Robust operating zones identification for energy storage day-ahead operation

This paper presents a tool to robustly allocate the allowable operating zones of active and reactive power margins for multi-energy storage systems (ESSs) without violating typical distribution system constraints. This tool helps ESSs to manage its day-ahead energy independently without violating the power system constraints. The main contribution is considering the power uncertainties (loads and renewable energy) without taking very conservative decisions. For defining a robust operating zone (ROZ) for ESSs; first, a particle swarm optimization (PSO) algorithm detects the day-ahead worst-case power flow due to loads, renewable energy sources (RESs), and contingency uncertainties. Second, a second-order cone programming problem (SOCP) optimizer determines the maximum charge and discharge active powers for each ESS that maintains safe system operation limits (voltage limits, cables capacity, and reverse power flow limits). While an uncertainty budget designed by the fuzzy expert, the PSO uses this budget to reshape its searching space with less conservatism. Case studies with one hundred different uncertainty scenarios are conducted on a real 41-bus Canadian system. Simulation results have shown that the proposed algorithm provides robust operating zones for ESSs that consider uncertainties with reducing conservatism.