Strategic bidding using fuzzy adaptive gravitational search algorithm in a pool based electricity market

作     者：Kumar, J. Vijaya Kumar, D. M. Vinod Edukondalu, K. 

作者机构：Natl Inst Technol Dept Elect Engn Warangal 506004 Andhra Pradesh India 

出 版 物：《APPLIED SOFT COMPUTING》 (Appl. Soft Comput. J.)

年 卷 期：2013年第13卷第5期

页      面：2445-2455页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Electricity market Bidding strategies Market clearing price (MCP) Fuzzy inference Gravitational search algorithm 

摘      要：A novel stochastic optimization approach to solve optimal bidding strategy problem in a pool based electricity market using fuzzy adaptive gravitational search algorithm (FAGSA) is presented. Generating companies (suppliers) participate in the bidding process in order to maximize their profits in an electricity market. Each supplier will bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. The gravitational search algorithm (GSA) is tedious to solve the optimal bidding strategy problem because, the optimum selection of gravitational constant (G). To overcome this problem, FAGSA is applied for the first time to tune the gravitational constant using fuzzy IF/THEN rules. The fuzzy rule-based systems are natural candidates to design gravitational constant, because they provide a way to develop decision mechanism based on specific nature of search regions, transitions between their boundaries and completely dependent on the problem. The proposed method is tested on IEEE 30-bus system and 75-bus Indian practical system and compared with GSA, particle swarm optimization (PSO) and genetic algorithm (GA). The results show that, fuzzification of the gravitational constant, improve search behavior, solution quality and reduced computational time compared against standard constant parameter algorithms. (C) 2012 Elsevier B. V. All rights reserved.