Optimal Rescheduling of Real Power to Mitigate Congestion with Incorporation of Wind Farm Using Gravitational Search Algorithm in Deregulated Environment

Abstract

In deregulated power system environment the congestion is considered as one of the vital issues concerning the system’s security and reliability. The Independent System Operator (ISO) bears the task to manage the congestion in the open access electricity market. This article puts forward a noble and efficient Congestion Management (CM) technique with the embodiment of wind farm as a renewable resource alongside the implementation of an efficient and reliable meta-heuristic technique. The proposed CM approach is established contemplating the Bus Sensitivity Factor (BSF) and the Generator Sensitivity Factors (GSF). The positioning of the wind farm is optimally achieved considering the BSF. The GSF values are computed to sort out the most sensitive generators for participating in the CM problem. The Gravitational Search Algorithm (GSA) is introduced in order to optimally minimize the active power yield of the generators taking part in the process of CM. The GSA is one of the latest meta-heuristic algorithms based on the Newton’s Laws of gravitational forces. The result obtained by GSA is contrasted with the outcomes reported in the past literatures. Modified 39-bus New England system is considered for the implementation of the potency of the proposed approach of CM with the inclusion of wind farm as a renewable resource.