A privacy-preserving and aggregate load controlling decentralized energy consumption scheduling scheme

In this manuscript, a decentralized and heuristic energy consumption scheduling scheme is proposed for implementing the day-ahead price-based demand side management program in a power distribution network. A customer, who participates in the proposed scheme, profits by minimizing his consumption cost and taking into account his own financial benefits and operational needs. This is done for each customer without a need for iterative interaction and other customers’ consumption information. Also, the supplier takes advantage of this scheme, by controlling the aggregate network consumption peak through solving a simplified optimization problem, which needs less information about customers’ consumption. The customers’ privacy is preserved in this scheme, because no individual behaviour, in the forthcoming scheduling time horizon, can be extracted from the data sent to the supplier. Besides, in one sense it is a fair solution because the less customer’s consumption peak is, the more relative financial benefit he gets. In our simulated case study, the proposed scheme was compared to the most related scheme, where the Commonwealth Edison company day-ahead pricing data-set is employed. The results show that the aggregate network consumption peak of our scheme is controllable, even when the percentage of the participant customers increases.