考虑网损的电力系统节点边际碳势理论研究与建模

doi:10.11930/j.issn.1004-9649.202305075

中国电力 ›› 2024, Vol. 57 ›› Issue (6): 215-224.DOI: 10.11930/j.issn.1004-9649.202305075

考虑网损的电力系统节点边际碳势理论研究与建模

吴静¹(), 刘轩宇²(), 李响¹(), 齐笑言¹, 李成俊¹, 张忠²

1. 国网辽宁省电力有限公司电力科学研究院，辽宁沈阳　110006
2. 大连理工大学电气工程学院，辽宁大连　116024

收稿日期:2023-05-16 接受日期:2023-09-19 出版日期:2024-06-28 发布日期:2024-06-25
作者简介:吴静（1972—），女，硕士，高级工程师，从事电力环境保护研究，E-mail：1822052970@qq.com
刘轩宇（1998—），男，硕士研究生，从事电力系统碳排放、电力系统低碳经济调度研究，E-mail：liuxuanyu9@mail.dlut.edu.cn
李响（1986—），男，通信作者，硕士，高级工程师，从事电力环境保护研究，E-mail：dbdkyhbs_lx@126.com
基金资助:
国网辽宁省电力有限公司电力科学研究院科技项目（省级电网碳流分析与碳排放监控技术研究，2022YF-71）。

Research and Modelling of Bus Marginal Carbon Intensity for Power Systems Considering Network Losses

Jing WU¹(), Xuanyu LIU²(), Xiang LI¹(), Xiaoyan QI¹, Chengjun LI¹, Zhong ZHANG²

1. Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China
2. School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China

Received:2023-05-16 Accepted:2023-09-19 Online:2024-06-28 Published:2024-06-25
Supported by:
This work is supported by Science and Technology Project of Electric Power Research Institute of State Grid Liaoning Electric Power Co., Ltd. (Research on Carbon Flow Analysis and Carbon Emission Monitoring Technology of Provincial Power Grid, No.2022YF-71).

摘要/Abstract

摘要：

用于电力系统碳排放计算的宏观核算法和碳流分析法未考虑网损、阻塞因素对电网边际碳排放的影响。为实现电网碳排放指标的精细化分析，建立考虑网损的电力系统节点边际碳势分析模型。考虑火电机组煤耗特性建立了机组的边际碳势模型；基于交流潮流模型，建立电网网损灵敏度模型；进而提出电力系统节点边际碳势的计算方法，并考虑网络阻塞因素进一步改进了该方法。采用IEEE 14节点系统和某500 kV实际系统算例验证了所建模型的合理性和适用性，分别分析了低碳和非低碳调度模式下节点碳势的变化规律；发现考虑网损后节点的正、负向边际碳势存在一定差异；网损因素也使得电网各节点边际碳势各异，考虑网损的模型可提供更为准确的节点边际碳势信息，可用于开展较为精准的实时碳排放分析。

关键词: 边际碳势, 网损间接碳排放, 边际理论, 碳流理论, 灵敏度分析

Abstract:

Network losses and congestion have not been considered in the current macro carbon calculation method and carbon flow analysis method for power systems. To achieve precise analysis of carbon emission indicators for power systems, this paper proposes a model to calculate the bus marginal carbon intensity (MCI) of power system considering network losses. A MCI model is established based on coal consumption characteristics of thermal power units. Based on AC power flow model, a sensitivity model of network losses is established, and a calculation method is proposed to calculate the bus MCI of power systems. The method is further improved with consideration of network constraints. The IEEE 14-bus test system and a real 500 kV system are used to verify the correctness and applicability of the proposed model. The characteristics of MCI is analyzed under low carbon and non-low carbon dispatch modes. It is found that the positive and negative MCI of a bus is different when considering the network losses. The network factor also causes the differences of MCI of each bus. The model considering network losses can provide more accurate bus MCI information, which can be used to conduct more accurate real-time carbon emission analysis.

Key words: marginal carbon intensity, indirect carbon emissions of network loss, marginal theory, carbon flow theory, sensitivity analysis

吴静, 刘轩宇, 李响, 齐笑言, 李成俊, 张忠. 考虑网损的电力系统节点边际碳势理论研究与建模[J]. 中国电力, 2024, 57(6): 215-224.

