CONSTRUCTION OF COMPREHENSIVE ENERGY SYSTEM BENEFIT EVALUATION MODEL FOR INDUSTRIAL PARKS COMBINING IGWO ALGORITHM AND SVM

Liu Shuyuan; Wang Xiao; Peng Jiahao; Zheng Jing; Zhang Jicheng

doi:10.19912/j.0254-0096.tynxb.2024-2163

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (4) : 74-81. DOI: 10.19912/j.0254-0096.tynxb.2024-2163

CONSTRUCTION OF COMPREHENSIVE ENERGY SYSTEM BENEFIT EVALUATION MODEL FOR INDUSTRIAL PARKS COMBINING IGWO ALGORITHM AND SVM

Liu Shuyuan, Wang Xiao, Peng Jiahao, Zheng Jing, Zhang Jicheng

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Abstract

In response to the problems of single indicators, traditional methods, and difficulty in fully reflecting the overall efficiency of the comprehensive energy system in current parks, this paper proposes a park comprehensive energy system efficiency evaluation model that combines improved grey wolf optimization algorithm and support vector machine. This method constructs a comprehensive evaluation index system covering three dimensions of society, economy, and environment, and uses an improved grey wolf optimization algorithm to optimize support vector machine parameters, thereby improving the convergence speed and prediction accuracy of the model, and achieving accurate and efficient evaluation of the comprehensive benefits of the park's integrated energy system. The empirical results show that the proposed improved hybrid model is significantly better than traditional support vector machines and the original hybrid model in terms of loss degree, training efficiency, and evaluation accuracy. It can provide scientific basis and decision support for the planning, optimization, and sustainable development of the energy system in the park.

Key words

energy system / energy storage / renewable energy / energy efficiency / support vector machine / grey wolf optimization algorithm

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Liu Shuyuan, Wang Xiao, Peng Jiahao, Zheng Jing, Zhang Jicheng. CONSTRUCTION OF COMPREHENSIVE ENERGY SYSTEM BENEFIT EVALUATION MODEL FOR INDUSTRIAL PARKS COMBINING IGWO ALGORITHM AND SVM[J]. Acta Energiae Solaris Sinica. 2026, 47(4): 74-81 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2163

