These data are intended to be used by researchers and other professionals working in power and energy related areas and requiring data for design, development, test, and validation purposes. These data should not be used for commercial purposes.
The public data sets are permanently available in https://site.ieee.org/pes-iss/data-sets.
Dissemination of this initiative is taking place so that the number and diversity of the published data sets increase over time and can be used as a valuable public resource for R&D activities. Your contribution for this initiative can be very important. Please disseminate and contribute; use our contact points (gecad@isep.ipp.pt; zav@isep.ipp.pt) to have all the data that can be made public published in the website.
Please check our Call for Open Data Sets.
These data sets can be used in research and development activities and the obtained results can be published in scientific publications.
Please send us your comments about the data sets and feedback on the use you’re making of them. If you use any of these data sets in your scientific publications, please don’t forget to make a reference to this web page (helping us to disseminate the initiative) and to the respective references (registered in the “sources” column of the data sets table).
We also kindly ask you to inform us about your publications that use any of these data sets so that we also include them in the dataset reference list.
The following tables below allow access to Data Sets for the following areas:
- Consumption
- Electric Vehicles
- Power Quality
- PV Generation
- Reliability
- Weather Data
- Wind Based Generation
- General Energy Data
You can access some references that use some of the available data sets here
Consumption
| Source | Short Descritpion | Link | Contact |
|---|---|---|---|
| Private Home 1 [Canizes, 2015] | Measurement site: Single family housing Sampling period: 5 minutes Start: 03-June-2011; End: 18-June-2011 Installation single-phase 5.75 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 2 [Canizes, 2015] | Measurement site: Single family housing Sampling period: 5 minutes Start: 16-July-2012; End: 26-July-2012 Installation three-phase 6.90 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 3 [Canizes, 2015] | Measurement site: Single family housing Sampling period: 5 minutes Start: 23-January-2013; End: 07-February-2013 Installation single-phase 5.75 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 4 [Canizes, 2015] | Measurement site: Single family housing Sampling period: 5 minutes Start: 06-January-2014; End: 30-January-2014 Installation single-phase 3.45 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 5 [Canizes, 2015] | Measurement site: Single family housing Sampling period: 5 minutes Start: 04-August-2011; End: 18-August-2011 Installation single-phase 6.9 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 6 | Measurement site: Single family housing Sampling period: 15 minutes Start: 25-December-2011; End: 15-March-2013 Installation single-phase 10.35 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 7 | Measurement site: Single student housing Sampling period: 5 minutes Start: 26-September-2011; End: 03-October-2011 Installation single-phase 6.9 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 8 | Measurement site: Single family housing Sampling period: 5 minutes Start: 01-June-2012; End: 15-June-2012 Installation single-phase 3.45 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 9 | Measurement site: Single family housing Sampling period: 5 minutes Start: 29-December-2012; End: 12-January-2013 Installation single-phase 3.45 kVA | Download as Excel | zav@isep.ipp.pt |
| Private Home 10 [Fernandes, 2013] | Measurement site: Single family housing Sampling period: 1 minute Start: 01-June-2012; End: 30-June-2012 Installation single-phase 17.25 kVA | Download as Excel | zav@isep.ipp.pt |
| Office 1 [Gomes, 2015] | Measurement site: Office Sampling period: 10 seconds Start: 11-July-2014; End: 17-July-2014 Installation three-phase with university contract power | Download as Excel | zav@isep.ipp.pt |
