Energy Storage Integration For Grid Reliability

The prevailing need to transition to carbon neutrality in the power sector mandates the global community to implement resources and investment in renewable energy sources (RES) as an alternative to conventional thermal plants. However, the inherent stochastic nature of RES introduces significant challenges in maintaining a stable power supply, thereby accentuating the indispensable role of Energy Storage Systems (ESS). While current research primarily focuses on identifying critical locations in the grid such as transmission line bottlenecks to place ESS, a critical aspect often neglected is the availability of surplus power from RES to charge the ESS. It is essential to assess the available power at each potential site to ensure efficient utilization of energy storage, which will significantly enhance grid reliability. This paper presents a methodology that integrates Sequential Monte Carlo simulations, sensitivity analysis via Lagrange Multipliers, and linear optimization to identify optimal sites for integration of ESS to grid. The method effectively identifies the best location by balancing two key factors: maximizing the contribution of ESS to prevent power outages (load curtailment) and ensuring sufficient excess power to supply the energy storage systems. The algorithm is implemented on the modified IEEE One Area RTS-96 test system, incorporating a substantial integration of wind power.