电气工程学报 ›› 2023, Vol. 18 ›› Issue (1): 153-159.doi: 10.11985/2023.01.017

• 电力系统 • 上一篇    下一篇

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考虑需求响应不确定性的综合能源系统优化调度研究*

李宁1(), 孙文慧2(), 毕云帆3(), 张智晟1()   

  1. 1.青岛大学电气工程学院 青岛 266071
    2.青岛地铁集团有限公司 青岛 266100
    3.中国移动通信集团山东有限公司青岛分公司 青岛 266071
  • 收稿日期:2021-09-27 修回日期:2021-11-25 出版日期:2023-03-25 发布日期:2023-04-19
  • 通讯作者: 张智晟,男,1975年生,博士,教授。主要研究方向为电力系统短期负荷预测和经济调度。E-mail:slnzzs@126.com
  • 作者简介:李宁,男,1996年生,硕士研究生。主要研究方向为综合能源系统经济运行与调度。E-mail:1367148613@qq.com
    孙文慧,女,1993年生,硕士。主要研究方向为电力系统供配电技术。E-mail:372744832@qq.com
    毕云帆,男,1994年生,硕士。主要研究方向为电力系统智能运维。E-mail:qd_biyunfan@139.com
  • 基金资助:
    *国网山东省电力公司科技资助项目(2020A-022)

Integrated Energy System Considering Demand Response Uncertainty Research on Optimal Scheduling

LI Ning1(), SUN Wenhui2(), BI Yunfan3(), ZHANG Zhisheng1()   

  1. 1. College of Electrical Engineering, Qingdao University, Qingdao 266071
    2. Qingdao Metro Group Co., Ltd., Qingdao 266100
    3. Qingdao Branch of China Mobile Shandong Co., Ltd., Qingdao 266071
  • Received:2021-09-27 Revised:2021-11-25 Online:2023-03-25 Published:2023-04-19

摘要:

为了降低需求响应在系统调度时的不确定性,提高系统运行时负荷侧响应的灵活性,建立了考虑需求响应不确定性和负荷预测误差的综合能源系统优化调度模型。在综合能源系统中引入电-气联合需求响应,在保证系统稳定运行前提下,合理安排各时段各机组出力。利用相关机会规划将目标函数转化为不确定环境下事件成立概率最大化的机会函数,通过多目标规划中的优先级算法,将多目标规划转化为单目标规划,运用粒子群优化算法对模型进行求解。通过实际的算例仿真分析,验证了模型的可行性和经济性。

关键词: 综合能源系统, 需求响应, 功率平衡方程, 相关机会规划, 不确定性

Abstract:

In order to reduce the uncertainty of demand side response in system scheduling and improve the flexibility of load side response during the integrated energy system operation, a comprehensive energy system optimal scheduling study considering demand response uncertainty and load forecasting error is established. Through the electrical joint demand response, the output of each unit in each period shall be reasonably arranged on the premise of ensuring the stable operation of the IES system. The objective function is transformed into an opportunity function to maximize the probability of event establishment in an uncertain environment by using relevant opportunity programming, so as to solve the model. Through the priority algorithm in multi-objective programming, the multi-objective programming is transformed into single objective programming, PSO algorithm is used to solve this model. The feasibility and economy of the model are verified by the simulation analysis of a practical example.

Key words: Integrated energy system, demand response, power balance equation, relevant opportunity planning, uncertainty

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