Chinese Journal of Management Science ›› 2024, Vol. 32 ›› Issue (9): 292-302.doi: 10.16381/j.cnki.issn1003-207x.2021.1115
Previous Articles Next Articles
Qingyuan Zhu1,Xifan Chen1,Jie Chen1,Jie Wu2()
Received:
2021-06-04
Revised:
2021-09-12
Online:
2024-09-25
Published:
2024-10-12
Contact:
Jie Wu
E-mail:jacky012@mail.ustc.edu.cn
CLC Number:
Qingyuan Zhu,Xifan Chen,Jie Chen,Jie Wu. Renewables Quota Allocation among Regional Power Industries under the Policy of Renewable Electricity Standard[J]. Chinese Journal of Management Science, 2024, 32(9): 292-302.
"
年份 | 统计量 | 投入 | 期望产出 | 非期望产出 | ||
---|---|---|---|---|---|---|
可再生电力装机容量 | 不可再生电力装机容量 | 可再生电力 | 不可再生电力 | CO2 | ||
2013年 | 均值 | 1237.90 | 2897.69 | 349.48 | 1408.07 | 12065.26 |
中位数 | 823.00 | 2127.00 | 179.20 | 1031.00 | 7707.03 | |
标准差 | 1274.60 | 2079.13 | 473.79 | 1073.28 | 9287.06 | |
最大值 | 5280.30 | 7555.00 | 2023.80 | 4174.00 | 36440.53 | |
最小值 | 25.60 | 235.00 | 5.80 | 136.00 | 1402.26 | |
2014年 | 均值 | 1408.90 | 3082.86 | 416.47 | 1423.14 | 11693.55 |
中位数 | 791.10 | 2138.00 | 146.70 | 997.00 | 7595.48 | |
标准差 | 1502.73 | 2217.05 | 606.79 | 1145.15 | 9334.44 | |
最大值 | 6327.40 | 8073.00 | 2582.50 | 4383.00 | 38271.61 | |
最小值 | 34.70 | 242.00 | 6.51 | 131.00 | 1349.01 | |
2015年 | 均值 | 1596.53 | 3321.24 | 445.85 | 1387.55 | 11400.89 |
中位数 | 1024.50 | 2261.00 | 184.40 | 1026.00 | 7254.73 | |
标准差 | 1672.31 | 2398.48 | 641.54 | 1150.33 | 9839.17 | |
最大值 | 7048.40 | 8754.00 | 2779.20 | 4484.00 | 37819.29 | |
最小值 | 42.10 | 318.00 | 6.80 | 120.00 | 1156.15 | |
2016年 | 均值 | 1795.44 | 3492.38 | 492.16 | 1416.52 | 11435.50 |
中位数 | 1401.80 | 2322.00 | 229.00 | 915.00 | 7247.39 | |
标准差 | 1748.82 | 2513.81 | 682.25 | 1201.56 | 10304.67 | |
最大值 | 7467.00 | 9540.00 | 3021.00 | 4671.00 | 38557.64 | |
最小值 | 90.00 | 402.00 | 9.13 | 151.00 | 1377.31 | |
2017年 | 均值 | 2065.92 | 3629.17 | 530.71 | 1490.00 | 12207.73 |
中位数 | 1706.00 | 2583.00 | 260.20 | 1075.00 | 7593.39 | |
标准差 | 1817.54 | 2657.80 | 733.80 | 1244.32 | 10707.63 | |
最大值 | 8059.00 | 10335.00 | 3215.00 | 4615.00 | 42623.96 | |
最小值 | 98.00 | 399.00 | 12.10 | 153.00 | 1352.72 |
"
DMUs | 投入 | 期望产出 | 非期望产出 | |||
---|---|---|---|---|---|---|
可再生电力装机容量 | 不可再生电力装机容量 | 可再生电力 | 不可再生电力 | CO2 | ||
天津 | 98.0 | 1402.0 | 12.1 | 584.0 | 4640.5 | 2.0 |
上海 | 32.7 | 2127.0 | 7.8 | 963.0 | 7434.3 | 0.8 |
江苏 | 1828.0 | 9430.0 | 230.0 | 4481.0 | 33648.2 | 4.9 |
北京 | 132.0 | 971.0 | 16.1 | 419.0 | 1592.0 | 3.7 |
山东 | 2220.8 | 10335.0 | 245.7 | 4615.0 | 35821.3 | 5.1 |
安徽 | 1415.0 | 5053.0 | 160.0 | 2311.0 | 17464.8 | 6.5 |
河南 | 1335.0 | 6544.0 | 174.0 | 2528.0 | 21658.1 | 6.4 |
陕西 | 1706.0 | 6366.0 | 263.0 | 2503.0 | 21673.9 | 9.5 |
陕西 | 1048.0 | 3144 | 176.0 | 1427.0 | 10116.7 | 11.0 |
河北 | 2231.0 | 4574.0 | 360.0 | 2296.0 | 17308.7 | 13.6 |
