• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2020, Vol. 41 ›› Issue (7): 100-109.doi: 10.12204/j.issn.1000-7229.2020.07.013

• 新能源发电 • 上一篇    下一篇

含高比例风光新能源电网的多目标无功优化算法

杨蕾1,吴琛2,黄伟2,郭成1,向川1,何鑫1,邢超1,奚鑫泽1,周鑫1,杨博3,张孝顺4   

  1. 1.云南电网有限责任公司电力科学研究院,昆明市 650200;2.云南电网有限责任公司电力调度控制中心,昆明市650051;3.昆明理工大学电力工程学院,昆明市650500;4. 汕头大学工学院,广东省汕头市 515063
  • 出版日期:2020-07-01
  • 作者简介:杨蕾(1986),女,硕士,高级工程师,研究方向为电力系统稳定分析与控制、继电保护等; 吴琛(1974),女,教授级高级工程师,研究方向为电网调度运行; 黄伟(1979),男,博士,工程师,研究方向为电力系统运行与分析; 郭成(1978),男,博士,高级工程师,研究方向为电力系统稳定与控制,电能质量监测与分析技术; 向川(1991),男,硕士,助理工程师,研究方向为系统仿真分析; 何鑫(1990),男,硕士,工程师,研究方向为电力系统仿真、电力系统稳定分析与控制; 邢超(1986),男,硕士,高级工程师,研究方向为直流输电与电力电子技术; 奚鑫泽(1988),男,博士,工程师,研究方向为新能源并网技术与系统分析; 周鑫(1984),男,硕士,高级工程师,研究方向为频率稳定与控制、网源协调等; 杨博(1988),男,博士,副教授,通信作者,研究方向为新能源与储能系统优化与控制,人工智能在智能电网中的应用; 张孝顺(1990),男,博士,副教授,研究方向为电力系统优化控制与启发式算法。
  • 基金资助:
    国家自然科学基金项目(61963020);云南电网公司科技项目 “多直流与高比例新能源的云南电网稳控拓展技术研究与闭环仿真平台” (KJDK2018210)

Pareto-Based Multi-objective Reactive Power Optimization for Power Grid with High-Penetration Wind and Solar Renewable Energies

YANG Lei1,WU Chen2,HUANG Wei2,GUO Cheng1,XIANG Chuan1,HE Xin1,XING Chao1,XI Xinze1,ZHOU Xin1,YANG Bo3,ZHANG Xiaoshun4   

  1. 1. Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming 650200, China;2. Power Dispatching Control Center, Yunnan Power Grid Co., Ltd., Kunming 650051, China;3. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China;4. College of Engineering, Shantou University, Shantou 515063, Guangdong Province, China
  • Online:2020-07-01
  • Supported by:
    This work is supported by National Natural Science Foundation of China(No. 61963020) and Science and Technology Project of Yunnan Power Grid Company “Yunnan Power Grid Stability Control Technology Research and Closed Loop Simulation Platform with Multiple DC and High Proportion of New Energy” (No. KJDK2018210).

摘要: 为适应新能源大量接入电网的趋势,基于不同时刻的风速、光照强度、温度等气象条件信息,评估出风光新能源的无功调节容量,搭建了含高比例风光新能源参与调控的电网多目标无功优化模型。为快速获得电网中变压器分接头档位调节、无功补偿设备投切、传统发电机组电压调节以及风光的无功输出等控制措施的帕累托最优解集,采用寻优性能高效的多目标樽海鞘群算法(multi-objective salp swarm algorithm, MSSA)进行无功优化求解。为更客观找出电网线损、电压偏差、静态电压稳定裕度等不同目标之间的折中解,采用改进的理想点法进行多目标最优解集决策。最后,利用扩展的IEEE标准9节点和39节点算例进行仿真分析,并引入传统多目标智能优化算法来进行比较验证。仿真结果表明:与其他2种传统多目标智能优化算法相比,所提算法获得的帕累托前沿分布更广、更均匀;利用改进理想点法进行决策之后,可有效降低电网的线损和电压偏差,同时提高了电网的静态电压稳定裕度。

关键词: 风光新能源, 帕累托, 多目标优化, 无功优化, 多目标樽海鞘群算法(MSSA)

Abstract: To adapt the trend of high-penetration renewable energies paralleled in power grid, this paper constructs a multi-objective reactive power optimization for power grid with the controlled participation of high-penetration wind and solar renewable energies. Particularly, the reactive power regulation capacities of renewable energies are evaluated according to the wind speed, solar irradiation, and temperature in different time. To obtain the optimal dispatch scheme of transformer taps, shunt capacitor states, voltage outputs of generators, and reactive power outputs of renewable energies, a multi-objective salp swarm algorithm (MSSA) is employed for the multi-objective reactive power optimization. Then an improved ideal-point based decision method is designed to select a compromise solution among multiple non-dominated points, thus three objectives of power loss, voltage deviation, and static voltage stability margin can be properly balanced. Finally, an extended IEEE 9-bus system and an extended IEEE 39-bus system are used to evaluate the performance of the proposed algorithm compared with conventional multi-objective intelligent optimization algorithms. Simulation results demonstrate that the proposed algorithm can obtain a widely spread and well-distributed Pareto front compared with conventional multi-objective optimization algorithms. Moreover, the improved ideal-point based decision method not only can effectively reduce the power loss and voltage deviation, but also can improve the static voltage stability margin.

Key words: wind and solar renewable energies, Pareto, multi-objective optimization, reactive power optimization, multi-objective salp swarm algorithm (MSSA)

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