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Decentralized coordination of the operation of residential heating units

机译:住宅供热机组运行的分散协调

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This work presents an approach to decentralized coordination of electro-thermal heating systems, like Combined Heat and Power systems (CHP), Heat Pumps (HP), or Electric Heating systems (EH), each equipped with thermal storage, within a group or cluster of residential buildings. The flexibility of these thermal systems can be exploited for coordinating the heating units for a higher-level objective, like balancing power fluctuations of Renewable Energy Sources (RES). In order to assess the decentralized coordination algorithm (DCA) presented in this paper, its performance is compared with that of a centralized approach. In the centralized approach, a Mixed Integer Program (MIP) is formulated and solved, obtaining the optimal schedules for each heating system within the building cluster. In the decentralized approach, an MIP is first executed for each heating system, providing a set of schedules, which all satisfy the local constraints as well as local objectives of the building. Next, one schedule per set is selected in a way that the combination of the selected schedules facilitates the higher-level objective. The results presented in this work show that the proposed DCA can in principle balance power fluctuations as global objective, while still enabling local optimization. However, the results appear to be strongly dependent on the flexibility of the local optimization.
机译:这项工作提出了一种在小组或集群内分散地协调电热加热系统(例如热电联产系统(CHP),热泵(HP)或电加热系统(EH))的分散协调方法住宅建筑。可以利用这些热力系统的灵活性来协调加热单元,以实现更高级别的目标,例如平衡可再生能源(RES)的功率波动。为了评估本文提出的分散式协调算法(DCA),将其性能与集中式方法进行了比较。在集中式方法中,制定并解决了混合整数程序(MIP),从而获得了建筑群内每个供暖系统的最佳计划。在分散式方法中,首先为每个供热系统执行MIP,以提供一组时间表,这些时间表均满足建筑物的局部约束和局部目标。接下来,以选择的时间表的组合促进更高级别目标的方式选择每组一个时间表。这项工作提出的结果表明,提出的DCA原则上可以平衡作为全局目标的功率波动,同时仍然可以进行局部优化。但是,结果似乎强烈依赖于局部优化的灵活性。

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