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The State of the Art in Model Predictive Control Application for Demand Response

Review paper

Journal of Sustainable Development of Energy, Water and Environment Systems
ARTICLE IN PRESS (volume and issue assigned later), 1090401
DOI: https://doi.org/10.13044/j.sdewes.d9.0401
Amru Alqurashi
Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

Abstract

Demand response programs have been used to optimize the participation of the demand side. Utilizing the demand response programs maximizes social welfare and reduces energy usage. Model Predictive Control is a suitable control strategy that manages the energy network, and it shows superiority over other predictive controllers. The goal of implementing this controller on the demand side is to minimize energy consumption, carbon footprint, and energy cost and maximize thermal comfort and social welfare.  This review paper aims to highlight this control strategy's excellence in handling the demand response optimization problem. The optimization methods of the controller are compared. Summarization of techniques used in recent publications to solve the Model Predictive Control optimization problem is presented, including demand response programs, renewable energy resources, and thermal comfort. This paper sheds light on the current research challenges and future research directions for applying model-based control techniques to the demand response optimization problem.

Keywords: Stochastic MPC, robust MPC, energy management, demand response, renewable energy

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