| Office 2 | Measurement site: Office Sampling period: 5 minutes Start: 01-November-2014; End: 30-November-2014 Installation three-phase with university contract power | Download as Excel | zav@isep.ipp.pt |
| Office 3 | Measurement site: Office Sampling period: 10 seconds Period: October 2014 to April 2015 Installation three-phase with university contract power | Download October 2014 as Excel Download November 2014 as Excel Download December 2014 as Excel Download January 2015 as Excel Download February 2015 as Excel Download March 2015 as Excel Download April 2015 as Excel | zav@isep.ipp.pt |
| Office 4 | Measurement site: Office Building Sampling period: 5 minutes Start: 01-July-2016; End: 31-December-2016 Installation three-phase with university contract power | Download as Excel | zav@isep.ipp.pt |
| Commercial 1 [Canizes, 2015] | Measurement site: Commercial bar Sampling period: 1 minute Start: 02-July-2014; End: 07-July-2014 Installation three-phase 27.60 kVA | Download as Excel | zav@isep.ipp.pt |
| Refrigerator | Measurement site: Refrigerator (power and sensors) Sampling period: 5 seconds Start: 01-May-2017; End: 15-June-2017 | Download as Excel | zav@isep.ipp.pt |
| Water Heater | Measurement site: Water Heater (power and sensors) Sampling period: 5 seconds Start: 10-May-2017; End: 10-June-2017 | Download as Excel | zav@isep.ipp.pt |
| Energy consumption and PV generation data of 15 prosumers (15 minute resolution) [Foroozandeh, 2020] | Measurement site: Energy consumption of a collective building contains 15 apartments and PV generation data Sampling period: 15 minutes Start: 01-Jan-2019; End: 01-Jan-2020 | Zenodo | zav@isep.ipp.pt |
Electric Vehicles
| Source | Short Description | Link | Contact |
|---|---|---|---|
| Case with 1800 EVs / GECAD [Soares, 2013a] [Soares, 2013b] | Database with a 24-period scenario of 1800 realistic EVs and PHEVs with a period resolution of 1 hour. The scenario represents a realistic behavior for a typical workday in a 33-bus MV sized network with 4.6MVA peak load. | Download as Excel | zav@isep.ipp.pt |
| 34 EVs database / GECAD | Electric Vehicles (EVs) database created by GECAD with multiple parameters that can be used in related works, i.e. impact assessment, smart grid optimization, road transport simulation, etc. | Download as Excel | zav@isep.ipp.pt |
| Energy consumption of 15 electric vehicles (one day resolution) [Foroozandeh, 2020] | Type: EV consumption Duration: One year Resolution: One day Sheets description: EV 1-15: Contains the information of the energy consumption and initial State of Charge of each EV. | Zenodo | zav@isep.ipp.pt |
Power Quality
| Source | Short Description | Link | Contact |
|---|---|---|---|
| Laboratorial Essays of Polypropylene and All-film Power Capacitors [Spavieri, 2017] | Database with 1380 files of current, voltage and active power measurements (a total of 460 laboratorial essays). These signals represent the real behaviour of polypropylene and all-film power capacitors under the influence of harmonic voltages. All voltage waveforms were configured in accordance with the IEEE, IEC and PRODIST (Brazilian) standards, relating to the harmonic limits. | Download as Zip | ricardo.asf@ufscar.br |
PV Generation
| Source | Short Description | Link | Contact |
|---|---|---|---|
| PV GECAD LASIE [Ramos, 2012a] [Ramos, 2012b] | Database from the GECAD PV system Sampling period: 5 minutes Period: 2013 | Download January as Excel Download February as Excel Download March as Excel Download April as Excel Download May as Excel Download June as Excel Download July as Excel Download August as Excel Download September as Excel Download October as Excel Download November as Excel Download December as Excel | zav@isep.ipp.pt |
