper selection of current and feedback.

Bangladesh is a highly inhabited country. It does gradually develop. Hence, people are facing various kind of problem here. Electricity is one of them. . Chittagong Hill Tract is out-of-the-way area in Bangladesh. People are deprived from their basic need of electricity. Currently, Government is concern about connecting them with power. However the transmission of power is very expensive and not easy here by reason of hilly track and river region. This research is primarily concerned among a feasibility study for a hybrid micro Sustainable power plant. Here people possibly will be the source of their own power plant, intensity of solar radiation is high and adequate wind flow available adjacent the year. Chittagong hilly area is the best preference of renewable hybrid power plant.

A topology for traction power systems with a single feeding wire, which consists of a three-phase V/V transformer and a three-phase converter, is proposed at first and then a control strategy based on the repetitive control is developed to deal with the power quality issues in the system. Because of the repetitive controller, all the harmonic and negative sequence currents generated by locomotives, which are single phase nonlinear loads, are compensated and only the active power is drawn from the grid. Different from the commonly used hysteresis controllers in traction power systems, the repetitive controller has a fixed switching frequency, which reduces the stress on the power semiconductor devices. Simulation results are provided to illustrate the performance of the system.

Along with rapid economic growth, urban traffic has become a complicated worldwide issue, which synthesizes out-of-order jam, energy consumption and GHG emission. An autonomic traffic and energy model is proposed based on the micro behavior simulation, in which an information decision factor is introduced. Thus the travel patterns and choice of the road trip have been controlled and optimized dynamically. Simulation with NetLogo verifies that the model can realize the optimization among traffic, energy and greenhouse gas emission and some practical use for solving the existing traffic problems.

Storage devices can be used in a power grid to store the excess energy when the energy production is high and the demand is low and utilize the stored energy when the produced energy cannot meet the high demands of the consumers. This paper represents two different studies of micro grid consisting of a conventional synchronous generator, as well as renewable energy sources, energy storage, and loads in order to investigate the effective energy flow control and transient stability improvement by employing storage. Thermal storage, unlike electrical one (such as battery) is more environmental friendly, has longer life span, and is more effective in power flow control. In this paper, resistive type thermal storages are proposed and its stability effects on micro grids are evaluated. A suitable model is developed for the storage and the grid’s stability analysis is adopted by using linearization methods. Consequently, by designing an optimal controller for the storage the stability of the micro grid is improved as verified through the simulations.

This paper presents zones for the control and operation of future complex power systems, which could be highly distributed both in terms of generation sources but also concerning the control and decision making components. The zones presented are sub regions of a power network and constitute sympathetic entities in terms of operational flexibility, with potentially dynamic boundaries, serving a judiciously selected control algorithm or technique. The IEEE 57-bus power system is used as a case study and the significance of the control intelligence to zoning is further emphasized.

This study concerns with the developments in the field of power grids in the India. It traces its evolution, the need to upgrade and its current state of affairs in terms of various initiatives being undertaken to realize a significant transformation in the area of power grids development.

In this paper a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on 6-bus and 18-bus power systems and the results are provided.

Wind turbines (WTs) employing a wound rotor induction generator with adjustable external resistors are known as Type–2 WTs. This WT topology is available in USA since 2001. This WT is regulated by controlling its pitch angle and its external rotor resistor to operate as a variable slip WT. The slip range can reach up to 10% above synchronous speed. This paper demonstrates that with a proper control, Type–2 WTs are capable to damp out subsynchronous resonance (SSR) oscillations commonly found in series–compensated transmission lines. The size of wind power plant (WPP) has increased over the years and some WPP exceeds 500 MW. They can be treated as energy sources which can regulate the power delivered to the grid. In order to analyze the capability of Type–2 WPPs to damp power system oscillations, the IEEE first benchmark model for SSR studies is modified with an aggregated Type–2 WPP model connected to the system. An additional control loop is implemented to modulate the effective rotor resistance so that SSR oscillations can be damped. The models are implemented and simulated using PSCAD/EMTDC software platform.

Integrating residential photovoltaic (PV) power generation and energy storage systems into the Smart Grid is an effective way of utilizing renewable power and reducing the consumption of fossil fuels. This has become a particularly interesting problem with the introduction of dynamic electricity energy pricing models since electricity consumers can use their PV-based energy generation and controllable energy storage devices for peak shaving on their power demand profile from the grid, and thereby, minimize their electricity bill cost. A realistic electricity price function is considered in this paper with billing period of a month, comprised of both the energy price component and the demand price component. Due to the characteristics of the realistic electricity price function and the energy storage capacity limitation, the residential storage control algorithm should properly account for various energy loss components during system operation, including the energy loss components due to rate capacity effect in the storage system as well as power dissipation in the power conversion circuitries. A near-optimal storage control algorithm is proposed accounting for these aspects, based on the PV power generation and load power consumption prediction results in the previous papers. The near-optimal control algorithm, which controls charging/discharging schemes of the storage system, is effectively implemented by solving a convex optimization problem at the beginning of each day with polynomial time complexity. Experimental results demonstrate that the proposed near-optimal residential storage control algorithm achieves up to 36.0% enhancement in electricity cost reduction than the baseline control algorithm.

