发电技术 ›› 2023, Vol. 44 ›› Issue (2): 253-260.DOI: 10.12096/j.2096-4528.pgt.22119

• 智能电网 • 上一篇    下一篇

考虑需求响应的源--储多时间尺度协同优化调度策略

杨锡勇1, 张仰飞1, 林纲2, 张玉卓1, 安允展3, 杨昊天3   

  1. 1.南京工程学院电力工程学院, 江苏省 南京市 211167
    2.国网福建省电力有限公司泉州供电公司, 福建省 泉州市 362000
    3.国网浙江省电力有限公司绍兴供电公司, 浙江省 绍兴市 312000
  • 收稿日期:2022-07-09 出版日期:2023-04-30 发布日期:2023-04-28
  • 作者简介:杨锡勇(1998),男,硕士研究生,研究方向为电力系统运行与控制、优化调度,yangxiyong1998@163.com
  • 基金资助:
    国家自然科学基金项目(52107098)

Multi-Time Scale Collaborative Optimal Scheduling Strategy for Source-Load-Storage Considering Demand Response

Xiyong YANG1, Yangfei ZHANG1, Gang LIN2, Yuzhuo ZHANG1, Yunzhan AN3, Haotian YANG3   

  1. 1.School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, Jiangsu Province, China
    2.Quanzhou Power Supply Company, Fujian Electric Power Co. , Ltd. , Quanzhou 362000, Fujian Province, China
    3.Shaoxing Power Supply Company, Zhejiang Electric Power Co. , Ltd. , Shaoxing 312000, Zhejiang Province, China
  • Received:2022-07-09 Published:2023-04-30 Online:2023-04-28
  • Supported by:
    National Natural Science Foundation of China(52107098)

摘要:

为应对未来高比例新能源接入带来的挑战,需充分挖掘不同类型调度资源的可调潜力。为此,提出了一种考虑需求响应的源-荷-储多时间尺度优化调度策略,旨在通过源-荷-储参与电网协同优化调度,提高系统运行的经济性和可靠性。首先,分析了不同类型可调资源的特性,构建了多时间尺度滚动调度总体框架,将整体调度分为日前调度和日内调度2个阶段;其次,基于多场景随机规划方法,建立了以系统总运行成本最小为目标的日前、日内优化调度模型,并在保证系统可靠运行的前提下对模型进行求解;最后,采用改进IEEE-30节点系统进行仿真分析,验证了所提策略的可行性和有效性。

关键词: 新能源, 源-荷-储, 需求响应, 多时间尺度, 滚动调度, 多场景随机规划

Abstract:

In order to meet the challenges brought by the high proportion of new energy access in the future, it is necessary to fully tap the adjustable potential of different types of scheduling resources. Therefore, a multi-time scale optimal scheduling strategy of source-load-storage considering demand response was proposed to improve the economy and reliability of system operation by participating in the coordinated optimal scheduling of power grid. Firstly, the characteristics of different types of adjustable resources were analyzed, and the overall framework of multi-time scale rolling scheduling was constructed. The overall scheduling was divided into two stages: day-ahead scheduling and intra-day scheduling. Secondly, based on the multi-scenario stochastic programming method, the day-ahead and intra-day optimal scheduling models with the goal of minimizing the total operating cost of the system were established, and the models were solved under the premise of ensuring the reliable operation of the system. Finally, the improved IEEE-30 node system was used for simulation analysis to verify the feasibility and effectiveness of the proposed strategy.

Key words: new energy, source-load-storage, demand response, multi-time scale, rolling scheduling, multi-scenario stochastic planning

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