| PV data Enerq-USP / Southeast of Brazil [Fernandes, 2016] | Measurement site: Petrolina FV1 – Enerq/USP PV system profile Sampling period: 5 minutes Start: 01 – December – 2013; End: 10 – December – 2013 Season: Summer (Southeast of Brazil) Start: 01 – June – 2014; End: 10 – June – 2014 Season: Winter (Southeast of Brazil) | Download Summer as Excel Download Winter as Excel | nelsonk@pea.usp.br |
| PV GECAD N | Measurement site: Photovoltaic Generation Sampling period: 1 minute Start: 27-July-2016; End: 16-November-2016 Installation 10 kW | Download as Excel | zav@isep.ipp.pt |
| PV GECAD N (Photovoltaic generation and temperature for the year 2019) [Vale, 2021] | This dataset has photovoltaic generation data and temperature data regarding a research building in ISEP/P.Porto (Instituto Superior de Engenharia do Porto / Politécnico do Porto). The data was measured using 5-minutes periods during the entire year of 2019. The temperature sensor was located near the photovoltaic panels (without having direct sunlight). The photovoltaic installation has a theoretical peak generation of 7.5 kW. The dataset presents some errors in the data, representing failures in the acquisition system. | Download as Excel | zav@isep.ipp.pt |
| Photovoltaic generation and temperature for the year 2019 | This dataset has photovoltaic generation data and temperature data regarding a research building in ISEP/P.Porto (Instituto Superior de Engenharia do Porto / Politécnico do Porto). The data was measured using 5-minutes periods during the entire year of 2019. The temperature sensor was located near the photovoltaic panels (without having direct sunlight). The photovoltaic installation has a theoretical peak generation of 7.5 kW. The dataset presents some errors in the data, representing failures in the acquisition system. | Zenodo | zav@isep.ipp.pt |
Reliability
| Source | Short Description | Link | Contact |
|---|---|---|---|
| IEEE Reliability 24 bus / GECAD [Canizes, 2011] [Canizes, 2012] | Complete fault database (10 years data – 2000 to 2009) for realiabilty test system 24 bus | Download as Excel | zav@isep.ipp.pt |
Weather Data
| Source | Short Description | Link | Contact |
|---|---|---|---|
| National Solar Radiation Data Base 1961-1990 (NSRDB) | NSRDB contains 30 years of solar radiation and supplementary meteorological data from 237 NWS sites in the U.S., plus sites in Guam and Puerto Rico. | NSRDB website | Site Webmaster |
| NREL wind speed [Pinto, 2012] [Pinto, 2014] [Ramos, 2011] | Database from the National Wind Technology – National Renewable Energy Laboratory (M2 Tower, latitude: 39° 54′ 38.34″ North; Longitude: 105° 14′ 5.28″ West; Elevation: 1855 meters AMSL)Sampling period: 5 minutes Start: January-2008; End: December-2012 | Download as Excel | zav@isep.ipp.pt |
| Weather data / Porto, Portugal | Measurement site: Weather Station ISEP/IPP Sampling period: 5 minutes Data: Solar radiation, Temperature, Humidity, Wind Start: 01 – January – 2015; End: 31 – May – 2015 | Download as Excel | zav@isep.ipp.pt |
| Weather data / Porto, Portugal | Measurement site: Weather Station ISEP/IPP Sampling period: 5 minutes Data: Solar radiation, Temperature, Humidity, Wind Start: 01 – January – 2016; End: 31 – December – 2016 | Download as Excel | zav@isep.ipp.pt |
| Weather data / South of Brazil [Abreu, 2000] | Measurement site: Horizon at station Florianopolis Sampling period: 1 hour Data: Solar radiation, Temperature, Humidity, Wind Start: 01 – January – 2000; End: 31 – January – 2000 Season: Summer (South of Brazil) Start: 01 – July – 2000; End: 31 – July – 2000 Season: Winter (South of Brazil) | Download January as Excel Download July as Excel | abreu@ifsc.edu.br |
| Weather 1 / South of Brazil | Measurement site: Sao Martinho da Serra Sampling period: 1 minute Data: Solar radiation, Temperature, Humidity, Wind Start: 01 – July – 2014; End: 31 – July – 2014 Season: Winter (South of Brazil) Start: 01 – January – 2015; End: 31 – January – 2015 Season: Summer (South of Brazil) | Download July 2014 as Excel Download January 2015 as Excel | sonda@inpe.br |
