论文标题
在线分布式算法，用于最佳功率流问题，并遗憾分析
Online Distributed Algorithm for Optimal Power Flow problem with Regret Analysis
论文作者
论文摘要
我们研究了动态和不确定的环境，研究了分布式的DC最佳功率流（DC-OPF）问题。不可预测的可再生资源供应和电力市场价格变化是导致不确定性的一些因素。我们建议使用在线凸优化的框架来解决此问题，在线凸出功能由于不确定性而未知，并且随着时间的推移仅会逐步显示。我们还考虑了一个分布式设置，在该设置中，电源网络中的每个代理（发电机和负载）仅适用于其自己的本地目标和约束，但可以与邻居进行交流。基于修改的原始偶对方法提出了分布式在线算法。在线算法的性能是使用遗憾（静态）函数评估的，这是通过采用拟议算法和事后看来的最佳固定决定所产生的实际成本之间的差异。由于我们处理了一个受约束的优化问题，因此在每个步骤中还计算了违反约束违规的概念。我们建立了根据对步进尺寸和成本功能的适当假设的静态遗憾和约束违规的限制。最后，我们使用标准IEEE-14总线系统来演示算法的性能。
We investigate the distributed DC-Optimal Power Flow (DC-OPF) problem for a dynamic and uncertain environment. The unpredictable supply of renewable resources and varying prices of the electricity market are a few factors responsible for the uncertainty. We propose to address this problem using the framework of online convex optimization, where the cost functions are not known apriori because of the uncertainty and are revealed only incrementally over time. We also consider a distributed setting, where each agent (generators and loads) in the power network is only privy to their own local objectives and constraints but can communicate with their neighbours. A distributed online algorithm is proposed based on the modified primal-dual approach. The performance of the online algorithm is evaluated using the regret (static) function, which is the difference between the actual cost incurred by employing the proposed algorithm and the optimal fixed decision in hindsight. Since we deal with a constrained optimization problem, analogous to the notion of regret the accumulation of the constraint violation is also calculated at each step. We establish a sub-linear bound on the static regret and constraint violation under suitable assumptions on step-size and cost function. Finally, we use the standard IEEE-14 bus system to demonstrate the performance of our algorithm.
