Advances in renewable energy generation and introduction of the government targets to improve energy efficiency gave rise to a concept of a Zero Energy Building (ZEB). A ZEB is a building whose net energy usage over a year is zero, i.e., its energy use is not larger than its overall renewables generation. A collection of ZEBs forms a Zero Energy Community (ZEC). This paper addresses the problem of energy sharing in such a community. This is different from previously addressed energy sharing between buildings as our focus is on the improvement of community energy status, while traditionally research focused on reducing losses due to transmission and storage, or achieving economic gains. We model this problem in a multi-agent environment and propose a Deep Reinforcement Learning (DRL) based solution. Each building is represented by an intelligent agent that learns over time the appropriate behaviour to share energy. We have evaluated the proposed solution in a multi-agent simulation built using osBrain. Results indicate that with time agents learn to collaborate and learn a policy comparable to the optimal policy, which in turn improves the ZEC's energy status. Buildings with no renewables preferred to request energy from their neighbours rather than from the supply grid.
The authors of @cite_20 define a Central Energy Sharing (CES) systems as the one that consists of a central controller that has information of all the distributed energy resources in the micro-grid as well as the forecasting systems, and schedules resources accordingly. This type of system allows broad observability but reduces the flexibility. Work in @cite_14 introduces a CES system that classifies homes into sets of suppliers and consumers, and then uses a greedy strategy to initiate energy exchange between homes. Another interesting system - IDES @cite_9 uses a sophisticated distributed energy generation and sharing approach (DES) with a novel pricing model to incentivize energy sharing between homes.
@cite_9 @cite_14 @cite_20
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In this paper, we propose a model for households to share energy from community energy storage (CES) such that both households and utility company benefit from CES. In addition to providing a range of ancillary grid services, CES can also be used for demand side management, to shave peaks and fill valleys in system load. We introduce a method stemming from consumer theory and cooperative game theory that uses CES to balance the load of an entire locality and manage household energy allocations respectively. Load balancing is derived as a geometric programming problem. Each households contribution to overall non-uniformity of the load profile is modeled using a characteristic function and Shapley values are used to allocate the amount and price of surplus energy stored in CES. The proposed method is able to perfectly balance the load while also making sure that each household is guaranteed a reduction in energy costs. This paper develops a novel energy trading system with a community energy storage (CES) device for demand-side load management within a neighborhood area network. The energy users in the proposed system that have their own photovoltaic power generation are allowed to trade energy from their personal surplus with the grid and the CES device. We adopt a dynamic noncooperative repeated game with Pareto-efficient pure strategies as the decentralized approach for the users to determine optimal energy trading amounts for the next day. This decentralized model needs minimal information exchange or communication between users. Simulation results show that our system is able to provide peak load leveling for the grid, while providing financial benefits to users. Moreover, the performance benefits of our system are robust to both inaccuracy in day-ahead power forecasts and CES battery inefficiencies. Buildings consume a significant amount of electricity, which is normally generated from dirty sources causing an increase in carbon footprints. To reduce carbon footprint, distributed renewable energy generation has been proposed. However, the amount of renewable energy harvested normally does not match the amount of energy consumed in individual homes. To address this mismatch, we propose a distributed solution to share renewable energy among homes, which form a microgrid. Specifically we (i) design an incentive-driven distributed energy sharing system (iDES) in a microgrid to enable effective energy sharing and reduce the communication overhead, and (ii) develop energy sharing pricing model to incentivize energy sharing. The energy sharing price generally reflects the installation costs of on-site renewable and energy storage units, the dynamic changes of energy supply-demand relationship, and the remaining energy level of batteries. We validated the effectiveness of our system with extensive evaluations that use empirical traces. The results show that our energy sharing pricing model can effectively motivate and encourage homes to share energy. Abstract Nowadays, micro-generation technologies are well developed and these make local energy production more possible. In terms of building scale, in April 2009 the Japanese government decided to accelerate its efforts towards zero energy building (ZEB). However, it is said that achieving a ZEB status without a grid connection would be quite difficult. In this study, thus, the definition of zero energy building (ZEB) is extended to the community level, ‘energy community’, which is defined here as a cluster of buildings in which every building generates both heat and electricity using micro-generation technologies and shares both types of energy with the other buildings. This article describes energy-sharing possibilities among four buildings in Japan: an office building, a hotel, a hospital and a shopping centre. The comparisons of primary energy consumption of the separate and shared cases of buildings show that the energy-sharing cases have the advantage of energy management within the boundary compared with the buildings studied as separated cases. The combination of hotel and hospital has the higher potential for achieving ZEB status. The results of this study show that the advantages of energy sharing are dependent on the type of buildings in the combination and CHP operation strategy.