论文标题
用跨凝结法有效评估电力分配网络的充分性
Efficient Assessment of Electricity Distribution Network Adequacy with the Cross-Entropy Method
论文作者
论文摘要
确定电力分销网络中未来的拥塞点是分配系统运营商面临的重要挑战。解决这一挑战的一种经过验证的方法是使用未来需求的概率模型来评估分布网格充足性。但是，在评估具有长期预测范围的大型概率需求预测模型时，计算成本可能会成为一个严重的挑战。在本文中，开发了蒙特卡洛方法，以提高从自下而上的随机需求模型获得资产超载概率的计算效率。跨渗透性优化的重要性抽样与常规蒙特卡洛采样形成对比。提出方法的基准结果表明，本工作中介绍的基于抽样的重要性方法适合估算少数客户资产的罕见过载概率。
Identifying future congestion points in electricity distribution networks is an important challenge distribution system operators face. A proven approach for addressing this challenge is to assess distribution grid adequacy using probabilistic models of future demand. However, computational cost can become a severe challenge when evaluating large probabilistic electricity demand forecasting models with long forecasting horizons. In this paper, Monte Carlo methods are developed to increase the computational efficiency of obtaining asset overload probabilities from a bottom-up stochastic demand model. Cross-entropy optimised importance sampling is contrasted with conventional Monte Carlo sampling. Benchmark results of the proposed methods suggest that the importance sampling-based methods introduced in this work are suitable for estimating rare overload probabilities for assets with a small number of customers.