Jing WU, Xuanyu LIU, Xiang LI, Xiaoyan QI, Chengjun LI, Zhong ZHANG. Research and Modelling of Bus Marginal Carbon Intensity for Power Systems Considering Network Losses[J]. Electric Power, 2024, 57(6): 215-224.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305075

https://www.electricpower.com.cn/CN/Y2024/V57/I6/215

图/表 11

图 1 电网节点-支路关系简图

Fig.1 Schematic diagram of a power grid

图 2 电力系统节点边际碳势计算流程

Fig.2 Flow chart for calculating bus marginal carbon intensity of power system

图 3 改进的IEEE 14节点系统

Fig.3 A modified IEEE 14-bus system

表 1 发电机参数

Table 1 Generator parameters

节点	出力/MW		煤耗系数			碳排放系数/%
节点	最小	最大	a/ (t·(MW²·h)^–1)	b/ (t·(MW·h)^–1)	c/(t·h^–1)	碳排放系数/%
1	100	200	0.000338	0.2298	4.975	2.37
2	60	120	0.000421	0.2127	4.300	2.63
6	20	50	0.000677	0.2097	1.881	2.57
8	10	20	0.000927	0.2128	1.280	2.40

表 2 发电机碳势与节点碳势

Table 2 Carbon intensity of generators and buses 单位：t/(MW·h)

节点编号	火电机组碳势	节点平均碳势	节点正向边际碳势	节点负向边际碳势
1	0.743	0.743	0.687	0.712
2	0.793	0.770	0.701	0.726
3		0.605	0.741	0.767
4		0.761	0.726	0.751
5		0.754	0.716	0.742
6	0.723	0.726	0.710	0.735
7		0.721	0.729	0.755
8	0.709	0.709	0.729	0.755
9		0.730	0.731	0.757
10		0.726	0.732	0.758
11		0.726	0.724	0.749
12		0.726	0.721	0.747
13		0.726	0.726	0.752
14		0.727	0.744	0.771

图 4 考虑网损前后的节点边际碳势

Fig.4 Bus marginal carbon intensity before and after considering network losses

图 5 低碳调度模式下考虑网损前后的节点边际碳势

Fig.5 Bus marginal carbon intensity before and after considering network losses under low carbon dispatching mode

图 6 500 kV系统的发电机碳势与节点碳势

Fig.6 Generator and bus carbon intensity of a 500 kV system

图 7 500 kV系统的节点边际碳势

Fig.7 Bus marginal carbon intensity of a 500 kV system

图 8 考虑网损前后的500 kV系统节点边际碳势

Fig.8 Bus marginal carbon intensity of a 500 kV system before and after considering network losses

图 9 考虑网络阻塞前后的节点边际碳势

Fig.9 Bus marginal carbon intensity before and after considering network congestion

