Optimal placement of remote-controlled switches in distribution networks considering load forecasting

Abstract

The application of long-term load forecasting (LTLF) in solving the problem of optimal placement of remote-controlled switches (RCSs) in distribution networks is considered in this paper. The mixed-integer linear programming (MILP) formulation for the RCSs placement problem is modified to include LTLF results obtained using the proposed reference historical load data model. Different methods are selected and validated in terms of forecasting accuracy. The modified MILP model for RCSs placement problem has been tested on distribution network RBTS-bus4 which has been used extensively for optimal switch placement studies. It is shown that LTLF results could significantly improve the accuracy of total cost estimation when compared to approximated constant annual load increase rates regularly used in previous research papers. Load profiling data have been included in LTLF analysis. The forecasting of annual U.S. dollar values has been performed to additionally improve the optimal solution accuracy. It is highly recommended for distribution companies to consider LTLF before making the final decision on RCSs investment.