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Optimal electrical and thermal energy management of a residential energy hub, integrating demand response and energy storage system

机译:住宅能源枢纽的最佳电力和热能管理,整合需求响应和储能系统

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摘要

Energy crisis along with environmental concerns are some principal motivations for introducing "energy hubs" by integrating energy production, conversion and storage technologies such as combined cooling, heating and power systems (CCHPs), renewable energy resources (RESs), batteries and thermal energy storages (TESs). In this paper, a residential energy hub model is proposed which receives electricity, natural gas and solar radiation at its input port to supply required electrical, heating and cooling demands at the output port. Augmenting the operational flexibility of the proposed hub in supplying the required demands, an inclusive demand response (DR) program including load shifting, load curtailing and flexible thermal load modeling is employed. A thermal and electrical energy management is developed to optimally schedule major household appliances, production and storage components (i.e. CCHP unit, PHEV and TES). For this purpose, an optimization problem has been formulated and solved for three different case studies with objective function of minimizing total energy cost while considering customer preferences in terms of desired hot water and air temperature. Additionally, a multi-objective optimization is conducted to consider consumer's contribution to CO2, NOx and SOx emissions. The results indicate the impact of incorporating DR program, smart PHEV management and TES on energy cost reduction of proposed energy hub model. (C) 2014 Elsevier B.V. All rights reserved.
机译:能源危机以及对环境的关注是通过整合能源生产,转换和存储技术(例如联合制冷,供暖和电力系统(CCHP),可再生能源(RES),电池和热能存储)来引入“能源枢纽”的一些主要动机。 (TES)。在本文中,提出了一种住宅能源枢纽模型,该模型在其输入端口接收电,天然气和太阳辐射,以在输出端口提供所需的电,热和冷需求。为了提高建议中枢在提供所需需求方面的操作灵活性,采用了包含性的需求响应(DR)程序,其中包括负载转移,负载缩减和灵活的热负载建模。开发了热能和电能管理器,以优化主要家用电器,生产和存储组件(即CCHP单元,PHEV和TES)的调度。为此,针对三个不同的案例研究制定并解决了一个优化问题,其目标功能是将总能源成本降至最低,同时根据所需的热水和空气温度考虑客户的偏好。此外,还进行了多目标优化,以考虑消费者对CO2,NOx和SOx排放的贡献。结果表明,将灾难恢复程序,智能PHEV管理和TES合并对拟议的能源枢纽模型的能源成本降低具有影响。 (C)2014 Elsevier B.V.保留所有权利。

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