A Pricing Control Algorithm for Industrial Demand Response Considering Disturbances

This paper proposes a pricing control algorithm for utility companies to purchase load adjustment from industrial consumers. Specifically, the electricity cost is modeled under forecast errors in the retail markets, and an optimization problem is formulated considering the thermal comfort of the industrial Heating, Ventilation and Air Conditioning (HVAC) units. Then, an iterative pricing control algorithm is developed to search for the optimal retail price and market-clearing price with only local information available in electricity markets. Specially, we consider the disturbances from the metering errors and communications interference and establish the conditions to stabilize the pricing control algorithm under additive disturbances. Numerical results demonstrate the convergence and effectiveness of the proposed pricing algorithm.