摘要
随着我国经济持续快速稳定发展,我国能源消耗总量也在大幅增加。目前,传统的粗放式经济发展模式正面临资源过度消耗的瓶颈,能源产业面临着能源利用效率低、污染严重、结构不合理等问题。因此,我国政府提出了“节约优先、立足国内、多元发展、保护环境、科技创新、深化改革、国际合作、改善民生”的能源发展战略。而分布式供能系统作为先进的供能系统是解决上述问题以及促进能源结构优化、能源供应多元发展的有效措施之一,它符合能源梯级利用理论,是以大电网、大电厂为代表的集中式供能方式的重要补充。此外,储能系统是分布式供能系统的重要组成部分,作为负荷平衡设备和备用电源为分布式供能系统能源供应的安全性和可靠性提供了重要保障。因此,为更好地保持在能源领域的核心竞争力,我国必须加强分布式供能领域相关方向的核心技术研究,以便提高我国整体的能源利用水平,并促进我国能源产业结构的优化调整。
办公楼宇分布式供能系统是分布式供能系统的重要组成部分,本文以楼宇电力负荷数据为基础并将储能技术引入办公楼宇分布式供能系统,以便提高系统整体的电能输出稳定性、调度灵活性,同时,解决其系统故障率高等问题。本文主要研究适用于分布式供能系统的储能系统,具体的研究内容包括：
(1)基于研究所办公楼的电力负荷数据、反向传播(Back Propagation, BP)神经网络算法和储能系统规模计算模型的储能系统需求研究表明：BP神经网络技术适用于带有储能系统的分布式供能系统的短期电力负荷预测,预测精度达到87.5%；通过设定调峰比例以及储能系统的性能参数,使用储能系统规模需求计算模型可以得到用户的电能需求和储能需求,该方法对于确定适用于分布式供能系统的合理储能需求具有指导意义。
(2)根据储能系统技术设计方案确定的系统结构原理,通过对储能系统各部件的数学建模以及PID控制、常规模糊控制和变论域模糊PID控制等控制技术的比较分析,利用Matlab-Simulink软件的函数自编程功能实现的储能系统恒功率输出的自动控制仿真研究表明：变论域模糊PID控制相比较于常规PID控制技术的调节时间更短并且没有超调量,有利于系统实现稳定、快速输出的预期响应要求。
(3)设计并完成了液压气压结合的储能试验平台的搭建,并通过最高压力9～18MPa、转速100～800r/min的不同组合工况下系统循环运行的试验研究表明：当储能转速恒定为100r/min,释能转速为400r/min时系统的循环效率(电-电)取得最优值；同时,当储/释能转速分别恒定为100r/min和200r/min,系统循环效率在系统最高压力9～12MPa时随着压力的升高而升高,而在12～18MPa时随着压力的升高而上下波动,最大值为50.72%,最小值为48.98%,平均值在50%左右；液压马达/泵的容积效率随着转速以及蓄能器最高压力的变化而变化是影响系统循环效率的重要因素之一。
(4)建立了较完善的储能系统经济及社会效益评估模型,并将其应用于液压气压结合的储能系统可以得到：综合考虑当前经济状况指标、未来亟需的储能产业政策以及其它的模型参数设置,通过计算在不同起始投资补贴比例、辅助效益补贴模式以及调峰比例的情况下的临界经济性评估指标,从而得到系统投资盈利的临界每千瓦成本(功率成本)和每千瓦时成本(容量成本),可以为储能系统投资的决策提供方法指导和数据参考；而量化评估储能系统的节能减排效益很好地体现了给社会带来的定量节能环保价值,对于准确分析储能系统的社会效益具有重要的参考价值。
Along with the sustained, rapid and steady development of national economy, energy consumption in China also increases significantly. Recently, traditional extensive economic development mode is facing bottleneck problems about energy consumption, in details, i.e., low energy use efficiency, overmany pollutant emissions and greenhouse gases emissions, unreasonable energy structure, etc. Therefore, the government has proposed comprehensive energy policies, the basic contents of which are "giving priority to conservation, relying on domestic resources, encouraging diverse development, protecting the environment, promoting scientific and technologic innovation, deepening reform, expanding international cooperation, and improving the people's livelihood". Actually, as one of the advanced energy supply systems, distributed energy supply system (DESS) is one of the available solutions to the abovementioned problems, as well as, is the critical reinforcement of the large-scale one because of its graded use of energy. Additionally, energy storage subsystem (ESS) is the key part as the load balance equipment and backup power resource. Also, ESS is necessary for the safety and reliability of DESS operation. Hence, more research on those related technologies will be crucial for maintaining national core competitiveness, improvement of energy utilization efficiency, and the reformation of energy structure.
