Congestion management using multi-objective hybrid DE-PSO optimization with solar-ess based distributed generation in deregulated power Market

Abstract

Transmission congestion is one of the major drawbacks of deregulated power system. Due to increase in load demand, generation increases, but capacity of transmission line is limited, and transmission lines carry power more than its rated capacity, as a result congestion occurs. Congestion management in deregulated power system is a challenging and tough task which can be achieved by introducing one or more Distributed Generators (DG) at optimal location. Optimal location and sizing of DGs is very important for maximizing the social welfare function which is profit to both the producers and consumer of electricity. In this paper hourly congestion management is proposed. It manages the network congestion by optimal placement and sizing of DG in ‘24 h’ time frame. Transmission Congestion Rent (TCR) is used to find the optimal location for DG placement whereas hybrid Differential Evolution (DE) and Particle Swarm Optimization (PSO) technique is used for finding optimal size of DG. In this work, Solar PV along with Energy Storage System (ESS) is utilized as Distributed Energy Storage System (DESS). ESS along with DG is used to store surplus energy during off-load period which will be utilized at peak load thereby enhancing the overall efficiency of the system. 24 h solar irradiance and temperature data of Delhi is taken to mathematically model the power generated from Solar PV. Results obtained with hybrid optimization technique are compared with PSO based optimization. It is observed that hybrid optimization technique outperforms the PSO optimization technique in managing resources and congestion problem in the network for the ‘24 h’ time frame. Proposed work has been carried out on IEEE 30 bus test system.