Efficient building energy management is very essential for energy saving and green society. This paper investigates a sustainable energy management for an energy building cluster with distributed transaction. The building cluster consists of several types of energy buildings, e.g., office, industrial, and commercial buildings. We firstly formulate utility functions for the buildings of consuming energy based on the characteristics of their controllable loads. Then a two-stage energy sharing strategy is presented. In the first stage the total social energy cost is minimized through finding the optimal energy sharing profiles in a distributed way. In the second stage the clearing for mutual energy sharing is modeled as a non-cooperative game, and the existence of the equilibrium of the game is illustrated and a relaxation-based algorithm is introduced to search for the equilibrium. Moreover, a real-time model for each building to overcome real-time uncertainties such as renewable energy generation and base loads is provided. The simulation results show that the proposed energy sharing strategy is economically beneficial for the energy buildings, computationally efficient, and is promising to facilitate a sustainable regional building cluster.

With the rapid development of energy buildings, advanced energy management is urgently demanded for a green society. In this paper, focusing on the coordinated energy management for a building community, we present a new and fair peer-to-peer energy sharing framework to realize an economic and sustainable building community. Specifically, in the building-centric peer-to-peer mode, buildings directly share their energy supplies/demands and offer the related payments within the community under the constraints of community energy and payment balance. We propose a non-cooperative energy sharing game for the selfish buildings, and we further show that a generalized Nash equilibrium of the game is independent of the energy sharing payments. Consequently, we firstly derive the energy sharing profiles by seeking the equilibrium. Since the buildings’ energy sharing payments are mutually coupled and influenced, we propose a cost reduction ratio distribution model to determine the payments to ensure the fairness in the sense that buildings can get as large cost reductions and similar cost reduction ratios as possible. Simulation results show that all buildings can reduce their energy costs and have smoother and smaller net demand profiles on the main grid, thus making the proposed schemes and algorithms promising in real applications.

In this article, we propose an economic storage sharing framework for prosumers and energy storage providers (ESPs) to promote renewable energy utilization cooperatively. The optimal shared capacities of ESPs and the energy sharing profiles of prosumers are first derived via minimizing social energy costs. Then the storage sharing profits of ESPs and the energy sharing payments of prosumers are successively determined by the asymmetric bargaining-based benefits sharing model. Specifically, the prosumer group bargains with the ESPs with the nominal required capacity and the shared capacities as their bargaining power to share the storage sharing benefits. Then prosumers bargain with each other to share the energy sharing benefits with their bargaining power quantified by a nonlinear energy sharing mapping method. Therefore, the benefits sharing model based on the contributions of prosumers and ESPs is fair enough for the participants. Numerical simulation tests verify the efficiency of the proposed framework.

The paper proposes a two-stage energy sharing framework for a new prosumer microgrid with renewable energy generation, multiple storage units and load shifting. In the first stage, a robust bi-level energy sharing model is formulated to provide a robust energy sharing schedule for prosumers and retailer overcoming the impact of the uncertainties of market prices and renewable energy. Through proper linearization techniques, the bi-level optimization problem is transformed into a single-level mixed integer linear programming (MILP) problem which is practically solvable. In the second stage, an online optimization model is formulated for each prosumer to continually optimize its energy schedule at each hour according to the latest system state, and the proposed punishment mechanism is embedded for prosumers adjusting their previous energy sharing schedules. The simulation cases show the benefits of the energy sharing management framework.

This paper investigates the energy cooperation between photovoltaic prosumers and community energy storage (CES) to improve community energy efficiency. The optimal energy sharing profiles between prosumers and CES are firstly derived by solving the energy optimization problem minimizing social energy cost. To guarantee the incentives for prosumers and CES to participate in the energy cooperation, a Nash bargaining based benefits sharing model is presented to determine the energy sharing payments. Two implementation modes, i.e., Data-Centric and Prosumers-to-CES mode, are developed to protect privacy for both prosumers and CES. Cheating behaviors in benefits sharing, the critical yet challenging matter, are analyzed; a cheating equilibrium based solution is proposed and achieved by a relaxation algorithm for a stable cooperation. In addition, the alternating direction method of multipliers with adaptive parameter selection is introduced to solve the formulated problems in a distributed way. Numerical simulation tests show the efficiency of the novel models.