New Type Power System and the Integrated Energy

Performance Evaluation Index and Method of Micro-Grid Distributed Electricity Trading Under the Background of “Carbon Peaking and Carbon Neutrality”

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  • Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China

Received date: 2021-10-08

  Online published: 2022-04-01

Abstract

With the rapid development of distributed power generation research and application, the distributed trading market, as a new type of power trading mode, can effectively increase the consumption rate of renewable energy and is an important means to promote the realization of the goal of “carbon peaking and carbon neutrality”. Introducing the market evaluation mechanism into distributed transactions will prompt users to consider the impact of the market evaluation mechanism on their trading strategies and promote the sound development of the distributed transaction market. The distributed power trading market among micro-grid users is studied in this paper. First, taking the market participants and transaction supporting software and hardware as the research object, a multi-dimensional performance evaluation index system is established from the aspects of power supply capacity, user satisfaction, and platform security. Next, the research status of distributed power trading market evaluation methods is summarized. The key technologies of distributed power trading performance evaluation are analyzed from the establishment of index system, the index calculation method, and the comprehensive evaluation method. Finally, in combination with the current development status, the research direction of the distributed power trading performance evaluation in the future is prospected.

Cite this article

WANG Wenbin, ZHENG Shujiang, FAN Ruixiang, CHEN Wen, ZHOU Shiyang . Performance Evaluation Index and Method of Micro-Grid Distributed Electricity Trading Under the Background of “Carbon Peaking and Carbon Neutrality”[J]. Journal of Shanghai Jiaotong University, 2022 , 56(3) : 312 -324 . DOI: 10.16183/j.cnki.jsjtu.2021.391

