Comparison between Differential Evolution Algorithm and Particle Swarm Optimization for Market Clearing with Voltage Dependent Load Models

Abstract

The day ahead concept of real power market clearing is applied for generator scheduling in a deregulated environment. The earlier approach of cost minimization declines the consumer benefit instead considers the reduction of overall generation cost. This brings in limitation which is compensated by the approach of social welfare maximization which is to maximize the profit for the supplier and consumer i.e. societal benefit. During optimization of these objectives, the behavior of control variables are observed keeping the different technical and operating constraints of the system. The modeling of loads as voltage dependent is implemented so as to analyze the effect on load served maximization and voltage stability enhancement index. The former tries to serve the maximum loads and the later maintains the flat profile of the voltages to avoid the voltage collapse on overloading and fault situations. The obligation by market participants to achieve the best solution is done by differential evolution algorithm and particle swarm optimization. A comparison is also made between these two optimization techniques. The investigation is performed on IEEE 30 bus system.