| Weather 2 / Midwest of Brazil | Measurement site: Brasilia station Sampling period: 1 minute Data: Solar radiation, Temperature, Humidity, Wind Start: 01 – July – 2014; End: 31 – July – 2014 Season: Winter (Midwest of Brazil) Start: 01 – January – 2015; End: 31 – January – 2015 Season: Summer (Midwest of Brazil) | Download July 2014 as Excel Download January 2015 as Excel | sonda@inpe.br |
| Weather 3 / Northeast of Brazil | Measurement site: Petrolina station Sampling period: 1 minute Data: Solar radiation, Temperature, Humidity, Wind Start: 01 – July – 2014; End: 31 – July – 2014 Season: Winter (Northeast of Brazil) Start: 01 – January – 2015; End: 31 – January – 2015 Season: Summer (Northeast of Brazil) | Download July 2014 as Excel Download January 2015 as Excel | sonda@inpe.br |
Wind Based Generation
| Source | Short Description | Link | Contact |
|---|---|---|---|
| GECAD wind speed [Ramos, 2013] | The data-base includes the values of the wind speed, recorded with time intervals of 10 minutes during the entire year of 2011. | Download as Excel | zav@isep.ipp.pt |
General Energy Data
| Source | Short description | Link | Contact |
|---|---|---|---|
| Energy | European Union Open Data Portal | Multiple open datasets in the energy domain, made available by the institutions and other bodies of the European Union (EU). Data are free for you to use and reuse for commercial or non-commercial purposes. | Website | Contact |
| Non-intrusive Appliance Load Monitoring (NIALM) | Public data sets on household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NIALM) or energy disaggregation. | Website | matthias.stifter@ait.ac.at |
| Data 13 Bus Distribution Network [Canizes, 2019] | Consumption and netwrok data of a MV 13-bus network in a smart city environment | Zenodo | zav@isep.ipp.pt |
| Dataset of uGIM deployed in an office building [Gomes, 2019] | A dataset of sensor and energy data collected from uGIM system in an office building located in Portugal. The dataset has a total of three days (24 hour records for each 10 seconds): – summer day – winter day – cloudy day | Zenodo | zav@isep.ipp.pt |
| uGIM: week monitorization data of a microgrid with five agents (10/04/19-16/04/19) [Gomes, 2020a] | This dataset has data regarding a week (from 10-04-2019 to 16-04-2019) of a microgrid with five players (all offices). All agents have consumption and generation data. One of the agents also has sensor data, such as temperature, movement and humidity. | Zenodo | zav@isep.ipp.pt |
| uGIM: a week with peer-to-peer transactions (03/06/2019 – 09/06/2019) [Gomes, 2020b] | This dataset has data regarding a week (from 03-06-2019 to 09-06-2019) of a microgrid with five players (all offices). All agents have consumption and generation data and are able to participate in peer-to-peer transactions using an auction model. The dataset presents the data regarding: energy values (consumption and generation); energy forecasting (consumption and generation); auction participations; and peer-to-peer transactions. | Zenodo | zav@isep.ipp.pt |
| Week monitorization data of a microgrid with five agents (04/08/2019 – 10/08/2019) [Gomes, 2020a] | This dataset has data regarding a week (from 04-08-2019 to 10-08-2019) of a microgrid with five players (all offices). All agents have consumption and generation data. One of the agents also has sensor data, such as temperature, movement and humidity. | Zenodo | zav@isep.ipp.pt |
| uGIM: a week with peer-to-peer transactions (02/03/2020 – 08/03/2020) [Gomes, 2020c] | This dataset has data regarding a week (from 02-03-2020 to 08-03-2020) of a microgrid with five players (all offices). All agents have consumption and generation data and are able to participate in peer-to-peer transactions using an auction model. The dataset presents the data regarding: energy values (consumption and generation); energy forecasting (consumption and generation); auction participations; and peer-to-peer transactions. | Zenodo | zav@isep.ipp.pt |
