Name
Title | ||
|---|---|---|
Environmentally constrained economic dispatch using Pareto archive particle swarm optimisation |
Abstract | ||
|---|---|---|
The objective proposed is of environmental/economic dispatch (EED) taking into account the environmental impact to achieve simultaneously the minimisation of fuel costs and pollutant emissions, while satisfying the operational constraints of power systems. The multiarea environmental/economic dispatch (MEED) deals with the optimal power dispatch of multiple areas (or countries). In this investigation, EED/MEED is proposed to address the environmental issue during the economic dispatch. In this article, the EED/MEED problem is first formulated and then a proposed Pareto archive multiobjective particle swarm optimisation (PAMPSO) algorithm is developed to derive a set of Pareto-optimal solutions. Its aim is to dispatch the power among different areas by simultaneously minimising the operational costs and pollutant emissions. In the proposed PAMPSO, local search is used to increase its search efficiency. To ensure the system security, tie-line transfer limits between different areas are incorporated as a set of constraints in the optimisation process. Numerical studies based on a four-area test power generation system are carried out to demonstrate the validity of the proposed optimisation method as well as the results from different problem formulations. Comparative results of PAMPSO and three other competitive multiobjective evolutionary algorithms (MOEAs) are also presented. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1080/00207720903576472 | Int. J. Systems Science |
Keywords | Field | DocType |
environmental issue,proposed optimisation method,environmental impact,optimal power dispatch,pollutant emission,economic dispatch,power system,proposed pampso,four-area test power generation,particle swarm optimisation,different area,local search,satisfiability,system security,power generation,unit commitment | Particle swarm optimization,Economic dispatch,Mathematical optimization,Evolutionary algorithm,Power system simulation,Electric power system,Minimisation (psychology),Local search (optimization),Pareto principle,Mathematics | Journal |
Volume | Issue | ISSN |
41 | 5 | 0020-7721 |
Citations | PageRank | References |
9 | 0.60 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yee Ming Chen | 1 | 64 | 8.33 |
| Wen-Shiang Wang | 2 | 9 | 0.60 |