结合IGWO算法和SVM的园区综合能源系统效益评价模型构建

刘书圆, 王枭, 彭佳豪, 郑靖, 章继成

太阳能学报 ›› 2026, Vol. 47 ›› Issue (4) : 74-81.

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太阳能学报 ›› 2026, Vol. 47 ›› Issue (4) : 74-81. DOI: 10.19912/j.0254-0096.tynxb.2024-2163

结合IGWO算法和SVM的园区综合能源系统效益评价模型构建

  • 刘书圆, 王枭, 彭佳豪, 郑靖, 章继成
作者信息 +

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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文章历史 +

摘要

针对当前园区综合能源系统效益评价中存在的指标单一、方法传统、难以全面反映系统综合效能的问题,提出一种结合改进灰狼优化算法与支持向量机的园区综合能源系统效益评价模型。该方法通过构建涵盖社会、经济、环境3个维度的综合评价指标体系,并利用改进灰狼优化算法优化支持向量机参数,提升模型收敛速度与预测精度,从而实现对园区综合能源系统综合效益的准确、高效评估。实证结果表明,所提改进混合模型在损失度、训练效率和评价准确性方面均显著优于传统支持向量机及原始混合模型,能够为园区能源系统的规划、优化与可持续发展提供科学依据与决策支持。

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.

关键词

能源系统 / 能源存储 / 可再生能源 / 能源效率 / 支持向量机 / 灰狼优化算法

Key words

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

引用本文

导出引用
刘书圆, 王枭, 彭佳豪, 郑靖, 章继成. 结合IGWO算法和SVM的园区综合能源系统效益评价模型构建[J]. 太阳能学报. 2026, 47(4): 74-81 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2163
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
中图分类号: F124.5   

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基金

中国长江电力股份有限公司资助项目(z152302044/z612302013)

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