考虑乡村振兴贡献度的农网项目投资决策模型

doi:10.11930/j.issn.1004-9649.202306125

中国电力 ›› 2024, Vol. 57 ›› Issue (6): 181-192.DOI: 10.11930/j.issn.1004-9649.202306125

考虑乡村振兴贡献度的农网项目投资决策模型

赵会茹¹(), 姚满宇¹(), 李兵抗²(), 谢光龙³(), 丁智华⁴(), 胡臻达⁵()

1. 华北电力大学经济与管理学院，北京　102206
2. 华北电力大学经济管理系，河北保定　071003
3. 国网能源研究院有限公司，北京　102209
4. 国网福建省电力有限公司，福建福州　350001
5. 国网福建省电力有限公司经济技术研究院，福建福州　350012

收稿日期:2023-06-30 接受日期:2024-01-04 出版日期:2024-06-28 发布日期:2024-06-25
作者简介:赵会茹（1963—），女，博士，教授，从事电力产业经济与管理研究，E-mail：huiruzhao@163.com
姚满宇（1998—），女，硕士研究生，从事电力产业经济与管理研究，E-mail：yaomanyu1998@163.com
李兵抗（1993—），男，博士，从事电力市场理论及应用技术研究，E-mail：libingkang@163.com
谢光龙（1985—），男，博士，高级工程师，从事城市能源战略规划、城市能源协同管理研究，E-mail：xieguanglong@sgeri.sgcc.com.cn
丁智华（1968—），男，硕士，高级工程师，从事电力系统规划、经营管理研究，E-mail：89331523@qq.com
胡臻达（1986—），男，硕士，工程师，从事电网规划及柔性交直流输电研究，E-mail：pr_huzhenda@cet.sgcc.com.cn
基金资助:
国家电网有限公司科技项目（1300-202157362A-0-0-00）。

Investment Decision Model of Rural Power Grid Projects Considering Contribution of Rural Revitalization

Huiru ZHAO¹(), Manyu YAO¹(), Bingkang LI²(), Guanglong XIE³(), Zhihua DING⁴(), Zhenda HU⁵()

1. College of Economics and Management, North China Electric Power University, Beijing 102206, China
2. Department of Economics and Management, North China Electric Power University, Baoding 071003, China
3. State Grid Energy Research Institute Co., Ltd., Beijing 102209, China
4. State Grid Fujian Electric Power Co., Ltd., Fuzhou 350001, China
5. Economic and Technical Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350012, China

Received:2023-06-30 Accepted:2024-01-04 Online:2024-06-28 Published:2024-06-25
Supported by:
This work is supported by Science and Technology Project of SGCC (No.1300-202157362A-0-0-00).

摘要/Abstract

摘要：

深入推进乡村振兴战略对农村电网发展提出更高要求，量化新时代农网项目贡献度，辅助农网实现精准投资成为关键。基于乡村振兴战略对现代农村电网发展提出的新要求，构建包含安全可靠、精准服务、绿色低碳、数字智能等4个维度的农网贡献度评价指标体系，采用最小交叉熵模型融合完全一致性方法（FUCOM）-变异系数法赋权系数对指标进行组合赋权，运用加权马氏距离TOPSIS法量化农网贡献度。以农网单位投资贡献度最优及财务效益最大为目标，构建农网项目投资决策模型，并基于c-DPEA算法进行求解。某县某批次20个农网项目的算例仿真结果表明，所提量化模型能科学评价农网项目贡献度，投资决策模型能为农网实现精准投资提供有效参考。

关键词: 农村电网, 乡村振兴贡献度, 投资决策, 组合赋权, 多目标优化

Abstract:

Deepening the rural revitalization strategy puts forward higher requirements for rural grid development, quantifying the contribution of rural grid projects in the new era and assisting rural grids to achieve accurate investment become key. Based on the new requirements of the rural revitalization strategy for the development of modern rural power grids, a rural power grid contribution evaluation index system comprising four dimensions, including safety and relia-bility, precise service, green and low-carbon, and digital intelligence, is constructed, and the minimum cross-entropy model is used to combine the FUCOM-variance coefficient method to assign weights to the indexes and quantify the contribution of rural power grids by applying the weighted Marxian distance TOPSIS. With the objective of optimising the contribution of rural grid units and maximising financial benefits, a rural grid investment decision model was con-structed and solved based on the c-DPEA algorithm. The simulation results of a batch of 20 rural grid projects in a county show that the proposed quantitative model can scientifically evaluate the contribution of rural grid projects, and the investment decision model can provide an effective reference for precise investment in rural grid.

