A hybrid multiobjective optimization technique for optimal sizing of BESS‐WtE supported multi‐MW HRES to overcome ramp rate limitations on thermal stations

In India, favorable renewable energy policies have resulted in a higher proportion of renewable energy in the system. However, this led to the lower capacity utilization factor of thermal power stations. Any additional burden on thermal stations by enforcing higher ramp rates during peak hours would seriously affect technically as well as economically. In this regard, further renewable additions must be supported by energy storage systems to meet the ramping requirements. Waste‐to‐energy (WtE) plants play a crucial role in improving grid resilience in a high‐renewable energy scenario to support expensive battery energy storage systems. In this article, the potential of WtE is assessed for a smart city in India, selected based on the possible urban and industrial growth, along with three other renewable energy technologies such as floating solar, bifacial rooftops solar, and wind energy conversion systems. The selected location has a total renewable energy potential of 439 MW. To achieve the municipality's techno‐economic objectives, a multiobjective‐enabled adaptive local attractor–based quantum‐behaved particle swarm optimization (ALA‐mQPSO) is proposed with mutation. With the proposed ALA‐mQPSO, Pareto optimal sets of the hybrid renewable energy sources aided by the combination of battery energy storage system and WtE plant is achieved. The Pareto fronts are then compared with the benchmark techniques such as differential evolution along with the recently proposed multiobjective golden eagle optimizer algorithm. The results show that with the addition of the WtE plant, the grid can provide greater reliability for an optimal set of BESS and HRES. The obtained optimal configuration resulted in a levelized cost of $0.0539 along with just 0.049% of loss of power supply probability and 0.048 cycle loss of BESS, and when compared with similar works from the literature, the results proved to be superior and realistic. Potiential Assesment and optimal Sizing of Hybrid Renewable Energy system To improve the Grid Sustainbility.