面向新型电力系统的可再生能源绿色电力证书差异化配置模型

doi:10.16183/j.cnki.jsjtu.2022.150

摘要/Abstract

摘要：

实现我国“30·60”双碳目标,能源绿色低碳转型是基础支撑,构建以新能源为主体的新型电力系统是关键举措,绿色电力证书(简称绿证)则是体现可再生能源绿色价值的重要凭证.当前我国绿证分配机制单一,无法有效衡量不同可再生能源发电类型可获得绿色价值的差异性,并发挥其平衡可再生能源协调发展的杠杆作用.为此,从可再生能源发电类型电量兑换绿证的差异化入手,建立考虑可再生能源综合价值的绿证差异化评价指标体系,应用CRITIC法、熵权法和TOPSIS法构建可再生能源电力绿证差异化评价模型.以2030年碳达峰目标为发展场景,分析模型对集中式光伏发电、分布式光伏发电、陆上风力发电和海上风力发电绿色收益的影响,进而修正其发展规划,并提出绿证相关政策建议.所构建的绿证差异化分配模型可为我国绿证市场机制的建设和完善提供相应的辅助决策支持.

关键词: 新型电力系统, 可再生能源, 绿证差异化, CRITIC-熵权法, TOPSIS法

Abstract:

In order to achieve China’s “30·60” decarbonization goal, the green and low-carbon transformation of the energy system is the fundamental support; the construction of new-type power system is the key step, and the green certificate is the important voucher to reflect the green value of renewable energy. Currently, the distribution mechanism of green certificates in China is oversimplified, which neither effectively measures the variability of green values generated by different types of renewable energy, nor balances the coordinated development of renewable energy. Therefore, to differentiate the exchange mechanism of green certificates by different types of renewable energy power in this paper, an evaluation index system is established, which describes the difference between green certificates, considering the comprehensive value of renewable energy, and an evaluation model is built with the criteria importance by using the intercriteria correlation (CRITIC) method, the entropy weight method, and the technique for order preference by similarity to an ideal solution (TOPSIS) method. Under the development scenario of peaking carbon emissions before 2030, the impact of the differentiated distribution model on the green incomes of centralized photovoltaic distributed photovoltaic power, onshore wind power, and offshore wind power is analyzed. Moreover, the development plan of renewable energy is modified in consideration of the effect of the differentiated distribution model, and policy suggestions on green certificates are proposed accordingly. The results show that the differentiated distribution model of green certificates is practical to provide corresponding decision-making support to the construction and improvement of green certificates trading mechanism in China.

Key words: new-type power system, renewable energy, difference between green certificates, criteria importance through intercriteria correlation (CRITIC)-entropy weight method, technique for order preference by similarity to an ideal solution (TOPSIS) method

中图分类号:

TM715
TM 732

张硕, 李薇, 李英姿, 刘强, 曾鸣. 面向新型电力系统的可再生能源绿色电力证书差异化配置模型[J]. 上海交通大学学报, 2022, 56(12): 1561-1571.

ZHANG Shuo, LI Wei, LI Yingzi, LIU Qiang, ZENG Ming. Differentiated Allocation Model of Renewable Energy Green Certificates for New-Type Power System[J]. Journal of Shanghai Jiao Tong University, 2022, 56(12): 1561-1571.

图/表 15

表1

表2

百分整数制评分区间

评分区间	评分区间数值	发展程度
t_s	$100 (o - 1) s$ ≤t_s< $100 o s$	s级
…	…	…
t₂	100/s≤t_s<200/s	二级
t₁	0≤t_s<100/s	一级

表2

表3

图1

图2

表4

表5

Guiding price元/(kW·h)

发电类型	p_ge	$p - g e$
集中式光伏	I类资源区为0.35,II类资源区为0.40,III类资源区为0.49	0.41
分布式光伏	0.46	0.46
陆上风电	I类资源区为0.29,II类资源区为0.34,III类资源区为0.38,IV类资源区为0.47	0.37
海上风电	近海为0.75,潮间带竞价确定	0.75

