Single and multi-area multi-fuel economic dispatch using a fuzzified squirrel search algorithm  

作　　者：V.Ponnuvel Sakthivel P.Duraisamy Sathya 

机构地区：[1]Department of Electrical and Electronics Engineering,Government College of Engineering,Dharmapuri,Tamilnadu,636704,India [2]Department of Electronics and Communication Engineering,FEAT,Annamalai University,Chidambaram,Tamilnadu,608002,India

出　　处：《Protection and Control of Modern Power Systems》2021年第1期147-159,共13页现代电力系统保护与控制（英文）

摘　　要：Multi-Area Multi-Fuel Economic Dispatch (MAMFED) aims to allocate the best generation schedule in each area and to offer the best power transfers between different areas by minimizing the objective functions among the available fuel alternatives for each unit while satisfying various constraints in power systems. In this paper, a Fuzzified Squirrel Search Algorithm (FSSA) algorithm is proposed to solve the single-area multi-fuel economic dispatch (SAMFED) and MAMFED problems. Squirrel Search Algorithm (SSA) mimics the foraging behavior of squirrels based on the dynamic jumping and gliding strategies. In the SSA approach, predator presence behavior and a seasonal monitoring condition are employed to increase the search ability of the algorithm, and to balance the exploitation and exploration. The suggested approach considers the line losses, valve point loading impacts, multi-fuel alternatives, and tie-line limits of the power system. Because of the contradicting nature of fuel cost and pollutant emission objectives, weighted sum approach and price penalty factor are used to transfer the bi-objective function into a single objective function. Furthermore, a fuzzy decision strategy is introduced to find one of the Pareto optimal fronts as the best compromised solution. The feasibility of the FSSA is tested on a three-area test system for both the SAMFED and MAMFED problems. The results of FSSA approach are compared with other heuristic approaches in the literature. Multi-objective performance indicators such as generational distance, spacing metric and ratio of non-dominated individuals are evaluated to validate the effectiveness of FSSA. The results divulge that the FSSA is a promising approach to solve the SAMFED and MAMFED problems while providing a better compromise solution in comparison with other heuristic approaches.

关 键 词：Fuzzy set theory Heuristic optimization Multi-area economic dispatch Pareto-optimal front Squirrel search algorithm Tie-line constraint 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]