Hierarchical energy management system for controlling distributed energy resources in a community microgridTools Elkazaz, Mahmoud (2021) Hierarchical energy management system for controlling distributed energy resources in a community microgrid. PhD thesis, University of Nottingham.
AbstractCommunity Energy Systems (CES) can be used to unlock the potential of Distributed Energy Resources (DERs), maximize the local consumption of Renewable Energy Resources (RES) at the lowest level of electricity grid, and offer collective benefits to the end-users involved. If different electricity producers and consumers (prosumers) are connected to form a CES, the economic behaviour of the system needs to be fully understood. Therefore, a high priority in this important area is the development of a novel design procedure which allows the comprehensive and analytical investigation of the CES using integrating control, management strategies, optimal planning and scheduling and sizing procedures. This thesis presents novel centralized and decentralized hierarchical Community Energy Management Systems (CEMSs) which facilitate energy trading between prosumers in the CES by coordinating the operation of energy resources such as distributed or centralized battery energy storage and shiftable home appliances (located in each house) to achieve a further reduction in the daily household energy costs for each house, compared to being operated individually (i.e. not a part of the CES). The hierarchical CEMS represents an optimization-based real-time interactive algorithm which uses a combination of a Peer-to-Peer (P2P) energy trading scheme and a hierarchical optimization and control framework. This hierarchical CEMS reduces energy costs for end-users, maximizes self-consumption of locally generated energy, reduces the dependency of the CES on the main electrical grid, and reshapes the consumption profile of the CES to reduce peak consumption, while taking into account the battery degradation costs and the use of Demand Side Management (DSM) techniques. The novel structure of the hierarchical CEMS enables the algorithm to deal with frequent changes in the system using a short sample time.
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