Optimal Scheduling of Demand Response Aggregators in Industrial Parks Based on Load Disaggregation Algorithm

Nowadays, industrial parks play a significant role in the development of electricity market plans, and can thus provide excellent opportunities for market players to actively participate in various electricity markets. The demand response aggregator (DRA) is a major market player that can take advantage of these opportunities. In restructured electricity markets, identifying the consumption patterns of different classes of consumers can be effective in furthering the goals of the DRA. In previous studies on the self-scheduling of the DRA, consumer behavior has not been considered. Such an approach leads to numerous technical problems in the restructured electricity markets. For this purpose, herein, a practical mechanism is presented for executing the self-scheduling process of the DRA by considering the load disaggregation algorithm. The integration of self-scheduling and load disaggregation processes creates a hierarchical optimization problem. The main aim of the constructed hierarchical structure is to find the optimal self-scheduling of the DRA to consciously participate in the electricity markets by identifying the behavior of different consumers. The proposed structure is implemented and evaluated on the industrial park in Saveh, Iran. The time-of-use (TOU) and reward-based demand response (DR) programs are considered as the tools available for the DRA to trade the DR volumes in the day-ahead and balancing electricity markets.