Load-Shifting Scheduling based on Manufacturing Process for Demand Response with Bidding Probability

This study develops a load-shifting scheduling algorithm for demand response to improve the profit of industrial customers. The objective function is determined to maximize the expected profit of demand response (DR) participation to reflect the market structure. For this, it converts the profit of the economic DR by using the bidding probability. Moreover, it derives the DR schedules of each manufacturing process separately and organizes constraints to improve the participation amount and minimize damage to each manufacturing machine. The proposed algorithm utilizes a genetic algorithm (GA) to derive an optimal DR solution. The actual market data and power consumption coefficient of South Korea are used to simulate the proposed algorithm.