浙江 | 1934.9 | 6109.0 | 302.0 | 2482.2 | 17845.5 | 10.8 |
广东 | 1796.0 | 7721.0 | 481.0 | 2850.0 | 20963.7 | 14.4 |
辽宁 | 1229.0 | 3193.0 | 207.0 | 1349.0 | 13898.5 | 13.3 |
黑龙江 | 767.0 | 2201.0 | 138.7 | 816.0 | 7769.1 | 14.5 |
海南 | 191.0 | 465.0 | 35.0 | 195.0 | 1689.6 | 15.2 |
宁夏 | 1605.0 | 2583.0 | 247.0 | 1158 | 11228.8 | 17.6 |
内蒙古 | 3655.0 | 8170.0 | 688.0 | 3736.0 | 42624.0 | 15.6 |
新疆 | 3472.0 | 5207.0 | 681.0 | 2349.0 | 22404.9 | 22.5 |
江西 | 1233.0 | 1934.0 | 218.0 | 967.0 | 6961.8 | 18.4 |
吉林 | 823.0 | 1694.0 | 182.9 | 590.0 | 7249.1 | 23.7 |
福建 | 1545.0 | 2902.0 | 682.5 | 915.0 | 7360.7 | 42.7 |
重庆 | 781.0 | 1544.0 | 260.2 | 467.0 | 3520.8 | 35.8 |
广州 | 2382.0 | 2684.0 | 860.2 | 1071.0 | 6444.8 | 44.5 |
湖南 | 1800.0 | 2322.0 | 600.7 | 732.0 | 5364.7 | 45.1 |
甘肃 | 2936.0 | 2059.0 | 635.0 | 707.0 | 6264.9 | 47.3 |
湖北 | 4337.0 | 2787.0 | 1570.0 | 1075.0 | 7487.2 | 59.4 |
广西 | 1697.2 | 1652.0 | 768.5 | 544.0 | 3815.9 | 58.6 |
青海 | 2144.0 | 399.0 | 463.0 | 153.0 | 1424.6 | 75.2 |
四川 | 8059.0 | 1662.0 | 3215.0 | 354.0 | 2496.8 | 90.1 |
云南 | 7344.0 | 1613.0 | 2718.0 | 240.0 | 2314.1 | 91.9 |
"
区域 | 占比均值 (2013-2017) | 实际完成 (2018) | 可再生电力消纳责任权重(2018) | 目标 | ||
---|---|---|---|---|---|---|
最小 | 激励性 | |||||
天津 | 1.3 | 11.4 | 11.0 | 12.1 | 2.0 | 2.8 |
上海 | 1.4 | 32.1 | 31.5 | 34.9 | 0.8 | 2.8 |
江苏 | 2.9 | 14.7 | 12.5 | 13.7 | 4.9 | 5.2 |
北京 | 3.1 | 13.2 | 11.0 | 12.1 | 3.7 | 5.4 |
山东 | 3.4 | 9.9 | 9.5 | 10.4 | 5.1 | 5.3 |
安徽 | 4.1 | 14.9 | 13.0 | 14.3 | 6.5 | 7.2 |
河南 | 4.8 | 16.9 | 13.5 | 14.9 | 6.4 | 7.1 |
陕西 | 6.2 | 16.4 | 15.0 | 16.5 | 9.5 | 9.6 |
陕西 | 7.9 | 20.3 | 17.5 | 19.2 | 11.0 | 13.0 |
河北 | 9.6 | 12.2 | 11.0 | 12.1 | 13.6 | 15.4 |
浙江 | 9.7 | 17.8 | 18.0 | 19.8 | 10.9 | 13.1 |
广东 | 11.2 | 32.9 | 31.0 | 34.2 | 14.4 | 16.2 |
辽宁 | 11.4 | 14.2 | 12.0 | 13.2 | 13.3 | 16.0 |
黑龙江 | 11.8 | 19.4 | 19.5 | 21.5 | 14.5 | 18.4 |
海南 | 12.4 | 13.6 | 11.0 | 12.1 | 15.2 | 21.2 |
宁夏 | 12.8 | 25.2 | 20.0 | 22.2 | 17.6 | 21.0 |
内蒙古 | 13.1 | 18.6 | 18.5 | 20.4 | 15.6 | 16.6 |
新疆 | 17.7 | 26.8 | 21.0 | 23.1 | 22.5 | 23.3 |
江西 | 17.9 | 22.9 | 23.0 | 25.1 | 18.4 | 26.6 |
吉林 | 20.1 | 24.9 | 20.0 | 22.0 | 23.7 | 30.4 |
福建 | 30.9 | 19.0 | 17.0 | 18.7 | 42.7 | 47.3 |
重庆 | 34.6 | 45.9 | 47.5 | 52.1 | 35.8 | 45.3 |
广州 | 38.2 | 36.2 | 33.5 | 36.9 | 44.5 | 50.4 |
湖南 | 40.6 | 42.1 | 46.0 | 50.5 | 45.1 | 52.0 |
甘肃 | 42.9 | 48.4 | 44.0 | 48.4 | 47.3 | 55.0 |
湖北 | 50.1 | 46.0 | 51.0 | 56.2 | 58.6 | 66.8 |
广西 | 57.0 | 38.0 | 39.0 | 43.0 | 59.4 | 65.2 |
青海 | 76.4 | 78.2 | 70.0 | 77.0 | 75.2 | 83.8 |
四川 | 85.2 | 81.9 | 80.0 | 88.0 | 90.1 | 93.1 |
云南 | 86.7 | 83.4 | 80.0 | 88.0 | 91.9 | 91.9 |
1 | Song M L, Xie Q J, Wang S H, et al. Intensity of environmental regulation and environmentally biased technology in the employment market[J]. Omega, 2021,100:102201. |