| Single-unit and multi-unit peer-to-peer transactions in a microgrid (uGIM dataset) [Teixeira, 2021] | uGIM is a microgrid intelligent management platform that can represent individual end-users using a multi-agent approach. This dataset has data regarding two weeks (May 13th to May 18th, 2019, and September 30th to October 6th, 2019) where auction-based peer-to-peer transactions were performed in a real microgrid. The data was collected by uGIM agents and auctions were executed every hour. The hour-ahead auctions are performed by the sellers in a fully distributed approach. To create this dataset two NanoPi M1 Plus (with 1.2 GHz quad-core CPUs and 1 GB of RAM running the Ubuntu 16.04.6 LTS operating system), and three Raspberry Pi Model B+ (with 1.4 GHz 64-bit quad-core CPUs and GB of RAM running the Raspberry Pi OS operating system) were used. | Zenodo | zav@isep.ipp.pt |
| Energy consumption and renewable generation data of 5 aggregators – 15 minute resolution (13 bus grid) [Almeida, 2021] | Type: Energy consumption and renewable generation data Period of data collection: 19-03-2019 to 25-03-2019 (15-minute 672 periods) Resolution: 15 minutes Network: 13-bus MV grid Aggregator list: Further data: | Zenodo | zav@isep.ipp.pt |
| Production line dataset for task scheduling and energy optimization – Schedule Optimization [Mota, 2021] | The case study of this dataset uses real production data, provided by a textile company that manufactures hang tags. Their working schedule is from 7h00 of Monday to 23h00 of Saturday. This dataset uses a period of 5 minutes for all task durations and energy data. The case study considers a six-day period from 7h00 of Monday to 23h00 of Saturday. The scheduling algorithm was used for three machines that share the same cell. | Zenodo | zav@isep.ipp.pt |
| Production line dataset for task scheduling and energy optimization – Demand Response Participation [Mota, 2021] | Using the previous dataset at https://zenodo.org/record/4106746 it was simulated an announcement of a demand response program at period 757, describing a demand response event from period 937 (Friday at 21:00h) to 960 (Friday at 23:00h) , where each period represents five minutes. The demand response program imposed a limit consumption, during its event, of 2.5 kWh. The announcement of the demand response allowed the use of the proposed solution to limit the energy consumption. For that, the algorithm described in section 3.3 was executed at period 769 (Friday at 7:00h). | Zenodo | zav@isep.ipp.pt |
| Energy consumption and PV generation data of 50 prosumers and energy consumption of 40 electric vehicles – 15-minute resolution [Faia, 2021] | Type: Energy consumption and PV generation data Duration: 24 hours (15-minute 96 periods) Resolution: 15 minutes Sheets description: – Gen: Contain the generation of each prosumer – Load: Contain the load of each prosumer – Prices_buy: Buy prices for prosumers (EDP commercial retailer) – Prices_sell: Price of feed-in in Portugal (2019 and 2020) – Bat: Contain the information of prosumers batteries – Grid: Contain the information related with prosumers grid interactions – EV_Moves: contain the information if the EV are on movement or stopped (0- stopped, 1 on move) – EV_min: contain the minimum limit for EV batteries (% of maximum capacity of battery) – EV_con: contain the minimum limit for EV batteries (% of maximum capacity of battery) – EV_Buy_Prices: Buy prices for EV (EDP commercial retailer) – EV_Grid: Contain the information related with EV grid interactions – EV_inf: contain information of EVs batteries – EV_model: Models of EVs used – General Information: contain information regarding all 90 players – Tariff: Contain 13 different tariff for buy electricity (EDP commercial retailer) | Zenodo | zav@isep.ipp.pt |
