Calculation Method of Dynamic Network Usage Charge for Distributed Energy Nearby Trading with Rights and Responsibilities Matching

doi:10.16183/j.cnki.jsjtu.2024.462

Abstract

Abstract:

Reasonable calculation of network usage charge is an important prerequisite for promoting the development of distributed energy nearby trading. However, existing methods for calculating network usage charge struggle to balance the needs of grid companies to recover transmission and distribution asset investment and the operational requirement of guiding distributed energy nearby trading in smoothing the net load curve. Therefore, a two-stage calculation method for dynamic network usage charge considering rights-responsibilities matching is proposed in this paper. First, a calculation method for static network usage charge based on rights-responsibilities matching is developed to ensure the fair and reasonable recovery of network construction costs. Then, a time-of-use dynamic adjustment method for network usage charge is designed to incentivize participants in distributed energy nearby trading to flatten the peak-to-valley differences of net load curves through price signals. On this basis, a bilevel optimization model is established, with a dynamic adjustment model of network usage charge in the upper level and a distributed energy nearby trading model in the lower level. The value of the dynamic network usage charge is measured by solving the model. Finally, simulation results show that the proposed calculation method for dynamic network usage charge can not only effectively ensure the reasonable recovery of transmission and distribution asset investments for grid companies but also significantly reduces the peak-to-valley difference rate of net load curves.

Key words: dynamic network usage charge, distributed energy nearby trading, transmission and distribution asset investment, rights-responsibilities matching principle

CLC Number:

TM732
F426

YAN Yi, PING Jian, YAN Zheng, JIA Qiangang. Calculation Method of Dynamic Network Usage Charge for Distributed Energy Nearby Trading with Rights and Responsibilities Matching[J]. Journal of Shanghai Jiao Tong University, 2026, 60(7): 1076-1086.