2 | Zhu Q Y, Li X C, Li F, et al. The potential for energy saving and carbon emission reduction in China’s regional industrial sectors[J]. Science of The Total Environment, 2020, 716: 135009. |
3 | Zhu Q Y, Li X C, Li F, et al. Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions[J]. Energy Economics, 2020, 89: 104817. |
4 | Sergi B, Azevedo I, Xia T, et al. Support for emissions reductions based on immediate and long-term pollution exposure in China[J]. Ecological Economics, 2019, 158: 26-33. |
5 | Zhou P, Wang M. Carbon dioxide emissions allocation: A review[J].Ecological Economics, 2016,125: 47-59. |
6 | Athanassopoulos A D. Goal programming & data envelopment analysis (GoDEA) for target-based multi-level planning: Allocating central grants to the Greek local authorities[J]. European Journal of Operational Research, 1995, 87(3): 535-550. |
7 | 李晓亚,崔晋川.基于DEA方法的额外资源分配算法[J].系统工程学报, 2007, 22(1): 57-61+3. |
Li X Y, Cui J C. Arithmetic of extra resource allocation based on DEA method[J]. Journal of Systems Engineering,2007,22(1):57-61+73. | |
8 | 丁晶晶,毕功兵,梁樑.并联系统资源和目标配置双准则DEA模型[J].管理科学学报, 2013, 16(1): 10-21. |
Ding J J, Bi G B, Liang L. Bi-criteria DEA model for resource allocation and target setting in parallel production system[J]. Journal of Management Science in China,2013,16(1):10-21. | |
9 | Asmild M, Paradi J C, Pastor J T. Centralized resource allocation BCC models[J]. Omega, 2009, 37(1): 40-49. |
10 | Cherchye L, Rock B D, Dierynck B, et al. Opening the ‘black box’ of efficiency measurement: Input allocation in multioutput settings[J]. Operations Research, 2013, 61(5): 1148-1165. |
11 | Du J, Cook W D, Liang L, et al. Fixed cost and resource allocation based on DEA cross-efficiency[J]. European Journal of Operational Research, 2014, 235(1): 206-214. |
12 | 王荧,王应明. 基于未来效率的兼顾公平与效率的资源分配DEA模型研究——以各省碳排放额分配为例[J]. 中国管理科学, 2019, 27(5): 161-173. |
Wang Y, Wang Y M. Study on resource allocation DEA model based on the future efficiency with consideration of efficiency & equity: An application in distribution of carbon emission rights in each chinese province[J]. Chinese Journal of Management Science,2019,27(5):161-173. | |
13 | Fang L. Centralized resource allocation based on efficiency analysis for step-by-step improvement paths[J]. Omega, 2015, 51: 24-28. |
14 | Wu J, Zhu Q Y, An Q X, et al. Resource allocation based on context-dependent data envelopment analysis and a multi-objective linear programming approach[J]. Computers & Industrial Engineering, 2016, 101: 81-90. |
15 | Gomes E G, Lins M P E. Modelling undesirable outputs with zero sum gains data envelopment analysis models[J]. Journal of the Operational Research Society, 2008, 59(5): 616-623. |