| Joint optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources including CO2 emissions: Study data [Lima, 2021] | Table 1 shows the operational scenarios, while the data for the substations is shown in Table 2. The demand data for each node is shown in Table 3. The parameters related to RES are shown in Table 4 and Table 5. The PV units have a nominal power capacity of 100 kW and are composed by 40 modules with 2.5 kW each. A maximum of 60 generators of this type can be installed in each node. The power factors for PV and WT units are defined as 0.98 and 0.90, respectively. Table 6 presents the data for the two EV chargers alternatives. Finally, Fig.1 shows the initial system topology. R&D center: http://www.gecad.isep.ipp.pt and https://www.feis.unesp.br/#!/lapsee Project website: http://www.gecad.isep.ipp.pt/CENERGETIC/ | Zenodo | zav@isep.ipp.pt |
References mentioned in the Data Sets tables above
| [Abreu, 2000] | Samuel L. Abreu, Sergio Colle, Anand P. Almeida, Sylvio L. M. Neto Qualificação e Recuperação de Dados de Radiação Solar Medidos em Florianópolis – SC 8th Brazilian Congress of Thermal Engineering and Sciences Porto Alegre, Brazil, 2000 |
| [Almeida, 2021] | José Almeida, João Soares, Bruno Canizes, Fernando Lezama, M. A. Ghazvini Fotouhi and Zita Vale Evolutionary Algorithms for Energy Scheduling under uncertainty considering Multiple Aggregators 2021 IEEE Congress on Evolutionary Computation (CEC), 2021, pp. 225-232 doi: 10.1109/CEC45853.2021.9504942 |
| [Canizes, 2011] | Bruno Canizes, Zita Vale, João Soares, Hussein Khodr Fuzzy Monte Carlo Mathematical Model for Load Curtailment Minimization in Transmission Power Systems 17th Power Systems Computation Conference (PSCC 2011) Stockholm, Sweden August 22 – 26, 2011 http://hdl.handle.net/10400.22/1422 |
| [Canizes, 2012] | Bruno Canizes, João Soares, Zita Vale, Hussein Khodr Hybrid Fuzzy Monte Carlo Technique for Reliability Assessment in Transmission Power Systems Energy, vol. 45, no. 1, pp. 1007-1017, September 2012 doi: 10.1016/j.energy.2012.06.049 Accession Number: WOS: 000309243700108 |
| [Canizes, 2015] | Bruno Canizes, Marco Silva, Pedro Faria, Sergio Ramos, Zita Vale Resource Scheduling in Residential Microgrids Considering Energy Selling to External Players Clemson University Power Systems Conference 2015 (PSC 2015), Madren Conference Center Clemson, South Carolina, USA 10-13 March, 2015 doi: 10.1109/PSC.2015.7101700 |
| [Canizes, 2019] | Bruno Canizes, João Soares, Zita Vale, Juan M. Corchado Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City Energies 2019, 12(4), 686 doi: 10.3390/en12040686 |
| [Faia, 2021] | Ricardo Faia, João Soares, Mohammad Ali Fotouhi Ghazvini, John F. Franco, Zita Vale Local Electricity Markets for Electric Vehicles: An Application Study Using a Decentralized Iterative Approach Frontiers in Energy Research, 04 November 2021 doi: 10.3389/fenrg.2021.705066 |
| [Fernandes, 2013] | Filipe Fernandes, Hugo Morais, Pedro Faria, Zita Vale, Carlos Ramos SCADA House Intelligent Management for Energy Efficiency Analysis in Domestic Consumers 2013 IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America 2013) São Paulo, Brazil 15-17 April, 2013 doi: 10.1109/ISGT-LA.2013.6554494 |
| [Fernandes, 2016] | Filipe Fernandes, Hugo Morais, Valdomiro V. Garcia, Luis Gomes, Zita Vale and Nelson Kagan Dynamic loads and micro-generation method for a House Management System 2016 Clemson University Power Systems Conference (PSC) Clemson, SC, USA, 2016 doi: 10.1109/PSC.2016.7462829 |
| [Foroozandeh, 2020] | Zahra Foroozandeh, Sérgio Ramos, João Soares, Fernando Lezama, Zita Vale, António Gomes, Rodrigo L. Joench A mixed binary linear programming model for optimal energy management of smart buildings Energies 13, no. 7: 1719 doi: 10.3390/en13071719 |
| [Gomes, 2015] | Luis Gomes, Filipe Fernandes, Pedro Faria, Marco Silva, Zita Vale, Carlos Ramos Contextual and Environmental Awareness Laboratory for Energy Consumption Management Clemson University Power Systems Conference 2015 (PSC 2015), Madren Conference Center Clemson, South Carolina, USA 10-13 March, 2015 doi: 10.1109/PSC.2015.7101678 |
| [Gomes, 2019] | Luis Gomes, João Spínola, Zita Vale, Juan M. Corchado Agent-based architecture for demand side management using real-time resources’ priorities and a deterministic optimization algorithm Journal of Cleaner Production, Volume 241, 20 December 2019, 118154 doi: 10.1016/j.jclepro.2019.118154 |
