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Uncertainty in developing supervisory demand-side controls in buildings: A framework and guidance

机译:在建筑物中开发监督性需求侧控制的不确定性:框架和指导

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Successful demand-side control depends on the accuracy of the prediction of the power demand. This prediction should express margins of expected ranges of the power demand. Therefore, uncertainty is an unavoidable ingredient that has to be explicitly considered when evaluating performance of demand-side control. However, there is at present neither serious attention to system uncertainty nor to human-introduced uncertainty in developing the supervisory controls of building and HVAC&R systems. There is, in fact, neither a commonly shared terminology nor an agreement on a generic typology of uncertainty. Apart from introducing a common terminology and typology of uncertainty, this study provides a conceptual framework for systemic management of uncertainty, along with a process of developing the supervisory demand-side controls. This study reviews relevant uncertainty sources. Surveyed sources are classified according to the typology, and then encoded into the uncertainty matrix as part of the framework. The uncertainty matrix is used for a priori uncertainty assessment that enables model developers to identify, articulate, and prioritize critical uncertainty; it is a crucial step for gathering more adequate identification and for proper treatment of uncertainty before developing a significant model. The a priori uncertainty assessment identified that heuristic uncertainty and scenario uncertainty tend to introduce higher risks for the demand-side control in meeting its objectives. Upon this assessment, this study suggests a theoretical guide to manage and reduce risks due to uncertainty: heuristic uncertainty can be preventable if models are constructed through the formal modeling framework; physical uncertainty including both scenario uncertainty and statistical uncertainty can be compiled into model in order to render the model immune to uncertainty.
机译:成功的需求方控制取决于电力需求预测的准确性。该预测应表示电力需求的预期范围的余量。因此,不确定性是不可避免的因素,在评估需求方控制的绩效时必须明确考虑。但是,目前在开发建筑物和HVAC&R系统的监督控制时,既没有严重关注系统不确定性,也没有关注人为引入的不确定性。实际上,既没有通用的术语,也没有关于不确定性的通用类型的协议。除了介绍不确定性的通用术语和类型之外,本研究还为不确定性的系统管理提供了一个概念框架,并提供了开发监管需求侧控制的过程。这项研究回顾了相关的不确定性来源。根据类型对被调查源进行分类,然后将其编码到不确定性矩阵中作为框架的一部分。不确定性矩阵用于先验不确定性评估,使模型开发人员可以识别,阐明和确定关键不确定性;这是在开发重要模型之前收集更充分的识别信息和正确处理不确定性的关键步骤。先验不确定性评估确定了启发式不确定性和方案不确定性往往会给需求侧控制实现目标带来更高的风险。根据这一评估,本研究提出了管理和降低不确定性风险的理论指导:如果通过正式建模框架构建模型,则启发式不确定性可以预防;可以将包括场景不确定性和统计不确定性在内的物理不确定性编译到模型中,以使模型不受不确定性的影响。

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