期刊文献+

管制市场中激励分布式能源发电的电能虚拟存储政策(英文) 被引量:6

Electrical Power Virtual Storage Policy for Stimulating Distributed Generation in Regulated Markets
下载PDF
导出
摘要 可再生、清洁能源分布式发电(distributed generations,DGs),是能源、环境可持续发展的重要途径之一。在管制的电力市场中,用户自建分布式能源会影响自然垄断的电网企业的利益。中国国家电网公司已经开放DG并网,为此,需对DG并网后的计量、计费、管理政策等进行深入研究,提出一种适应管制电力市场的电能虚拟存储政策模型来推行电能虚拟存储政策。该模型应能确保用户自建分布式能源对电力企业利益的影响在其可接受范围之内,而且能够最大程度激励用户自建分布式能源。然后通过对该政策模型的参数优化确定了最优模型参数和所有用户自建分布式能源的容量。为促进该项政策的实施,在不同的阶段,通过提高允许的政策参数,逐步提升对用户自建分布式能源的激励力度。最后通过算例验证了所提模型的适应性和有效性。 The application of renewable and clean distributed generations(DGs) is one of the important measures taken to solve the problem of energy shortage and environment pollution. In regulated electricity market, the integration of consumers' self-built DGs may harm the interests of the power utilities under present policies. The State Grid Corporation of China has claimed that it will try its best to accommodate the integration of DGs. In order to realize the objective, further research about measurement, accounting and management policy is still needed. In this paper, electrical power virtual storage policy model was proposed to promote the policy in regulated electricity market. The model can ensure the influence resulting from self-built DGs is within the agreed scope and encourage consumers to build DGs as more as possible. Then the optimal policy parameters and the total capacity of all the consumers' self-built DGs were determined by parameter optimization in the policy model. To implement the policies, the incentive strength on consumers' self-built DGs is promoted by improving the allowed policy parameters at different stages. The case study shows that the proposed model is adaptable and effective.
出处 《中国电机工程学报》 EI CSCD 北大核心 2014年第19期3141-3147,共7页 Proceedings of the CSEE
基金 The National High Technology Research and Development of China 863 Program(2011AA050203) The State Key Laboratory Open Topics of Control and Simulation of Power System and Generation Equipment(SKLD11KZ07)~~
关键词 分布式发电 电力政策 政策参数 电力企业 管制电力市场 distributed generations(DGs) power policy policy parameters power utility regulated electricity market
  • 相关文献

参考文献23

  • 1Marei M I,EI-saadany E F,Salama M M A.A novel control algorithm for the DG interface to mitigate power quality problems[J].IEEE Transactions on Power Delivery,2004,19(3):1384-1392.
  • 2Katsaprakakis D A,Christakis D G,Zervos A,et al.A power-quality measure[J].IEEE Transactions on Power Delivery,2008,23(2):553-561.
  • 3裴玮,盛鹍,孔力,齐智平.分布式电源对配网供电电压质量的影响与改善[J].中国电机工程学报,2008,28(13):152-157. 被引量:293
  • 4Bae I S,Kim J O.Reliability evaluation of distributed generation based on operation mode[J].IEEE Transactions on Power Systems,2007,22(2):785-790.
  • 5Zhu D,Broadwater R P,Tam K S,et al.Impact of DG placement on reliability and efficiency with time-varying loads[J].IEEE Transactions on Power Systems,2006,21(1):419-427.
  • 6Chiradeja P,Ramakumar R.An approach to quantify the technical benefits of distributed generation[J].IEEE Transactions on Energy Conversion,2004,19(4):764-773.
  • 7Abu-Mouti F S,El-Hawary M E.Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm[J].IEEE Transactions on Power Delivery,2011,6(4):2090-2101.
  • 8张节潭,程浩忠,姚良忠,王淳.分布式风电源选址定容规划研究[J].中国电机工程学报,2009,29(16):1-7. 被引量:127
  • 9Brahma S M,Girgis A A.Development of adaptive protection scheme for distribution systems with high penetration of distributed generation[J].IEEE Transactions on Power Delivery,2004,19(1):56-63.
  • 10Wang C,Nehrir M H.Analytical approaches for optimal placement of distributed generation sources in power systems[J].IEEE Transactions on Power Systems,2004,19(4):2068-2076.

二级参考文献54

共引文献494

同被引文献95

  • 1王志群,朱守真,周双喜,黄仁乐,王连贵.分布式发电对配电网电压分布的影响[J].电力系统自动化,2004,28(16):56-60. 被引量:417
  • 2汪海宁,苏建徽,张国荣,茆美琴,丁明.光伏并网发电及无功补偿的统一控制[J].电工技术学报,2005,20(9):114-118. 被引量:109
  • 3刘振亚. 智能电网与第三次工业革命[N]. 科技日报, 2013-12-05.
  • 4Ramsay C, Pudjianto D, Strbac G. Microgrids and virtual power plants- concept to support the integration of distributed energy resources[C]//Proceedings of the Institution of Mechanical Engineers Part A: Journal of Power and Energy, 2008.
  • 5Palensky Peter, Dietrich Dietmar. Demand side management: Demand response, intelligent energy systems, and smart loads[J]. IEEE Transactions onIndustrial lnformatics, 2011, 7(3): 381-8.
  • 6Sharma I, Bhattacharya K, Canizares C. Smart distribution system operations with price-responsive and controllable loads[J]. IEEE Transactions on Smart Grid, 6(2): 795-807.
  • 7Pudjianto D R C, Strbac G. Virtual power plant and system integration of distributed energy resources[J], lET Renewable Power Generation, 2007, 1(1): 10-6.
  • 8Asmus P. Microgrids, virtual power plants and our distributed energy future[J]. The Electricity Journal, 2010, 23(10)- 72-82.
  • 9Sheng Wanxing, Zhao Shanshan, Song Xiaohui, et al. Maximum penetration level of distributed generation in consideration of voltage fluctuations based on multi-resolution model[J]. SET Generation, Transmission and Distribution, 2014.
  • 10Massucco Stefano, Pitto Andrea, Silvestro Federico. A gas turbine model for studies on distributed generation penetration into distribution networks[J] . IEEE Transactions onPowerSystems, 2011, 26(3). 992-999.

引证文献6

二级引证文献93

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部