基于随机规划的可再生能源与暖通空调负荷协调调度

D. Nguyen, H. T. Nguyen, L. Le
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引用次数: 9

摘要

本文研究了利用集中供热、通风和空调(HVAC)负荷来平滑风电场和/或太阳能电场的功率波动,使这些随机资源更具可调度性的潜力。我们特别考虑了一个虚拟发电厂(VPP),它由几个风能/太阳能发电单元、一些带有HVAC系统的建筑物和一个电池存储设施组成。可再生能源(RESs)发电的一部分用于运行HVAC系统,其余部分(如果有的话)出售给主电网。设计目标是确定VPP必须提交给电力市场的最佳小时计划电力调度,以实现其效益最大化。可再生能源发电的短期波动(即超过小时间隔)可以通过智能调整灵活的HVAC负荷来缓解,这使得VPP能够提供一个固定的小时调度。该优化问题是一个两阶段的随机规划,其中系统的不确定参数采用蒙特卡罗模拟建模。该优化框架考虑了建筑热动力学模型和用户气候舒适标准。数值结果表明了该模型的有效性。
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Coordinated dispatch of renewable energy sources and HVAC load using stochastic programming
This paper investigates the potential of using aggregated heating, ventilation, and air-conditioning (HVAC) loads to smooth out the power fluctuation of a wind farm and/or a solar farm to make these stochastic resources more dispatchable. Specially, we consider a Virtual Power Plant (VPP) which consists of several wind/solar power units, a number of buildings with their HVAC systems, and a battery storage facility. A portion of the power generation from renewable energy sources (RESs) is used to operate HVAC systems and the rest (if any) is sold to the main grid. The design goal is to determine an optimal hourly scheduled power dispatch that the VPP must submit to electricity market to maximize its benefit. The short-term fluctuation of renewable energy generation (i.e., over intrahour intervals) is mitigated by smartly adjusting the flexible HVAC load, which enables the VPP to provide a firmed hourly dispatch. The underlying optimization problem is formulated as a two-stage stochastic program where system uncertain parameters are modeled using Monte-Carlo simulation. Building thermal dynamics model and users' climate comfort criteria are considered in the proposed optimization framework. Numerical results is presented to illustrate the effectiveness of the proposed model.
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