16 | 林坦,宁俊飞.基于零和DEA模型的欧盟国家碳排放权分配效率研究[J]. 数量经济技术经济研究, 2011, 28(3): 36-50. |
Lin T, Ning J F. Study on allocation efficiency of carbon emissionpermit in EUETS based on ZSG-DEA model[J]. The Journal of Quantitative & Technical Economics, 2011,28(3):36-50. | |
17 | Wu J, Zhu Q Y, Chu J F, et al. A DEA-based approach for allocation of emission reduction tasks[J]. International Journal of Production Research, 2016, 54(18): 5618-5633. |
18 | Guo X D, Zhu L, Fan Y, et al. Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA[J].Energy Policy, 2011, 39(5): 2352-2360. |
19 | Zhou P, Sun Z R, Zhou D Q. Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis[J]. Energy Economics, 2014, 45: 99-110. |
20 | 崔玉泉,张宪,芦希,等.随机加权交叉效率下的资源分配问题研究[J].中国管理科学,2015,23(1): 121-127. |
Cui Y Q, Zhang X, Lu X, et al. Research theresource allocationproblem in stochastic weighted cross efficiency[J]. Chinese Journal of Management Science,2015,23(1):121-127. | |
21 | Feng C P, Chu F, Ding J J, et al. Carbon emissions abatement (CEA) allocation and compensation schemes based on DEA[J]. Omega, 2015, 53: 78-89. |
22 | Yu A Y, You J X, Rudkin S, et al. Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis[J].Applied Energy,2019,233-234:232-243. |
23 | Wang B J, Zhao J L, Wu Y F, et al. Allocating on coal consumption and CO2emission from fair and efficient perspective: Empirical analysis on provincial panel data of China[J]. Environmental Science and Pollution Research, 2019, 26(18): 17950-17964. |
24 | 王文举. 中国省级区域初始碳配额分配方案研究——基于责任与目标、公平与效率的视角[J].管理世界, 2019, 35(3): 81-98. |
Wang W J. Study on the allocation plan of initial carbon allowances in China's province-level regions:Based on the perspective of responsibility and goals, fairness and efficiency[J]. The Journal of Quantitative & Technical Economics,2019,35(3):81-98. | |
25 | Tamás M M, Shrestha S B, Zhou H Z. Feed-in tariff and tradable green certificate in oligopoly[J]. Energy Policy, 2010, 38(8): 4040-4047. |
26 | 叶泽,吴永飞,张新华,等. 需求响应下解决交叉补贴的阶梯电价方案研究——基于社会福利最大化视角[J]. 中国管理科学, 2019, 27(4): 149-159. |
Ye Z, Wu Y F, Zhang X H, et al. Research on the inclining block tariffs scheme for solving cross-subsidy under demand response: Based on the perspective of maximizing social welfare[J]. Chinese Journal of Management Science,2019,27(4):149-159. | |
27 | Sun P, Nie P Y. A comparative study of feed-in tariff and renewable portfolio standard policy in renewable energy industry[J]. Renewable Energy, 2015, 74: 255-262. |
28 | Pineda S, Bock A. Renewable-based generation expansion under a green certificate market[J]. Renewable Energy, 2016, 91: 53-63. |
29 | 吕燕. 基于供应链协同的可再生能源政策评估研究[J]. 管理世界, 2015, 000(12): 180-181. |
Lv Y. Research on renewable energy policy evaluation based on supply chain collaboration[J]. Management World,2015(12):180-181. | |
