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首页> 外文期刊>Smart Grid, IEEE Transactions on >Privacy-Preserving Collaborative Operation of Networked Microgrids With the Local Utility Grid Based on Enhanced Benders Decomposition
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Privacy-Preserving Collaborative Operation of Networked Microgrids With the Local Utility Grid Based on Enhanced Benders Decomposition

机译：基于增强型弯管分解的局部公用电网，保护网络微电网的隐私合作操作

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摘要

In this paper, a privacy-preserving decision-making framework is developed for a collaborative operation of networked microgrids and the local utility grid, where the distribution system operator (DSO) interacts with microgrid master controllers (MCs) in a leader-followers fashion. First, the paper models the decision-making in the collaborative operation presented as an integrated mixed-integer second-order cone programming problem which satisfies various technical and operational requirements in a look-ahead manner. Then, the integrated optimization problem is decomposed into a master problem and a set of subproblems in order to decentralize the decision-making process of DSO and MCs. The master problem is solved by DSO for optimizing the local utility grid operation, and the subproblems are solved independently by MCs for optimizing the operation of individual microgrids. We propose an enhanced Benders decomposition algorithm to guide the iterations between the master problem and subproblems. In particular, an enhanced approach is introduced in the Benders decomposition algorithm for generating valid cutting planes from mixed-integer linear programming subproblems. Mathematically, the proposed algorithm can find the globally optimal solution after a finite number of iterations. Accordingly, DSO and MCs manage to collaborate on making operational decisions that would maximize the social welfare without compromising independent decision-making and privacy provisions. Numerical experiments are conducted on a simplified two-bus system and a modified IEEE 123-bus system. The results validate the efficiency, the robustness, and the scalability of the proposed collaborative decision-making framework in power systems.
机译：在本文中，开发了一种隐私保留的决策框架，用于组网微电网和本地公用电网的协作操作，其中分配系统操作员（DSO）以领导者追随者的方式与微电网主控制器（MCS）相互作用。首先，该纸张模型在作为集成的混合整数二阶锥形编程问题上呈现的协作操作中的决策，其以期待的方式满足各种技术和操作要求。然后，综合优化问题被分解成主问题和一组子问题，以便分散DSO和MCS的决策过程。通过DSO解决了主问题，以优化本地实用电网操作，并且通过MCS独立解决了子问题，以优化各个微电网的操作。我们提出了一个增强的弯曲者分解算法，以指导主问题和子问题之间的迭代。特别地，在弯曲器分解算法中引入了增强的方法，用于从混合整数线性编程子问题生成有效切割平面。在数学上，所提出的算法可以在有限数量的迭代之后找到全局最佳解决方案。因此，DSO和MCS设法建立运营决策，这将使社会福利最大化，而不会影响独立的决策和隐私条款。在简化的两巴士系统和改进的IEEE 123总线系统上进行数值实验。结果验证了电力系统中所提出的协作决策框架的效率，鲁棒性和可扩展性。

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