References

[1] 邓旭, 谢俊, 滕飞. 何谓“碳中和”?[J]. 气候变化研究进展, 2021, 17(1):107-113.
[1] DENG Xu, XIE Jun, TENG Fei. What is carbon neutrality?[J]. Climate Change Research, 2021, 17(1):107-113.
[2] 王灿, 张雅欣. 碳中和愿景的实现路径与政策体系[J]. 中国环境管理, 2020, 12(6):58-64.
[2] WANG Can, ZHANG Yaxin. Implementation pathway and policy system of carbon neutrality vision[J]. Chinese Journal of Environmental Management, 2020, 12(6):58-64.
[3] 张雅欣, 罗荟霖, 王灿. 碳中和行动的国际趋势分析[J]. 气候变化研究进展, 2021, 17(1):88-97.
[3] ZHANG Yaxin, LUO Huilin, WANG Can. Progress and trends of global carbon neutrality pledges[J]. Climate Change Research, 2021, 17(1):88-97.
[4] HADDADI A, BOULET B, YAZDANI A, et al. A μ-based approach to small-signal stability analysis of an interconnected distributed energy resource unit and load[J]. IEEE Transactions on Power Delivery, 2015, 30(4):1715-1726.
[5] 盛万兴, 吴鸣, 季宇, 等. 分布式可再生能源发电集群并网消纳关键技术及工程实践[J]. 中国电机工程学报, 2019, 39(8):2175-2186.
[5] SHENG Wanxing, WU Ming, JI Yu, et al. Key techniques and engineering practice of distributed renewable generation clusters integration[J]. Proceedings of the CSEE, 2019, 39(8):2175-2186.
[6] 王蓓蓓, 李雅超, 赵盛楠, 等. 基于区块链的分布式能源交易关键技术[J]. 电力系统自动化, 2019, 43(14):53-64.
[6] WANG Beibei, LI Yachao, ZHAO Shengnan, et al. Key technologies on blockchain based distributed energy transaction[J]. Automation of Electric Power Systems, 2019, 43(14):53-64.
[7] 李彬, 覃秋悦, 祁兵, 等. 基于区块链的分布式能源交易方案设计综述[J]. 电网技术, 2019, 43(3):961-972.
[7] LI Bin, QIN Qiuyue, QI Bing, et al. Design of distributed energy trading scheme based on blockchain[J]. Power System Technology, 2019, 43(3):961-972.
[8] 王成山, 王守相. 智能微网在分布式能源接入中的作用与挑战[J]. 中国科学院院刊, 2016, 31(2):232-240.
[8] WANG Chengshan, WANG Shouxiang. The role and challenge of smart mircogrid in the integration of distributed energy resources[J]. Bulletin of Chinese Academy of Sciences, 2016, 31(2):232-240.
[9] LONG C, WU J Z, ZHANG C H, et al. Peer-topeer energy trading in a community microgrid[C]// 2017 IEEE Power & Energy Society General Meeting. Chicago, IL, USA: IEEE, 2017: 1-5.
[10] LI Z T, KANG J W, YU R, et al. Consortium blockchain for secure energy trading in industrial Internet of Things[J]. IEEE Transactions on Industrial Informatics, 2018, 14(8):3690-3700.
[11] KUMAR M, SRIVASTAVA S C, SINGH S N, et al. Development of a control strategy for interconnection of islanded direct current microgrids[J]. IET Renewable Power Generation, 2015, 9(3):284-296.
[12] TUSHAR W, SAHA T K, YUEN C, et al. Peer-to-peer energy trading with sustainable user participation: A game theoretic approach[J]. IEEE Access, 2018, 6:62932-62943.
[13] MORSTYN T, FARRELL N, DARBY S J, et al. Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants[J]. Nature Energy, 2018, 3(2):94-101.
[14] WANG D, SU P F, LIU B, et al. Research on bidding strategy based on evaluation mechanism for peer-to-peer energy tradingin microgrid[C]// 2019 The 11th International Conference on Applied Energy. Västerås, Sweden: Elsevier, 2019.
[15] 刘聪, 周京阳, SHAHIDEHPOUR M, 等. 市场环境下输配电系统一体化分布式交易优化方法[J]. 电力系统自动化, 2019, 43(21):103-110.
[15] LIU Cong, ZHOU Jingyang, SHAHIDEHPOUR Mohammad, et al. Optimization method for decentral transaction of integrated transmission and distribution system in market environment[J]. Automation of Electric Power Systems, 2019, 43(21):103-110.
[16] WANG D, SU P F, YANG Q. A novel pricing scheme for peer-to-peer energy trading based on evaluation mechanism in microgrid[C]// 2019 IEEE Innovative Smart Grid Technologies-Asia. Chengdu, China: IEEE, 2019: 4318-4322.
[17] XU S Y, CHEN M Y, WADE N, et al. Reliability evaluation of electric power system containing distribution generation[C]// Advanced Materials Research, 2011, 389-390:3472-3478.
