• 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 ›› 2015, Vol. 36 ›› Issue (1): 65-71.doi: 10.3969/j.issn.1000-7229.2015.01.010

• 主动配电网关键技术专辑 • 上一篇    下一篇

考虑不确定性的多阶段主动配电网规划模型研究

曾鸣,韩旭,李博   

  1. 华北电力大学经济与管理学院,北京市102206
  • 出版日期:2015-01-01
  • 作者简介:曾鸣(1957),男,教授,博士生导师,研究方向为电网规划,电力市场理论与实务,需求侧管理; 韩旭(1990),女,硕士,研究方向为电网规划,需求侧管理; 李博(1990),女,硕士,研究方向为电网规划,需求侧管理。

Study of Multistage Planning for Active Distribution Networks Under Uncertainty

ZENG Ming,HAN Xu,LI Bo   

  1. College of Economics and Management, North China Electric Power University, Beijing102206,China
  • Online:2015-01-01

摘要:

针对主动配电网(active distribution networks,ADN)规划方法未充分计及实际拓展影响因素多样性的缺点,提出一种考虑需求和分布式发电(distributed generation,DG)不确定性的多阶段规划方法。基于生物地理学优化算法,量化分析实际条件下电网运行的多种不确定因素对主动配电网的受迫影响及其经济代价,构建可综合反映主动配电网在不同约束条件下的系统扩容综合成本模型。提出加权多维寻优理论,设计基于生物地理学优化算法的多维拓展规划流程;利用精益化管理思想,根据伪动态规划法,获得多阶段配电网规划下的系统最佳拓展方案。算例分析结果表明,所提方法能够实现对主动配电网拓展规划的优化设计,有效提高实际运行条件下系统的经济性和可靠性。

关键词: 主动配电网(ADN), 生物地理学优化算法, 多阶段规划, 分布式发电(DG)

Abstract:

 

This paper presents a multistage planning methodology for active distribution networks(ADN)planning which has not fully considered the defects of variable practical operation conditions, where the demand and distributed generation(DG) uncertainties are taken into account. Based on biogeography-based optimization, the forced affect and economy cost are analyzed by quantifying the uncertain factors under practical network operation, considering the network radial structure and expansion alternative, building the system composite cost function which can comprehensive reflect different constraints. Proposed weighted multidimensional optimization theory, designed expansion planning process and used lean management thinking to obtain the best system multi-stage expansion plan under distribution network planning according to the pseudo-dynamic programming method. After analyzing the results of example, the methodology can achieve the optimal design of planning and improve the system reliability and profit under practical operation effectively.

Key words: active distribution networks(ADN), biogeography-based optimization, multi-stageplanning, distributed generation(DG)