This paper proposes a novel decentralized energy scheduling framework for demand response of energy communities in the case of limited overall capacity of distribution networks. A combined energy scheduling of heating, ventilation, and air conditioning systems and a community energy storage system (CESS) for multiple smart residential users is presented. The proposed approach aims at minimizing the total expected energy costs while ensuring the occupants' thermal comfort. The optimization problem is first formulated as a mixed-integer linear programming problem, which is converted into a linear programming problem using a tractable approximation method based on a non-complementary charging/discharging strategy of the CESS. The decentralized resolution process is based on multi-block proximal Jacobian alternating direction method of multipliers, ensuring efficient computation and protecting users' privacy. We assess the effectiveness of the proposed approach through numerical experiments on a realistic case study.
Multi-block ADMM Approach for Decentralized Demand Response of Energy Communities with Flexible Loads and Shared Energy Storage System / Hosseini, S.; Carli, R.; Jantzen, J.; Dotoli, M.. - (2022), pp. 67-72. (Intervento presentato al convegno 30th Mediterranean Conference on Control and Automation, MED 2022 tenutosi a grc nel 2022) [10.1109/MED54222.2022.9837173].
Multi-block ADMM Approach for Decentralized Demand Response of Energy Communities with Flexible Loads and Shared Energy Storage System
Hosseini S.;Carli R.;Dotoli M.
2022-01-01
Abstract
This paper proposes a novel decentralized energy scheduling framework for demand response of energy communities in the case of limited overall capacity of distribution networks. A combined energy scheduling of heating, ventilation, and air conditioning systems and a community energy storage system (CESS) for multiple smart residential users is presented. The proposed approach aims at minimizing the total expected energy costs while ensuring the occupants' thermal comfort. The optimization problem is first formulated as a mixed-integer linear programming problem, which is converted into a linear programming problem using a tractable approximation method based on a non-complementary charging/discharging strategy of the CESS. The decentralized resolution process is based on multi-block proximal Jacobian alternating direction method of multipliers, ensuring efficient computation and protecting users' privacy. We assess the effectiveness of the proposed approach through numerical experiments on a realistic case study.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.