Open AccessA novel approach towards uncertainty modeling in multiobjective optimal power flow with renewable integration
Author(s) -
Saha Anulekha,
Bhattacharya Aniruddha,
Das Priyanath,
Chakraborty Ajoy Kumar
Publication year - 2019
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12136
Subject(s) - mathematical optimization , power flow , metaheuristic , computer science , probabilistic logic , renewable energy , interior point method , multi objective optimization , electricity generation , electric power system , power (physics) , mathematics , engineering , artificial intelligence , physics , quantum mechanics , electrical engineering
Summary This paper presents a novel methodology for solving multiobjective optimal power flow (MOPF) considering uncertain renewable generation. Two‐point estimate method (2PEM) is employed to take care of the uncertainty in renewable generation. Optimal power flow (OPF) is a very challenging optimization problem to solve due to its nonlinear nature. To overcome the constraints faced by classical optimization techniques, a novel hybrid metaheuristic algorithm is designed and applied to solve the MOPF problem. Since uncertainty in generation is considered, a probabilistic approach is required. Five different algorithms have been applied to the MOPF problem using 2PEM for the sake of comparison, and results show superiority of the proposed metaheuristic in achieving optimal results.