COMPETITIVE ELECTRICAL ENERGY MARKET BIDDING STRATEGY USING OPTIMIZING TECHNIQUES, PARTICLE SWARM OPTIMIZATION (PSO) & ADAPTIVE PARTICLE SWARM OPTIMIZATION (APSO)

摘要

In an open competitive power market for power providers (generators) need an appropriate bidding form to maxmized individual profit The main contributon of the present paper is to increase supplier (GENCOs) income and minimize consumer (DISCOMs) costs taking into account. The limits of available power supply, power demand market clearance price (MCP) and constraints. It is extremely imperative that the electrical energy market is balanced according to reasonable rules. In this paper, Particles swarms Optimization (PSO) and Adaptive Particles Swarms Optimization (APSO) approaches towards as a transaction optimization problem. These optimization techniques (PSO and APSO) contain many characteristics analogous to evolutionaries computational strategies along with Genetic optimizational Algorithm (GA). Firstly, by integrating the random solution and updating the generation, we get optimal results in the problem space. The possible solutions known as particles are flowing in every direction through the problem area in the PSO, subsequent the best possible recent (particle) resolution. Adaptive PSO (APSO) is recommended for enhancing PSO efficiency through weight varies according to the particle size (i.e. a different weight modification technique). The main characteristics of the proposed method can be represented by a mathematical solution with six generators (GENCOs) and two large consumers (DISCOMs), are taken into consideration in which total profit is better than in APSO as compared to PSO as regards optimal profit.