Key words: rural power grid, contribution to rural revitalization, investment decision, portfolio empowerment, multi-objective optimization

赵会茹, 姚满宇, 李兵抗, 谢光龙, 丁智华, 胡臻达. 考虑乡村振兴贡献度的农网项目投资决策模型[J]. 中国电力, 2024, 57(6): 181-192.

Huiru ZHAO, Manyu YAO, Bingkang LI, Guanglong XIE, Zhihua DING, Zhenda HU. Investment Decision Model of Rural Power Grid Projects Considering Contribution of Rural Revitalization[J]. Electric Power, 2024, 57(6): 181-192.

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图/表 12

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指标	$ {w}_{i} $	指标	$ {w}_{i} $	指标	$ {w}_{i} $
$ {T}_{11} $	0.138	$ {T}_{22} $	0.070	$ {T}_{41} $	0.067
$ {T}_{12} $	0.112	$ {T}_{23} $	0.112	$ {T}_{42} $	0.047
$ {T}_{13} $	0.078	$ {T}_{31} $	0.121	$ {T}_{43} $	0.360
$ {T}_{21} $	0.106	$ {T}_{32} $	0.113

指标	$ {w}_{i} $	指标	$ {w}_{i} $	指标	$ {w}_{i} $
$ {T}_{11} $	0.138	$ {T}_{22} $	0.070	$ {T}_{41} $	0.067
$ {T}_{12} $	0.112	$ {T}_{23} $	0.112	$ {T}_{42} $	0.047
$ {T}_{13} $	0.078	$ {T}_{31} $	0.121	$ {T}_{43} $	0.360
$ {T}_{21} $	0.106	$ {T}_{32} $	0.113

指标	$ y''_i $	$ {S}_{i} $	$ {V}_{i} $	$ {w}_{i} $
$ {T}_{11} $	0.2232	0.0143	0.0640	0.0807
$ {T}_{12} $	0.2232	0.0146	0.0652	0.0822
$ {T}_{13} $	0.2227	0.0211	0.0948	0.1194
$ {T}_{21} $	0.2235	0.0061	0.0272	0.0343
$ {T}_{22} $	0.2231	0.0156	0.0697	0.0879
$ {T}_{23} $	0.2213	0.0331	0.1497	0.1887
$ {T}_{31} $	0.2211	0.0341	0.1543	0.1945
$ {T}_{32} $	0.2234	0.0109	0.0490	0.0617
$ {T}_{41} $	0.2234	0.0099	0.0444	0.0560
$ {T}_{42} $	0.2234	0.0090	0.0404	0.0509
$ {T}_{43} $	0.2235	0.0077	0.3470	0.4370

指标	$ y''_i $	$ {S}_{i} $	$ {V}_{i} $	$ {w}_{i} $
$ {T}_{11} $	0.2232	0.0143	0.0640	0.0807
$ {T}_{12} $	0.2232	0.0146	0.0652	0.0822
$ {T}_{13} $	0.2227	0.0211	0.0948	0.1194
$ {T}_{21} $	0.2235	0.0061	0.0272	0.0343
$ {T}_{22} $	0.2231	0.0156	0.0697	0.0879
$ {T}_{23} $	0.2213	0.0331	0.1497	0.1887
$ {T}_{31} $	0.2211	0.0341	0.1543	0.1945
$ {T}_{32} $	0.2234	0.0109	0.0490	0.0617
$ {T}_{41} $	0.2234	0.0099	0.0444	0.0560
$ {T}_{42} $	0.2234	0.0090	0.0404	0.0509
$ {T}_{43} $	0.2235	0.0077	0.3470	0.4370

指标类型	指标	w_i	排序	组合权重
安全可靠$ {T}_{1} $	农网供电可靠率预计提升程度$ {T}_{11} $	0.1089	3	0.3083
	户均配电容量预计提升程度$ {T}_{12} $	0.0991	5
	农网综合电压合格率预计提升程度$ T $	0.0996	4
精准服务$ {T}_{2} $	单位投资预计增供电量$ {T}_{21} $	0.0622	9	0.2972
	节能型配变比例预计提升程度$ {T}_{22} $	0.0808	7
	农村电气化率预计提升程度$ {T}_{23} $	0.1501	2
绿色低碳$ {T}_{3} $	可再生能源渗透率预计提升程度$ {T}_{31} $	0.1584	1	0.2424
绿色低碳$ {T}_{3} $	单位投资预计新增碳排放量$ {T}_{32} $	0.0862	6	0.2424
数字智能$ {T}_{4} $	智能终端覆盖率预计提升程度$ {T}_{41} $	0.0632	8	0.1521
	电力光纤长度比例预计提升程度$ {T}_{42} $	0.0505	10
	智能变电站比率预计提升程度$ {T}_{43} $	0.0409	11

