Voltage control in a smart distribution network using demand response

Increasing demand on the conventional grid coupled with the unwillingness to add new transmission facilities, constitute a potential threat that can ultimately sprawl to jeopardize the grid's reliability. Demand response (DR) is a potent smart grid technology that can take care of that perceived threat, instead of constructing more power plants to meet the increasing demand. DR provides electricity consumers with opportunities to manage their electricity usage for the purpose of reducing their electricity bills and alleviating the power peak-average-ratio. A Genetic Algorithm (GA) based-optimization approach is developed in this paper to consider the optimum scheduling of energy utilization for consumers, participating in the DR program, to reduce voltage deviations and feeder losses. The IEEE 123 test feeder is considered as the test system. Effectiveness of the proposed method is validated through a time sequence analysis over a 24-hourly simulation period. The corresponding voltage profile is analyzed under different operating conditions, with a high penetration level of wind energy. Test results show that the DR tool causes reduction in system losses and enhances system capability to maintain voltages within the permissible limits.