多能互补分布式能源系统容量配置和优化运行研究现状

崔琼; 黄磊; 舒杰; 王浩; 吴昌宏

doi:10.3969/j.issn.2095-560X.2019.03.009

新能源进展 >

2019 , Vol. 7 >Issue 3: 263 - 270

DOI: https://doi.org/10.3969/j.issn.2095-560X.2019.03.009

多能互补分布式能源系统容量配置和优化运行研究现状

崔琼 ,
黄磊 ,
舒杰 ,
王浩 ,
吴昌宏

展开

1. 中国科学院广州能源研究所,广州 510640;
2. 中国科学院可再生能源重点实验室,广州 510640;
3. 中国科学院大学,北京 100049

崔琼（1982-）,女,硕士,助理研究员,主要从事分布式能源系统优化运行研究。舒杰（1969-）,男,博士,研究员,主要从事可再生能源及微电网技术研究。

收稿日期: 2018-10-14

修回日期: 2019-03-04

网络出版日期: 2019-06-29

基金资助

国家重点研发计划项目（2016YFB0901405）; 海南省重点研发计划项目（ZDYF2018003）

收起

Research Status of Capacity Configuration and Optimal Operation for Multi-Energy Complementary Distributed Energy System

CUI Qiong ,
HUANG Lei ,
SHU Jie ,
WANG Hao ,
WU Chang-hong

Expand

1. Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China;
2. CAS Key Laboratory of Renewable Energy, Guangzhou 510640, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2018-10-14

Revised date: 2019-03-04

Online published: 2019-06-29

Fold

摘要

多能互补分布式能源系统作为能源互联网的重要物理载体,是推动能源可持续发展的重要手段。本文综述了能互补分布式能源系统与能源互联网之间的关系。基于分布式能源系统国内外发展现状,重点围绕多能互补分布式能源系统容量配置与优化运行的相关研究内容进行全面梳理,阐明了其研究现状,并指出其未来的研究趋势。

关键词： 多能互补分布式能源系统; 容量配置; 优化运行

本文引用格式

崔琼 , 黄磊 , 舒杰 , 王浩 , 吴昌宏 . 多能互补分布式能源系统容量配置和优化运行研究现状[J]. 新能源进展, 2019 , 7(3) : 263 -270 . DOI: 10.3969/j.issn.2095-560X.2019.03.009

Abstract

As an important physical carrier of energy internet, multi-energy complementary distributed energy system is an important means to promote the sustainable development of energy. In this paper, the relationship between multi-energy complementary distributed energy system and energy Internet was reviewed. Based on the current development state of distributed energy systems, the research status and future development trend of capacity configuration and optimal operation of multi-energy complementary distributed energy system were particularly clarified.

Key words： multi-energy complementary distributed energy system; capacity configuration; optimal operation

