The enhancement of distribution reactive power compensation in Taipower with immune algorithm

SUMMARY This paper presents an optimal capacitor planning strategy by considering the reactive load duration curvesof distribution feeders to reduce system power loss and enhance reactive power compensation in Taipower. The objective function is formulated by including feeder peak power loss, annual energy loss and investment cost of capacitors with discrete capacities. In the proposed method, the immune algorithm (IA) is applied to solve the optimization problem and to derive the optimal sizes and locations of capacitors to be installed along the feeders by representing the objective function and constraints as antigens. The affinity calculation is embedded in the solution process to guarantee the diversity and prevent the stagnation of local sub-optimality. After performing the genetic evolution, an antibody which fits the antigen best is determined to be the optimal capacitor planning. The three-phase load flow analysis is executed by considering time-varying load characteristic of customers to solve system power loss on annual basis with various capacitor-planningscenarios. The marginal cost benefit (MCB) of the reactivepower compensation is applied to solve the timings for the switched-type capacitors. A practical distribution feeder is selected for computer simulation to demonstrate the effectiveness of the proposed IA methodology to solve the capacitor planning by evaluating the yearly peak power loss and total energy loss over the life cycle of capacitor investment. Copyright # 2009 John Wiley & Sons, Ltd.