Figures/Tables 10

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References 26

[1]	林俐, 许冰倩, 王皓怀. 典型分布式发电市场化交易机制分析与建议[J]. 电力系统自动化, 2019, 43(4): 1-8.
	LIN Li, XU Bingqian, WANG Haohuai. Analysis and recommendations of typical market-based distributed generation trading mechanisms[J]. Automation of Electric Power Systems, 2019, 43(4): 1-8.
[2]	关立, 黄国栋, 吴锋, 等. 面向高比例分布式光伏的电力调度及市场化机制研究[J]. 浙江电力, 2022, 41(8): 10-16.
	GUAN Li, HUANG Guodong, WU Feng, et al. Research on power dispatching and marketization mechanism for high-proportion distributed photovoltaic[J]. Zhejiang Electric Power, 2022, 41(8): 10-16.
[3]	KIRAN I K, LAXMI A J. Power flow tracing based contract path method for transmission pricing[J]. Advances in Natural & Applied Sciences, 2015, 9(15):32-38.
[4]	ILIĆ M D, YOON Y T, ZOBIAN A, et al. Toward regional transmission provision and its pricing in New England[J]. Utilities Policy, 1997, 6(3): 245-256. doi: 10.1016/S0957-1787(97)00020-9 URL
[5]	HAPP H H. Cost of wheeling methodologies[J]. IEEE Transactions on Power Systems, 1994, 9(1): 147-156. doi: 10.1109/59.317547 URL
[6]	肖江, 刘瑞丰, 荆朝霞, 等. 英国改进的输电过网费定价机制分析[J]. 中国电力, 2019, 52(2): 53-60.
	XIAO Jiang, LIU Ruifeng, JING Zhaoxia, et al. Analysis on improved transmission use of system charging methodology in UK[J]. Electric Power, 2019, 52(2): 53-60.
[7]	PING J, LI D, YAN Z, et al. A trusted peer-to-peer market of joint energy and reserve based on blockchain[J]. Electric Power Systems Research, 2023, 214: 108802. doi: 10.1016/j.epsr.2022.108802 URL
[8]	PING J, YAN Z, CHEN S J. A privacy-preserving blockchain-based method to optimize energy trading[J]. IEEE Transactions on Smart Grid, 2023, 14(2): 1148-1157. doi: 10.1109/TSG.2022.3198165 URL
[9]	林佩伶, 江岳文. 计及过网费与线损费用的分布式发电交易优化[J]. 供用电, 2023, 40(11): 84-93.
	LIN Peiling, JIANG Yuewen. Transaction optimization of distributed energy considering network fees and line loss expenses[J]. Distribution & Utilization, 2023, 40(11): 84-93.
[10]	沈泽宇, 陈思捷, 严正, 等. 基于区块链的分布式能源交易技术[J]. 中国电机工程学报, 2021, 41(11): 3841-3850.
	SHEN Zeyu, CHEN Sijie, YAN Zheng, et al. Distributed energy trading technology based on blockchain[J]. Proceedings of the CSEE, 2021, 41(11): 3841-3850.
[11]	PAUDEL A, SAMPATH L P M I, YANG J W, et al. Peer-to-peer energy trading in smart grid considering power losses and network fees[J]. IEEE Transactions on Smart Grid, 2020, 11(6): 4727-4737. doi: 10.1109/TSG.5165411 URL
[12]	CHANG X Y, XU Y L, GUO Q L, et al. A Byzantine-resilient distributed peer-to-peer energy management approach[J]. IEEE Transactions on Smart Grid, 2023, 14(1): 623-634. doi: 10.1109/TSG.2022.3185140 URL
[13]	WEI X, XU Y L, SUN H B, et al. Peer-to-peer energy trading of carbon-aware prosumers: An online accelerated distributed approach with differential privacy[J]. IEEE Transactions on Smart Grid, 2024, 15(6): 5595-5609. doi: 10.1109/TSG.2024.3398041 URL
[14]	RAZAVI S M, AREFIZADEH S, BOLOUKI S, et al. P2P trade with prosumers’ actual approximate utility functions within near-potential games framework[J]. IEEE Transactions on Smart Grid, 2024, 15(6): 5923-5938. doi: 10.1109/TSG.2024.3439402 URL
[15]	NOORFATIMA N, JUNG J, ONEN A, et al. Bilevel peer-to-peer energy trading to maintain network quality and benefit distribution[J]. IEEE Transactions on Applied Superconductivity, 2024, 34(8): 5401105.
[16]	文安, 刘年, 黄维芳, 等. 英国电力市场的价格机制分析[J]. 南方电网技术, 2015, 9(1): 1-6. doi: 10.13648/j.cnki.issn1674-0629.2015.01.001