参考文献 34

1	代贤忠. 碳中和对能源领域的影响[EB/OL]. (2021-10-17)[2023-04-09]. https://baijiahao.baidu.com/s?id=1702895338045951179&wfr=spider&for=pc.
2	张运洲, 张宁, 代红才, 等. 中国电力系统低碳发展分析模型构建与转型路径比较[J]. 中国电力, 2021, 54 (3): 1- 11.
	ZHANG Yunzhou, ZHANG Ning, DAI Hongcai, et al. Model construction and pathways of low-carbon transition of China's power system[J]. Electric Power, 2021, 54 (3): 1- 11.
3	董福贵, 夏美娟, 李婉莹. 基于PSO-GWO的省级能耗强度预测与碳减排潜力估算[J]. 中国电力, 2023, 56 (9): 226- 234.
	DONG Fugui, XIA Meijuan, LI Wanying. Prediction of provincial energy consumption intensity and estimation of carbon emission reduction potential based on PSO-GWO[J]. Electric Power, 2023, 56 (9): 226- 234.
4	王小飞, 任洪波, 吴琼, 等. 考虑中长期碳减排约束的区域综合能源系统多阶段动态规划[J]. 中国电力, 2023, 56 (11): 185- 196.
	WANG Xiaofei, REN Hongbo, WU Qiong, et al. Multi-stage dynamic plan of regional integrated energy system considering medium and long-term carbon emission reduction constraints[J]. Electric Power, 2023, 56 (11): 185- 196.
5	陈丽霞, 孙弢, 周云, 等. 电力系统发电侧和负荷侧共同碳责任分摊方法[J]. 电力系统自动化, 2018, 42 (19): 106- 111.
	CHEN Lixia, SUN Tao, ZHOU Yun, et al. Method of carbon obligation allocation between generation side and demand side in power system[J]. Automation of Electric Power Systems, 2018, 42 (19): 106- 111.
6	KANG C Q, ZHOU T R, CHEN Q X, et al. Carbon emission flow from generation to demand: a network-based model[J]. IEEE Transactions on Smart Grid, 2015, 6 (5): 2386- 2394. DOI
7	李姚旺, 张宁, 杜尔顺, 等. 基于碳排放流的电力系统低碳需求响应机制研究及效益分析[J]. 中国电机工程学报, 2022, 42 (8): 2830- 2842.
	LI Yaowang, ZHANG Ning, DU Ershun, et al. Mechanism study and benefit analysis on power system low carbon demand response based on carbon emission flow[J]. Proceedings of the CSEE, 2022, 42 (8): 2830- 2842.
8	汪超群, 陈懿, 文福拴, 等. 电力系统碳排放流理论改进与完善[J]. 电网技术, 2022, 46 (5): 1683- 1691.
	WANG C Q, CHEN Y, WEN F S, et al. Improvement and perfection of carbon emission flow theory in power systems[J]. Power System Technology, 2022, 46 (5): 1683- 1691.
9	李岩松, 刘启智, 张朕搏, 等. 基于电网功率分布的碳排放流计算方法[J]. 电网技术, 2017, 41 (3): 840- 844.
	LI Yansong, LIU Qizhi, ZHANG Zhenbo, et al. Algorithm of carbon emission flow based on power distribution[J]. Power System Technology, 2017, 41 (3): 840- 844.
10	周全, 冯冬涵, 徐长宝, 等. 负荷侧碳排放责任直接分摊方法的比较研究[J]. 电力系统自动化, 2015, 39 (17): 153- 159.
	ZHOU Quan, FENG Donghan, XU Changbao, et al. Methods for allocating carbon obligation in demand side: a comparative study[J]. Automation of Electric Power Systems, 2015, 39 (17): 153- 159.
11	康重庆, 杜尔顺, 李姚旺, 等. 新型电力系统的“碳视角”: 科学问题与研究框架[J]. 电网技术, 2022, 46 (3): 821- 833.
	KANG Chongqing, DU Ershun, LI Yaowang, et al. Key scientific problems and research framework for carbon perspective research of new power systems[J]. Power System Technology, 2022, 46 (3): 821- 833.
12	WANG X, GONG Y, JIANG C W. Regional carbon emission management based on probabilistic power flow with correlated stochastic variables[J]. IEEE Transactions on Power Systems, 2015, 30 (2): 1094- 1103. DOI
13	SHEN W, QIU J, MENG K, et al. Low-carbon electricity network transition considering retirement of aging coal generators[J]. IEEE Transactions on Power Systems, 2020, 35 (6): 4193- 4205. DOI
14	DENG L R, LI Z S, SUN H B, et al. Generalized locational marginal pricing in a heat-and-electricity-integrated market[J]. IEEE Transactions on Smart Grid, 2019, 10 (6): 6414- 6425. DOI
15	ZHONG W F, XIE K, LIU Y, et al. Nash mechanisms for market design based on distribution locational marginal prices[J]. IEEE Transactions on Power Systems, 2022, 37 (6): 4297- 4309. DOI
16	BAI L Q, WANG J H, WANG C S, et al. Distribution locational marginal pricing (DLMP) for congestion management and voltage support[J]. IEEE Transactions on Power Systems, 2018, 33 (4): 4061- 4073. DOI
17	WANG Y Q, QIU J, TAO Y C. Optimal power scheduling using data-driven carbon emission flow modelling for carbon intensity control[J]. IEEE Transactions on Power Systems, 2022, 37 (4): 2894- 2905. DOI
18	LV S, CHEN S, WEI Z N, et al. Power–transportation coordination: toward a hybrid economic-emission dispatch model[J]. IEEE Transactions on Power Systems, 2022, 37 (5): 3969- 3981. DOI
19	张刚, 张峰, 张利, 等. 考虑碳排放交易的日前调度双阶段鲁棒优化模型[J]. 中国电机工程学报, 2018, 38 (18): 5490- 5499.
