Robust Allocation of Reserve Policies for a Multiple-Cell Based Power System

This paper applies a robust optimization technique for coordinating reserve allocations in multiple-cell based power systems. The linear decision rules (LDR)-based policies were implemented to achieve the reserve robustness, and consist of a nominal power schedule with a series of linear modifications. The LDR method can effectively adapt the participation factors of reserve providers to respond to system imbalance signals. The policies considered the covariance of historic system imbalance signals to reduce the overall reserve cost. When applying this method to the cell-based power system for a certain horizon, the influence of different time resolutions on policy-making is also investigated, which presents guidance for its practical application. The main results illustrate that: (a) the LDR-based method shows better performance, by producing smaller reserve costs compared to the costs given by a reference method; and (b) the cost index decreases with increased time intervals, however, longer intervals might result in insufficient reserves, due to low time resolution. On the other hand, shorter time intervals require heavy computational time. Thus, it is important to choose a proper time interval in real time operation to make a trade off

Decentralized and discretized control for storage systems offering primary frequency control

The provision of ancillary services is an additional revenue stream for the owners of inverter-equipped storage systems, such as batteries and electric vehicles. As real demonstrations have shown, primary frequency control (PFC) is a suitable and economically viable service for small-scale energy storage (ES) systems. This paper proposes a decentralized stochastic control policy, which significantly reduces ES units’ losses when providing PFC. The proposed controller can be tuned to obtain the desired service reserve provision errors, while achieving a balance between tracking accuracy and efficiency. An extension of the algorithm significantly reduces the switching rate of the devices by up to 95%. Analytical expressions for the reserve errors and the switching rates, dependent on the aggregation size and the controllers’ settings, are derived and verified by simulations. Simulation results show that the proposed controller can significantly reduce ES units’ losses when they are providing PFC by 8–15.5%, while achieving the expected tracking performance