上海交通大学学报

上海交通大学学报 >

2024 , Vol. 58 >Issue 9: 1432 - 1442

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.035

新型电力系统与综合能源

不确定性条件下农业微电网与灌溉系统相结合的鲁棒优化调度

  • 杨森 ,
  • 郭宁 ,
  • 张寿明
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  • 昆明理工大学 信息工程与自动化学院,昆明 650500
杨 森(1998—),硕士生,从事微电网优化运行与进化计算研究.
张寿明,教授; E-mail:1740229323@qq.com.

收稿日期: 2023-02-06

  修回日期: 2023-07-08

  录用日期: 2023-07-11

  网络出版日期: 2024-01-02

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Robust Optimal Scheduling of Agricultural Microgrid Combined with Irrigation System Under Uncertainty Conditions

  • YANG Sen ,
  • GUO Ning ,
  • ZHANG Shouming
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  • Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China

Received date: 2023-02-06

  Revised date: 2023-07-08

  Accepted date: 2023-07-11

  Online published: 2024-01-02

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摘要

农业微电网以低成本的方式为偏远农村地区的能源供应提供了一种有前景的解决方案.综合考虑风光抽水蓄能一体化农业微电网满足用电负荷和用水负荷需求,在可再生能源出力及用电负荷需求的不确定性条件下,提出包含抽水蓄能(PHS)电站的孤岛型农业微电网和灌溉系统相结合的鲁棒优化调度模型,利用农村地区水资源富足的特点和风光抽蓄补偿的优势,在最小化系统总成本的同时提高可再生能源的消纳.所提模型考虑分布式发电、用电负荷和用水负荷需求、涡轮流量和灌溉流量,具有多样性、多约束、非连续的特点.提出一种引力鲸鱼优化算法(GWOA)求解该模型,在某农业微电网上的仿真结果表明,GWOA可以获得比CPLEX求解器及其他新开发算法更具竞争力的解.另外,探究了降水量不确定性引起灌溉系统用水负荷需求变化对系统运行成本的影响以及使用PHS电站的必要性.

关键词： 农业微电网; 抽水蓄能; 灌溉系统; 不确定性条件; 引力鲸鱼优化算法

本文引用格式

杨森 , 郭宁 , 张寿明 . 不确定性条件下农业微电网与灌溉系统相结合的鲁棒优化调度[J]. 上海交通大学学报, 2024 , 58(9) : 1432 -1442 . DOI: 10.16183/j.cnki.jsjtu.2023.035

Abstract

Agricultural microgrids offer a promising solution for energy supply in remote rural areas in a low-cost manner. In this paper, under uncertain conditions of renewable energy output and electricity load demand, a robust optimal scheduling model combined with the isolated agricultural microgrid and irrigation system containing a pumped hydro storage (PHS) power station is proposed, considering the factors that the wind-landscape pumped storage integrated agricultural microgrid can satisfy the uncertain fluctuations of power load demand and water load demand. By utilizing the abundant water resources in rural areas and the advantages of landscape drainage and storage compensation, the total cost of the system is minimized while the absorption of renewable energy is increased. Considering distributed generation, power load demand and water load demand, turbine flow, and irrigation flow, the proposed model is characterized by diversity, multi-constraint, and discontinuity. A gravitational whale optimization algorithm (GWOA) is proposed to solve the model. The simulation results of an agricultural microgrid show that the GWOA can obtain a more competitive solution than the CPLEX solver and other newly developed algorithms do. In addition, the impact of the change of water load demand caused by precipitation uncertainty on the operating cost of the irrigation system and the necessity of using PHS power station are explored.

Key words： agricultural microgrid; pumped hydro storage (PHS); irrigation system; uncertainty condition; gravitational whale optimization algorithm (GWOA)

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