A Novel Approach Based Optimal Power Scheduling of GENCOs to Improve the Profit in Electricity Market Considering Wind Power Generation

Abstract

Objectives:The main objective of this present work is to maximize the profit of Power Generation Companies (GENCOs) and minimize the environmental emissions in a competitive electricity Market. The unit commitment methodology is considered to enhance the profit of GENCOs. Here, the steam plants are integrated with wind farms to improve the income of GENCOs. Methods: A novel nature-inspired human-based optimization algorithm of Corona Virus Herd Immunity Optimizer (CVHIO) is proposed for solution of this problem. Initially, the searching parameters of CVHIO determine the best scheduling of thermal and wind generators. Then the CVHIO efficiently optimizes the thermal and wind variables like real power, reserve power allocation and wind speed. Findings: Numerical example with IEEE 39 bus test system (10 thermal units 24 hours) integrated with two wind generating forms is considered to assess the performance of planned CVHIO. The obtained simulation results of Thermal power, Wind power; Reserve power, Emission level, Revenue, Total operating cost and Profit are tabulated. Novelty: The CVHIO is recently developed powerful optimizer and parameter free algorithm, so easily reaches the global optimal solutions. The final outcomes of this approach are analyzed with other conventional and intelligent techniques for validating the superiority of devised algorithm.