2018 Operational planning of sustainable power systems (Competition & panel) « IEEE PSACE Working Group on Modern Heuristic Optimization

2018 Competition & panel: Emerging heuristic optimization algorithms for operational planning of sustainable electrical power systems

The operational planning of sustainable electrical power systems is facing higher stochasticity introduced by massive integration of variable renewable generation and the diversification of the sources for flexibility in highly interactive energy markets and multi-energy sector coupling. Therefore, the scheduling problems involved in operational planning need consideration of non-linear models, probabilistic models, and a large number of decision variables. This entails mathematically complex and computationally expense formulations, which cannot be tackled by classical optimization tools.

This panel and competition, which took place at the 2018 IEEE PES General Meeting, introduced two benchmark problems (also denoted as optimization test beds):

Test bed 1: Stochastic OPF in Presence of Renewable Energy and Controllable Loads. Developers: Sergio Rivera (Universidad Nacional de Colombia), Ameena Saad Al-Sumaiti (Masdar Institute, Khalifa University of Science and Technology), Diego Rodriguez (GERS USA LLC), Manuel Gers (GERS USA LLC), José Rueda (Delft University of Technology), Kwang Y. Lee (Baylor University), and István Erlich (University Duisburg-Essen).
Test bed 2: Dynamic OPF in Presence of Renewable Energy and Electric Vehicles. Developers. Sergio Rivera (Universidad Nacional de Colombia), Ameena Saad Al-Sumaiti (Masdar Institute, Khalifa University of Science and Technology), Camilo Cortes (Universidad Nacional de Colombia), José Rueda (Delft University of Technology), Kwang Y. Lee (Baylor University), and István Erlich (University Duisburg-Essen).

Besides, the panel presented the results and a comparative evaluation concerning the performance of different modern heuristic optimization algorithms, which are developed by different researchers worldwide. Researchers were challenged to solve the benchmarks, which are treated as black-box problems. They were only allowed to improve the methodological framework of their algorithms.

The first three ranked algorithms were selected for presentation at the panel, for which only PowerPoint presentations are required. All interested participants were encouraged to send an email to j.l.ruedatorres@tudelft.nl by 20-01-2018, indicating their names, affiliation, and the algorithm to be used. The deadline for submission of results and codes was 20-03-2018.

The evaluation process finished on 20-4-2018. The top two ranked algorithms (sorted lists) for each test bed:

Test bed 1: Stochastic OPF in Presence of Renewable Energy and Controllable Loads.

CE+EPSO (Cross-Entropy Method and Evolutionary Particle Swarm Optimization)

Developers:

Leonel Carvalho. INESC TEC, Porto, Portugal
Vladimiro Miranda. INESC TEC, Porto, Portugal and Faculty of Engineering of the University of Porto – FEUP, Porto, Portugal
Armando Leite da Silva. Pontifícia Universidade Católica do Rio de Janeiro – PUC Rio, Rio de Janeiro, Brazil
Carolina Marcelino. COPPE/Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Elizabeth Wanner. School of Engineering and Applied Sciences, Birmingham, UK and Centro Federal de Educação de Minas Gerais – CEFET-MG, Minas Gerais, Brazil

EE-CMAES (Entropy Enhanced Covariance Matrix Adaptation Evolution Strategy)

Developers:

Kartik Pandya. Dept. of Electrical Eng., CSPIT, Charusat, Changa, India

Jigar Sarda. Dept. of Electrical Eng., CSPIT, Charusat, Changa, India

Test bed 2: Dynamic OPF in Presence of Renewable Energy and Electric Vehicles. Developers.

CE+EPSO (Cross-Entropy Method and Evolutionary Particle Swarm Optimization)

Developers:

SNA (Shrinking Net Algorithm)

Developers:

Chengchen Qian. Stated Grid Shanghai Municipal Electrical Power Company, China
Haoming Liu. College of Energy and Electrical Engineering, Hohai University, China
Yunhe Hou. Department of Electric and Electronics Engineering, the University of Hongkong, China

Organizers of the panel:

Chairman: Dr. José Rueda, Delft University of Technology, Netherlands (j.l.ruedatorres@tudelft.nl)
Co-chair 1: Prof. István Erlich ,University of Duisburg-Essen, Germany (istvan.erlich@uni-due.de)
Co-chair 2: Dr. Sergio Rivera, Universidad Nacional de Colombia, Colombia (srriverar@unal.edu.co)

The details of the evaluation process and the order of the top 2 algorithms for each test bed were announced in the 2018 IEEE PES General Meeting.

Downloads:

The call for competition can be downloaded here.

The problem definitions, implementation & submission guidelines, and Matlab codes for the test beds can be downloaded here.

Presentations given in the panel session at the 2018 IEEE PES General meeting:

15PESGM2441-Test bed 1: Stochastic OPF in Presence of Renewable Energy and Controllable Loads

Presenter: Sergio Rivera; Universidad Nacional de Colombia

15PESGM2442-Test bed 2: Dynamic OPF in Presence of Renewable Energy and Electric Vehicles

Presenter: Sergio Rivera; Universidad Nacional de Colombia

15PESGM2850-Entropy Enhanced Covariance Matrix Adaptation Evolution Strategy

Presenter: Kartik Pandya; CSPIT, CHARUSAT-Gujarat

Jigar Sarda; CSPIT, CHARUSAT-Gujarat