Optimal Reactive Power Dispatch in Electricity Markets Using A Multiagent-Based Differential Evolution Algorithm

Reactive power dispatch in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. In an open electricity market reactive power support is an ancillary service for real power transportation. From the viewpoint of ISO, this paper provides a dispatching reactive power model, based on optimal power flow, by which both the cost of procuring reactive power as auxiliary service and the losses of active power are minimized. In this paper the cost of reactive power support consists of two components: reactive power cost of generators and shunt capacitors. In addition an extremely powerful differential evolution optimization approach based on multiagent systems (MADE) is presented, and applied to the reactive power optimization problem in electricity markets. In the proposed method, agents live in a lattice-like environment and each agent competes with its neighbors, and also learns by using its own knowledge. MADE uses these agent-agent interactions and the evolutionary mechanism of DE to obtain the global optimum. The effectiveness of the proposed method is then verified using the IEEE 30-bus system, and its performance is compared to other stochastic search approaches.