参考文献

[1] 冯琳清, 张延迟, 赵晨, 等. 能源互联网研究综述[J]. 电源世界, 2017(5): 26-29.
[2] 吴利兰, 荆朝霞, 吴青华, 等. 基于Stackelberg博弈模型的综合能源系统均衡交互策略[J]. 电力系统自动化, 2018, 42(4): 142-150, 207. DOI: 10.7500/AEPS20170914011.
[3] 余晓丹, 徐宪东, 陈硕翼, 等. 综合能源系统与能源互联网简述[J]. 电工技术学报, 2016, 31(1): 1-13. DOI: 10.3969/j.issn.1000-6753.2016.01.001.
[4] 周孝信. 构建新一代能源系统[J]. 电气时代, 2017(1): 45-47.
[5] 王伟亮, 王丹, 贾宏杰, 等. 能源互联网背景下的典型区域综合能源系统稳态分析研究综述[J]. 中国电机工程学报, 2016, 36(12): 3292-3305. DOI: 10.13334/j.0258- 8013.pcsee.152858.
[6] 李立浧, 张勇军, 徐敏. 我国能源系统形态演变及分布式能源发展[J]. 分布式能源, 2017, 2(1): 1-9. DOI: 10.16513/j.cnki.10-1427/tk.2017.01.001.
[7] 卢胤龙, 韩明新, 任洪波, 等. 多能互补分布式能源系统优化设计研究进展[J]. 上海电力学院学报, 2018, 34(3): 229-235. DOI: 10.3969/j.issn.1006-4729.2018.03.005.
[8] 钟迪, 李启明, 周贤, 等. 多能互补能源综合利用关键技术研究现状及发展趋势[J]. 热力发电, 2018, 47(2): 1-5, 55. DOI: 10.19666/j.rlfd.201706049.
[9] 彭克, 张聪, 徐丙垠, 等. 多能协同综合能源系统示范工程现状与展望[J]. 电力自动化设备, 2017, 37(6): 3-10. DOI: 10.16081/j.issn.1006-6047.2017.06.001.
[10] 陈娟. 能源互联网背景下的区域分布式能源系统规划研究[D]. 北京: 华北电力大学(北京), 2017.
[11] 郭井宽, 孙华. 分布式能源系统的发展动态[J]. 装备机械, 2016(1): 70-74.
[12] CHO H, SMITH A D, MAGO P.Combined cooling, heating and power: a review of performance improvement and optimization[J]. Applied energy, 2014, 136: 168-185. DOI: 10.1016/j.apenergy.2014.08.107.
[13] 李博彤. 分布式能源集成供能系统研究[D]. 北京: 华北电力大学(北京), 2017.
[14] 邱留良. 基于TRNSYS的分布式能源系统运行模拟及优化分析[D]. 上海: 上海电力学院, 2017.
[15] 宋英华, 张敏吉, 肖钢. 分布式能源综论[M]. 武汉: 武汉理工大学出版社, 2011.
[16] 任洪波, 邱留良, 吴琼, 等. 分布式能源系统优化与设计综述[J]. 中国电力, 2017, 50(7): 49-55. DOI: 10.11930/j.issn.1004-9649.2017.07.049.07.
[17] WEBER C, SHAH N.Optimisation based design of a district energy system for an eco-town in the united kingdom[J]. Energy, 2011, 36(2): 1292-1308. DOI: 10.1016/j.energy.2010.11.014.
[18] OMU A, CHOUDHARY R, BOIES A.Distributed energy resource system optimisation using mixed integer linear programming[J]. Energy policy, 2013, 61: 249-266. DOI: 10.1016/j.enpol.2013.05.009.
[19] 任洪波, 杨健, 班银银, 等. 分布式能源互联网的探索与展望[J]. 中国能源, 2015, 37(3): 38-41, 17. DOI: 10.3969/j.issn.1003-2355.2015.03.008.
[20] 蔡博, 康书硕, 李洪强, 等. 基于天然气基分布式能源系统智能建筑能源物联网研究[J]. 工程热物理学报, 2012, 33(12): 2047-2051.
[21] DESHMUKH M K, DESHMUKH S S.Modeling of hybrid renewable energy systems[J]. Renewable and sustainable energy reviews, 2008, 12(1): 235-249. DOI: 10.1016/j.rser.2006.07.011.
[22] WANG L, YEH T H, LEE W J, et al.Benefit evaluation of wind turbine generators in wind farms using capacity-factor analysis and economic-cost methods[J]. IEEE transactions on power systems, 2009, 24(2): 692-704. DOI: 10.1109/TPWRS.2009.2016519.
[23] ZHOU W, LOU C Z, LI Z S, et al.Current status of research on optimum sizing of stand-alone hybrid solar- wind power generation systems[J]. Applied energy, 2010, 87(2): 380-389. DOI: 10.1016/j.apenergy.2009.08.012.
[24] YANG H X, ZHOU W, LU L, et al.Optimal sizing method for stand-alone hybrid solar-wind system with LPSP technology by using genetic algorithm[J]. Solar energy, 2008, 82(4): 354-367. DOI: 10.1016/j.solener. 2007.08.005.
[25] YANG H X, LU L, ZHOU W.A novel optimization sizing model for hybrid solar-wind power generation system[J]. Solar energy, 2007, 81(1): 76-84. DOI: 10.1016/j.solener.2006.06.010.
[26] SHIRVANI M, MEMARIPOUR A, ABDOLLAHI M, et al.Calculation of generation system reliability index: expected energy not served[J]. Life science journal, 2012, 9(4): 344.
[27] NUGRAHA P Y, WIDYOTRIATMO A, LEKSONO E.Optimization of a grid-tied microgrid configuration using dual storage systems[C]//Proceedings of the 15th International Conference on Control, Automation and Systems. Busan, South Korea: IEEE, 2015. DOI: 10.1109/ICCAS.2015.7364896.
[28] PELET X, FAVRAT D, LEYLAND G.Multiobjective optimisation of integrated energy systems for remote communities considering economics and CO₂ emissions[J]. International journal of thermal sciences, 2005, 44(12): 1180-1189. DOI: 10.1016/j.ijthermalsci.2005.09.006.
[29] BOROWY B S, SALAMEH Z M.Methodology for optimally sizing the combination of a battery bank and PV array in a wind/PV hybrid system[J]. IEEE transactions on energy conversion, 1996, 11(2): 367-375. DOI: 10.1109/60.507648.
