陈修鹏;李庚银;周明;夏勇;

• 1:新能源电力系统国家重点实验室(华北电力大学)
• 2:国网江苏省电力公司

摘要(Abstract)：

交互能源(transactive energy,TE)是一种兼具市场特性和控制功能的机制,在保障系统安全灵活运行的基础上,以经济价值为控制因素实现系统供需动态平衡。首先,文章以含光伏(photovoltaic,PV)出力、储能系统(energy storage system,ESS)和可控负荷(controllable load,CL)的高渗透率产消者组成的配网为研究对象,建立允许产消者之间以及产消者和主网点对点(peer to peer,P2P)交易的交互平台,充分提高用户侧资源的灵活性。然后建立以配网运行成本最小的日前优化调度模型,其中基于截断通用分布模型准确描述光伏出力随机性成本,定量体现光伏出力预测偏差带来的经济损失,鼓励产消者提高预测精度。之后通过交替方向乘子法在保证产消者隐私的前提下进行分布式求解,通过有限的信息交互实现产消者P2P交易。最后,通过算例验证该模型的有效性。

关键词(KeyWords)： 交互能源;产消者;光伏随机性;点对点交易;交替方向乘子法

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划项目(2016YFB0901100)~~

作者(Author): 陈修鹏;李庚银;周明;夏勇;

Email:

DOI: 10.13335/j.1000-3673.pst.2020.0102a

参考文献(References)：

• [1] Dimeas A,Drenkard S,Hatzigrgyriou N,et al.Smart houses in the smart grid:developing an interactive network[J].IEEE Electrification Magazine,2014,2(1):81-93.
• [2] Parag Y,Sovacool B K.Electricity market design for the prosumer era[J].Nature Energy,2016,1(4):1-6.
• [3]殷爽睿，艾芊，曾顺奇，等．能源互联网多能分布式优化研究挑战与展望[J]．电网技术，2018,42(5):1359-1369.Yin Shuangrui,Ai Qian,Zeng Shunqi,et al.Challenges and prospects of multi-energy distributed optimization for energy internet[J].Power System Technology,2018,42(5):1359-1369(in Chinese).
• [4]张涛，张福兴，张彦．面向能源互联网的能量管理系统研究[J]．电网技术，2016,40(1):146-155.Zhang Tao,Zhang Fuxing,Zhang Yan.Study on energy management system of energy internet[J].Power System Technology,2016,40(1):146-155(in Chinese).
• [5]蒲天骄，刘威，陈乃仕，等．基于一致性算法的主动配电网分布式优化调度[J]．中国电机工程学报，2017,37(6):1579-1590.Pu Tianjiao,Liu Wei,Chen Naishi,et al.Distributed optimal dispatching of active distribution network based on consensus algorithm[J].Proceedings of the CSEE,2017,37(6):1579-1590(in Chinese).
• [6] The G A C. GridWise transactive energy framework version1.0[EB/OL].(2015-01-21).http://www.gridwiseac.org/pdfs/te_framework_report_pnnl-22946.pdf.
• [7]胡俊杰，王坤宇，艾欣，等．交互能源：实现电力能源系统平衡的有效机制[J]．中国电机工程学报，2019,39(4):953-966.Hu Junjie,Wang Kunyu,Ai Xin,et al.Transactive energy:an effective mechanism for balancing electric energy system[J].Proceedings of the CSEE,2019,39(4):953-966(in Chinese).
• [8] Qiu J,Zhao J,Yang H,et al.Optimal scheduling for prosumers in coupled transactive power and gas systems[J].IEEE Transactions on Power Systems,2018,33(2):1970-1980.
• [9] Renani Y K,Ehsan M,Shahidehpour M.Optimal transactive market operations with distribution system operators[J].IEEE Transactions on Smart Grid,2018,9(6):6692-6701.
• [10]马丽，刘念，张建华，等．基于主从博弈策略的社区能源互联网分布式能量管理[J]．电网技术，2016,40(12):3655-3661.Ma Li, Liu Nian, Zhang Jianhua, et al. Distributed energy management of community energy internet based on leader-followers game[J].Power System Technology,2016,40(12):3655-3661(in Chinese).
• [11]胡俊杰，李阳，吴界辰，等．基于配网节点电价的产消者日前优化调度[J]．电网技术，2019,43(8):2770-2780.Hu Junjie,Li Yang,Wu Jiechen,et al.A day-ahead optimization scheduling method for prosumer based on iterative distribution locational marginal price[J].Power System Technology,2019,43(8):2770-2780(in Chinese).
• [12]王皓，艾芊，吴俊宏，等．基于交替方向乘子法的微电网群双层分布式调度方法[J]．电网技术，2018,42(6):1718-1727.Wang Hao,Ai Qian,Wu Junhong,et al.Bi-level distributed optimization for microgrid clusters based on alternating direction method of multipliers[J].Power System Technology,2018,42(6):1718-1727(in Chinese).
• [13]吴界辰，艾欣，胡俊杰，等．面向智能园区多产消者能量管理的对等模型(P2P)建模与优化运行[J]．电网技术，2020,44(1):52-61.Wu Jiechen,Ai Xin,Hu Junjie,et al.Peer-to-peer modeling and optimal operation for prosumer energy management in intelligent community[J].Power System Technology,2020,44(1):52-61(in Chinese).
• [14] Morstyn T,McCulloch M D.Multiclass Energy management for peer-to-peer energy trading driven by prosumer preferences[J].IEEE Transactions on Power Systems,2019,34(5):4005-4014.
• [15] Sorin E,Bobo L,Pinson P.Consensus-based approach to peer-to-peer electricity markets with product differentiation[J].IEEE Transactions on Power Systems,2019,34(2):994-1004.
• [16] Li J,Zhang C,Xu Z,et al.Distributed transactive energy trading framework in distribution networks[J].IEEE Transactions on Power Systems,2019,33(6):7215-7227.
• [17] Nizami M S H,Hossain M J,Amin B M R,et al.Transactive energy trading of residential prosumers using battery energy storage systems[C]//2019 IEEE Milan PowerTech.Milan,Italy:IEEE,2019:1-6.
• [18] Tang C,Xu J,Sun Y,et al.Look-ahead economic dispatch with adjustable confidence interval based on a truncated versatile distribution model for wind power[J].IEEE Transactions on Power Systems,2018,33(2):1755-1767.
• [19]唐程辉，张凡，张宁，等．考虑可再生能源随机性和需求响应的电力系统日前经济调度[J]．电力系统自动化，2019,43(15):18-25.Tang Chenghui,Zhang fan,Zhang Ning,et al.Day-ahead economic dispatch of power system considering renewable power uncertainty and demand response[J].Automation of Electric Power Systems,2019,43(15):18-25(in Chinese)
• [20]刘一兵，吴文传，张伯明，等．基于混合整数二阶锥规划的主动配电网有功–无功协调多时段优化运行[J]．中国电机工程学报，2014,34(16):2575-2583.Liu Yibing,Wu Wenchuan,Zhang Boming,et al.A mixed integer second-order cone programming based active and reactive power coordinated multi-period optimization for active distribution network[J].Proceedings of the CSEE,2014,34(16):2575-2583(in Chinese)
• [21] Ratnam E L,Weller S R,Kellett C M,et al.Residential load and rooftop PV generation:an Australian distribution network dataset[J].International Journal of Sustainable Energy,2015:1-20.