	WEN An, LIU Nian, HUANG Weifang, et al. Analysis of the price mechanism of the UK electricity market[J]. Southern Power System Technology, 2015, 9(1): 1-6. doi: 10.13648/j.cnki.issn1674-0629.2015.01.001
[17]	吴磊, 韩冬, 毛贵江, 等. 适应分布式发电市场化交易的过网费计算方法[J]. 上海交通大学学报, 2023, 57(7): 887-898. doi: 10.16183/j.cnki.jsjtu.2022.061
	WU Lei, HAN Dong, MAO Guijiang, et al. Calculation method of network usage charge for market-oriented trading in distributed generation market[J]. Journal of Shanghai Jiao Tong University, 2023, 57(7): 887-898.
[18]	邱辰. 可再生能源分布式发电市场化交易试点 “过网费” 价格机制分析与建议[J]. 水力发电, 2022, 48(9): 104-107.
	QIU Chen. Analysis and suggestions on the pricing mechanism of transmission and distribution fee of pilot distributed power generation nearby trading[J]. Water Power, 2022, 48(9): 104-107.
[19]	朱廷虎, 刘洋, 许立雄, 等. 基于区块链技术的微电网群分布式电能交易模式[J]. 电力建设, 2022, 43(6): 12-23. doi: 10.12204/j.issn.1000-7229.2022.06.002
	ZHU Tinghu, LIU Yang, XU Lixiong, et al. Research on distributed electricity transaction mode of microgrid cluster applying blockchain technology[J]. Electric Power Construction, 2022, 43(6): 12-23. doi: 10.12204/j.issn.1000-7229.2022.06.002
[20]	SÜTÖ B, DIVÉNYI D P. Local electricity market design utilizing network state dependent dynamic network usage tariff[J]. IEEE Access, 2023, 11: 19247-19258. doi: 10.1109/ACCESS.2023.3249113 URL
[21]	吴治国, 刘继春, 张帅, 等. 多售电主体点对点交易模式及其动态过网费机制[J]. 电力系统自动化, 2021, 45(19): 100-108.
	WU Zhiguo, LIU Jichun, ZHANG Shuai, et al. Peer-to-peer transaction model of multiple power sellers and its dynamic network fee mechanism[J]. Automation of Electric Power Systems, 2021, 45(19): 100-108.
[22]	王蓓蓓, 吴文强, 张汀荟, 等. 考虑动态过网费的分布式电能交易与配电网运营联合交互[J]. 电力系统自动化, 2023, 47(18): 91-100.
	WANG Beibei, WU Wenqiang, ZHANG Tinghui, et al. Joint interaction between distributed power trading and distribution network operation considering dynamic network tariffs[J]. Automation of Electric Power Systems, 2023, 47(18): 91-100.
[23]	姚昊天, 向月, 刘俊勇. 基于过网费动态更新的分布式电源多主体协同规划方法[J]. 电力系统自动化, 2021, 45(17): 70-78.
	YAO Haotian, XIANG Yue, LIU Junyong. Multi-agent collaborative planning method for distributed generators based on dynamic updating of network tariffs[J]. Automation of Electric Power Systems, 2021, 45(17): 70-78.
[24]	CUENCA J J, JAMIL E, HAYES B P. Revenue-based allocation of electricity network charges for future distribution networks[J]. IEEE Transactions on Power Systems, 2023, 38(2): 1728-1738. doi: 10.1109/TPWRS.2022.3176186 URL
[25]	张粒子. 我国输配电价改革中的机制建设和方法探索[J]. 价格理论与实践, 2016(2): 29-31.
	ZHANG Lizi. Discussion on the mechanism construction of transmission and distribution electricity price reform in China[J]. Price (Theory & Practice), 2016(2): 29-31.
[26]	杨磊, 杨禹莎. 面向电动汽车充电运营商的动态阶梯过网费策略研究[J]. 电力与能源, 2024, 45(5): 544-549.
	YANG Lei, YANG Yusha. Research on dynamic tiered network access fee strategy for electric vehicle charging operators[J]. Power & Energy, 2024, 45(5): 544-549.

用户	${\mathit{\delta }}_{\mathit{j}}^{\mathit{d}}$	${\mathit{\delta }}_{\mathit{j}}^{\mathit{u}}$	转移前最大负荷/kW	${\mathit{P}}_{\mathit{j}}^{\mathit{L},\mathit{m}\mathit{a}\mathit{x}}$/kW
F	0.45	0.25	790.6	960
G	0.50	0.30	265.4	350
H	0.55	0.35	433.2	530

交易情况	峰谷差/kW	峰谷差率
动态过网费下参与交易	1081.7	0.1557
静态过网费下参与交易	1188.3	0.1710
不参与交易	1944.3	0.2651

过网费测算方法	回收的输配电资产投资费/ 万元	净负荷曲线峰谷差/kW	峰谷差率
所提静态过网费基准	0.4469	1188.3	0.1710
所提动态过网费	0.4470	1081.7	0.1557
文献[24]中测算方法	0.4336	1106.3	0.1607
文献[26]中测算方法	0.0438	1096.6	0.1578