The transition towards fully renewable energy-based power systems will require to increase the number of reserves at the System Operators’ (SOs) disposal to provide flexibility on the energy management process. The microgrid’s ability of integrating distributed energy resources, loads and energy storage systems (ESS) appears as a powerful flexibility tool. Nevertheless, the associated control problem of microgrids increases with the number of connected devices. A structuration of the distribution grids in networks of microgrids is proposed, focusing on their ability to provide flexibility services. The complexity of the associated optimization algorithm is faced using Distributed Model Predictive Control (MPC). The algorithm is divided in two steps. The first one is applied to the cooperative participation of microgrids in the day-ahead market. The second step covers the interaction with the SO offering flexibility services in exchange for a financial benefit. The financial benefit is optimally shared between the networked microgrids to satisfy the power profile requested by the SO at the lowest cost. As the proposed control algorithm presents both continuous and binary variables, its associated optimization problem is formulated using the Mixed Logic Dynamic (MLD) framework, which results in a Mixed Integer Quadratic Programming problem (MIQP).

中文翻译：

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使用模型预测控制的支持电网灵活性服务的网络微电网协同优化

向完全基于可再生能源的电力系统的过渡将需要增加系统运营商（SO）处置的储备数量，以在能源管理过程中提供灵活性。微电网整合分布式能源，负荷和储能系统（ESS）的能力似乎是一种强大的灵活性工具。然而，微电网的相关控制问题随着所连接设备的数量而增加。提出了微电网网络中配电网的结构，重点是其提供灵活性服务的能力。使用分布式模型预测控制（MPC）会面临相关联的优化算法的复杂性。该算法分为两个步骤。第一个应用于微电网在日前市场中的合作参与。第二步涉及与提供灵活性服务的SO的交互，以换取经济利益。在联网的微电网之间可以最佳地共享财务收益，从而以最低的成本满足SO要求的功率曲线。由于所提出的控制算法同时包含连续变量和二进制变量，因此使用混合逻辑动态（MLD）框架来制定其相关的优化问题，从而导致混合整数二次规划问题（MIQP）。