Abstract

Conventional economic load dispatch problem uses deterministic models, which are however not able to reflect some real situations in practical applications since certain inaccurate and uncertain factors are normally involved in system operations. Stochastic models are more suited to be used for investigating some of the power dispatch problems. In this paper, both deterministic and stochastic models are first formulated, and then an improved particle swarm optimization (PSO) method is developed to deal with the economic load dispatch while simultaneously considering the environmental impact. Comparative studies are carried out to examine the effectiveness of the proposed approach. First, a comparison is made between the proposed PSO approach and other approaches including weighted aggregation and evolutionary optimization. Then, based on the proposed PSO, the impacts of different problem formulations including stochastic and deterministic models on power dispatch results are investigated and analyzed.

Keywords: Stochastic economic emission load dispatch; Multi-objective optimization; Particle swarm optimization; Stochastic search and optimization

Article Outline

1. Introduction

2. Stochastic model

2.1. Expected fuel cost

2.2. Expected emission

2.3. Expected transmission loss

2.4. Constraints

2.5. Problem statement

3. Particle swarm optimization

4. The proposed approach

4.1. Multi-objective PSO framework

4.2. Encoding scheme

4.3. Guides selection

4.4. Archiving

4.5. Constraints handling

4.6. Computational procedure

5. Simulation results and analysis

5.1. Comparison with weighted aggregation

5.2. Comparison with evolutionary optimization

5.3. Deterministic versus stochastic models

6. Concluding remarks

References