Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration


In order to optimize their assets, electrical power distribution companies seek out various techniques to improve system operation and its different variables, like voltage levels, active power losses and so on. A few of the tools applied to meet these objectives include reactive power compensation, use of voltage regulators, and network reconfiguration. One target most companies aim at is power loss minimization; one available tool to do this is distribution system reconfiguration. To reconfigure a network in radial power distribution systems means to alter the topology changing the state of a set of switches normally closed (NC) and normally opened (NO). In restructured electrical power business, a company must also consider obtaining a topology as reliable as possible. In most cases, reducing the power losses is no guarantee of improved reliability. This paper presents a multiobjective algorithm to reduce power losses while improving the reliability index using the artificial immune systems technique applying graph theory considerations to improve computational performance and Pareto dominance rules. The proposed algorithm is tested on a sample system, 14-bus test system, and on Administracion Nacional de Electricidad (ANDE) real feeder (CBO-01 23-kV feeder).