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Operational planning for multi-building portfolio in an uncertain energy market

机译：不确定能源市场中多建筑物投资组合的运营计划

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摘要

In this study, we propose an optimization framework for day-ahead operational planning of a multibuilding portfolio under market uncertainty. The portfolio of interest consists of two groups of buildings: controllable and uncontrollable. In the proposed framework, first, physics-based and statistical models are developed for estimation and prediction of end-use consumptions including Heating, Ventilation Air Conditioning (HVAC), lighting, and equipment in controllable buildings. In addition, calculation of hourly load distributions in uncontrollable buildings is developed using a non-parametric bootstrapping method. Then a multi-objective mathematical programming is formulated to minimize the energy expenditure given utility price signals while satisfying the occupants' comfort. The proposed pricing scheme considers the differences between the day-ahead and real-time prices to reflect the trend of energy market uncertainty. It is demonstrated that this pricing scheme results in better performance, in terms of achieving to demand management goals, than the current scheme. Current pricing scheme is solely based upon the day-ahead forecasted price. The performance of the proposed framework is explored using real energy market data. Published by Elsevier B.V.
机译：在这项研究中，我们为市场不确定性下的多层建筑投资组合的提前运营规划提出了一个优化框架。感兴趣的投资组合包括两组建筑物：可控制的和不可控制的。在提出的框架中，首先，开发基于物理和统计的模型以估计和预测最终用途的消耗，包括加热，通风空调（HVAC），照明和可控建筑物中的设备。另外，使用非参数自举方法开发了不可控制建筑物中每小时负荷分布的计算。然后，制定了一个多目标数学程序设计，以在给定公用事业价格信号的同时最大程度地降低能源消耗，同时满足居住者的舒适度。拟议的定价方案考虑了日前价格与实时价格之间的差异，以反映能源市场不确定性的趋势。事实证明，在实现按需管理目标方面，该定价方案比当前方案具有更好的性能。当前的定价方案仅基于提前一天的预测价格。使用实际的能源市场数据来探索所提出框架的性能。由Elsevier B.V.发布

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