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Smart district energy optimization of flexible energy units for the integration of local energy storage

机译:灵活的能源单元的智能区域能源优化,以整合本地储能

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Several changes are involving electrical power systems, especially distribution networks. For this reason, the actors in charge of managing and operating reliably these grids are facing many technical issues regarding demand and supply balancing, Renewable Energy Sources and Electric Vehicles integration, peak load shaving, etc. In this context, many energy actions have been implemented for providing services to the power system managers by means of prosumers' demand and/or supply flexibility. This study reports the development of a centralized energy management solution for smart grids equipped with local storage devices, RES, consumers and other energy facilities in a district context. The district Energy Management System relies upon a multi-objective optimization implemented by means of a genetic algorithm, the Non-dominated Sorting Genetic Algorithm II. This optimization, based on both technical and economic criteria, aims at following a power profile sent by DSO exploiting the flexibility provided by every energy unit. The simulation models of the main components of the system are developed in order to simulate the district operations and are integrated in the Energy Management System. Moreover, the communication framework deployed between the different components of the system is reported and described.
机译:涉及电力系统,尤其是配电网络的几项变更。因此,负责可靠管理和运行这些电网的参与者面临着与需求和供应平衡,可再生能源和电动汽车集成,削峰负荷等有关的许多技术问题。在这种情况下,已经实施了许多能源行动通过生产者的需求和/或供应灵活性为电力系统经理提供服务的方法。这项研究报告了针对集中区域中配备本地存储设备,RES,用户和其他能源设施的智能电网的集中式能源管理解决方案的开发。区域能源管理系统依赖于通过遗传算法(非主导排序遗传算法II)实现的多目标优化。这种基于技术和经济标准的优化旨在利用DSO发送的功率曲线,利用每个能源单元提供的灵活性。开发系统主要组件的仿真模型是为了模拟区域运行,并将其集成到能源管理系统中。此外,报告并描述了在系统的不同组件之间部署的通信框架。

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