Ensuring expected security cost with flexible resources using modified DE algorithm based dynamic optimal power flow

Abstract

This paper presents a new approach to solve the Expected-Security-Cost with Dynamic Optimal Power Flow (ESCDOPF) problem incorporating flexible resources (FRs). The main objective of this approach is to minimize the expected total operation cost, which includes the overall system cost in both pre-and post-contingency states, by satisfying all the constraints of the model. The proposed model incorporates FRs such as game-theory based demand-response-management, battery-energy-storage-systems, and HVDC systems to reduce overall operating costs by ensuring adequate power balance and also maintaining the voltage and line loading limits. To solve the proposed model on an IEEE-30 bus system, a “Modified Differential Evolution” (MDE) algorithm is developed based on a combination of new crossover and new local adaptation approaches. This combination guarantees a good balance between exploration as well as extraction power with less computational costs and population size. The effectiveness of the proposed algorithm is tested for OPF, DOPF and ESCDOPF problems. From the results, it is observed that the proposed algorithm for the ESCDOPF problem helps to minimize the total system operation cost up to 3.04% in all scenarios when tested with/without FRs during pre-and post-contingency states.