Energy storage technology (EES) is introduced in building distributed energy system (BDES) as a key part of distributed energy system. EES should be a resolution of the problems such as electricity generation instability, high system failure rate. The detailed contents are as follows:
(1) Research based on the electricity load data of some office building, back propagation (BP) artificial neural networks (ANN) and energy storage size computation model show that:ANN can work efficiently for the case of DESS with EES, in another word,87.5%of predicted load data is within the acceptable relative error; electricity demand and ESS size can be determined based the ESS size determination model with the given peak load shifting and ESS technology characters. They are of certain directive significance to rational size determination and investment of DESS.
(2)Simulation modeling by Matlab-Simulink is on the basis of system mathematical modeling of each part of HAES, as well as the theory analysis of PID control, conventional fuzzy control, and variable-universe fuzzy control. With the need of constant power output, simulation results in terms of the control characters reveal that variable-universe fuzzy control with smaller over shoot and shorter adjusting time is obviously better than PID control.
(3)According to the different cases for the pressure from9MPa to18MPa and the hydraulic motor/pump rotation speed beween100revolutions per minute (r/min) and800r/min after the Hydraulic-air energy storage (HAES) experiment test platform is built, the results show that the system cycle efficiency gets the best when the discharge speed is400r/min and100r/min for the charging. When the speeds for charging and discharging are100r/min and200r/min, respectively, the HAES system cycle efficiency increases with the pressure additions for the pressure from9MPa to12MPa; and the one fluctuates between50.72%and48.98%for the pressure from12MPa to18MPa; also, volumetric efficiency varying with hydraulic motor/pump speed and the accumulator pressure is the key factor of HAES system cycle efficiency.
(4)Based on the economic and social benefits analysis model, the analysis results for HAES illustrate that the critical cost per kW or kWh are of important directive significance to rational HAES investment, and it is done through the critical cost computation along with the critical economic indexes considering the factors of different subsidization rates of grid assistant service and initial investment, different peak load shifting, and current or future economic conditions; the quantitative analysis of the energy saving and gas emission reductions benefits show the underlying benefits in environment protection of HAES, and it can be a reference method for other cases studying in energy saving and gas emission reductions.
引文
[1]国家统计局.(2011)2011年中国统计年鉴[EB/OL].http://www.stats.gov.cn/tjsj /ndsj/2011/indexch.htm.
[2]金红光,林汝谋.能的综合梯级利用与燃气轮机总能系统[M].北京：科学出版社,2008.
[3]中华人民共和国国务院新闻办公室.(2012)中国能源政策[EB/OL].http://www. gov.cn/zwgk/2012-10/24/content_2250617.htm.
[4]国家发展改革委.能源发展“十一五”规划[R].北京：国家发展改革委,2007.
[5]国家能源局.国家能源科技“十二五”规划[R].北京：国家能源局,2011.
[6]苏飞,张平宇.中国区域能源安全攻击脆弱性分析[J].中国人口·资源和环境,2008,18(6)：94-99.
[7]中国电机工程学会编辑部.(2012)大力推进区域能源建设促进节能减排[EB/OL]. http://www.csee.org.cn/tplt001.aspx?PageId=e9ee7a95-621c-4620-85 53-4207956c6bdf&ArticleId=4402bf47-0bb0-4790-bba5-01042f367603.
[8]随军,闫月君.(2012)多能源互补的分布式功能系统专题：战略需求[EB/OL].http://www.iet.cas.cn/hdzt/135zl/ghssdt/dny hu/201206/t20120628_3606405.ht ml.
[9]刘杨华,吴政球,涂有庆等.分布式发电及其并网技术综述[J].电网技术,2008,32(15)：71-76.
[10]王成山,李鹏.分布式发电、微网与智能配电网的发展与挑战[J].电力系统自动化,2010,34(2)：10-15.
[11]王成山,王守相.分布式发电功能系统若干问题研究[J].电力系统自动化,2008,32(20)：1-5.
