采用融合遗传算法的高速公路服务区综合能源系统优化调度研究

李杰; 高爽; 袁博兴; 张懿璞

doi:10.7652/xjtuxb202405019

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采用融合遗传算法的高速公路服务区综合能源系统优化调度研究

—————————————————————— | 更新时间：2025-07-28

- 采用融合遗传算法的高速公路服务区综合能源系统优化调度研究
- Research on Optimal Scheduling of Integrated Energy System in Highway Service Area Based on a Genetic Algorithm-Sequential Quadratic Programming Algorithm
- 西安交通大学学报 2024年58卷第5期页码：200-211
- 作者机构：
  
  1. 长安大学能源与电气工程学院,西安,710064
  2. 长安大学电子与控制工程学院,西安,710064
- 作者简介：
  
  : 2023-10-18。作者简介: 李杰(1984—),男,博士,副教授,博士生导师。基金项目: 国家重点研发计划资助项目(2021YFB2601300)
- 基金信息：
  
  : 2023-10-18。作者简介: 李杰(1984—),男,博士,副教授,博士生导师。基金项目: 国家重点研发计划资助项目(2021YFB2601300);陕西省重点研发计划资助项目(2022GY-178)。
- DOI：10.7652/xjtuxb202405019
  中图分类号： TM734
- 网络首发：2024-05-10，
  
  纸质出版：2024
- 稿件说明：
移动端阅览
李杰, 高爽, 袁博兴, 等. 采用融合遗传算法的高速公路服务区综合能源系统优化调度研究[J]. 西安交通大学学报, 2024,58(5):200-211.

LI Jie, GAO Shuang, YUAN Boxing, et al. Research on Optimal Scheduling of Integrated Energy System in Highway Service Area Based on a Genetic Algorithm-Sequential Quadratic Programming Algorithm[J]. 2024, 58(5): 200-211.
李杰, 高爽, 袁博兴, 等. 采用融合遗传算法的高速公路服务区综合能源系统优化调度研究[J]. 西安交通大学学报, 2024,58(5):200-211. DOI： 10.7652/xjtuxb202405019.

LI Jie, GAO Shuang, YUAN Boxing, et al. Research on Optimal Scheduling of Integrated Energy System in Highway Service Area Based on a Genetic Algorithm-Sequential Quadratic Programming Algorithm[J]. 2024, 58(5): 200-211. DOI： 10.7652/xjtuxb202405019.

摘要

为达成“碳中和”目标愿景、促进公路交通系统与新能源的融合

以高速公路服务区为研究对象

考虑服务区内电、冷、热、气共4种负荷需求

构建了包含风光发电的新能源发电方式和电转气设备的高速公路服务区综合能源系统。在此基础上

以风电、光伏出力日前预测和多能负荷日前消耗为输入

各能源设备出力及购能分配为输出

以总成本最低为目标函数

考虑能量平衡、设备安全、运行状态等约束

建立了高速公路服务区综合能源系统优化调度模型。针对高速公路服务区综合能源系统调度问题

设计了遗传-序列二次规划融合优化算法

并以某服务区夏季典型日为例进行验证。结果表明:所构建的调度系统能够有效消纳可再生能源出力

协调外部购电、购气的比例

最终达到降低成本的效果; 所提融合算法的调度结果与传统遗传算法、传统序列二次规划算法相比

在成本上分别降低了11.52%、0.70%

求解耗时仅为传统遗传算法的6.7%

独立性相比传统序列二次规划算法得到了提高。

Abstract

To achieve the vision of “carbon neutrality” and promote the integration of highway transportation systems and new energy resources

the highway service areas is taken as the research object. Considering four types of load demands

including electricity

cooling

heating

and gas

a comprehensive energy system is developed for highway service areas

incorporating wind and solar power generation methods and power-to-gas equipment. On this basis

a comprehensive energy system optimization scheduling model for highway service areas is established

and the daily forecast of wind and solar power and the daily consumption of multi-energy load are taken as input

and the output of each equipment and the allocation of energy purchased are used as output

taking the lowest total cost as the objective function

considering constraints such as energy balance

equipment safety

and operating status. A genetic sequence quadratic programming fusion optimization algorithm is designed for the scheduling of comprehensive energy systems in highway service areas

and verified using a typical summer day in a service area as an example. The results show that the scheduling system can effectively accommodate renewable energy resources

coordinate the proportion of external electricity purchases and gas purchases

and ultimately reduce costs. The scheduling results obtained using the proposed fusion algorithm outperform those of traditional genetic algorithms and traditional sequential quadratic programming algorithms

with cost reductions of 11.52% and 0.70% respectively. The solving time is only 6.7% of that of traditional genetic algorithms

with improved independence compared to traditional sequential quadratic programming algorithms.

关键词

Keywords

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