30 | Kök A G, Shang K, Yücel Ş. Impact of electricity pricing policies on renewable energy investments and carbon emissions[J].Management Science, 2018, 64(1): 131-148. |
31 | 李力,朱磊,范英.不确定条件下可再能源项目的竞争性投资决策[J].中国管理科学, 2017, 25(7): 11-17. |
Li L, Zhu L, Fan Y. Competitive investment strategy for renewable power generation under uncertainty[J]. Chinese Journal of Management Science,2017,25(7):11-17. | |
32 | Zhao X G, Ren L Z, Zhang Y Z, et al. Evolutionary game analysis on the behavior strategies of power producers in renewable portfolio standard[J]. Energy, 2018, 162: 505-516. |
33 | Sunar N, Birge J R. Strategic commitment to a production schedule with uncertain supply and demand: Renewable energy in day-ahead electricity markets[J]. Management Science, 2019, 65(2): 714-734. |
34 | Goodarzi S, Aflaki S, Masini A. Optimal feed‐in tariff policies: The impact of market structure and technology characteristics[J]. Production and Operations Management, 2019, 28(5): 1108-1128. |
35 | Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis[J]. Management Science, 1984, 30(9): 1078-1092. |
36 | Koopmans T C. Analysis of production as an efficient combination of activities[J]. Activity Analysis of Production and Allocation, 1951, 13: 33-97. |
37 | Tyteca D. Linear programming models for the measurement of environmental performance of firms—concepts and empirical results[J]. Journal of Productivity Analysis, 1997, 8(2): 183-197. |
38 | Shi G M, Bi J, Wang J N. Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs[J]. Energy Policy, 2010, 38(10) : 6172-6179. |
39 | Lin W B, Yang J, Chen B. Temporal and spatial analysis of integrated energy and environment efficiency in China based on a green GDP index[J]. Energies, 2011, 4(9): 1376-1390. |
40 | Seiford L M, Zhu J. Modeling undesirable factors in efficiency evaluation[J]. European Journal of Operational Research, 2002, 142(1): 16-20. |
41 | Zhu Q Y, Wu J, Li X C, et al. China’s regional natural resource allocation and utilization: A DEA-based approach in a big data environment[J]. Journal of Cleaner Production, 2017, 142: 809-818. |
[1] | Qinghua Zeng,Gang Zong. Research on the Optimal Design of Urban Multi-level Bus Routes [J]. Chinese Journal of Management Science, 2024, 32(9): 121-130. |
[2] | Yeming Dai,Xilian Sun,Yao Qi,Jinpeng Duan. Multi-objective Bi-level Research on Decision-making of Power Retailers Considering Dual Uncertainty and User Disutility [J]. Chinese Journal of Management Science, 2024, 32(7): 163-171. |
[3] | Lin Wang,Shenghui Gu,Weilan Suo. Research on a Resilience-Oriented Resource Allocation for the Protection and Restoration of Critical Infrastructures Considering Multiple Interdependencies [J]. Chinese Journal of Management Science, 2024, 32(6): 301-311. |
