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According to the energy policy, which encourages local consumption of photovoltaic (PV) energy, the energy sharing among neighboring PV prosumers is proved to be a more effective way compared with independent operations of each prosumer. In this paper, an energy storage (ES)-equipped energy-sharing provider (ESP) is proposed to facilitate the energy sharing of multiple PV prosumers. With the help of the ESP, the autonomous PV prosumers can be formed as an energy-sharing network, and the energy-sharing activities can be categorized as direct sharing and buffered sharing. First, with the assistance of the ES, a day-ahead scheduling model of the ESP is built to increase the operation profit and improve the net power profile of the energy-sharing network, which considers the uncertainty of PV energy, electricity prices, and prosumers’ load via stochastic programming. Moreover, to further increase the energy sharing, a real-time demand response model based on a Stackelberg game is presented to coordinate the energy consumption behavior of prosumers by using internal prices. Finally, through a practical case study, the effectiveness of the method is verified in terms of improving the economic benefits and PV energy sharing. [ABSTRACT FROM PUBLISHER]

In a smart grid environment, the joint operation of multiple Smart Buildings (SBs) could be more advantageous than the independent operation of each individual SB. In order to enable the joint operation, the concept of Smart Building Cluster (SBC) is introduced in this paper. An energy management framework for achieving optimal operations of SBC is proposed, and the information exchange processes between the Smart Building Cluster Operator (SBCO) and the participating SBs are described. A multi-party energy management model for SBC based on non-cooperative game theory is proposed, considering building-integrated PV systems and automatic demand response (ADR), with all participating SBs viewed as players in the game. The existence of Nash equilibrium in the game model is proved, and the process for solving the Nash equilibrium strategy is modeled as a multi-objective optimization problem (MOP). Furthermore, the solution method and procedure based on an iterative method are proposed. Finally, via a practical example, the effectiveness of the model is verified. The proposed method is able to reduce the total cost of the SBs by 4.6% and improve the load factor of the SBC from 0.68 to 0.76 when the proportion of shiftable loads is 25% in the total load profile. [ABSTRACT FROM AUTHOR]