Welcome to the IEEE Task Force on Advanced Methods for Computational Intensive Power System Planning Applications (CIPSPA) Website!
This new task force was approved by IEEE Power and Energy Society (PES) Power System Operation, Planning and Economics (PSOPE) Committee in 2017. The task force aims to bring together experts in power systems, computer science, and applied mathematics to discuss and explore solutions that address the computational challenges in power system planning.
Call For Participation
You are cordially invited to participate in the newly approved IEEE Task Force on Advanced Methods for Computational Intensive Power System Planning Applications. Power system professionals facing such challenges are particularly encouraged to participate. We also welcome proposals on the relevant topics in the form of panels, webinars, tutorials, or special sections on IEEE Transactions. Please direct any question to Task Force Chair Dr. Rui Bo (rbo@mst.edu, rui.bo@ieee.org). Look forward to your participation!
The scope, activities, expected deliverables and other details of this Task Force are listed below for your reference. For past annual meetings, please see the meeting minutes.
Annual Task Force meetings will be held in the IEEE General Meetings. Please see meeting announcements and activities.
If you are new to this task force and interested in joining, please fill out the form.
NEW Task Force Survey: Identifying Computational Bottlenecks in Power System Planning. We kindly request you to take a few minutes to complete this survey: https://forms.gle/XLrZNvFQGJNDpJUaA .
Background
Power industry was an early adopter of computer technologies. Modern power system planning relies heavily on computer assisted simulation and optimization. In recent years, the computational needs have dramatically expanded due to the increased level of uncertainty facing the industry that resulted from renewable energy development, demand side participation and policy landscape changes. The traditional analytical and computational methods as well as the tools built upon them are facing great challenges in catching up with the ever growing computational demand of modern applications in power system planning.
This task force aims to bring together experts in power systems, computer science and mathematics to discuss and explore solutions that address the computational challenges through developing and employing new highly computational efficient analytical and computational methods, including but not limited to, scenario reduction, parametric analysis, machine learning, high performance computing, cloud computing, and other parallel computing techniques. The ultimate objective of this task force is to provide a platform for researchers and industry practitioners to collaborate and push the forefront of technologies used to address the computing needs in computational intensive power system planning applications.
Scope and Activities
The task force is expected to last 4 to 5 years and will be reviewed annually, with the focus on state of the art development in advanced methods for computational intensive applications in power system planning. The following is a list of topical areas that we propose to review within the scope of this task force:
1. Review of computational intensive applications in power system planning, current methods and challenges
As power system planning applications are getting increasingly sophisticated and computationally demanding, it is beneficial to review computational intensive applications, existing methodology and tools, and challenges facing the industry presently and in the foreseeable future. Synthesizing such information will identify proper planning applications and areas to focus on.
2. Emerging analytical methods and computing technology
In recent years, with advancement of computer technology and computational methods, power system engineers have attempted to solve traditional power system planning applications in innovative ways such as by using high performance computing platforms, including massive multicore systems, cloud computing platform, GPU-accelerated platform, and others. At the same time, techniques such as scenario reduction, parametric analysis, algorithmic decomposition, machine learning are being explored from methodology perspective. The strengths, weaknesses and adaptability of these emerging technology and methods will be examined for their capability to power system planning applications.
3. New advanced analytical methods and computing platform for computational intensive power system applications
The increased level of uncertainties facing power system planning has been continuously expanding the scope of conventional power system analyses such as contingency analysis, scenario analysis, production cost simulations, robust optimization, as well as pushing for the computational performance of such analyses. The increasing volume of available system data from devices such as PMU and smart meters also poses great challenges to conventional tools. The emerging analytical methods and computing technology will be employed and implemented to address the needs of contemporary power system planning applications with extremely high computational needs. New analytical methods and computing platform will also be explored. Ultimately, this Task Force will provide best practice recommendations to industry practitioners looking for innovative solutions to address conventional and unconventional planning needs.
Outcomes/Deliverable
The main expected deliverable of this task force will be two IEEE publications, one in the form of an IEEE journal paper, and one in the form of a technical report, documenting best practices and significant advancement. The paper will be issued approximately 2 years after the start of the task force, and will cover key insights from the task force, with a section on each of the proposed topics. The report will be issued 4 years after the start of the task force. The report will include an overview of the contemporary power system planning applications demanding intensive computation, the emerging technologies in computing and analytical methods, and finally present the development on new methods for those power system planning applications. The publications are to provide guidelines for industry practitioners seeking insights and directions to improve their practices and performance of computational intensive power system planning applications.
Another deliverable consists of panel sessions to be hosted at IEEE Power and Energy Society meetings with representation from Task Force members and interested IEEE members.