• 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 (10): 118-125.doi: 10.3969/j.issn.1000-7229.2019.10.014

• 智能电网 • 上一篇    下一篇

产消型智能社区储能系统配置与运行联合优化

程瑜,王望   

  1. 华北电力大学电气与电子工程学院,北京市102206
  • 出版日期:2019-10-01
  • 作者简介:程瑜(1978),女,博士,副教授,主要研究方向为需求响应、微能源网规划与运行、电价理论及应用; 王望(1994),女,硕士研究生,主要研究方向为微能源网规划与运行、电动汽车充电设施规划。
  • 基金资助:
    国家自然科学基金项目(51207050)

Planning and Operation Joint Optimization of Energy Storage System in Prosumer Smart Community

CHENG Yu, WANG Wang   

  1. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
  • Online:2019-10-01
  • Supported by:
    This work is supported by National Natural Science Foundation of China(No. 51207050).

摘要: 针对呈现生产和消费双重形态的智能社区,提出一种与社区内其他源-荷资源协同增效的储能系统配置与运行联合优化模型及其求解算法。计及智能社区可控负荷资源的分类调节特性和储能系统容量损耗特性,并考虑分布式光伏出力的不确定性,联合应用场景法和机会约束规划,建立随机优化模型,并将其转化为混合整数线性规划(mixed integer linear programming, MILP)模型以便求解。算例仿真分析了智能社区联络主网的变电容量、机会约束置信度、梯级利用电池对社区经济配置储能系统决策的影响。分析结果表明采用所提模型可计及可再生能源不确定性联合优化智能社区储能系统配置与运行策略。

关键词: 产消型智能社区, 储能系统配置优化, 机会约束, 混合整数线性规划(MILP)

Abstract: Aiming at the smart community with dual forms of production and consumption, a joint optimization model of energy storage system planning and operation and its solution algorithm are proposed in this paper. Considering the classification regulation characteristics of controllable load resources in the smart community, the capacity loss characteristics of the energy storage system and the uncertainty of distributed photovoltaic output, combining the scenario method and chance constraint programming, a stochastic optimization model is established and converted into a mixed integer linear programming model (MILP) for solving the problem. The influence of the substation capacity, the confidence of chance constraint and the cascade utilization of battery on the decision of the community economic allocation on energy storage system is analyzed. The results show that the model can be used to optimize the energy storage capacity planning and the operation schedule of smart community considering the uncertainties of renewable energy.

Key words: prosumer smart community, energy storage planning optimization, chance constraint, mixed integer linear programming(MILP)

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