• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Building and Environment >Building demand-side control using thermal energy storage under uncertainty: An adaptive Multiple Model-based Predictive Control (MMPC) approach
【24h】

Building demand-side control using thermal energy storage under uncertainty: An adaptive Multiple Model-based Predictive Control (MMPC) approach

机译：利用不确定性下的热能存储建立需求侧控制：自适应的基于多个模型的预测控制（MMPC）方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study investigates the demand-side control enhancement of TES though comparing the benchmark control strategies and newly-suggested adaptive MMPC designed to handle uncertainty in an adaptive fashion. Evaluations are performed through closed-loop simulations of an actual test building that is calibrated with real data and weather. While typical MPC centralizes computational burden (due to a provision for disturbances) on optimization through a single model, the adaptive MMPC distributes such burden (with less complexity) to multiple local models and optimizations in advance, then the online supervisory controller selects or interpolates the most adequate local models and control policies for the current conditions, thereby provides an effective global control policy for the entire operation regime. Building Energy Model (BEM) is used to construct local models for the adaptive MMPC, which enables more semantically feasible and acceptable model calibrations through which practitioners would obtain more model fidelity. This approach not only alleviates real time computation load, but also still achieves the desired performance. Evaluation results show that the adaptive MMPC outperforms the storage priority control and also ensures a near-optimal performance in load shifting under various uncertainty situations, including depreciation scenarios and unmeasured disturbance scenarios.
机译：这项研究通过比较基准控制策略和旨在以自适应方式处理不确定性的最新建议的自适应MMPC，研究了TES的需求侧控制增强。通过对实际测试建筑物进行闭环仿真来进行评估，并使用实际数据和天气进行校准。尽管典型的MPC通过单个模型集中优化的计算负担（由于提供了干扰），但是自适应MMPC会事先将这种负担（复杂度较低）分配给多个本地模型和优化，然后在线监控控制器选择或内插针对当前情况的最适当的本地模型和控制策略，从而为整个运营体制提供有效的全局控制策略。建筑能耗模型（BEM）用于构建自适应MMPC的本地模型，从而实现语义上更可行和可接受的模型校准，从而使从业人员可以获得更多的模型保真度。这种方法不仅减轻了实时计算的负担，而且仍然达到了预期的性能。评估结果表明，自适应MMPC的性能优于存储优先级控制，并且还可以确保在各种不确定情况下（包括折旧和不可测的干扰情况）下的负载转移性能接近最佳。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号