系统仿真学报 ›› 2022, Vol. 34 ›› Issue (4): 817-825.doi: 10.16182/j.issn1004731x.joss.20-0893

• 仿真建模理论与方法 • 上一篇    下一篇

计及可中断负荷的园区综合能源系统优化调度

马立新(), 程颍()   

  1. 上海理工大学 机械工程学院,上海 200093
  • 收稿日期:2020-11-13 修回日期:2020-12-22 出版日期:2022-04-30 发布日期:2022-04-19
  • 通讯作者: 程颍 E-mail:1022151953@qq.com;1375591359@qq.com
  • 作者简介:马立新(1960-),男,博士,教授,研究方向为电力系统稳定性与优化运行、电机控制、智能电网等。E-mail:1022151953@qq.com

Optimal Operation for Park Integrated Energy System Considering Interruptible Loads

Lixin Ma(), Ying Cheng()   

  1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2020-11-13 Revised:2020-12-22 Online:2022-04-30 Published:2022-04-19
  • Contact: Ying Cheng E-mail:1022151953@qq.com;1375591359@qq.com

摘要:

热电机组“以热定电”运行时在调峰能力上有一定的局限性,可中断负荷(interruptible load,IL)作为一种待挖掘的电力资源,可以应用在园区综合能源管理和微网系统中,引导用户减少高峰用电。在含有热电联产机组的园区综合能源系统中引入IL功能改善系统调峰能力,以经济性作为集成优化目标,建立相应模型。以北方某生态园区为算例,利用自适应混沌粒子群算法进行仿真求解。结果表明:引入IL功能后的园区微网可以进行削峰运行且运行经济性和供能灵活性均有较大提高。通过与传统算法的比较,自适应混沌粒子群算法在优化结果精度和优化效率上均更优。

关键词: 热电联产, 以热定电, 可中断负荷, 综合能源, 自适应混沌粒子群算法

Abstract:

The operating mode of thermal power generation units has certain limitations in peak shaving capacity. Interruptible load (IL), as a power resource to be tapped, can be applied to the park integrated energy management and microgrid systems to guide users to reduce peak electricity consumption. The IL function is introduced into the park integrated energy system with combined heat and power units to improve the system's peak shaving ability, and the corresponding model is established with the optimization goal of economy. Taking an ecological park of northern region as the example, the adaptive chaotic particle swarm algorithm is used in the simulation. The results show that the park microgrid after the introduction IL project can perform peak-shaving operation, and the operating economy and energy supply flexibility are greatly improved. Compared with the traditional algorithms, the adaptive chaotic particle swarm optimization algorithm is better in the optimization result accuracy and optimization efficiency.

Key words: combined heat and power, setting electricity by heat, interruptible loads, integrated energy, adaptive chaos particle swarm optimization

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