The proliferation of renewable generation brings challenges to the power supply-demand balance. To relieve the power fluctuations caused by photovoltaic (PV) generation variability, a multi-timescale allocation algorithm that considers the allocation of available energy and power is proposed. Contracted demand response energy (CDRE) refers to the regulation energy, which is specified in contracts in advance, that can be used to relieve power fluctuations. First, the capacity of CDRE and available regulation power (RP) provided by load aggregators (LAs) that aggregate different demand response resources (DRRs) are estimated. In hour-timescale, CDRE is allocated to maximize the control economy of all participants, where a sample average approximation-based Stackelberg game is proposed to optimize the behavior of each participant based on considering PV generation uncertainty. In minute-timescale, RP is allocated to smooth the power fluctuations and minimize the power deviations based on the allocated CDRE results. Simulation on a modified IEEE-24 bus system verifies the effectiveness of the proposed algorithm in terms of reducing the power supply-demand imbalance with maximum revenue.

中文翻译：

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智能电网需求响应的多时间尺度能源和电力分配算法：Stackelberg 博弈方法


可再生能源发电的激增给电力供需平衡带来了挑战。为了缓解光伏发电波动引起的功率波动，提出了一种考虑可用能源和功率分配的多时间尺度分配算法。合同需求响应能源（CDRE）是指预先在合同中约定的、可用于缓解电力波动的调节能源。首先，估计 CDRE 的容量和聚合不同需求响应资源 (DRR) 的负载聚合器 (LA) 提供的可用调节功率 (RP)。在小时时间尺度上，CDRE被分配以最大化所有参与者的控制经济性，其中提出了基于样本平均近似的Stackelberg博弈，以在考虑光伏发电不确定性的基础上优化每个参与者的行为。在分钟时间尺度上，根据分配的CDRE结果分配RP以平滑功率波动并最小化功率偏差。对改进的 IEEE-24 总线系统进行仿真验证了该算法在以最大收益减少电力供需不平衡方面的有效性。