Solving Probabilistic Optimal Power Flow with Battery Energy Storage in Transmission Networks Using Salp Swarm Algorithm

The probabilistic optimal power flow (POPF) problem is one of the most important non-linear difficulties for power network design for the efficient operation of contemporary upgraded energy system networks. In today’s world, energy storage technologies are essential for integrated power networks; that might be utilized for peak shaving as well as minimizing fluctuations caused by decentralized power sources. Battery technology advances made it possible to integrate extensive battery energy storage systems (BESs) into distribution networks. With the Salp Swarm Algorithm (SSA), a novel methodology is presented in this paper to solving the POPF problem in the IEEE-57 network system that incorporates BESs as an alternative power source along with the conventional thermal generators. The results of the study show that the SSA is an excellent method for addressing the POPF issue in electricity networks that have BESs. In addition, the efficacy of the suggested approach is thoroughly demonstrated through numerous simulation outcomes, statistical evaluations, and convergence properties of the proposed optimization mechanism.