Stress stemming from increasing energy demands in residential areas can cause electric overloads, which will either destroy grid components or shorten the equipment’s life expectancy. To overcome this problem, residential load management has become essential. In this paper, we propose a comfort based smart load management algorithm to efficiently manage the random and uncontrolled residential loads. Unlike most demand response programs, the proposed algorithm gives the user the choice to prioritize either comfort or savings. As a result, the end user’s comfort requirements and preferences are preserved. A game theoretic approach is used to formulate the energy consumption problem. Simulation results show that the algorithm achieves high cost savings and flattens the load while taking into account the user’s comfort. The algorithm is scalable, converges in acceptable times, preserves users’ privacy, and introduces a very limited amount of overhead in the system.

Useless electricity consumption is the electricity consumption of an electric appliance or system that is not performing its primary function or that is performing its primary function without being useful. So, useless electricity consumption does not only consist of standby losses. To identify the useless electricity consumption in a building, a profile-based approach is developed. This approach is used to investigate the useless electricity consumption in five buildings of the University of Leuven. The result of this study is that in these buildings the useless electricity consumption accounts for 4 to 13 % of the total electricity consumption. This paper will give a detailed discussion of a case study in a library of the university.

Nowadays, to indicate the quality of Thailand’s existing power system including the newly-installed distributed renewable energy sources, a number of pricy power quality analyzers are being used in most areas. This article proposes an alternative of such equipment called a smart recording power analyzer prototype (SRPA) using a combination of LabVIEWTM algorithms and a low-cost data acquisition (DAQ) device. The newly-proposed set of equipment not only has the ability to achieve the same accuracy and functionalities of currently-used power analyzers, but also has the advanced features supporting Thailand’s future-to-come smart grid system. The proposed SRPA is capable of simultaneous monitoring/recording both numerical data and waveforms in normal system operating conditions and when fault occurs e.g. voltage, current, frequency, real and reactive power, apparent power, energy consumption, power factor, harmonic distortion, voltage/frequency fluctuation, voltage unbalance, sag-swell, symmetrical components, flickers and many kind of faults detection. In this paper, the SRPA hardware configurations and LabVIEWTM algorithms will be thoroughly elaborated. The accuracy verification process has been strictly done under various controllable conditions by comparing the results of the SRPA with the standard measuring units in both laboratory environment and two renewable energy power plants. Experimental results in the laboratory illustrate that the proposed SRPA is comparable in accuracy and far superior to several references in terms of functionalities and flexibilities. Experimental results from the two renewable power plants: (1) a 130kW-biogas pig farm power plant and (2) a 1MW solar power plant demonstrate that the proposed SRPA is highly efficient and reliable compared to the factory-installed measuring units. The average percent errors are less than 2%. The proposed SRPA also has the ability to be set up as a network which will be potentially beneficial for a future smart grid/micro grid online monitoring system.

Future Smart Grids will consist of distributed Micro-Grids where the Advanced Metering Infrastructure (AMI) forms a central component. This consists basically of meters/sensors that are regularly communicating data towards/from a central Control Plane. Due to the ad-hoc topological nature of the meters/sensors, particularly in residential areas, Wireless Mesh Networks (WMNs) prove to be the ideal technology for AMI deployment. In this paper, we propose a wireless mesh network based architecture for AMI deployment that uses both Zigbee and IEEE 802.11. The paper presents the challenges and opportunity related to implementing such architecture in Moroccan market. This paper proposes a framework for renewable energy integration, and an appropriate Middleware design. The paper presents preliminary simulations on the wireless coexistence between the two technologies viand draw conclusions on the channel to be used and node placement problems.

This paper presents the concept for an ad-hoc self-organized microgrid based on moveable and renewable energy sources and fully distributed coordination between intelligent power routing nodes. The primary goal of the proposed architecture is to build an adaptive, scalable, and reliable system to support energy provisioning with limited infrastructural planning. Our vision focuses on two use-case scenarios: promoting electrification and energy sharing in isolated rural areas, and supporting emergency response crews in disaster relief situations. Both scenarios rely on the deployment of an autonomous microgrid based on movable generators and renewable sources which will dynamically reconfigure itself and adapt to changes with minimal user intervention.

