基于一致性原理和梯度下降法的微电网完全分布式优化调度

针对基于经典一致性算法的微电网优化调度中存在需要集中处理器对可控单元进行信息采集并做求和处理等问题，提出一种基于一致性原理和梯度下降法的完全分布式优化调度策略。该算法的一致性原理由一致项和调整项两部分组成。其中，一致项选择增量成本作为一致性算法的状态变量进行迭代计算，调整项根据功率偏差进行修正，使其满足约束条件。通过将梯度下降法和一致性原理相结合，实现微电网发电成本的优化并提高收敛速度。并且通过可控单元与相邻可控单元之间局部信息交互更新参数，应对拓扑结构的灵活变化。最后基于IEEE-14节点系统和IEEE-39节点系统仿真验证所提方法的有效性和可行性。

Fully distributed optimal dispatch of a microgrid based on consensus principle and gradient descent

There are problems with the classical consensus algorithm in microgrid optimal dispatching in that it requires a centralized processor to collect and sum the information of the controllable units. Thus a completely distributed optimal scheduling strategy based on a consensus algorithm and gradient descent is proposed. The consensus principle of the algorithm consists of two parts: a consensus term and an adjustment term. The consensus term selects incremental cost as the state variable for iterative calculation. The adjustment term is corrected according to the power deviation to meet the constraints. This paper combines the gradient descent with the consensus principle to optimize the power generation cost of the microgrid and improve the convergence speed. In addition, the parameters can be updated through local information interaction between the controllable unit and the adjacent controllable unit to flexibly cope with a change of topology. Finally, the effectiveness and feasibility of the proposed method are verified by system simulation results of IEEE-14 nodes and IEEE-39 nodes. This work is supported by the General Program of National Natural Science Foundation of China (No. 61873159).