论文标题
用于使用PV系统和储藏室的住宅单元汇总的随机决策模型
Stochastic Decision-Making Model for Aggregation of Residential Units with PV-Systems and Storages
论文作者
论文摘要
许多住宅能源消费者已经安装了光伏（PV）面板和储能系统。这些住宅用户可以汇总并参与能源市场。本文提出了这些住宅单位汇总的随机决策模型，以参与两组式市场。场景是使用季节性自回归综合移动平均线（SARIMA）模型和预测错误的联合概率分配功能生成的，以建模实时价格，PV代和需求的不确定性。本文提出的场景生成模型将预测错误视为随机变量，该变量允许在实时市场中观察到的新信息为情景生成过程，而无需重新验证SARIMA或重新拟合概率分布函数，以预测错误。这种方法显着改善了所提出模型的计算时间。对6个住宅单元的聚合进行了仿真研究，结果突出了聚集的好处以及所提出的随机决策模型。
Many residential energy consumers have installed photovoltaic (PV) panels and energy storage systems. These residential users can aggregate and participate in the energy markets. A stochastic decision making model for an aggregation of these residential units for participation in two-settlement markets is proposed in this paper. Scenarios are generated using Seasonal Autoregressive Integrated Moving Average (SARIMA) model and joint probability distribution function of the forecast errors to model the uncertainties of the real-time prices, PV generations and demands. The proposed scenario generation model of this paper treats forecast errors as random variable, which allows to reflect new information observed in the real-time market into scenario generation process without retraining SARIMA or re-fitting probability distribution functions over the forecast errors. This approach significantly improves the computational time of the proposed model. A simulation study is conducted for an aggregation of 6 residential units, and the results highlights the benefits of aggregation as well as the proposed stochastic decision-making model.
