Combined Stochastic Optimization of Frequency Control and Self-Consumption with a Battery
For owners of behind-the-meter battery storage systems, this work provides a method to increase revenue by jointly optimizing frequency control and self-consumption, addressing a practical need for maximizing battery utilization.
This work presents an optimized control strategy for a battery storage system that simultaneously provides primary frequency control and self-consumption, using a linear recharging policy and robust optimization to manage stochastic constraints. Simulations with real frequency data show that optimally combining the two services significantly increases battery value.
Optimally combining frequency control with self-consumption can increase revenues from battery storage systems installed behind-the-meter. This work presents an optimized control strategy that allows a battery to be used simultaneously for self-consumption and primary frequency control. Therein, it addresses two stochastic problems: the delivery of primary frequency control with a battery and the use of the battery for self-consumption. We propose a linear recharging policy to regulate the state of charge of the battery while providing primary frequency control. Formulating this as a chance-constrained problem, we can ensure that the risk of battery constraint violations stays below a predefined probability. We use robust optimization as a safe approximation to the chance-constraints, which allows to make the risk of constraint violation arbitrarily low, while keeping the problem tractable and offering maximum reserve capacity. Simulations with real frequency measurements prove the effectiveness of the designed recharging strategy. We adopt a rule-based policy for self-consumption, which is optimized using stochastic programming. This policy allows to reserve more energy and power of the battery on moments when expected consumption or production is higher, while using other moments for recharging from primary frequency control. We show that optimally combining the two services increases value from batteries significantly.