| [Gomes, 2020a] | Luis Gomes, Zita Vale, Juan M. Corchado Microgrid management system based on a multi-agent approach: An office building pilot Measurement, Volume 154, 15 March 2020, 107427 doi: 10.1016/j.measurement.2019.107427 |
| [Gomes, 2020b] | Luis Filipe de Oliveira Gomes μGIM – Microgrid intelligent management system based on a multi-agent approach and the active participation of end-users Ph.D. Thesis doi: 10.14201/gredos.144238 |
| [Gomes, 2020c] | Luis Gomes, Zita Vale, Juan M. Corchado Multi-Agent Microgrid Management System for Single-Board Computers: A Case Study on Peer-to-Peer Energy Trading IEEE Access, vol. 8, pp. 64169-64183, 2020 doi: 10.1109/ACCESS.2020.2985254 |
| [Lima, 2021] | Tayenne Dias de Lima, John F. Franco, Fernando Lezama, João Soares, Zita Vale Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions Energy Inform 4, 33, 2021 doi: 10.1186/s42162-021-00157-5 |
| [Mota, 2021] | Bruno Mota, Luis Gomes, Pedro Faria, Carlos Ramos, Zita Vale, and Regina Correia Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events Energies 14, no. 2: 462, 2021 doi: 10.3390/en14020462 |
| [Pinto, 2012] | Tiago Pinto, João Soares, Sérgio Ramos, Zita Vale Very Short-term Wind Forecasting to Support VPP Operation 11th Wind Integration Workshop Lisbon, Portugal 12-13 November 2012 |
| [Pinto, 2014] | Tiago Pinto, Sergio Ramos, Tiago Sousa, Zita Vale Short-term Wind Speed Forecasting using Support Vector Machines IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2014) Orland, Florida, USA 9-12 December 2014 |
| [Ramos, 2011] | Sérgio Ramos, J. P. Soares, Zita Vale, Hugo Morais A data-mining-based methodology for wind forecasting ISAP 2011 – 16th International Conference on Intelligent System Application to Power Systems, IEEE Hersonissos, Crete, Greece 25-28 September 2011 |
| [Ramos, 2012a] | Sérgio Ramos, Sónia F. Pinto, João J. Santana Development of a Solar Cell Model Using PSCAD 2nd International Workshop on Integration of Solar Power into Power Systems 12-13 November 2012 |
| [Ramos, 2012b] | Sérgio Ramos, Marco Silva, Filipe Fernandes, Zita Valea Modelling Real Solar Cell using PSCAD/MATLAB 2nd International of Solar Power into Power Systems (SIW12) Lisboa, Portugal, 13-15 November, 2012 http://hdl.handle.net/10400.22/1441 |
| [Ramos, 2013] | Sérgio Ramos, João Soares, Tiago Pinto, Zita Vale Short-term Wind Forecasting to Support Virtual Power Player Operation EWEA Annual Event 2013 (EWEA 2013) Vienna, Austria, 4-7 Fevereiro, 2013 |
| [Soares, 2013a] | João Soares, Zita Vale, Bruno Canizes, Hugo Morais Multi-objective Parallel Particle Swarm Optimization for Day-ahead Vehicle-To-Grid Scheduling CIASG 2013 – Computational Intelligence Applications in Smart Grid (CIASG) at the IEEE SSCI 2013 (IEEE Symposium Series on Computational Intelligence) Singapura, 15-19 Abril, 2013 doi: 10.1109/CIASG.2013.6611510 |
| [Soares, 2013b] | João Soares, Zita Vale, Hugo Morais Decision support tool for Virtual Power Players: Hybrid Particle Swarm Optimization applied to Day-ahead Vehicle-To-Grid Scheduling ISAP 2013 – 17th International Conference on Intelligent System Applications to Power Systems Tóquio, Japão, 01-04 Julho, 2013 |
| [Spavieri, 2017] | Guilherme Spavieri, Ricardo T.M. Ferreira, Ricardo A.S. Fernandes, Guilherme G. Lage, Daniel Barbosa, Mário Oleskovicz Particle Swarm Optimization-based approach for parameterization of power capacitor models fed by harmonic voltages Applied Soft Computing, vol. 56, pp. 55 – 64, Julho, 2017 doi: 10.1016/j.asoc.2017.02.017 |
| [Teixeira, 2021] | Daniel Teixeira, Luis Gomes, Zita Vale Single-unit and multi-unit auction framework for peer-to-peer transactions International Journal of Electrical Power & Energy Systems, Volume 133, December 2021, 107235 doi: 10.1016/j.ijepes.2021.107235 |
| [Vale, 2021] | Zita Vale, Pedro Faria, Omid Abrishambaf, Luis Gomes Photovoltaic generation and temperature for the year 2019 (Version 1.0) [Data set]. Zenodo. doi: 10.5281/zenodo.5017638 |