This paper discusses applications and benefits of distributed storage devices on the performance of distribution power systems. In particular, the paper focuses the uses of Battery Energy Storage System (BESS) for system improvement. An overview of predominant battery types are covered in this paper along with their benefits and advantages. Diverse applications for BESS are described such as peak load shaving, power quality improvement, load/frequency control, system balancing and congestion management. Impacts of plug-in electric vehicles are explained and problems regarding the dispatch of BESS units are also introduced.

The concept of examining the feasibility of small-scale integrated hybrid renewable energy systems for mobile backup power generation has expanded greatly over the past decade. Increases in large scale power outages have become a common theme across America and other parts of the world as a result of natural disasters such as earthquakes, floods, hurricanes, and other extreme environmental conditions. These outages often disrupting commerce, business, and the quality of life for many of the consumers impacted including loss of life and significant cost to the tax payers in mitigating the effects of these disruptions. In addition, increasingly hostile social climates and threats of war have exposed the need for more reliable small scale backup power plants (both renewable and non-renewable) integrated to rapid recovery systems. As greater emphasis is placed on reducing the green house effect and the emissions of pollutants into the environment, major technological advancements in renewable energy is driving innovative approaches to improving Energy Returned On Energy Invested (EROEI), thus enabling a stronger business case for renewable over strictly non-renewable power generation systems, including mobile backup hybrid renewable power generation capabilities.

A critical piece of the Smart Grid (SG) infrastructure is the supporting Communication Networks that facilitate data gathering, monitoring and control of the electric grid. Over the years, electric utilities built robust communication networks for their transmission and distribution systems, but stopped short of the ”last mile” connections to the end user. A primary goal of the SG is to expand the communications network throughout and beyond the Distribution Network (DN); thus, enabling a holistic management and control of the electric grid from generation to consumption. For the realization of the Smart Grid goals, two-way communication capabilities must extend beyond the Distribution Network to the end user, allowing two-way data flow, e.g., real–time energy pricing as well as real-time demand data back to the utility operators. Selecting an appropriate communications architecture is the first and most important decision in designing a communications network since it will have lasting effects on the efficiency, reliability and cost of the network. This paper presents and evaluates various communication architectures for deployment of the SG within the DN and to the end users.

Electric microgrids generate a significant amount of measurement data by virtue of the constituent distributed smaller capacity assets. Data reduction for performance quantification and visualization techniques for microgrids is presented here. The case study is performed on an operating microgrid in Fort Collins, Colorado, USA. Relevant NERC metrics are calculated and two more system level metrics are developed. Alternative approaches to peak load reduction calculations are also presented. A visualization GUI is developed and discussed as a deliverable to the power system operator for enhanced situational awareness.

Smart meter is one of the most important devices used in the smart grid (SG). The smart meter is an advanced energy meter that obtains information from the end users’ load devices and measures the energy consumption of the consumers and then provides added information to the utility company and/or system operator. Several sensors and control devices, supported by dedicated communication infrastructure, are utilized in a smart meter. This paper outlines some smart meter’s aspects and functions. In addition, it introduces two basic types of smart meter system’s communication technologies: Radio Frequency (RF) and Power Line Carrier (PLC) and recent advances with regard to these two technologies. This paper also presents different policy and current status as well as future projects and objectives of SG development in several countries.

Interconnection of the Distributed Generation (DG) at higher penetration levels to the distribution grid is causing different problems with voltage profile of a typical distribution feeder. In this paper some of the voltage problems caused by increasing penetration of DG along with the role of the Volt-VAr controlling devices to mitigate these problems are investigated and discussed. A real distribution circuit containing a synchronous generator, a line voltage regulator, and a Static VAr Compensator (SVC) was used for computer modeling. Simulations were conducted considering full load and light load conditions, without, then with DG at various penetration levels. Simulations’ results verifying the high voltage conditions and unacceptable voltage flickers due to increased penetration of DG have been presented. It was also concluded that voltage regulator with certain settings and SVC can mitigate some of these problems.

Theoretical and experimental study of a natural circulation solar water heater using R744 as mediating fluid is presented. Solar collector consists of nine parallel aluminum foil enveloped copper U tubes were suspended in evacuated glass tubes. U shape bent copper tubes were connected through stainless steel headers to heat exchanger. The shell-and-coil counter flow heat exchanger was designed, fabricated and tested using CO2 refrigerant material. The helical coil copper tube was immersed in bulk water tank. Hot CO2 was piped to upper coil baffle for circulation through counter flowing water to lower baffle. Water input/output pipes were inserted from the top and copper coil tubes from upper and lower sides of water tank. Evacuated glass tubes solar collector increased CO2 refrigerant temperature from 35 to 78C giving temperature difference of 43C. The CO2 temperature at exit from heat exchanger was measured to be 40C at ambient air temperature of 36C. Solar heat transfer raised the inlet water temperature from 26 to 55C under off water tap condition in about three hours. Water temperature difference between inlet and outlet ports of heat exchanger was measured to be 27C. Heat capacity increases manifolds at critical point, therefore, natural circulation solar water heater performance can further increase if the system is used in mild sunshine cold weather regions.

