Load-Shedding Optimization Using Hybrid Grey Wolf - Whale Algorithm to Improve The Isolated Distribution Networks

Abstract

The integration of distributed generation allows the distribution network to operate in either on-grid or off-grid mode. In off-grid mode, the power supply from the main grid is interrupted, and distributed generation becomes the main source of power to meet the load's power demand. The absence of power supply from the main grid reduces the grid's ability to meet load power demand. The load power demand is larger than the distributed generation capacity, causing a power deficit in the network. This paper studies strategies for restoring power balance through optimal load shedding, taking into account the presence of priority loads that require power demand to be maintained and met. The optimization objective is to maximize the remaining load with an optimal composition so that the power loss is minimal. The load-shedding optimization uses a hybrid Grey Wolf Algorithm and Whale Optimization Algorithm (GW-WOA). The performance of GW-WOA is tested by load shedding optimization on a 118-bus IEEE radial distribution system integrated with 12 units of DG. The network loading factor variation consists of 80%, 100%, and 140% of the base load. Regarding all loading factors, the GW-WOA hybrid algorithm is superior to the standard GWO and WOA. The GW-WOA hybrid algorithm can converge faster to obtain the global optimal solution to realize power balance, overcome power deficit, maximize remaining load, and minimize power loss in the network. The GW-WOA hybrid algorithm has improved the performance of load-shedding optimization in isolated distribution networks with global optimal results and shorter iterations.