Comparative Study of the Price Penalty Factors Approaches for Bi-objective Dispatch Problem via PSO

Mohammed Amine MEZIANE


The main ambition of utilities is to schedule the committed generating units outputs to meet the required load demand at minimum operating cost with minimum emission level caused by fossil based thermal generating units simultaneously. An allowable deviation in fuel cost and feasible tolerance in fuel cost has been called Combined Economic and Emission Dispatch (CEED) problem which is one of the important optimization problems concerning power system issues. A Particle Swarm Optimization algorithm (PSO) is based stochastic optimization technique which is inspired by the social learning of birds or fishes is applied to solve CEED problem. This paper analyses the impact of six penalty factors like "Min-Max", "Max-Max", "Min-Min", "Max-Min", "Average"and "Common" price penalty factors for CEED problem. The Price Penalty Factor for the CEED is the ratio of fuel cost to emission value. This bi-objective dispatch problem is solved for the Real West Algeria power network consisting of 22 buses with 7 generators. Results prove capability of PSO in solving CEED problem with various penalty factors and it concludes that Min-Max price penalty factor provides the best compromise solution in comparison to the other penalty factors. 


Combined Economic Emission Dispatch; Particle Swarm Optimization; Price Penalty Factor; Real West Algeria electrical Network; Bi-Objective Dispatch Problem

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