Energy storage scheduling for imbalance reduction of strategically formed balancing groups

摘要

A Power Producer and Supplier (PPS) in the deregulated energy market requires forward market interactions to procure energy as precisely as possible in order to reduce imbalance energy (on-line demand vs. supply gap). This paper presents, 1) (off-line) an effective demand aggregation based strategy for creating a number of balancing groups that leads to higher predictability of group-wise demand, 2) (on-line) a robust energy storage scheduling that minimizes the imbalance for a particular balancing group considering the demand prediction uncertainty. The group formation is performed by a probabilistic programming approach using Bayesian Markov Chain Monte Carlo (MCMC) method, applied on the historical demand statistics. An upper-limit of the storage rating/capacity is derived as a by-product of Bayesian MCMC, which is utilized in the on-line operation. A robust energy storage scheduling method is proposed that minimizes the on-line imbalance energy and cost (a non-linear function of imbalance energy) while incorporating the demand uncertainty of a particular group. The proposed methods are applied on the real apartment buildings' demand data in Tokyo (Japan). Simulation results are presented to verify the effectiveness of the proposed methods.