[30] 荆有印, 白鹤, 张建良. 太阳能冷热电联供系统的多目标优化设计与运行策略分析[J]. 中国电机工程学报, 2012, 32(20): 82-87.
[31] JAYASEKARA S, HALGAMUGE S K, ATTALAGE R A, et al.Optimum sizing and tracking of combined cooling heating and power systems for bulk energy consumers[J]. Applied energy, 2014, 118: 124-134. DOI: 10.1016/j.apenergy.2013.12.040.
[32] 王栋. 分布式能源系统现状分析与探讨[J]. 上海节能, 2016(12): 653-656. DOI: 10.13770/j.cnki.issn2095-705x. 2016.12.003.
[33] 魏大钧. 小型冷热电联供系统多目标优化设计与能量管理策略研究[D]. 济南: 山东大学, 2016.
[34] 侯建朝, 胡群丰, 谭忠富. 计及需求响应的风电-电动汽车协同调度多目标优化模型[J]. 电力自动化设备, 2016, 36(7): 22-27. DOI: 10.16081/j.issn.1006-6047.2016. 07.004.
[35] JALALZADEH-AZAR A A. A comparison of electrical- and thermal-load-following CHP systems[J]. ASHRAE transactions, 2004, 110(2): 85-94.
[36] WANG J J, ZHANG C F, JING Y Y.Multi-criteria analysis of combined cooling, heating and power systems in different climate zones in China[J]. Applied energy, 2010, 87(4): 1247-1259. DOI: 10.1016/j.apenergy.2009. 06.027.
[37] FANG F, WANG Q H, SHI Y.A novel optimal operational strategy for the CCHP system based on two operating modes[J]. IEEE transactions on power systems, 2012, 27(2): 1032-1041. DOI: 10.1109/TPWRS.2011.2175490.
[38] KAVVADIAS K C, MAROULIS Z B.Multi-objective optimization of a trigeneration plant[J]. Energy policy, 2010, 38(2): 945-954. DOI: 10.1016/j.enpol.2009.10.046.
[39] 周晓倩, 余志文, 艾芊, 等. 含冷热电联供的微网优化调度策略综述[J]. 电力自动化设备, 2017, 37(6): 26-33. DOI: 10.16081/j.issn.1006-6047.2017.06.004.
[40] 骆钊. 冷热电联供型微网能量优化管理研究[D]. 南京: 东南大学, 2017.
[41] 许东. 微型燃气轮机冷电联供系统能量优化与管理[D]. 天津: 天津大学, 2010.
[42] JU L W, TAN Z F, LI H H, et al.Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China[J]. Energy, 2016, 111: 322-340. DOI: 10.1016/j.energy.2016.05.085.
[43] 孙作潇. 冷热电联供型微电网多目标动态优化调度[D]. 杭州: 杭州电子科技大学, 2017.
[44] LIU X.Optimization of a combined heat and power system with wind turbines[J]. International journal of electrical power & energy systems, 2012, 43(1): 1421-1426. DOI: 10.1016/j.ijepes.2012.07.022.
[45] HU M Q, CHO H.A probability constrained multi- objective optimization model for CCHP system operation decision support[J]. Applied energy, 2014, 116: 230-242. DOI: 10.1016/j.apenergy.2013.11.065.
[46] LIU M X, SHI Y, FANG F.A new operation strategy for CCHP systems with hybrid chillers[J]. Applied energy, 2012, 95: 164-173. DOI: 10.1016/j.apenergy.2012.02.035.
[47] WU J Y, WANG J L, LI S.Multi-objective optimal operation strategy study of micro-CCHP system[J]. Energy, 2012, 48(1): 472-483. DOI: 10.1016/j.energy.2012.10.013.
[48] FACCI A L, ANDREASSI L, UBERTINI S.Optimization of CHCP (combined heat power and cooling) systems operation strategy using dynamic programming[J]. Energy, 2014, 66: 387-400. DOI: 10.1016/j.energy.2013.12.069.
[49] BYUN J, HONG I, KANG B, et al.A smart energy distribution and management system for renewable energy distribution and context-aware services based on user patterns and load forecasting[J]. IEEE transactions on consumer electronics, 2011, 57(2): 436-444. DOI: 10.1109/TCE.2011.5955177.
[50] OLIVARES D E, MEHRIZI-SANI A, ETEMADI A H, et al.Trends in microgrid control[J]. IEEE transactions on smart grid, 2014, 5(4): 1905-1919. DOI: 10.1109/TSG. 2013.2295514.
[51] KANG L G, YANG J H, AN Q S, et al.Effects of load following operational strategy on CCHP system with an auxiliary ground source heat pump considering carbon tax and electricity feed in tariff[J]. Applied energy, 2016, 194(5): 454-466. DOI: 10.1016/j.apenergy.2016.07.017.
[52] BISCHI A, TACCARI L, MARTELLI E, et al.A detailed MILP optimization model for combined cooling, heat and power system operation planning[J]. Energy, 2014, 74: 12-26. DOI: 10.1016/j.energy.2014.02.042.
[53] 魏大钧, 张承慧, 孙波. 计及变负荷特性的小型冷热电联供系统经济优化运行研究[J]. 电网技术, 2015, 39(11): 3240-3246. DOI: 10.13335/j.1000-3673.pst.2015.11.034.
[54] 李正茂, 张峰, 梁军, 等. 计及附加机会收益的冷热电联供型微电网动态调度[J]. 电力系统自动化, 2015, 39(14): 8-15. DOI: 10.7500/AEPS20141109002.
[55] MORADI M H, HAJINAZARI M, JAMASB S, et al.An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming[J]. Energy, 2013, 49: 86-101. DOI: 10.1016/j.energy.2012.10.005.

Options

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献