Virtual energy storage through decentralized load control with quality of service bounds

We propose a decentralized algorithm to help reduce demand-supply imbalance in a power grid by varying the demand from loads, just like charging and discharging a battery. The algorithm ensures strict bounds on the consumers' quality of service (QoS) by constraining the bandwidth of demand variation. A model-predictive-control formulation is adopted to compute local decisions at the loads. The algorithm is decentralized in the sense that loads do not communicate with one another. Instead, loads coordinate using local measurements of the grid frequency, which provide information about global demand-supply imbalance. It is envisioned that consumers will be recruited through long-term contracts, aided by the QoS guarantees provided by the proposed scheme. Simulation results show that loads are able to reduce frequency deviations while maintaining QoS constraints and that the performance of the algorithm scales well with the number of loads. Closed-loop stability is established under some assumptions.