Rather than considering light as passing through a PN junction we paradigm shift to a new class of traps in which the light travels along a PN junction, as a guided mode. Significantly this opens the door to importing energy from elsewhere and mode coupling it directly into the PN junction. The theoretical basis for this mode trapping is explored. We also create new simulation tools, which allow experimental data to be incorporated, in order to improve our understanding of the underlying processes and to aid in the optimization of nanophotonic devices. We consider devices with non-conductive nanoparticles and/or plasmonics as top-reflectors; used in conjunction with periodic and/or pseudo-random photonic crystal back-reflectors. The nonlinear effects of saturation allow us to clamp the electromagnetic modes to produce a uniform distribution of power across the photovoltaic surface for dimensions as large as we wish.

This paper presents a closed-form relation among voltage, current and power of PV cells. The methodology applied consists in a selective use of Taylor series with the purpose of obtaining a solvable analytical equation that presents similar results to the traditional numerical solution. This simplified solution enables an easier but precise evaluation of the PV voltage generated under specific conditions of temperature and solar radiance. The main benefit of this set of equations is the creation of a tool set that allows a precise evaluation of the yearly voltage profile based in PV datasheet and solar plant location. The expected yearly voltage profile provides valuable information in order to set the inverter voltage operation design in an optimal fashion for maximum yield benefits. These results may provide information valuable to compare and decide whether to install an inverter with or without a DC booster. The technique proposed in this work is validated by comparing the results of the set of equations derived with the traditional numerical solution and the PV manufactured values.

The world’s energy supply is heavily dependent on fossil fuels. The limited supply of fossil fuels and their impact on the environment has led to a greater global focus on the development of alternative renewable energy solutions. As a part of this effort, Sandia National Laboratories has sponsored a design team from New Mexico Institute of Mining and Technology to improve current heliostat designs by lowering heliostat production costs. To this end, a novel water-ballast drive system was designed which reduces the cost of the drive components and allows for a cheaper, lighter support system. A prototype utilizing a hybrid water-ballast drive system and a linear actuator is currently in production guided by strict specifications for durability and accuracy by Sandia National Labs. The second prototype improves on the initial prototype in both cost and in meeting the design specifications.

Photovoltaic (PV) modules have dramatically decreased in price in the past few years, spurring the expansion of PV deployment. Residential and commercial rooftop installations are connected to the distribution network; large-scale installation PV power plants have benefited from tax incentives and the low cost of PV modules. As the penetration of PV generation increases, the impact on power system reliability will also be greater. Utility power system planners must consider the role of PV generation in power systems more realistically by representing PV generation in dynamic stability analyses. Dynamic models of PV inverters have been developed in the positive sequence representation. We developed a PV inverter dynamic model in PSCAD /EMTDC. This paper validates the dynamic model with an actual hardware bench test conducted by Southern California Edison’s Distributed Energy Resources laboratory. All the fault combinations, symmetrical and unsymmetrical, were performed in the laboratory. We compared the simulation results with the bench test results.

Energy consumption by the US Army is becoming an increasingly important issue. The cost of providing fuel to Army outposts in deployed environments is particularly expensive due to numerous precautions required to defend fuel convoys from enemy attacks. This work is part of the Army’s Construction Engineering Research Laboratory (CERL) efforts to reduce the amount of energy consumed by temporary barracks structures commonly referred to as “B-Huts”. A prototype is being developed utilizing structurally insulated panels (SIP) and is referred to as a “SIP-Hut”. This paper explores the benefits of incorporating photovoltaic (PV) panels into the SIP-Hut’s power system. Powering a SIP-Hut is a unique challenge because SIP-Huts are typically located in remote and dangerous locations and, in addition, are temporary structures. A main thrust of this work was to examine if PV could be economically beneficial within this unique environment and short time span. However, the findings from this study can be applied to other remote locations where fossil fuels are not readily available. The SIP-Hut was modeled, solar resources estimated and analysis was performed using Hybrid Optimization Model for Electric Renewable (HOMER) software available from the National Renewable Energy Laboratory (NREL). Our analysis indicates that PV incorporation can have a significant positive impact on the amount of diesel fuel consumed and the overall cost of energy production.

