This paper investigates the combined economic environmental dispatch problem of Microgrids in a distributed manner. In order to optimize the competing agminated operation cost and environmental impact objectives simultaneously, a distributed method which combines the distributed consensus based algorithm with dynamic weights is proposed to assign the energy among generation units, energy storage units, and load units. By this method, each unit only needs to share its local information among neighbours, thus it offers better flexibility, robustness and privacy. Besides, different from existing distributed optimization algorithms, the proposed algorithm can solve the multi-objective problem over time-varying directed communication graph with a fixed step-size. Furthermore, it is proved that the proposed algorithm can converge to the optimal solution if the step-size does not exceed some upper bound. The simulation results show that the proposed method can simultaneously coordinate the two conflicting goals of the economic and environmental aspects of Microgrids, and obtain the entire Pareto front, effectively reducing operating costs and pollutant emissions. The advantage of convergence speed is also shown compared with some distributed algorithms.

中文翻译：

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时变有向通信图上的微电网分布式最优经济环境调度


本文研究分布式微电网的综合经济环境调度问题。为了同时优化竞争的综合运营成本和环境影响目标，提出了一种将分布式共识算法与动态权重相结合的分布式方法，在发电单元、储能单元和负载单元之间分配能量。通过这种方法，每个单元只需要在邻居之间共享其本地信息，因此提供了更好的灵活性、鲁棒性和隐私性。此外，与现有的分布式优化算法不同，该算法能够以固定步长解决时变有向通信图上的多目标问题。进一步证明，在步长不超过某个上限的情况下，该算法能够收敛到最优解。仿真结果表明，该方法能够同时协调微电网经济和环境两个相互冲突的目标，并获得整个帕累托前沿，有效降低运营成本和污染物排放。与一些分布式算法相比，也显示出了收敛速度的优势。