[18] 潘晓杰, 徐友平, 朱成亮, 等. 基于深度学习的多输入特征融合的暂态电压稳定性评估方法[J]. 电网与清洁能源, 2021, 37(2):79-84.
[18] PAN Xiaojie, XU Youping, ZHU Chengliang, et al. Transient voltage stability evaluation method based on multi-input feature fusion of deep learning[J]. Power System and Clean Energy, 2021, 37(2):79-84.
[19] 侯磊, 杨欣可, 沙云鹏, 等. 新型多端口电能路由器关键技术研究[J]. 信息技术, 2021, 45(1):48-52.
[19] HOU Lei, YANG Xinke, SHA Yunpeng, et al. Key technologies of new multi-port power router[J]. Information Technology, 2021, 45(1):48-52.
[20] YANG Q, WANG H, WANG T T, et al. Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant[J]. Applied Energy, 2021, 294:117026.
[21] 曹清山. 售电市场放开环境下基于多属性决策的电力客户经济性评估和选择研究[D]. 杭州: 浙江大学, 2018.
[21] CAO Qingshan. Multi-attribute decision making model for customer economic evaluation and selection in opening electricity market[D]. Hangzhou: Zhejiang University, 2018.
[22] 中华人民共和国国家发展和改革委员会. 国家能源局关于开展分布式发电市场化交易试点的通知[EB/OL]. (2017-10-31) [2021-09-10]. http://zfxxgk.nea.gov.cn/auto87/201711/t20171113_3055.htm .
[22] National Development and Reform Commission. Notice of the national development and reform commission and the national energy administration on launching the pilot of market-oriented transaction of distributed generation[EB/OL]. (2017-10-31) [2021-09-10]. http://zfxxgk.nea.gov.cn/auto87/201711/t20171113_3055.htm .
[23] 贾清泉, 宋家骅, 兰华, 等. 电能质量及其模糊方法评价[J]. 电网技术, 2000, 24(6):46-49.
[23] JIA Qingquan, SONG Jiahua, LAN Hua, et al. Quality of electricity commodity and its fuzzy evaluation[J]. Power System Technology, 2000, 24(6):46-49.
[24] 李世林, 郭汀, 刘亚芳, 等. 电能质量供电电压允许偏差[S]. 北京:中华人民共和国国家质量监督检验检疫总局, 2003.
[24] LI Shilin, GUO Ting, LIU Yafang, et al. Quality of electric energy supply admissible deviation of supply voltage[S]. Beijing: General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China, 2003.
[25] 曲涛, 任元, 林海雪, 等. 电能质量公用电网谐波[S]. 北京: 国家技术监督局, 1993.
[25] QU Tao, REN Yuan, LIN Haixue, et al. Power quality harmonics in public power grid[S]. Beijing: State Bureau of Technical Supervision, 1993.
[26] 杨小彬, 李和明, 尹忠东, 等. 基于层次分析法的配电网能效指标体系[J]. 电力系统自动化, 2013, 37(21):146-150.
[26] YANG Xiaobin, LI Heming, YIN Zhongdong, et al. Energy efficiency index system for distribution network based on analytic hierarchy process[J]. Automation of Electric Power Systems, 2013, 37(21):146-150.
[27] 张尚, 王涛, 顾雪平. 基于直觉模糊层次分析法的电网运行状态综合评估[J]. 电力系统自动化, 2016, 40(4):41-49.
[27] ZHANG Shang, WANG Tao, GU Xueping. Synthetic evaluation of power grid operating states based on intuitionistic fuzzy analytic hierarchy process[J]. Automation of Electric Power Systems, 2016, 40(4):41-49.
[28] 李蕊, 李跃, 徐浩, 等. 基于层次分析法和专家经验的重要电力用户典型供电模式评估[J]. 电网技术, 2014, 38(9):2336-2341.
[28] LI Rui, LI Yue, XU Hao, et al. Assessment on typical power supply mode for important power consumers based on analytical hierarchy process and expert experience[J]. Power System Technology, 2014, 38(9):2336-2341.
[29] XUE S, WU Z C, ZHANG H, et al. Evaluation model of key driving factors for different types of demand side distributed power resources to participate in market transactions[J]. IOP Conference Series: Earth and Environmental Science, 2021, 829(1):012009.
[30] 欧阳森, 石怡理. 改进熵权法及其在电能质量评估中的应用[J]. 电力系统自动化, 2013, 37(21):156-159.
[30] OUYANG Sen, SHI Yili. A new improved entropy method and its application in power quality evaluation[J]. Automation of Electric Power Systems, 2013, 37(21):156-159.
[31] 商立群, 王守鹏. 改进主成分分析法在火电机组综合评价中的应用[J]. 电网技术, 2014, 38(7):1928-1933.
[31] SHANG Liqun, WANG Shoupeng. Application of improved principal component analysis in comprehensive assessment on thermal power generation units[J]. Power System Technology, 2014, 38(7):1928-1933.