The increasing deployment of renewable energy sources has raised concerns about the ramp-rate limitations of conventional steam and combustion turbines in providing load following during wind and solar transients. As one of the promising Generation IV reactor technologies, thorium molten salt reactors (TMSR) have a number of advantages in terms of their fuel cycle. In addition, recent advancements in reactor thermal hydraulics have increased the thermal feedback potential for TMSR. This paper examines the transient power characteristics of a TMSR with improved reactivity feedback performance by analyzing the neutronics and temperature interactions with reactor power feedback. Detailed simulations are given that include the nonlinear and transport delay effects of TMSR circulating-fuel reactor dynamics.

This paper presents a methodology for photovoltaic (PV) systems model validation through outdoor measurements. The paper first summarizes a PV model published by the authors in [1] which allows to precisely reproduce the current-voltage relationship of an array of an arbitrary size from information available in manufactures’ datasheets. The model is then validated through the methodology proposed herein under different PV panels configurations as well as under variable solar irradiance conditions.

A novel use case will be explored showing how modern graphical system design tools used together with SPICE in a co-simulation environment can be used to represent accurate simulations of practical real world digitally-controlled power inverters with a high level of accuracy while at the same time taking high level power measurements that would otherwise not be practical using separate design environments. This concept allows power design engineers to quickly explore various software and hardware methodologies while evaluating key performance metrics within the simulation. The benefit of using the graphical system design approach with SPICE is two-fold in that the control algorithms for the inverter design can be rapidly adjusted while key metrics of the design can be evaluated in an effort to optimize the design over a wide range of operating conditions. The graphical system design tool methodology of LabVIEW will be used in a collaborative fashion within a SPICE environment (Multisim) to explore the technique of extracting advance power metrics while performing circuit simulation. Using these techniques and co-simulation for implementing the digital control, the analog plant of an inverter scheme will be discussed to accurately evaluate loss, overall system efficiency and loss due to temperature effects and explore system behavior over various startup and load conditions. Simulation results for the digital inverter design with the presented methodology are given. To show the quality of the generated simulation data, simulation data is compared directly with data from a prototype implementation of the same design.

This paper presents a complete analytical model characterizing all the variations of multi-gate MOSFETs including the Tri-gate FinFET, all-around gate FinFET, Trapezoidal FinFET, Double-gate MOSFET, etc. Our presented model gives precise and compact expressions for all the device performance metrics such as drain current, subthreshold swing, threshold voltage, and gate capacitance. These final expressions are obtained without any approximation and are continuous and valid for all the regions of operation of the device. Also, in this paper, for the first time, we answer an important question and determine the ultimate limit for the scaling of Tri-gate FinFET using the results of our analytical model. And finally, in this article, for the first time complete analytical physics based models for all performance metrics of trapezoidal Tri-gate FinFETs and rectangular Tri-gate FinFETs are presented. As a result, a complete comparison between the performance of the two transistors is obtained that shows the advantages and disadvantages of the trapezoidal fin shape instead of the rectangular shape. Having this complete performance comparison is crucial after the recent discovery that Intel’s Tri-gate has trapezoidal fin shape instead of rectangular.

It is expected that large capacity distributed generation (DG) systems including photovoltaic (PV) power systems will be installed in future power systems. When the capacity of PV power systems installed in the distribution system increases, voltage of the system goes beyond the allowable voltage range due to reverse power flow from PV power systems. In order to minimize this problem, load control at the customer end would be a possible solution. In this paper, application of controllable customer equipment, Heat Pump Water Heater (HPWH), has been proposed in order to mitigate voltage violation. The input power of HPWH is applied in three different ways: rated input, step input and multiple inputs so as to find the optimum solution that keeps the voltage within allowable limit.

This research is aimed to study the storage tank stratification design parameters effects on the efficiency of the large solar hot water system. Detailed CFD simulation for the storage tank coupled with TRNSYS program simulation for the entire solar hot water system is performed to study the system performance under various thermal stratification baffles design for the storage tank. The study is made for three representative cities of Taiwan by input their typical-meteorological-year (TMY) data. The results indicate the performance of a large solar hot water system can be significantly improved with proper designed thermal stratification baffles in the storage tank.

Green power generation needs to include the manufacturing process as well as the generation itself. For a system to be truly environmentally responsible it should be a renewable system which requires no caustic chemicals or similarly damaging processes while being built. For the proposed system, solar energy can be converted into usable energy without the use of ecologically harmful silicon based manufacturing. To accomplish this, a Stirling cycle-based heat engine with concentrated solar power is proposed. Thermal conversion of power from solar energy creates no harmful emissions. The proposed system will additionally be efficient when compared to a photo voltaic (PV) system with an equal footprint. It will also show a significant improvement in energy return on investment (EROI) when compared to other solar solutions. The proposed system is significantly different from existing systems due to the location of the heat absorber of the Stirling engine.