References

[1] 马晓燕, 穆云飞, 李树荣, 等. 数据中心综合能源系统优化运行研究综述[J]. 电力建设, 2022, 43(11): 1-13.
MA X Y, MU Y F, LI S R, et al.Review on the optimal operation of integrated energy system in data center[J]. Electric power construction, 2022, 43(11): 1-13.
[2] 范英, 姚星, 樊伟. 能源系统低碳转型中的气象风险[J]. 石油科学通报, 2023, 8(4): 512-521.
FAN Y, YAO X, FAN W.Meteorological risks in the low carbon transitions of the energy system[J]. Petroleum science bulletin, 2023, 8(4): 512-521.
[3] 李嘉祺, 陈艳波, 陈来军, 等. 工业园区综合能源系统低碳经济优化运行模型[J]. 高电压技术, 2022, 48(8): 3190-3200.
LI J Q, CHEN Y B, CHEN L J, et al.Low-carbon economy optimization model of integrated energy system in industrial parks[J]. High voltage engineering, 2022, 48(8): 3190-3200.
[4] 张鸿宇, 黄晓丹, 张达, 等. 加速能源转型的经济社会效益评估[J]. 中国科学院院刊, 2021, 36(9): 1039-1048.
ZHANG H Y, HUANG X D, ZHANG D, et al.Evaluating economic and social benefits of accelerated energy transition[J]. Bulletin of Chinese Academy of Sciences, 2021, 36(9): 1039-1048.
[5] 王永真, 张靖, 潘崇超, 等. 综合智慧能源多维绩效评价指标研究综述[J]. 全球能源互联网, 2021, 4(3): 207-225.
WANG Y Z, ZHANG J, PAN C C, et al.Multi-dimensional performance evaluation index review of integrated and intelligent energy[J]. Journal of global energy interconnection, 2021, 4(3): 207-225.
[6] 钱梦羽, 窦真兰, 陈洪银, 等. 双碳目标下综合能源系统评价指标体系与方法研究进展[J]. 电气应用, 2021, 40(12): 72-79.
QIAN M Y, DOU Z L, CHEN H Y, et al.Research progress on evaluation index system and method of integrated energy system under the goal of “Carbon Peak and Neutrality”[J]. Electrotechnical application, 2021, 40(12): 72-79.
[7] 杨旭, 王瑞, 余畅文, 等. 基于改进灰狼优化算法的分布式能源系统优化调度[J]. 内蒙古电力技术, 2023, 41(1): 26-33.
YANG X, WANG R, YU C W, et al.Optimal scheduling of distributed energy system based on improved grey wolf optimization algorithm[J]. Inner Mongolia electric power, 2023, 41(1): 26-33.
[8] 孙朝云, 韩雨希, 户媛姣, 等. 基于IGWO-XGBoost融合模型的沥青路面抗滑性能评估[J]. 计算机系统应用, 2023, 32(4): 66-76.
SUN Z Y, HAN Y X, HU Y J, et al.Evaluation of skid resistance of asphalt pavement based on IGWO-XGBoost fusion model[J]. Computer systems & applications, 2023, 32(4): 66-76.
[9] 梁硕, 王艳松. 基于改进云物元模型的工业园区综合能源系统规划方案评价[J]. 电力系统保护与控制, 2023, 51(9): 165-176.
LIANG S, WANG Y S.Evaluation of an integrated energy system planning scheme for an industrial park based on an improved cloud matter-element model[J]. Power system protection and control, 2023, 51(9): 165-176.
[10] 胡业林, 马向阳, 钱文月, 等. 基于小波包信息熵和SO-SVM的滚动轴承故障诊断[J]. 电子测量技术, 2023, 46(14): 80-86.
HU Y L, MA X Y, QIAN W Y, et al.Fault diagnosis of rolling bearing based on wavelet packet entropy and SO-SVM[J]. Electronic measurement technology, 2023, 46(14): 80-86.
[11] 董文校, 任洪波, 皇甫艺, 等. 基于实测数据的工业企业光-沼-气-电多能耦合系统综合评价[J]. 科学技术与工程, 2024, 24(19): 8099-8108.
DONG W X, REN H B, HUANGFU Y, et al.Comprehensive evaluation study of PV-biogas-gas-electricity multi-energy coupling system for industrial enterprises based on actual measurement data[J]. Science technology and engineering, 2024, 24(19): 8099-8108.
[12] 陈星彤, 张宁, 王轶楠, 等. 基于混合赋权和MARCOS模型的低碳园区综合效益评价研究[J]. 智慧电力, 2024(5): 23-30.
CHEN X T, ZHANG N, WANG Y N, et al.Comprehensive benefit evaluation of low-carbon industrial parks based on combination weighting and MARCOS model[J]. Smart power, 2024(5): 23-30.
[13] 胡水彬, 李大华, 孔祥玉, 等. 电碳市场下考虑共享储能的多主体综合能源系统主从博弈优化运行[J]. 太阳能学报, 2025, 46(11): 481-491.
HU S B, LI D H, KONG X Y, et al.Optimization of master-slave game operation of multi agent integrated energy system considering shared energy storage under electric carbon market[J]. Acta energiae solaris sinica, 2025, 46(11): 481-491.
[14] 申融容, 姜丰, 韦泽全, 等. 基于博弈论组合赋权和MARCOS的能源互联网园区项目综合效益评价[J]. 综合智慧能源, 2023, 45(11): 70-81.
SHEN R R, JIANG F, WEI Z Q, et al.Comprehensive benefit evaluation for energy internet park projects based on combined weight of game[J]. Integrated intelligent energy, 2023, 45(11): 70-81.
[15] 王若平, 陈严, 王东, 等. 基于多特征提取与灰狼算法优化SVM的车内异响识别方法[J]. 计算机应用与软件, 2024, 41(3): 41-48.
WANG R P, CHEN Y, WANG D, et al.Vehicle interior abnormal noise recognition based on Muti-feature extraction and SVM optimized by gray wolf optimization[J]. Computer applications and software, 2024, 41(3): 41-48.
[16] 盛四清, 张佳欣, 李然. 基于组合赋权与灰云模型的综合能源系统需求响应效益评价[J]. 华北电力大学学报(自然科学版), 2024, 51(2): 41-52, I0008, I0009.
SHENG S Q, ZHANG J X, LI R. Demand response benefit evaluation of integrated energy system based on combination weighting and gray cloud model[J]. Journal of North China Electric Power University(natural science edition), 2024, 51(2): 41-52, I0008, I0009.
[17] 张治, 魏振华, 邓子琦. 基于热需求响应的综合能源系统可靠供能能力评估[J]. 科学技术与工程, 2022, 22(11): 4350-4358.
ZHANG Z, WEI Z H, DENG Z Q.Evaluation of the reliable energy supply interval of the integrated energy system with the participation of heat demand response[J]. Science technology and engineering, 2022, 22(11): 4350-4358.
[18] 李昌杰, 陈玉柱, 秦方, 等. 基于主从博弈的燃气-太阳能-地热能耦合系统运行优化[J]. 太阳能学报, 2024, 45(7): 333-339.
LI C J, CHEN Y Z, QIN F, et al.Optimal operation of coupled gas-solar-geothermal energy system based on Stackelberg game[J]. Acta energiae solaris sinica, 2024, 45(7): 333-339.
[19] 李亚峰, 王维庆, 寇洋, 等. 考虑绿证-碳联合交易与需求响应综合能源系统经济运行[J]. 太阳能学报, 2023, 44(11): 538-546.
LI Y F, WANG W Q, KOU Y, et al.Considering green certificate-carbon joint trading and demand response integrated energy system economic operation[J]. Acta energiae solaris sinica, 2023, 44(11): 538-546.
[20] 陈人杰, 李华取, 彭晓涛, 等. 基于改进TOPSIS的新能源大数据服务项目评价研究[J]. 电力建设, 2021, 42(3): 126-134.
CHEN R J, LI H Q, PENG X T, et al.Study on evaluation method for new energy big data service project applying improved TOPSIS[J]. Electric power construction, 2021, 42(3): 126-134.
[21] 许小刚, 嵇晓鹏, 周楠楠, 等. 光-气-储互补的综合能源系统全生命周期优化研究[J]. 太阳能学报, 2024, 45(7): 60-72.
XU X G, JI X P, ZHOU N N, et al.Research on whole life cycle optimization of integrated energy system with complementary solar, gas and storage[J]. Acta energiae solaris sinica, 2024, 45(7): 60-72.