The Working Group on Modern Heuristic Optimization (WGMHO) under the IEEE PES Analytic Methods in Power Systems (AMPS) Committee aims at identifying emerging developments in computational intelligence for solving power system optimization problems.
The transition of power systems worldwide towards widespread use of renewable energy sources and higher demand side response entails significant structural changes and new challenges in routine operation and planning activities. Within the framework of the so-called smart grid, many of these activities requires efficient solution of different types of optimization problems, whose mathematical complexity motivates further research and development on more powerful optimization methods.
Pioneer and recently introduced heuristic optimization methods are undergoing further extensions and developments by using novel high level mechanisms (metaheuristics) for improved search exploration and exploitation, including the possibility of using an ensemble of methods in a complementary manner (hybridization). Thus, the WGMHO will create task forces (TFs) to work on panels and tutorials on the application and benchmarking of these developments in all areas of the power and energy systems.
As an initial step, a special panel and competition was held at the 2014 IEEE PES General meeting, whose focus was on application of modern heuristic optimization methods for solving optimal power flow (OPF) problems. Guidelines and material related to the competition can be found here. Interested researchers are kindly encouraged to test their algorithms on the 2014 OPF test bed and to submit their results to J.L.RuedaTorres@tudelft.nl in case they beat the best results achieved so far.
This webpage is also intended to serve as a platform for dissemination of the activities of the WGMHO. This includes sharing experiences in the development and application of heuristic optimization algorithms, exchange of new ideas, and source codes.
2021 IEEE PES General Meeting Technical Session
Applications of Advanced Heuristic Optimization Methods in Sustainable Power and Energy Systems
Summary
The operation and planning of sustainable electrical power systems faces several challenges, like modified steady-state and dynamic properties, and high uncertainty due to the variability and high share of renewable power generation and random variations of demand and ancillary service providers. The different types of optimization problems defined for different applications in operation and planning are hard-to-solve due to the necessity of considering a large number of aspects, like probabilistic models that represent uncertain variables, combined with the complexity of a search space defined by non-linear equations modelling the physical system performance, as well as special problem properties like non-convexity, discontinuity and multi-modality. This panel will promote the vast expertise synthetized in the book “Applications of Modern Heuristic Optimization Methods in Power and Energy Systems”, edited by Prof. Kwang Y. Lee and Prof. Zita A. Vale. The book is the latest publication of the Working Group on Modern Heuristic Optimization (WGMHO). Namely, the panel will present advanced heuristic optimization methods and their applications in problems related to Planning and Operation of Sustainable Transmission and Distribution Systems, Control System Design, Integration of Renewable Energy in Smart Grid, and Electricity Markets.
Session Type: | Panel Session |
Time: | Wednesday, July 28, 2021 8:00 AM – 10:00 AM |
Room: | Online |
Committee: | (AMPS) Intelligent Systems |
Co-Sponsoring Committee 1: | Unspecified |
Co-Sponsoring Committee 2: | Unspecified |
Session Chair 1: | Zita Vale Polytechnic of Porto, Portugal |
Session Chair 2: | Kwang Y. Lee Baylor University |
Chair
Prof. José Luis Rueda Torres, Delft University of Technology, Netherlands
Vice-chair
Prof. Eduardo Asada, University of São Paulo, Brazil
Secretary
Prof. Samuele Grillo , Politecnico di Milano, Italy
Former chairpersons
Prof. Kwang Y. Lee, Baylor University, USA