• 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 ›› 2019, Vol. 40 ›› Issue (5): 128-.doi: 10.3969/j.issn.1000-7229.2019.05.015

• 智能电网 • 上一篇    

考虑运行风险的主动配电网分布式电源多目标优化配置

方金涛,龚庆武   

  1. 武汉大学电气与自动化学院,武汉市 430072
  • 出版日期:2019-05-01
  • 作者简介:国家电网公司科技项目(2018YFB0904205)

Multi-objective Optimization Configuration of Distributed Generation for Active Distribution Network Considering Operational Risk

FANG Jintao, GONG Qingwu   

  1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
  • Online:2019-05-01
  • About author:方金涛(1993),男,硕士研究生,主要研究方向为电力系统运行与控制; 龚庆武(1967),男,通信作者,教授,博士生导师,主要研究方向为电力系统运行与控制、电力系统仿真等。
  • Supported by:
    This work is supported by State Grid Corporation of China Research Program(No. 2018YFB0904205).

摘要: 考虑配电网运行中的不确定性,文章通过改进蒙特卡洛法生成大量预想事故集,利用潮流计算和拓扑分析得到接入分布式电源后系统运的行风险。提出一种考虑主动配电网运行风险的分布式电源多目标优化配置模型,将主动配电网运行带来的运行风险RL与分布式电源运行成本CDG作为目标函数,采用改进的粒子群算法对多目标优化模型进行求解,获得分布式电源安装位置和安装容量以及运行风险与运行成本之间的权衡关系。仿真算例表明,所提出的考虑主动配电网运行风险的分布式电源多目标优化配置方法,与单一只考虑经济性或者可靠性的优化模型相比更加合理,适用于分布式电源的优化选址和定容,验证了该模型的可行性。

关键词: 风险评估, 改进蒙特卡洛法, 分布式电源, 改进粒子群算法, 优化配置

Abstract: Considering the uncertainty in the operation of distribution network, a risk assessment model is established to evaluate the system operation risk of accessing distributed power by the improved Monte Carlo method using the power flow calculation and topology analysis. A multi-objective optimal allocation model of distributed generation considering the operational risk of active distribution network is proposed. The operational risk RL  and operational cost  CDG  of active distribution network operation are taken as objective functions. An improved particle swarm optimization algorithm is used to solve the multi-objective optimization model to obtain the configuration of distributed generation and the trade-off between operational risk and operating costs. The simulation results show that the proposed multi-objective optimal allocation method for distributed generation considering the operational risk of active distribution network is more reasonable than the single optimization model considering only economy or reliability. It is suitable for seeking the optimal location and capacity of distributed generation, and the feasibility of the model is verified.

Key words: risk assessment, improved Monte Carlo method, distributed generation, improved particle swarm optimization algorithm, optimization configuration

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