Probabilistic Pricing for Collaborative Demand‐Side Management With Coordinated Operation of Energy Storage Systems for Optimal Peak Load Control in Smart Grids

ABSTRACT Peak load management is a pivotal aspect of power generation and distribution, representing one of the primary challenges for power companies. A key feature of smart grids is their capability to manage available resources effectively to mitigate peak load while accounting for the inherent uncertainties in load demand and the generation of all renewable energy sources. Thereby, this paper proposes a two‐stage coordination approach that integrates price‐based demand response (PBDR) and energy storage systems, encompassing Battery Energy Storage Systems (BESS) and Compressed Air Energy Storage (CAES). This approach integrates CAES with BESSs to optimise the charging and discharging processes while minimising degradation costs. Specifically, it aims to address the substantial degradation expenses of BESSs by strategically utilising CAES as a complementary storage solution. The objective is to minimise operational costs while controlling peak demand load in smart microgrids. Moreover, to simultaneously address the inherent uncertainties associated with the demanded load and the generating power of renewable energy sources, a method incorporating scenario generation and reduction is introduced to improve scheduling accuracy and enhance the reliability of energy management. To tackle this multifaceted challenge, a novel scenario‐based Developed Two‐Stage Interval Optimisation (DTSIO) model has been proposed to effectively address uncertainty. By employing the scenario generation method in conjunction with the k‐means technique to reduce scenarios with low probabilities of occurrence, the analysis process is optimised for better problem‐solving efficiency. The proposed model's efficacy is validated through its implementation on a 33 and 69 bus microgrid, showcasing its ability to enhance profitability, manage peak load, reduce reliance on the upstream grid, and lower carbon dioxide emissions.