Due to the rising renewable penetration rate, modern low voltage distribution network (LVDN) calls for active control with tractable computation and limited communication. To tackle this, the paper proposes a novel stochastic distributed optimization approach. The computation of optimum is completely decentralized, with a global broadcast signal is used as public reference in order to guarantee the consistency among individual shapeable energy resources. The proposed approach employs Bernoulli trials to imitate the searching process in classical gradient descent approach, and player compatible relationship is employed to play the role of gradients to indicate the direction of the search. Working in a model‐free manner without relying on iterations, the proposed approach offers an approximate optimization to minimize the accumulated compensation of reshaping/deferring the shapeable energy resources in a given LVDN while respecting the system constraints. A 103 nodes test network based on a realistic Belgian semi‐urban distribution network is used for validation. With two different profiles and a special case of communication failure, the proposed approach is validated and benchmarked with a classical AC optimal power flow algorithm. The results prove that the proposed approach is able to deliver a good approximation to the theoretical optimum with reasonable gap.

中文翻译：

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有限通信条件下低压配电网中可成形能源的随机分布优化

由于可再生能源渗透率的不断提高，现代低压配电网（LVDN）要求通过可控的计算和有限的通信进行主动控制。为了解决这个问题，本文提出了一种新颖的随机分布优化方法。最优的计算完全分散，将全球广播信号用作公共参考，以确保各个可成型能源之间的一致性。所提出的方法采用伯努利试验来模仿经典梯度下降方法中的搜索过程，并且采用玩家兼容关系来扮演梯度的角色，以指示搜索方向。以无模型的方式工作而无需依赖迭代，所提出的方法提供了一种近似优化，以在考虑系统约束的同时最小化给定LVDN中重塑/延展可成形能源的累积补偿。基于真实的比利时半城市分布网络的103个节点测试网络用于验证。在两个不同的配置文件和特殊情况下的通信失败的情况下，采用经典的交流最优潮流算法对提出的方法进行了验证和基准测试。结果证明，所提出的方法能够以合理的差距提供理论上的最佳近似值。在两个不同的配置文件和特殊情况下的通信失败的情况下，采用经典的交流最优潮流算法对提出的方法进行了验证和基准测试。结果证明，所提出的方法能够以合理的差距提供理论上的最佳近似值。在两个不同的配置文件和特殊情况下的通信失败的情况下，采用经典的交流最优潮流算法对提出的方法进行了验证和基准测试。结果证明，所提出的方法能够以合理的差距提供理论上的最佳近似值。