This study presents a multi-objective bi-level optimization model for distributed generation (DG) allocation in smart distribution grids integrating energy storage devices. As part of smart distribution grids, four active management schemes, coordinated on-load tap-changer voltage control, DG power factor control, DG curtailment and demand side management, are embedded in the proposed model. Uncertainties related to DGs, loads and contingencies and the capability of energy storage devices for peak shaving and renewable energy compensation are also inherent. The allocation model simulates the network transfer process to postpone the DG investment. The trade-off between the defined annual total cost and N-1 security margin index is achieved in the optimal allocation methodology considering operation thresholds and security improvements. The DG allocation solutions are solved by a hybrid algorithm. The correlated input parameters of the optimization problem, such as wind speed, illumination intensity and load, are generated using quasi Monte Carlo simulation and singular value decomposition and then simplified by fuzzy C-means clustering to improve the computation efficiency of optimal power flow. A modified 104-bus distribution case is used to demonstrate the effectiveness and flexibility of the proposed model.

中文翻译：

---

考虑主动管理和突发事件的智能配电网分布式电源协调优化配置

本研究提出了一种多目标双层优化模型，用于集成储能设备的智能配电网中的分布式发电 (DG) 分配。作为智能配电网的一部分，所提出的模型中嵌入了四种主动管理方案，即协调有载分接开关电压控制、DG 功率因数控制、DG 弃电和需求侧管理。与 DG、负载和突发事件相关的不确定性以及储能设备用于调峰和可再生能源补偿的能力也是固有的。分配模型模拟网络转移过程，推迟DG投资。在考虑操作阈值和安全改进的优化分配方法中实现了定义的年度总成本和 N-1 安全边际指数之间的权衡。DG 分配解决方案由混合算法求解。优化问题的相关输入参数，如风速、光照强度和负载，使用拟蒙特卡罗模拟和奇异值分解生成，然后通过模糊C-means聚类进行简化，以提高最优潮流的计算效率。修改后的 104 总线配电案例用于证明所提出模型的有效性和灵活性。