| 引用本文: | 程 杉,傅 桐,李沣洋,高心杰,王 灿.含高渗透可再生能源的配电网灵活性供需协同规划[J].电力系统保护与控制,2023,51(22):1-12.[点击复制] |
| CHENG Shan,FU Tong,LI Fengyang,GAO Xinjie,WANG Can.Flexible supply demand collaborative planning for distribution networks with high penetration of renewable energy[J].Power System Protection and Control,2023,51(22):1-12[点击复制] |
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| 摘要: |
| 高渗透率可再生能源并网加剧了配电网运行的波动性和不确定性。为提高配电网灵活性和抗干扰能力，提出了含高渗透率可再生能源的配电网灵活性供需协同规划方法。根据系统运行灵活性供需关系，定义灵活性评价指标。进而提出配电网灵活性供需协同规划策略，建立考虑季节特性的配电网灵活性资源双层优化配置模型。上层以投资成本和灵活性不足率最小为目标，制定灵活性资源配置方案。下层考虑需求侧对季节性电价激励的响应程度进行有功-无功联合优化，实现对配电网日内多场景时序运行的最优调度。为求解该双层混合整数非线性规划模型，采用二阶锥松弛对潮流方程进行凸优化，进而利用KKT条件将双层模型转化为单层混合整数二阶锥规划模型进行求解。算例仿真结果表明，该方法有效提升了配电网运行灵活性和稳定性，为分布式可再生能源规模化并网等相关工程提供决策参考。 |
| 关键词: 高渗透率可再生能源 配电网 灵活性指标 供需协同规划 有功-无功联合优化 |
| DOI：10.19783/j.cnki.pspc.230576 |
| 投稿时间：2023-05-17修订日期：2023-09-20 |
| 基金项目:国家自然科学基金项目资助(52107108)；电力系统智能运行与安全防御宜昌市重点实验研究项目资助(2020DLXY01) |
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| Flexible supply demand collaborative planning for distribution networks with high penetration of renewable energy |
| CHENG Shan,FU Tong,LI Fengyang,GAO Xinjie,WANG Can |
| (Yichang Key Laboratory of Intelligent Operation and Security Defense of Power System
(China Three Gorges University), Yichang 443002, China) |
| Abstract: |
| High penetration renewable energy grid connection has exacerbated the volatility and uncertainty of distribution network operation. To improve the flexibility and anti-interference ability of distribution networks, a flexible supply-demand collaborative planning method for networks containing high penetration of renewable energy is proposed. From the supply-demand relationship of system operation flexibility, flexibility evaluation indicators are defined. A collaborative planning strategy for distribution network flexibility supply and demand is proposed, and a bilevel optimal allocation model for the network flexibility resources considering seasonal characteristics is established. The upper layer formulates a flexible resource allocation scheme with the objective of minimizing investment cost and insufficient flexibility rate. The lower layer takes into account the response of the demand side to seasonal electricity price incentives for active and reactive power joint optimization to achieve the optimal scheduling of multi scenario time series operation of the network during the day. To solve the bilevel mixed integer nonlinear programming model, a second-order cone relaxation is used to convexly optimize the power flow equation, and then the bilevel model is transformed into a single-layer mixed integer second-order cone programming model using the KKT condition. Simulation results show that this method effectively improves the flexibility and stability of distribution network operation, and provides decision-making reference for large-scale grid connection of distributed renewable energy and other related projects. |
| Key words: high penetration renewable energy distribution grid flexibility index supply demand coordination planning joint active-reactive optimization |
