Risk-averse energy management for integrated electricity and heat systems considering building heating vertical imbalance: An asynchronous decentralized approach

Abstract

To improve the energy efficiency of integrated electricity and heat systems (IEHS) with the flexibility of buildings, this paper proposes a risk-averse decentralized energy management strategy for IEHS with intelligent buildings (IBs). First, a thermal dynamic model for IBs considering building height is formulated based on the building's thermal inertia and vertical heating structure. Then, to alleviate the negative effects of uncertainties from renewables and energy prices, a stochastic optimization model for IEHS with IBs is formulated. Further, a conditional value-at-risk (CVaR) based risk evaluation method is integrated into the overall model to avoid over-optimistic solutions. Finally, to protect the privacy of scheduling information among different networks and mitigate computational burdens, the two-stage accelerated asynchronous decentralized alternating direction method of the multipliers (TSA-AD-ADMM) algorithm is proposed to solve the risk-averse energy management problem in a parallel way. The results show that the thermal dynamic model with building height describes the vertical imbalance of the heating network, besides, the risk-averse decentralized operation method effectively limits the system risks and significantly enhances the solving efficiency.