	ZHANG Gang, ZHANG Feng, ZHANG Li, et al. Two-stage robust optimization model of day-ahead scheduling considering carbon emissions trading[J]. Proceedings of the CSEE, 2018, 38 (18): 5490- 5499.
20	周孟然, 王旭, 邵帅, 等. 考虑需求响应和碳排放额度的微电网分层优化调度[J]. 中国电力, 2022, 55 (10): 45- 53.
	ZHOU Mengran, WANG Xu, SHAO Shuai, et al. Hierarchical optimal scheduling of microgrid considering demand response and carbon emission quota[J]. Electric Power, 2022, 55 (10): 45- 53.
21	陈厚合, 茅文玲, 张儒峰, 等. 基于碳排放流理论的电力系统源-荷协调低碳优化调度[J]. 电力系统保护与控制, 2021, 49 (10): 1- 11.
	CHEN Houhe, MAO Wenling, ZHANG Rufeng, et al. Low-carbon optimal scheduling of a power system source-load considering coordination based on carbon emission flow theory[J]. Power System Protection and Control, 2021, 49 (10): 1- 11.
22	卢治霖, 刘明波, 尚楠, 等. 考虑碳排放权交易市场影响的日前电力市场两阶段出清模型[J]. 电力系统自动化, 2022, 46 (10): 159- 170.
	LU Zhilin, LIU Mingbo, SHANG Nan, et al. Two-stage clearing model for day-ahead electricity market considering impact of carbon emissions trading market[J]. Automation of Electric Power Systems, 2022, 46 (10): 159- 170.
23	缑新科, 崔乐乐, 巨圆圆, 等. 火电厂机组煤耗特性曲线拟合算法研究[J]. 电力系统保护与控制, 2014, 42 (10): 84- 89.
	GOU Xinke, CUI Lele, JU Yuanyuan, et al. Study on curve fitting algorithm for thermal power plant units coal consumption[J]. Power System Protection and Control, 2014, 42 (10): 84- 89.
24	冯欣, 杨军. 考虑网络损耗的碳排放流理论改进与完善[J]. 电力自动化设备, 2016, 36 (5): 81- 86.
	FENG Xin, YANG Jun. Improvement and enhancement of carbon emission flow theory considering power loss[J]. Electric Power Automation Equipment, 2016, 36 (5): 81- 86.
25	RUIZ P A, RUDKEVICH A. Analysis of marginal carbon intensities in constrained power networks[C]//2010 43rd Hawaii International Conference on System Sciences. Honolulu, HI, USA. IEEE, 2010: 1–9.
26	周全. 节能减排环境下电力系统碳排放责任分摊机制研究[D]. 上海: 上海交通大学, 2016.
	ZHOU Quan. The study of carbon emission obligation allocation in power systems under the environment of energy-saving and emission-reduction[D]. Shanghai: Shanghai Jiaotong University, 2016.
27	陈厚合, 张鹏, 姜涛, 等. 基于灵敏度分析的综合能源系统运行安全性的研究[J]. 电力自动化设备, 2019, 39 (8): 95- 103.
	CHEN Houhe, ZHANG Peng, JIANG Tao, et al. Security analysis based on sensitivity analysis for integrated electric and gas energy system[J]. Electric Power Automation Equipment, 2019, 39 (8): 95- 103.
28	高慧敏, 章坚民, 江力. 基于二阶网损无功灵敏度矩阵的配电网无功补偿选点[J]. 电网技术, 2014, 38 (7): 1979- 1983.
	GAO Huimin, ZHANG Jianmin, JIANG Li. Optimal location of reactive power compensation for distribution network based on second order loss-reactive power sensitivity matrix[J]. Power System Technology, 2014, 38 (7): 1979- 1983.
29	蔡宇, 李保卫, 胡泽春, 等. 燃煤机组碳排放指标计算及影响因素分析[J]. 电网技术, 2013, 37 (5): 1185- 1189.
	CAI Yu, LI Baowei, HU Zechun, et al. Calculation of carbon emission index of coal-fired generating unit and analysis on influencing factors[J]. Power System Technology, 2013, 37 (5): 1185- 1189.
30	沈照人. 回归分析法在碳排放核查中测算发电企业燃煤发热量的应用[J]. 煤质技术, 2021, 36 (5): 69- 74. DOI
	SHEN Zhaoren. The application of regression analysis method to measure the calorific value of coal in power generation enterprises in carbon emission verification[J]. Coal Quality Technology, 2021, 36 (5): 69- 74. DOI
31	康重庆, 程耀华, 孙彦龙, 等. 电力系统碳排放流的递推算法[J]. 电力系统自动化, 2017, 41 (18): 10- 16. DOI
	KANG Chongqing, CHENG Yaohua, SUN Yanlong, et al. Recursive calculation method of carbon emission flow in power systems[J]. Automation of Electric Power Systems, 2017, 41 (18): 10- 16. DOI
32	王景亮, 张焰, 王承民, 等. 基于灵敏度分析与最优潮流的电网无功/电压考核方法[J]. 电网技术, 2005, 29 (10): 65- 69.
	WANG Jingliang, ZHANG Yan, WANG Chengmin, et al. Power system reactive power/voltage assessment based on sensitivity analysis and optimal power flow[J]. Power System Technology, 2005, 29 (10): 65- 69.
33	王洪涛, 邹斌, 张亮. 基于节点传输贡献量的省间联络线潮流近似计算[J]. 电力自动化设备, 2020, 40 (6): 135- 141.
	WANG Hongtao, ZOU Bin, ZHANG Liang. Approximate calculation of inter-provincial tie-line power flow based on node transmission contribution[J]. Electric Power Automation Equipment, 2020, 40 (6): 135- 141.
34	VENKATESWARA REDDY M, MUNI B P, SARMA A V R S. Enhancement of voltage profile for IEEE 14 bus system with inter line power flow controller[C]//2016 Biennial International Conference on Power and Energy Systems: Towards Sustainable Energy (PESTSE). Bengaluru, India. IEEE, 2016: 1–5.

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