Transmission network congestion control by DESS through interval computation and capacity optimization via hybrid DE‐PSO technique

Abstract

Transmission congestion is one of major drawbacks of deregulated power system. Congestion gradually violates the physical, operational and policy constraints of the present electricity market. Congestion management in huge power system remains a challenging and tough task, which can be achieved by introducing one or more Distributed Energy Resources (DERs) such as Distributed Generation (DG), electric vehicles, modern micro grid, Energy Storage Systems (ESSs) etc. over congested lines. Consequently, this work proposes the hourly congestion management by optimal allocation of DG in ‘24 hours’ time frame. Further, Transmission Congestion Rent is used to determine the optimal and sub optimal locations for DG, whereas Differential Evolution and Particle Swarm Optimization based hybrid optimization technique is exploited to identify optimal DG size. In this work, solar based DG along with battery based ESS is considered to act as Distributed Energy Storage System ‘DESS. Subsequently, Interval computation method is introduced in this work to consider the intermittency of solar DG. Battery Energy Storage System ‘BESS’ is integrated with DGs due to its excess energy storage capability during off-load period and make it available at peak load conditions, thereby enhancing the overall efficiency of the network. The ‘24 hours’ solar irradiance and temperature data of Delhi, India is taken into account to mathematically model the power generated from Solar DG. The proposed methodology is tested on IEEE 30-bus system and ‘24 hours’ demand data is generated from the original IEEE load data. From the obtained results, it has been established that the hybrid optimization technique results into a better solution as compared to their individual enforcement in managing available generation resources and congestion problem.