Two-Stage Stochastic Optimization of Sodium-Sulfur Energy Storage Technology in Hybrid Renewable Power Systems

Energy storage systems (ESS) are considered among the key elements for mitigating the impact of renewable intermittency and improving the economics for establishing a sustainable power grid. The high cost combined with the need for optimal capacity and allocation of ESS proves to be pertinent to maintain the power quality as well as the economic and operational viability of a renewable integrated power grid. In case of ESS sizing in terms of optimized power (kW) and energy (kWh) capacity, an oversized ESS results in high capital investment and in some cases increases the system losses. Conversely, an undersized ESS significantly impacts the reliability and availability of the power network. In this paper, a two-stage stochastic optimization strategy is presented for sodium-sulfur (NaS) battery considering the output power uncertainties of wind and solar energy sources. The objective aims at minimizing the total cost of NaS-ESS incorporation while maintaining acceptable system operation using AC optimal power flow. Many scenarios from the historical data are considered for the development of the system stochasticity on a 24-bus reliability test system (RTS) that is incorporated with a hybrid renewable energy system (HRES), namely solar and wind. Moreover, to demonstrate the efficacy of the proposed stochastic optimization framework a comparative analysis is performed with a deterministic optimization technique based on several reliability indices.