表5

表6

表7

图3

表8

表9

图4

图5

图6

参考文献 22

[1]	中华人民共和国国家发展和改革委员会, 国家能源局. 关于建立健全可再生能源电力消纳保障机制的通知[EB/OL].(2019-05-10)[2022-04-07]. https://www.ndrc.gov.cn/xwdt/xwfb/201905/t20190515_954419.html.
	National Development and Reform Commission, National Energy Administration. Notice on establishing and improving the consumption guarantee mechanism of renewable energy electricity[EB/OL]. (2019-05-10)[2022-04-07]. https://www.ndrc.gov.cn/xwdt/xwfb/201905/t20190515_954419.html.
[2]	中华人民共和国国家发展和改革委员会, 中华人民共和国财政部, 国家能源局. 关于试行可再生能源绿色电力证书核发及自愿认购交易制度的通知[EB/OL].(2017-02-06)[2022-04-07]. http://www.nea.gov.cn/2017-02/06/c_136035626.htm.
	National Development and Reform Commission, Ministry of Finance of the People’s Republic of China, National Energy Administration. Notice on the trial implementation of renewable energy green power certificate issuance and voluntary subscription and trading system[EB/OL]. (2017-02-06)[2022-04-07]. http://www.nea.gov.cn/2017-02/06/c_136035626.htm.
[3]	游广增, 汤翔鹰, 胡炎, 等. 基于典型运行场景聚类的电力系统灵活性评估方法[J]. 上海交通大学学报, 2021, 55(7): 802-813.
	YOU Guangzeng, TANG Xiangying, HU Yan, et al. Flexibility evaluation method for power system based on clustering of typical operating scenarios[J]. Journal of Shanghai Jiao Tong University, 2021, 55(7): 802-813.
[4]	黄龙. 考虑可再生能源配额制的电力市场研究[D]. 广州: 华南理工大学, 2020.
	HUANG Long. Research on electricity market considering renewable portfolio standards[D]. Guangzhou: South China University of Technology, 2020.
[5]	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. doi: 10.1016/j.energy.2018.07.209 URL
[6]	曲明, 丁涛, 白佳文, 等. 非水可再生能源电力消纳责任权重划分下的全国绿证中长期跨省交易测算分析[J]. 电网技术, 2020, 44(10): 3885-3894.
	QU Ming, DING Tao, BAI Jiawen, et al. Green certificate transaction analysis in China under responsibility for non-water renewable energy integration ratio[J]. Power System Technology, 2020, 44(10): 3885-3894.
[7]	HELGESEN P I, TOMASGARD A. An equilibrium market power model for power markets and tradable green certificates, including Kirchhoff’s Laws and Nash-Cournot competition[J]. Energy Economics, 2018, 70: 270-288. doi: 10.1016/j.eneco.2018.01.013 URL
[8]	陈文溆乐, 向月, 彭光博, 等. “双碳”目标下电力系统供给侧形态发展系统动力学建模与分析[J]. 上海交通大学学报, 2021, 55(12): 1567-1576.
	CHEN Wenxule, XIANG Yue, PENG Guangbo, et al. System dynamic modeling and analysis of power system supply side morphological development with dual carbon targets[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1567-1576.
[9]	彭谦, 周晓洁, 杨睿. 国家绿色电力证书交易市场与省级日前电力市场协调均衡机制设计[J]. 电网技术, 2020, 44(7): 2565-2571.
	PENG Qian, ZHOU Xiaojie, YANG Rui. Design of coordination and balance mechanism between national green power certificate trading market and provincial day-ahead power market[J]. Power System Technology, 2020, 44(7): 2565-2571.
[10]	俞萍萍. 绿色证书交易机制下可再生能源发电定价研究: 期权博弈模型及数值模拟[J]. 价格理论与实践, 2018(11): 38-41.
	YU Pingping. Pricing model of renewable energy under tradable green certificate system: Option games model and numerical simulation[J]. Price: Theory & Practice, 2018(11): 38-41.
[11]	文云峰, 杨伟峰, 汪荣华, 等. 构建100%可再生能源电力系统述评与展望[J]. 中国电机工程学报, 2020, 40(6): 1843-1856.
	WEN Yunfeng, YANG Weifeng, WANG Ronghua, et al. Review and prospect of toward 100% renewable energy power systems[J]. Proceedings of the CSEE, 2020, 40(6): 1843-1856.
[12]	WEN Q M, LIU G, WU W, et al. Multicriteria comprehensive evaluation framework for industrial park-level distributed energy system considering weights uncertainties[J]. Journal of Cleaner Production, 2021, 282: 124530. doi: 10.1016/j.jclepro.2020.124530 URL
[13]	董福贵, 时磊. 可再生能源配额制及绿色证书交易机制设计及仿真[J]. 电力系统自动化, 2019, 43(12): 113-121.
	DONG Fugui, SHI Lei. Design and simulation of renewable portfolio standard and tradable green certificate mechanism[J]. Automation of Electric Power Systems, 2019, 43(12): 113-121.
[14]	CHEN Y J, YANG X L, LUO D, et al. Remaining available energy prediction for lithium-ion batteries considering electrothermal effect and energy conversion efficiency[J]. Journal of Energy Storage, 2021, 40: 102728. doi: 10.1016/j.est.2021.102728 URL
[15]	POURGHADERI N, FOTUHI-FIRUZABAD M, MOEINI-AGHTAIE M, et al. Commercial demand response programs in bidding of a technical virtual power plant[J]. IEEE Transactions on Industrial Informatics, 2018, 14(11): 5100-5111. doi: 10.1109/TII.2018.2828039 URL
[16]	KARAMOV D N, MINARCHENKO I M, KOLOSNITSYN A V, et al. Installed capacity optimization of autonomous photovoltaic systems under energy service contracting[J]. Energy Conversion and Management, 2021, 240: 114256. doi: 10.1016/j.enconman.2021.114256 URL
[17]	段翔颖. 甘肃某风电场建设项目综合评价研究[D]. 北京: 华北电力大学, 2015.
	DUAN Xiangying. Study on synthetic evaluation of a wind farm project in Gansu[D]. Beijing: North China Electric Power University, 2015.
[18]	杜刚, 赵冬梅, 刘鑫, 等. 基于重尾分布的风电功率波动特性概率分布[J]. 电力自动化设备, 2021, 41(7): 52-57.
	DU Gang, ZHAO Dongmei, LIU Xin, et al. Probability distribution of wind power fluctuation characteristics based on heavy-tailed distribution[J]. Electric Power Automation Equipment, 2021, 41(7): 52-57.
[19]	傅为忠, 储刘平. 长三角一体化视角下制造业高质量发展评价研究: 基于改进的CRITIC-熵权法组合权重的TOPSIS评价模型[J]. 工业技术经济, 2020, 39(9): 145-152.
	FU Weizhong, CHU Liuping. Research on the evaluation of high quality development of manufacturing industry from the perspective of integration of the Yangtze River Delta: TOPSIS evaluation model based on improved CRITICAL-Entropy weight method[J]. Journal of Industrial Technological Economics, 2020, 39(9): 145-152.
[20]	代洲, 王钢, 严英杰, 等. 基于组合赋权和模糊综合评判的电网企业物资品控体系综合能效评价[J]. 华南理工大学学报(自然科学版), 2020, 48(7): 47-54.
	DAI Zhou, WANG Gang, YAN Yingjie, et al. Evaluation on the comprehensive energy efficiency of power grid enterprise material quality control system based on combination weighting and fuzzy comprehensive evaluation method[J]. Journal of South China University of Technology (Natural Science Edition), 2020, 48(7): 47-54.
[21]	安进, 徐廷学, 曾翔, 等. 组合赋权下的装备质量状态信息融合评估方法[J]. 控制与决策, 2018, 33(9): 1693-1698.
	AN Jin, XU Tingxue, ZENG Xiang, et al. Equipment quality condition assessment under fusion information based on combination weighting[J]. Control and Decision, 2018, 33(9): 1693-1698.
[22]	国家能源局. 国家能源局发布2020年全国电力工业统计数据[EB/OL]. (2021-01-20) [2022-04-07]. http://www.nea.gov.cn/2021-01/20/c_139683739.htm.
	National Energy Administration. National Energy Administration releases national electricity industry statistics for 2020[EB/OL]. (2021-01-20) [2022-04-07]. http://www.nea.gov.cn/2021-01/20/c_139683739.htm.

