Abstract With larger scale renewable energy integrated, high-penetration renewable energy is deemed as one of the most important characteristics in the future power system. However, the inevitable uncertainty of both source and demand has brought significant challenges to planners. Since discoordination planning schemes restrict the optimal operation, a novel and efficient co-planning methodology is urgent to be investigated. Thus, we propose an innovative co-planning model of wind farm, energy storage and transmission network, which successfully takes imbalanced power, unit ramp capacity and incentive mechanism for renewable energy into consideration. To facilitate the renewable consumption, flexible implementations comprising optimal transmission switching (OTS) and unit commitment (UC) are integrated to further optimize the network topology and achieve flexible startup/shutdown of conventional unit. Furthermore, a linear tie-line model designed for multi-regional planning problems has been constructed to capture the presumed limitations. Afterwards, a decentralized decomposition algorithm based on analytical target cascading (ATC) is modified to deal with the proposed model through a completely parallel mode. The modified IEEE 48-bus test system demonstrates the priority of our proposed co-planning model and the corresponding solution algorithm.

中文翻译：

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具有高渗透率可再生能源的风电场、储能和输电网络协调规划

摘要 随着大规模可再生能源并网，高渗透率的可再生能源被认为是未来电力系统最重要的特征之一。然而，来源和需求不可避免的不确定性给规划者带来了重大挑战。由于不协调的规划方案限制了优化操作，迫切需要研究一种新颖有效的协同规划方法。因此，我们提出了一种创新的风电场、储能和输电网络协同规划模式，成功地考虑了不平衡的功率、单位斜坡容量和可再生能源的激励机制。为促进可再生能源消费，融合了最优传输切换（OTS）和单元承诺（UC）等灵活实现方式，进一步优化网络拓扑结构，实现传统单元的灵活启动/关闭。此外，还构建了一个为多区域规划问题设计的线性联系线模型，以捕捉假定的局限性。然后，修改了基于分析目标级联（ATC）的分散分解算法，以通过完全并行的模式处理所提出的模型。修改后的 IEEE 48 总线测试系统证明了我们提出的协同规划模型和相应的求解算法的优先级。为多区域规划问题设计的线性联系线模型已被构建以捕捉假定的局限性。然后，修改了基于分析目标级联（ATC）的分散分解算法，以通过完全并行的模式处理所提出的模型。修改后的 IEEE 48 总线测试系统证明了我们提出的协同规划模型和相应的求解算法的优先级。为多区域规划问题设计的线性联系线模型已被构建以捕捉假定的限制。然后，修改了基于分析目标级联（ATC）的分散分解算法，以通过完全并行的模式处理所提出的模型。修改后的 IEEE 48 总线测试系统证明了我们提出的协同规划模型和相应的求解算法的优先级。