[12]郭烈锦,赵亮.基于可再生能源的分布式多目标功能系统(一)[J].西安交通大学学报,2002,36(5)：446-451.
[13]郭烈锦,赵亮.基于可再生能源的分布式多目标功能系统(二)[J].西安交通大学学报,2002,36(5)：446-451.
[14]谭靖,李国杰,唐志伟.基于压缩空气储能的风电场功率调节剂效益分析[J].电力系统自动化,2011,35(8)：33-37.
[15]丁明,张颖媛,茆美琴等.包含钠硫电池储能的微网系统经济运行优化[J].中国电机工程学报,2011,31(4)：7-14.
[16]胡国珍,段善旭,蔡涛等.基于液流电池储能的光伏发电系统容量配置及成本分析[J].电工技术学报,2012,27(5)：260-267.
[17]雷金勇,谢俊,甘德强.分布式发电供能系统能量优化及节能减排效益分析[J].电力系统自动化,2009,33(23)：29-36.
[18]徐林,阮新波,张步涵等.风光蓄互补发电系统容量的改进优化配置方法[J].中国电机工程学报,2012,32(25)：18-29.
[19]H. S. Chen, N. Tang, W. Yang, et al. Progress in electrical energy storage system: a critical review[J]. Progress in Natural Science.2009,19(3):291-312.
[20]严晓辉,徐玉杰,纪律,陈海生,谭春青.我国大规模储能技术发展预测及分析[J].中国电力,46(8)：22-29.
[21]兴建机械有限公司水轮机厂.(2014)3-75kW自动控制微型水轮发电机组[EB/OL]. http://www.miniwaterpower.com/china/cpzs_E03.htm.
[22]中国科学院工程热物理研究所.微型抽水储能系统：中国,CN201020632300.9[P].2011-06-01.
[23]Y. L. Li, X. Wang, D. C. Li, et al. A trigeneration system based on compressed air and thermal energy storage[J]. Applied Energy,2012,99(c):316-323.
[24]张新敬.压缩空气储能系统若干问题研究[D].北京：中国科学院研究生院,2011.
[25]刘文毅.压缩空气蓄能电站热力性能仿真分析[D].北京：华北电力大学,2008.
[26]S. M. Schoenung, W. V. Hassenzahal. Long-vs. Short-Term Energy Storage Technologies Analysis[R]. California:Sandia National Laboratories,2003.
[27]陈海生,徐玉杰,严晓辉等.北京大规模储能技术路径及产业化发展趋势研究报告[R].北京：中国科学院工程热物理研究所,2012.
[28]S. Zhang. (2009) Prudent energy announces installation of a MW class VBR energy storage system for CEPRI[EB/OL]. http://www.pdenergy.com/press_030 211_cepri.html.
[29]赵晏强,李金坡.基于中国专利的锂电池发展趋势分析[J].情报杂志,2012,31(1)：35-41.
[30]冯代伟.串联型液压混合动力汽车的能量管理策略研究[D].成都：电子科技大学,2006.
[31]Green Car Congress. (2004) Eaton and peterbilt to produce hydralic hybrids[EB/OL]. http://www.greencarcongress.com/2004/10/eaton_and_peter.ht ml.
[32]United States Environment Protection Agency. Hydraulic techology:a proven approach[P].2004, EPA420-F-04-24.
[33]Altair Product Design. (2011) The bus solutions story:envolution of the LCO-140H hybrid hydraulic bus[EB/OL]. http://www.altairbussolutions.com.
[34]J. H. Lumkes J. R. Design, simulation, and testing of an energy storage hydraulic vehicle transmission and controller[D]. Madison, USA. University of Wisconsin-Madison,1997.
[35]C. Lin, Z, Filipi, L. Louca, et al. Modelling and control of a medium duty hybrid electric truck[J]. Heavy Vehicle System, International Journal of Vehicle Design, 2004,11(3/4):349-370.
[36]肖华.上海交大神舟液压混合动力系统-城市公交的新选择[J].城市车辆,2007(5)：24.
[37]姜继海,韩永刚,王德海,等.二次调节静液驱动系统的智能PID控制[J].哈尔滨工业大学学报,1998(1)：45-48.
[38]曾洋.静液驱动二次调节技术的研究[D].广州：华南理工大学,2002.