Solar energy is renewable energy par excellence. Environmentally friendly, it has many specific advantages because of the foreseeable depletion of fossil energy resources. The solar cells are currently dominated by silicon and expensive, hence the widespread enthusiasm of researchers interested in the possibility of manufacturing solar cells from plastic materials or organic. These new cells have the advantage of being simpler and more malleable than those made from a silicon [1]. Several organic dyes, such as styryl [2], coumarines [3], polyenes [4] and indole derivatives [5], have been proposed as potential candidates for solar cells. Rhodanine derivatives, electron acceptors are used in a wide range of organic molecules “Push-Pull” These have applications in optics and more recently non linéaire [6] are used in the manufacture of DSSCs [7] and are obtained with a high conversion efficiency compared to other. We were interested in the synthesis of new chromophores containing the pattern rhodanine, a molecule from the leader aminothiazoline thione as a synthetic strategy developed previously in our laboratory.

The Smart Grid Initiative (SGI) encourages the integration of storage and peak-shaving technologies including plugin hybrid electric vehicles (PHEVs). PHEV sales in the US are expected to significantly increase primarily due to their potential to lower fuel costs by reducing fossil fuel consumption and to lower emissions. The rising penetration rate of these vehicles may however cause problems to utilities, especially as they may dramatically increase demand peaks if not managed properly. In this paper, a methodology is proposed to determine the impact of PHEV fleets with vehicle-to-grid (V2G) capabilities on electric distribution systems. The methodology relies on a probabilistic PHEV fleet characteristics model and a linear programming algorithm to determine the optimal charging patterns of the fleet vehicles, which are then used for utility peak-shaving purposes. Results for several scenarios show that a 30% penetration level of V2G-capable PHEVs can be achieved without increasing peak load and without requiring any capacity update on the distribution infrastructure of the selected test system. Detailed results also show that daily load profiles would be modified for residential customers, and would stay closer to their average value than today.

Anaerobic digestion is widely used for treatment of excess sludge from sewage plants to produce biogas and reduce biosolids content. The process typically comprises the hydrolysis, acidogenesis, and methanogenesis phases. The acid formers prefer an acidic environment and are fast growing while methane formers prefer a neutral pH or higher environment and are slow growing; therefore, it is a challenge to optimize the activities of the two microbial communities in the single stage anaerobic reactor. Waste activated sludge also has relatively low biodegradability and the single stage system operated under long HRT (about 30 days) can typically only achieve up to 40% VS reduction efficiency. The two phase process spatially separates the hydrolysis/acidogenesis phases from the acetogenesis/methanogenesis phase to achieve higher organic stabilization, and more gas production. While there have been reports of sewage sludge digestion in 2-phase systems compared with the conventional single stage system, the results have not been consistent. While higher VS reduction and gas yield in the 2-phase system was demonstrated, other researchers have reported the increase in VS reduction in a 2-phase system fed with 1:1 primary and waste sludge was only 1.9-6%. Therefore before commitment to full scale application, it is necessary to investigate digestion of sewage sludge in the single stage and 2-phase anaerobic systems to determine performance and to reinforce the findings to simultaneously explore the microbial community profiles in the two systems to determine differences if any. The degradation of sewage sludge in single stage and 2 phase anaerobic systems was investigated in bench-scale batch reactors. Average COD reduction efficiency in 2 phase system in this initial phase of the study was 4.5% (30 days HRT) and 3.3% (20 days HRT) higher compared to single stage system. Reducing the HRT from 30 days to 20 days had little influence in VS reduction in the two systems. The average methane content in the biogas was 61.8%, 66.5%, and 64.8% (30 days HRT) in acid reactor, methane reactor and single stage reactor, respectively, and the corresponding values were 57.7%, 66.5% and 64.9% at 20 days HRT. The microbial community analyzed by qPCR using primer/probes specific for orders of Archaea involved in methanogenesis showed that hydrogen and acetate utilizing methanogens were present in all the reactors, but relative abundance of methanogens in the acid reactor was lower compared to the methane and single stage reactors. Reducing the HRT from 30 days to 20 days decreased the relative abundance of methanogens and changed the methanogen community structure.