考虑乡村振兴贡献度的农网项目投资决策模型

Investment Decision Model of Rural Power Grid Projects Considering Contribution of Rural Revitalization

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参考文献 26

相关文章 15

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Metrics

项目序号	$ {d}_{i}^{+} $	$ {d}_{i}^{-} $	$ {S}_{i} $	排名
$ {A}_{1} $	4.526	4.022	0.5588	9
$ {A}_{2} $	4.705	4.266	0.5488	10
$ {A}_{3} $	4.628	3.929	0.5812	7
$ {A}_{4} $	3.745	5.177	0.3435	18
$ {A}_{5} $	3.681	5.023	0.3494	17
$ {A}_{6} $	4.470	4.590	0.4868	14
$ {A}_{7} $	4.140	4.698	0.4372	15
$ {A}_{8} $	4.570	4.340	0.5258	12
$ {A}_{9} $	3.664	5.073	0.3428	19
$ {A}_{10} $	4.672	4.018	0.5749	8
$ {A}_{11} $	4.795	4.038	0.5850	6
$ {A}_{12} $	5.391	3.546	0.6980	1
$ {A}_{13} $	5.024	3.737	0.6439	3
$ {A}_{14} $	5.025	3.590	0.6621	2
$ {A}_{15} $	4.238	4.092	0.5175	13
$ {A}_{16} $	4.027	4.821	0.4110	16
$ {A}_{17} $	5.093	4.082	0.6089	4
$ {A}_{18} $	4.939	3.992	0.6049	5
$ {A}_{19} $	3.479	5.246	0.3054	20
$ {A}_{20} $	4.376	4.120	0.5301	11

模型	指标赋权方法	综合评价方法
1	最小交叉熵模型融合FUCOM-变异系数法	加权马氏TOPSIS
2	FOCUM	加权马氏TOPSIS
3	变异系数法	加权马氏TOPSIS

项目序号	贡献度排名
项目序号	模型1	模型2	模型3
$ {A}_{1} $	9	12	10
$ {A}_{2} $	10	11	12
$ {A}_{3} $	7	16	11
$ {A}_{4} $	18	3	13
$ {A}_{5} $	17	7	2
$ {A}_{6} $	14	4	8
$ {A}_{7} $	15	5	3
$ {A}_{8} $	12	8	5
$ {A}_{9} $	19	6	7
$ {A}_{10} $	8	15	16
$ {A}_{11} $	6	13	18
$ {A}_{12} $	1	1	1
$ {A}_{13} $	3	2	17
$ {A}_{14} $	2	14	14
$ {A}_{15} $	13	10	4
$ {A}_{16} $	16	9	6
$ {A}_{17} $	4	17	19
$ {A}_{18} $	5	19	15
$ {A}_{19} $	20	20	20
$ {A}_{20} $	11	18	9

模型	标准差σ	变异系数υ	灵敏度η
1	0.0422	0.0647	0.0577
2	0.0356	0.0564	0.0462
3	0.0344	0.0536	0.0437

场景	项目序号	资金总额/ 万元	资金利用率	项目总评分	单位投资贡献度	净现值/ 万元
1）多目标场景	$ {\text{A}}_{\text{3}} $、$ {A}_{6} $、$ {A}_{14} $、$ {A}_{17} $	1242	35%	2.3390	0.00188	3385
	$ {A}_{3} $、$ {A}_{6} $、$ {A}_{8} $、$ {A}_{12} $、$ {A}_{14} $、$ {A}_{15} $、$ {A}_{17} $、$ {A}_{20} $	2636	75%	4.6104	0.00175	6347
	$ {A}_{3} $、$ {A}_{6} $、$ {A}_{12} $、$ {A}_{14} $、$ {A}_{15} $、$ {A}_{17} $、$ {A}_{20} $	2308	66%	4.0846	0.00177	5653
2）单位投资贡献度最优场景	$ {A}_{3} $、$ {A}_{6} $、$ {A}_{14} $	889	25%	1.7301	0.00195	2663
3）财务效益最优场景	$ {A}_{1} $、$ {A}_{3} $、$ {A}_{6} $、$ {A}_{14} $、$ {A}_{15} $、$ {A}_{17} $、$ {A}_{18} $、$ {A}_{20} $	2712	77%	4.5503	0.00168	6421

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考虑乡村振兴贡献度的农网项目投资决策模型

Investment Decision Model of Rural Power Grid Projects Considering Contribution of Rural Revitalization

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