[4] | Cheng Cheng,Runfei An,Kangyin Dong,Xiaohang Ren,Zhen Wang,Guohao Zhao. Research on Innovation Strategy for Renewable Power Generation Enterprises under the Background of Carbon Trading Mechanism——from the Perspective of Evolutionary Game [J]. Chinese Journal of Management Science, 2024, 32(3): 82-94. |
[5] | Hui Li,Xi Wang,Zhiya Zuo. Multi-objective Integrated Optimization of Flexible Resource Allocation and Scheduling in the Aerospace Production Workshop [J]. Chinese Journal of Management Science, 2024, 32(10): 146-155. |
[6] | Wei Chen,Yongle Tian,Yongkai Ma,Chunguang Bai. Impact of Leasing Mode with Renewable Energy Storage Equipment on Electricity Quality and Price [J]. Chinese Journal of Management Science, 2024, 32(1): 309-318. |
[7] | Li-ping XIAO,Jia-lian LI,Xue-yan SHAO,Hong CHI. Medical Alliance System Optimization Based on Queuing Network under Hierarchical Diagnosis and Treatment [J]. Chinese Journal of Management Science, 2023, 31(9): 186-195. |
[8] | CHEN Wei, MA Yong-kai, BAI Chun-guang. Research on Upstream and Downstream Enterprises of Renewable Energy Investment under Cap-and-Trade Mechanism [J]. Chinese Journal of Management Science, 2023, 31(1): 70-80. |
[9] | ZHOU De-qun, , ZHOU Xian-yang, , DING Hao,. Research on Renewable Electricity Bidding Strategy under Multi-market Coordination [J]. Chinese Journal of Management Science, 2023, 31(1): 248-255. |
[10] | LIU Feng-gen, WANG Yi-ding, YAN Jian-jun, ZHANG Min. Urban Resource Allocation, Population Agglomeration and Rising Real Estate Prices——An Empirical Evidence from 95 Cities in China [J]. Chinese Journal of Management Science, 2022, 30(7): 31-46. |
[11] | ZHOU De-qun, DING Hao, ZHOU Peng, WANG Qun-wei. Renewable Energy Technology Diffusion Model Based on Process Division [J]. Chinese Journal of Management Science, 2022, 30(2): 217-225. |
[12] | CAI Qiang, WEI Gui-wu, HUANG Jing, XIA Hui. Evaluation on R&D Incentive Policies of Renewable Energy Power Generation Based on Social Welfare [J]. Chinese Journal of Management Science, 2022, 30(1): 206-221. |
[13] | ZENG Qian, HAN Xun, FANG Xin. Resources Allocation Decisions of Business and Government in The Perspective of Efficiency and Fairness [J]. Chinese Journal of Management Science, 2020, 28(10): 88-97. |
[14] | WANG Qia. On-Demand Extra Resource Allocation [J]. Chinese Journal of Management Science, 2019, 27(6): 206-216. |
[15] | WANG Ying, WANG Ying-ming. Study on Resource Allocation DEA Model Based on the Future Efficiency with Consideration of Efficiency & Equity: An Application in Distribution of Carbon Emission Rights in each Chinese Province [J]. Chinese Journal of Management Science, 2019, 27(5): 161-173. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||
|