Robust Optimal Control for Demand Side Management of Multi-Carrier Microgrids

This paper focuses on the control of microgrids where both gas and electricity are provided to final customer, i.e., multi-carrier microgrids. Hence, these include thermal electrical loads, renewable energy sources, storage systems, heat pumps, combined power units. The parameters characterizing microgrid subject several disturbances, such as fluctuations in provision energy, variability demand, uncertainties pricing. With aim accounting for data microgrid, we propose a Robust Model Predictive Control (RMPC) approach whose goal is minimize total economical cost, while satisfying comfort requests users. In related literature various RMPC approaches have been proposed, focusing either or Only few contributions addressed robust Consequently, an innovative algorithm that employs uncertainty set-based method can provide better performance compared with deterministic model predictive controllers applied mitigating conservativeness approach, define suitable robustness factors investigate effects solution against variations uncertain parameters. We show effectiveness proposed by applying it realistic residential comparing obtained results ones baseline method. Note Practitioners —This work motivated emerging need effective management inherent difficulty scheduling simultaneously operations infrastructures (e.g., electricity, natural gas) exacerbated inevitable presence affect inter-dependent dynamics different resources equipment. MPC-based strategy allows manager effectively determine optimal multi-faceted system components, making tradeoff between protection uncertainty. presented comprehensive generic, be frameworks integrating types components sources uncertainty, at same time being implementable any system.