一级指标	二级指标	指标特性
技术	能源开发成熟度/%	能源开发,正向
	合理建设周期/d	能源开发,负向
	能源转换效率/%	设施条件,正向
	能源利用效率/%	设施条件,正向
	装机容量平均增长量/%	设施条件,正向
经济	单位容量造价/(元·kW^-1)	运行成本,负向
	平准化度电成本/(元·kW^-1·h^-1)	运行成本,负向
	平均年投资额/元	运行成本,正向
	年带动就业人数/(人·MW^-1)	运行收益,正向
	上网电价/(元·kW^-1·h^-1)	运行收益,负向
资源	资源开发潜力/MW	能源潜力,正向
	电力季节性波动率/%	能源潜力,负向
	弃风、光率/%	能源潜力,负向
	可再生能源发电量占比/%	利用水平,正向
	可再生能源装机量占比/%	利用水平,正向
环境	供电降污排放量/t	降污成效,正向
	供电降碳排放量/t	降污成效,正向
	供电降废排放量/t	降污成效,正向
	供电节水量/t	保护成效,正向
	单位土地装机量/(kW·m^-3)	保护成效,正向

评分区间	发展程度	发展状态	绿证设定量/ (张·MW^-1·h^-1)
81~100	五级	成熟	1
61~80	四级	较成熟	2
41~60	三级	一般成熟	3
21~40	二级	较不成熟	4
0~20	一级	不成熟	5

发电类型	TOPSIS 评分	百分整数制转化/分	发展程度	兑换绿证量/ (张·MW^-1·h^-1)
集中式光伏	0.469 2	47	三级	3
分布式光伏	0.320 1	32	四级	4
陆上风电	0.679 8	68	二级	2
海上风电	0.298 5	30	四级	4

电网区域	p_coal
南方电网	0.400 2
国家电网	0.372 8
蒙西电网	0.282 9
煤电交易基准价平均值	0.352 0

发电类型	p_g	p_ge	p_c	p_coal	p_r
集中式光伏	0.529 5	0.41	0.939 5	0.352	0.587 5
分布式光伏	0.706	0.46	1.166	0.352	0.814
陆上风电	0.353	0.37	0.723	0.352	0.371
海上风电	0.706	0.75	1.456	0.352	1.104