[39]韩文.新型电控液驱车关键技术研究-驱动／制动系统[D].南京：南京理工大学,2005.
[40]吴光强,王会义.车辆静液驱动与智能控制系统[M].上海：上海科学技术文献出版社,1998.
[41]陈华志,苑仕华.城市用车辆制动能量回收的液压系统设计[J].液压与启动,2003(4)：1-3.
[42]赵金祥.液压节能汽车制动能量回收及动态调节控制策略的研究[D].长春： 吉林大学,2009.
[43]L. Pe'rez-Lombard, J. Ortiz, Christine Pout. A review on building energy consumption information[J]. Energy and Building,2008,40(3):394-398.
[44]K. G Xie, C. Y. Li, J. Q. Zhou. Research of the combination forecasting model for load based on artificial neural networks[J]. Proceedings of the CSEE,2002, 22(7):85-89.
[45]S. L. Lei, C. X. Sun, Q. Zhou, X. X. Zhang, Q. Y. Cheng. Short-term load forecasting method based on RBF neural network and ANFIS system[J]. Proceedings of the CSEE,2005,25(22):78-82.
[46]Z. Y. Wang, C. X. Guo, Y. J. Cao. A method for short term load forecasting integrating fuzzy-rough set with artificial neural network[J]. Proceedings of the CSEE,25(19):7-11.
[47]李士勇.模糊控制·神经网络和智能控制论[M].黑龙江：哈尔滨工业大学出版社,2006.
[48]丁士圻,郭丽华.人工神经网络基础[M].黑龙江：哈尔滨工程大学出版社,2008.
[49]G Q. Zhang, B. E. Patuwo, Y. M. Hu. Forecasting with artificial neural networks: the state of the art[J]. International Journal of Forecasting,1998,14(1):35-62.
[50]H. S. Hippert, C. E. Pedreira, R. C. Souza. Neural networks for short-term load forecasting:a review and evaluation[J]. IEEE Transaction on Power System, 2001,16(1):44-55.
[51]B. Girard, Y. Girard, M. Mangeas, C. Muller. Neural modeling for time series:a statistical stepwise method for weight elimination[J]. IEEE Transactions on Neural Networks,1995,6(6):1355-1364.
[52]M. Cottrell, B. Girard, P. Rousset. Forecasting of curves using a Kohonen classification[J]. Journal of Forecasting,1998,17(5-6):429-439.
[53]P. F. Yan, C. C. Zhang. Artificial neural networks and simulated evolutionary computation(2nd version)[M]. Beijing:Tsinghua University Press,2005,11-139.
[54]A. S. Kalogirou. Applications of artificial neural networks in energy systems a review[J]. Energy Conversion & Management,2001,40(10):1073-1087.
[55]D. Strnivasan, C. A. Liew, S. C. Chang. A neural network short-term load forecaster[J]. Electric Power System Research,1994,28(3):227-234.
[56]K. L. Zhou, Y. H. Kang. Neural networks models and its simulation program with Matlab[M]. Beijing:Tsinghua Uinversity Press,2004.
[57]T. P. Vogl, J. K. Mangis, A. K. Rigler, et al. Accelerating the convergence of the backpropagation method[J]. Biological Cybernetics,1988,59(4-5):257-263.
[58]X. Wen, L. Zhou, D. L. Wang, X. Y. Xiong. Matlab neural network application design[M]. Beijing:Science Press,2000:207-243.
[59]Beijing Municipal Commission of Development and Reform. (2012) Notice on peak hours adjustment in Beijing [EB/OL]. http://www.bjpc.gov.cn/tztg/201106/ t822024.htm.
[60]C. Lv. Short-term load forecasting based on BP artificial neural networks[D]. Wuhan, China:Huazhong University of Science & Technology,2007.
[61]C. Venu, Y. Riffonneau, S. Bacha, et al. Battery storage system sizing in distribution feeders with distribution photovoltaic systems [C].2009 IEEE Bucharest Power Tech conference, June 28th-July 2nd, Bucharest, Romania.
[62]马舒朗.调峰调频公司在整个南网战略中扮演重要角色[N].南方电网报,2011-5-28(B1).
[63]梁宵,温兆银,刘宇.高性能锂硫电池材料研究进展[J].化学进展,2011,23(2/3)：520-526.
