A Hybrid Lagrangian and Improved Class Topper Optimization for Optimal Sizing of Battery Energy Storage System

Power generation using distributed generation become the potential solution to augment the conventional grid issues and mitigate global environmental impact. However, the problems associated with distributed generation are sporadic in nature, stochastic, and pose a threat to the effective functioning of the power system. Ungoverned supply demand balance in autonomous microgrid (MG) compels to incorporate battery energy storage system (BESS). Moreover, the installation of BESS enhances the reserve capacity and frequency stability of the MG as well. Non-optimal selection of size of BESS fetches meagre results. The proposed work highlights a new hybrid Lagrangian relaxation and improved class topper optimization which is a cost-based approach for the optimal sizing of BESS considering the operational, emission cost of MG and aims to reduce the total cost of the system. A hybrid method has been developed for robust scenario reduction by combining K-means and density based spatial clustering applications with noise (DBSCAN) for WT scenario reduction and DBSCAN and principal component analysis for PV and load demand scenario reduction. This hybrid approach offers advantages in handling clusters of varying shapes and densities, providing a more accurate representation of the underlying data structure. Extensive investigation has been carried out in order to get the optimal size of BESS by comparing various optimization algorithms such as particle swarm optimisation, grey wolf optimisation, modified grey wolf optimisation, whale optimisation algorithm and sine cosine algorithm with the proposed method. Three case studies are executed on sizing of BESS to analyse the reduction in emission cost and operational cost. From the results, it is found that the proposed algorithm is outperforming. From case 1 to case 2, the operational cost is reduced from 1620.4 to 1512 which is a reduction of 7.1%, case 1 to case 3 it is 1620.4 to 1422.84 a reduction of 13.8% and from case 2 to case 3 it is reduced from 1512 to 1422.84 which is a reduction of 6.2%.