[32] DONG J, WANG D X, LIU D R, et al. Operation health assessment of power market based on improved matter-element extension cloud model[J]. Sustainability, 2019, 11(19):5470.
[33] SHENG J M, CHEN T Y, JIN W, et al. Selection of cost allocation methods for power grid enterprises based on entropy weight method[J]. Journal of Physics: Conference Series, 2021, 1881(2):022063.
[34] 施建华, 荆朝霞, 陈达鹏. 广东电力市场评价指标与方法模型研究[J]. 广东电力, 2020, 33(8):111-119.
[34] SHI Jianhua, JING Zhaoxia, CHEN Dapeng. Research on evaluation indexs and method model of Guangdong power market[J]. Guangdong Electric Power, 2020, 33(8):111-119.
[35] 李涛, 王盛煜. 基于灰色关联度和模糊综合评价法的我国电力市场交易评价体系研究[J]. 工业技术经济, 2018, 37(9):130-137.
[35] LI Tao, WANG Shengyu. Research on evaluation system of electricity market transaction in China based on gray relational grade analysis and fuzzy analytic hierarchy process[J]. Journal of Industrial Technological Economics, 2018, 37(9):130-137.
[36] 施建华. 广东电力市场评价指标与方法模型研究[D]. 广州: 华南理工大学, 2020.
[36] SHI Jianhua. Research on evaluation indexes and methods of Guangdong power market[D]. Guangzhou: South China University of Technology, 2020.
[37] NGUYEN P H, TSAI J F, VENKATA AJAY KUMAR G, et al. Stock investment of agriculture companies in the Vietnam stock exchange market: An AHP integrated with GRA-TOPSIS-MOORA approaches[J]. The Journal of Asian Finance, Economics and Business, 2020, 7(7):113-121.
[38] HE J, ZHAO W, HUANG H Z, et al. The evaluation system of power market monitoring based on AHP and the entropy method[J]. IOP Conference Series: Earth and Environmental Science, 2021, 831(1):012027.
[39] 何涛. 适用于分布式能源交易场景的区块链关键算法与技术研究[D]. 成都: 电子科技大学, 2020.
[39] HE Tao. Research on key algorithms and technologies of blockchain for distributed energy trading scenarios[D]. Chengdu: University of Electronic Science and Technology of China, 2020.
[40] SHALUKHO A V, LIPUZHIN I A, VOROSHILOV A A. Power quality in microgrids with distributed generation[C]// 2019 International Ural Conference on Electrical Power Engineering. Chelyabinsk, Russia: IEEE, 2019: 54-58.
[41] ABDULGALIL M A, KHALID M, ALSHEHRI J. Microgrid reliability evaluation using distributed energy storage systems[C]// 2019 IEEE Innovative Smart Grid Technologies-Asia. Chengdu, China: IEEE, 2019: 2837-2841.
[42] RAVADA B R, TUMMURU N R, ANDE B N L. Photovoltaic-wind and hybrid energy storage integrated multisource converter configuration-based grid-interactive microgrid[J]. IEEE Transactions on Industrial Electronics, 2021, 68(5):4004-4013.
[43] SHENG H Z, WANG C F, LI B W, et al. Multi-timescale active distribution network scheduling considering demand response and user comprehensive satisfaction[J]. IEEE Transactions on Industry Applications, 2021, 57(3):1995-2005.
[44] 陈玮. 新能源背景下的主动配电网故障恢复关键技术研究[D]. 杭州: 浙江大学, 2020.
[44] CHEN Wei. Research on service restoration of active distribution networks under the background of renewable energy[D]. Hangzhou: Zhejiang University, 2020.
[45] MARTORANA F, BONOMOLO M, LEONE G, et al. Solar-assisted heat pumps systems for domestic hot water production in small energy communities[J]. Solar Energy, 2021, 217:113-133.
[46] ZHAO H, ZHAO J H, QIU J, et al. Data-driven risk preference analysis in day-ahead electricity market[J]. IEEE Transactions on Smart Grid, 2021, 12(3):2508-2517.
[47] STRINGER N, HAGHDADI N, BRUCE A, et al. Fair consumer outcomes in the balance: Data driven analysis of distributed PV curtailment[J]. Renewable Energy, 2021, 173:972-986.
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