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Development and validation of an intelligent load control algorithm

机译:智能负载控制算法的开发与验证

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The renewable generation technologies form a significant (>20%) fraction of grid capacity, however their generation capabilities remain variable in nature. Therefore, utilities will be forced to maintain a significant standby capacity to mitigate the imbalance between supply and demand. Because more than 75% of electricity consumption occurs in buildings, building loads can be used to mitigate some of the imbalance. This paper describes the development and validation of an intelligent load control (ILC) algorithm that can be used to manage loads in a building or group of buildings using both quantitative and qualitative criteria. ILC uses an analytic hierarchy process to prioritize the loads for curtailment. The ILC process was developed and tested in a simulation environment to control a group of rooftop units (RTUs) to manage a building's peak demand while still keeping zone temperatures within acceptable deviations. The ILC algorithm can be implemented at a low cost on a supervisory controller without the need for additional sensing. By anticipating future demand, the process can be extended to add advanced control features such as precooling and preheating to alleviate comfort when operation of the RTUs is curtailed to manage the peak demand. (C) 2016 Elsevier B.V. All rights reserved.
机译:可再生能源发电技术占电网容量的很大一部分(> 20%),但是其发电能力本质上仍是可变的。因此,公用事业将被迫维持大量的备用能力,以缓解供需之间的不平衡。由于超过75%的电力消耗发生在建筑物中,因此可以使用建筑物负荷减轻某些失衡。本文介绍了智能负载控制(ILC)算法的开发和验证,该算法可用于使用定量和定性标准来管理建筑物或一组建筑物中的负载。 ILC使用分析层次结构过程确定负载的优先级以进行缩减。在模拟环境中开发并测试了ILC过程,以控制一组屋顶单元(RTU),以管理建筑物的峰值需求,同时仍将区域温度保持在可接受的偏差范围内。可以在监控控制器上以低成本实现ILC算法,而无需其他检测。通过预测未来需求,可以扩展该过程以添加高级控制功能,例如预冷和预热,以在限制RTU的运行以管理高峰需求时减轻舒适感。 (C)2016 Elsevier B.V.保留所有权利。

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