Due to a century of gas-tank / gas-station legacy, most of the focus to date on Electrical Vehicle (EV) charging has been with respect to public charging, charging speed, and impact on the grid. Unfortunately, most of this focus is misguided and simply wrong due to legacy thinking that constrains the consideration of EV’s only in light of the “gas-tank/gas-station model”. The true promise of the EV is its ability to charge anywhere and everywhere from the national grid using the most accessible, and visible ubiquity of the standard 120v outdoor outlet (L1 charging). The often touted issues of availability, time-to-charge, and impact on the grid virtually vanish when one considers that the true promise of the EV is met when it is simply plugged into a standard outlet while parked. A typical American car spends 21 hours or more a day parked. This is plenty of time to maintain even the 100 mile range vehicle always fully charged not only every day, but also at the start of every trip if it is simply plugged in at home and at work or any other place where it will be parked for hours. Similarly, the impact of an EV on the national grid when plugged into 120v is no more than a coffeepot. Whereas the impact of the higher voltage (L2) and fast DC chargers (L3) can draw more power than a dozen homes at once and is a very significant issue (though misguided due to legacy gas-station fill-to-full thinking). Finally, too, the smart-grid can do nothing to manage the load of millions of EV’s if the EV’s are not always plugged in while parked! This paper shows how simple 120v charging (L1) is the most practical, lowest cost, most efficient charging method with the least impact on the power distribution grid for our future of EV’s and can be done Smartly now while waiting for the Smart Grid.

Railroads are very fuel-efficient in moving freight by land. The history of rail begins with steam power, moving to eventual dieselization. Some components, advantages and disadvantages of internal combustion engines (gasoline, diesel) and external combustion engines (steam) are explored. Interesting developments with steam turbines and even gas turbine propulsion are recounted in this paper. Improvements to steam using computerization and other techniques are proposed. The use of biocoal as an experimental, environmentally-friendly fuel source in a piston-driven steam locomotive is described. The steam engine is seen to have a large environmental benefit over diesels when these enhancements and the complete system life cycle are taken into account.

The impact of forecasting error in wind power on unscheduled flows (USFs) is investigated here. Normal distribution is used to model the forecasting error distribution. Upper and lower bounds on wind farm output with a positive correlation of errors are obtained. Monte Carlo simulations using the interval forecasts of wind farm outputs are run to obtain interval branch flows. Ordinary least squares and ridge regression are used for the estimation of a mathematical artifact – minor loop flows – for accommodating USFs. Model adequacy and statistical inferences of the loop flow estimates is discussed. Impact of forecasting error on distributions of estimated loop flow is explored on the basis of Kolmogorov-Smirnov (KS) and chi-square goodness-of-fit tests.

The modular multilevel converter (MMC) is an attractive topology for HVDC/FACTS systems. In this paper a new single-phase MMC-based D-STATCOM inverter for grid connection is proposed. The proposed inverter is designed for grid-connected wind turbines in the small- to mid-sized (10kW-20kW) range using the most advanced multi-level inverter topology. The proposed MMC D-STATCOM inverter controls the DC link voltage as well as the active and reactive power transferred between the renewable energy source, specifically wind turbine, and the grid in order to regulate the power factor (PF) of the grid regardless of the input active power from wind turbine. The goal of this paper is to present a new inverter with D-STATCOM capability in a single unit without any additional cost. The 5-level D-STATCOM inverter is simulated and the results are presented to verify the operation of the proposed system. The simulation studies are carried out in the MATLAB/Simulink environment. To validate the simulation results, an experimental configuration of a 5-Level DSTATCOM inverter has been built and tested.

In this paper, we introduce a new method for finding the proper size of energy storage system (ESS). This design is dedicated to reduce the size of ESS considering the uncertainty of wind speed. It considers the statistical behavior and also the state of charge (SOC) of ESS. The impact of wind uncertainty and its impact on the SOC of ESS are studied. The optimization is done by using the defined uncertainty limits and some other criteria. The probability density function and cumulative density function are calculated in this method. The presented method provides a significant reduction in the size of ESS in terms of power and energy capacity which consequently reduces a considerable capital cost of ESSs for applications in wind turbine generators. The main goal of this design is to cut the unnecessary parts of ESS that do not have a beneficial role in ESS. All the calculations and plotting are done using MATLAB.

A study of vibration suppression of a rotating wind turbine blade with unsteady aerodynamic loads and trailing-edge Microtabs was made. The focus is on the aeroelastic dynamics of the spinning blade with dynamic loads, the closed-loop experiments by Adaptive Control with small-size, energy-efficient, fast-response actuation, Microtabs, and stability demonstration. The experiment results reveals good performance of Adaptive Controller and confirms the usefulness of Microtabs as a effective tool for active flow control for a wind turbine blade. The stability of the designed controller is also proved by Adaptive Stability Theorem, which is also demonstrated according to each wind velocity case.

The Jet Propulsion Laboratory, California Institute of Technology, has developed a novel advanced hydraulic wind energy design, which typically has about 8%–28% performance improvement over conventional wind turbine and hydraulic wind energy systems. It also has significant cost advantages over conventional and direct drive wind energy systems. The design is equally applicable to tidal energy systems and has passed preliminary laboratory proof-of-performance tests, as funded by the Department of Energy.

