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Stochastic gradient-push for economic dispatch on time-varying directed networks with delays

机译:具有时滞的时变有向网络上的经济调度的随机梯度推

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Economic dispatch problem (EDP) is an elementary optimization problem of power systems whose purpose is to minimize the total generation cost while meeting total demands and complying with individual generator output constraints. This paper proposes a distributed optimization algorithm with noisy gradient based on stochastic gradient-push approach to solve the EDP on time-varying directed communication networks potentially with time delays. It shows that the proposed algorithm can be ensured to solve the EDP when the time-varying directed communication networks are uniformly jointly strongly connected. The algorithm with asynchronous step-sizes can deal with the finite time-varying delays on communication links as well. The generation cost functions are considered as strictly convex and strongly convex functions respectively with convergence rate of O((lnk)/root k) and O ((ink)/ k). Simulation results are provided to validate the availability of the algorithm.
机译:经济调度问题(EDP)是电力系统的基本优化问题,其目的是在满足总需求并遵守单个发电机输出约束的同时,将总发电成本降至最低。提出了一种基于随机梯度推方法的带噪声梯度的分布式优化算法,以解决时变定向通信网络中可能存在时延的EDP问题。结果表明,当时变定向通信网络统一联合强连接时,可以保证所提算法能够解决EDP问题。具有异步步长的算法也可以处理通信链路上的时变有限时延。生成成本函数被认为分别是具有O((lnk)/ root k)和O((ink)/ k)收敛速度的严格凸函数和强凸函数。提供仿真结果以验证算法的可用性。

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