IEEE

2017 Smart Grid Operation Problems (Competition & panel)

2017 Competition & panel: Evaluating the Performance of Modern Heuristic Optimizers on Smart Grid Operation Problems

The increasing penetration of renewable energy sources and the new and adaptive patterns of demand side response entail a higher level of variability of the operation of electrical sustainable power systems. In this context, operational problems posse highly complex mathematical properties (e.g. non-convexity, discontinuity, multi-modality, high-dimensionality), which emphasizes the need of advanced optimization solvers in order to find optimal solutions that guarantee efficient and flexible operations.

This panel and competition, which took place at the 2017 IEEE PES General Meeting, introduced two benchmark problems (also denoted as optimization test beds):

  • Test bed 1: Stochastic OPF based active-reactive power dispatch. Developers: Sergio Rivera (Universidad Nacional de Colombia), Andres Romero (Universidad Nacional de San Juan), José Rueda (Delft University of Technology), Kwang Y. Lee (Baylor University), István Erlich (University Duisburg-Essen)
  • Test bed 2: Optimal scheduling of distributed energy resources. Developers: Zita Vale and João Soares (Institute of Engineering – Polytechnic of Porto)

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 are challenged to solve the benchmarks, which are treated as black-box problems. They are only allowed to improve the methodological framework of their algorithms.

The call for competition was made on 14-01-2017. It was indicated that the first three ranked algorithms will be 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 30-01-2017, indicating their names, affiliation, and the algorithm to be used. The deadline for submission of results and codes was 30-03-2017.

The evaluation process finished on 28-4-2017. The top three ranked algorithms (sorted lists):

Test bed 1: Stochastic OPF based active-reactive power dispatch

 

Cross entropy method and evolutionary particle swarm optimization (CEEPSO)

Developers:

Leonel Carvalho, INESC TEC (Portugal)

Vladimiro Miranda, INESC TEC and Faculty of Engineering of the University of Porto – FEUP, (Portugal)

Armando Leite da Silva, Pontifícia Universidade Católica do Rio de Janeiro (Brazil)

Carolina Marcelino, Centro Federal de Educação de Minas Gerais (Brazil)

Elizabeth Wanner, School of Engineering and Applied Sciences (UK) and Centro Federal de Educação de Minas Gerais (Brazil)

Jean Sumaili, INESC TEC (Portugal)

Variable Neighborhood Search algorithm (VNS)

Developers:

Leonardo H. Macedo, São Paulo State University-Ilha Solteira (Brazil)

John F. Franco, São Paulo State University-Ilha Solteira (Brazil)

Rubén Romero, São Paulo State University-Ilha Solteira (Brazil)

Miguel A. Ortega-Vazquez, University of Washington (USA)

Marcos J. Rider, University of Campinas (Brazil).

Levy Differential Evolutionary Particle Swarm Optimization (LEVY DEEPSO)

Developers:

Kartik S. Pandya, CSPIT CHARUSAT-Gujarat (India)

S.K. Joshi, The M.S. University of Baroda-Gujarat (India)

S.N.Singh, IIT-Kanpur U.P. (India)

 

Test bed 2: Optimal scheduling of distributed energy resources

 

Variable Neighborhood Search algorithm (VNS)

Developers:

Leonardo H. Macedo, São Paulo State University-Ilha Solteira (Brazil)

John F. Franco, São Paulo State University-Ilha Solteira (Brazil)

Rubén Romero, São Paulo State University-Ilha Solteira (Brazil)

Miguel A. Ortega-Vazquez, University of Washington (USA)

Marcos J. Rider, University of Campinas (Brazil).

Modified Chaotic Biogeography-based Optimisation (CBBO) with Random Sinusoidal Migration

Developers:

Sergio Rivera, Universidad Nacional de Colombia (Colombia)

Camilo Cortes, Universidad Nacional de Colombia (Colombia)

Sergio Contreras, Universidad Nacional de Colombia (Colombia)

María Guzmán, Universidad Nacional de Colombia (Colombia)

Cross entropy method and evolutionary particle swarm optimization (CEEPSO)

Developers:

Leonel Carvalho, INESC TEC (Portugal)

Vladimiro Miranda, INESC TEC and Faculty of Engineering of the University of Porto – FEUP, (Portugal)

Armando Leite da Silva, Pontifícia Universidade Católica do Rio de Janeiro (Brazil)

Carolina Marcelino, Centro Federal de Educação de Minas Gerais (Brazil)

Elizabeth Wanner, School of Engineering and Applied Sciences (UK) and Centro Federal de Educação de Minas Gerais (Brazil)

Jean Sumaili, INESC TEC (Portugal)

 

The details of the evaluation process and the order of the top 3 algorithms for each test bed was announced in the 2017 IEEE PES General Meeting.

 

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: Prof. Kwang Y. Lee, Baylor University, USA (kwang_y_lee@baylor.edu)

 

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 2017 IEEE PES General meeting:

Sergio Rivera, Universidad Nacional de Colombia, Colombia

Test bed 1: Stochastic OPF based active-reactive power dispatch

Zita Vale, Institute of Engineering – Polytechnic of Porto, Portugal

Test bed 2: Optimal scheduling of distributed energy resources

Leonardo H. Macedo, São Paulo State University-Ilha Solteira, Brazil

Solving Smart Grid Operation Problems Through Variable Neighborhood Search

Kartik S. Pandya, CSPIT CHARUSAT-Gujarat, India

Levy Differential Evolutionary Particle Swarm Optimization (LEVY DEEPSO)

Sergio Rivera, Universidad Nacional de Colombia, Colombia

Modified Chaotic Biogeography-based Optimisation (CBBO) with Random Sinusoidal Migration

Leonel Carvalho, INESC TEC, Portugal

Cooperative Combination of the Cross-Entropy Method and the Evolutionary Particle Swarm Optimization to Improve Search Domain Exploration and Exploitation

José Rueda, Delft University of Technology, Netherlands

Evaluating the Performance of Modern Heuristic Optimizers on Smart Grid Operation Problems (INCLUDING RANKING)

 

Codes and results of the top three algorithms – Test bed 1

First Place: CEEPSO.
Second Place: VNS.
Third Place: LEVY DEEPSO.

Codes and results of the top three algorithms – Test bed 2

First Place: VNS.
Second Place: Modified CBBO.
Third Place: CEEPSO.

 

Journal paper about the competition:

Fernando Lezama, João Soares, Zita Vale, Jose Rueda, Sergio Rivera, István Elrich, “2017 IEEE competition on modern heuristic optimizers for smart grid operation: Testbeds and results,” Swarm and Evolutionary Computation, (In press) Available online since 21 May 2018.

 

Important dates:

Call for competition: 14 January 2017

Confirmation of participation: 30 January 2017

Submission of results and codes: 30 March 2017

Announcement of best three ranked algorithms: 28 April 2017

2017 IEEE PES General Meeting: 16-20 July 2017