This paper presents the current status of wind energy technology and its developments. There are some challenges in the wind energy technology, once these challenges are overcome, wind energy can provide most of the electricity needs in the world. Wind is known globally as an environmentally friendly and cost effective solution to energy shortages. However, challenges remain in designing efficient and effective control systems that would maximize the output power of the turbines. This paper aims to provide a brief review of the current state of control technology for wing energy systems and also explores technical designs, challenges and areas of ongoing research.

This paper develops a power system stabilizer (PSS) design for a wind turbine equipped with a doubly fed induction generator (DFIG) based on vector control to improve the performance and dynamic stability of DFIG under fault conditions. The proposed PSS design is combined with genetic algorithm to obtain the high-fitness answer as a strong optimization technique to the design of PSS parameters. A study network containing a wind farm equipped with DFIG was employed and all simulations were carried out using MATLAB. It is shown that the employment of a proposed PSS can substantially enhance the contribution of a DFIG-based wind farm to network damping and dynamic stability.

Wind turbine generators (WTGs) consist of many different components to convert kinetic energy in the wind into electrical energy for the end users. Wind energy is accessed to provide mechanical torque for driving the shaft of the generator. The conversion from wind power to mechanical power is governed by the aerodynamic conversion. The aerodynamic efficiency of the WTG is influenced by efficiency of blades, the gearbox, the generator, and the power converter. This paper describes the use of MATLAB/Simulink to simulate the electrical and grid-related aspects of a WTG and the FAST aero-elastic wind turbine code to simulate the aerodynamic and mechanical aspects of the WTG. The combination of the two enables studies involving both electrical and mechanical aspects of the WTG. For example, mechanical engineers can formulate generator control that may preserve the life of the gearbox, or mitigate the impact of transient events occurring on the transmission lines (faults, voltage and frequency dips, unbalanced voltages etc.). Similarly, electrical engineers can study the impact of high ramping wind speeds on power systems, as well as the impact of turbulence on the voltage and frequency of small islands.

Wind and solar power are playing an increasing role in the electrical grid, but their inherent power variability can augment uncertainties in the operation of power systems. One solution to help mitigate the impacts and provide more flexibility is enhanced wind and solar power forecasting; however, its relative utility is also uncertain. Within the variability of solar and wind power, repercussions from large ramping events are of primary concern. At the same time, there is no clear definition of what constitutes a ramping event, with various criteria used in different operational areas. Here the Swinging Door Algorithm, originally used for data compression in trend logging, is applied to identify variable generation ramping events from historic operational data. The identification of ramps in a simple and automated fashion is a critical task that feeds into a larger work of: 1) defining novel metrics for wind and solar power forecasting which attempt to capture the true impact of forecast errors on system operations and economics, and 2) informing various power system models in a data-driven manner for superior exploratory simulation research. Both allow inference on sensitivities and meaningful correlations, as well as quantify the value of probabilistic approaches for future use in practice.

This paper provides the results of a study conducted to assess the impacts of the “wind generation variability” on the voltage profile in a small-scale radial power system. The power network has been modeled using one of the well-known simulation programs used by the industry known as Powerworld®. The study takes into account the irregular behavior of the wind patterns and focuses on effects of wind generation at variable penetration levels on the voltage profile of a 13-bus radial power system. The assessment introduces two unique scenarios. In one scenario, the wind-generation farms are connected to a remote location with a critical voltage profile. The intensity of wind penetration is fluctuated methodically to evaluate the influence on the grid’s voltage profile. The Smallest Singular Value of Jacobian (SSVJ) analysis of the power flow Jacobian matrix is applied to further assess the networks voltage profile. This method has been favored and utilized as an index for evaluating voltage profiles by the industry as well as the utilities. Simulation results along with recommendation and suggestions for improvements in each scenario have been provided.

In this paper, a doubly-fed induction generator (DFIG) wind turbine is modeled using the general vector representation of voltage, current and magnetic flux in the presence of harmonics. The general vector representation provides insights to how harmonics are injected in the rotor side because of the use of the DC/AC inverter, and how rotor current is modulated with the rotor’s mechanical speed before it is inserted into the stator side through the air gap. We have also used repetitive rectangular pulses to account for the change in the area of interface between the stator’s poles and the rotor’s poles caused by the mechanical speed using. For the 6-pole DFIG, the periodicity of rectangular pulse creates multiples of the sixth harmonic of the induced magnetic flux which is modulated with the flux of the synchronous speed. Hence it produces multiples of (n6±1)ωs Our simulation shows that the 6-pole DFIG wind turbine stator current injects 5th, 7th and 11th harmonics in addition to a sub fundamental frequency into the grid. Hence, the general vector representation model maybe used for to design optimal controller that would also minimize harmonics of the stator current.