Decision making under wind power generation and load demand uncertainties: a two-stage stochastic optimal reactive power dispatch problem. (2nd January 2022)

• Record Type: Journal Article
• Authors: Ucheniya, Ravi; Saraswat, Amit; Siddiqui, Shahbaz Ahmed
• Is Part Of: International journal of modelling & simulation. Volume 42:Number 1(2022)
• Page Start: 47
• Page End: 62
• Publication Date: 2022-01-02
• Subjects: Wind energy integration -- uncertainty analysis -- scenario-based analysis -- stochastic optimization -- hybrid fuzzy evolutionary algorithm; Mathematical models -- Periodicals; Simulation methods -- Periodicals; Mathematical models; Simulation methods; Periodicals; 003.3
• DOI: 10.1080/02286203.2020.1829443
• Languages: English
• ISSNs: 0228-6203

Abstract

ABSTRACT: For the modern power systems with intensive renewable energy sources integration, the uncertainty analysis of its performance become necessary for desired decision making. An appropriate choice of modelling and handling methodology, for uncertain parameters associated with the renewable energy, remains one of major concerns for the power system engineers. This paper presents a stochastic optimization framework for some critical decisions making on reactive power dispatch in two consecutive stages by incorporating both generation outputs of wind farms along with load demand uncertainties. The proposed method is generic for optimal reactive power dispatch in any modern wind-integrated power system. A methodology based on scenario-based analysis is adopted for handling these uncertainties. Moreover, a hybrid fuzzy evolutionary algorithm (HFEA) is applied to obtain high-quality solutions for this complex two-stage stochastic optimization problem. Furthermore, the proposed HFEA-based stochastic optimization approach is tested on IEEE 14-bus power system with two distinct wind farms. The simulation results prove the robustness of HFEA for generating feasible and optimal solutions for all the considered scenarios.