[64]K. C. Divya, J. Stergaard. Battery energy storage technology for power systems-an overview[J]. Electric Power System Research,2009,79(4):511-520.
[65]温兆银,俞国勤,顾中华等.中国钠硫电池技术的发展与现状概述[J].供用电,2010,27(6)：25-28.
[66]杨霖霖,廖文俊,苏青等.全钒液流电池技术发展现状[J].储能科学与技术,2013,2(2)：140-145.
[67]张华民,张宇,刘宗浩等.液流储能电池技术研究进展[J].化学进展,2009,21(11)：2333-2340.
[68]许抑曾.中国液压行业发展战略的新机遇新格局及新思维[J].液压气动与 密封,2012(3)：1-7.
[69]章宏甲,黄谊.液压传动[M].北京：机械工业出版社,1995.
[70]王瑞杰.蓄能器在液压工程中的应用[J].能源研究与利用,1995(5)：25-29.
[71]张路军,李继志,潘伟等.蓄能器类型及应用综述[J].机床与液压,2001(6)：5-7.
[72]中国机械设计大典编委会.中国机械设计大典(五)(M).北京：机械工业出版社,2001.
[73]赵琦.蓄能器及其工作回路的计算机辅助设计[D].河北：燕山大学,2000.
[74]Y. Shinichi, S. Hisashi, Y. Hirotugu. Study on an active accumlator. (Active control of high-frequency pulsation of flow rate in hydraulic systems)[J]. JSME International Journal Series B,39(1):119-124.
[75]邢科礼,葛思华,丁崇生,等.新型串联囊式蓄能器对油源动力脉动影响的影响的试验研究[J].机床与液压,1998(1)：39-41.
[76]徐绳武.轴向柱塞泵和马达的发展动向[J].液压气动与密封,2003(4)：10-15.
[77]N. D. Manring. The discharge flow ripple of axial piston swash-plate hydraostatic pump[J]. Journal of Tribology,2004(126):511-518.
[78]杨华勇,张斌,徐兵.轴向柱塞泵/马达技术的发展演变.机械工程学报,2008,44(10)：1-8.
[79]C. G Li, Z. X. Jiao. Thermal-hydraulic modeling and simulation of pistion pump[J]. Chinese Journal of Aeronautics,2006,19(4):354-358.
[80]马雅丽,黄志坚.蓄能器实用技术[M].北京：化学工业出版社,2007.
[81]李永林,徐浩军,曹克强,等.航空柱塞泵全工况效率分析及热力学建模[J].北京航空航天大学学报,2010,36(12)：1469-1472.
[82]H. H. Triet, A. K. Kyoung. Design and control of a closed-loop hydraulic energy-regenerative system[J]. Automation in construction,2012,22:444-458.
[83]K. E. Rydberg. Energy efficient hydraulic hybrid drives[C]. The 11th scandinavian international conference on fluid power, SICFP'09, June 2-4,2009, Sweden.
[84]J. O. Maloney. Perry's chemical engineers'handbook(8thediton)[M]. USA:the McGraw-Hill Companies, Inc,2008.
[85]A. Pourmovahed, N. H. Beachley, F. J. Fronczak. Modeling of a hydraulic energy regeneration system-part I:analytical treatment[J]. Journal of dynamic system, measurement, and control, Transactions of the ASME,1992,114: 155-159.
[86]A. Pourmovahed, N. H. Beachley, F. J. Fronczak. Modeling of a hydraulic energy regeneration system-part Ⅱ:experimental program[J]. Journal of dynamic system, measurement, and control, Transactions of the ASME,1992, 114:160-165.
[87]L. A. Drew. Simulation of a diesel-hydraulic series hybrid[D]. USA:the Faculty of California Polytechnic State University, San Luis Obispo,2010.
[88]D. W. Feng, D. G Huang. Modeling and control of a series hydrulic hybrid vehicle[J]. Journal of Computational Information System,2012,8(5):1805-1819.
[89]A. Pourmovahed. Energy storage capacity of gas-charged hydraulic accumulator [J]. AIAA, Thermophysics, Plasmadhynamics and Lasers Conference, San Antonio, TX, June 27-29,1988,12.
[90]韩文.新型电控液驱车关键技术的研究-驱动／制动系统[D].南京：南京理工大学,2005.
[91]H. Lbrahim, R. Younes, T. Basbous, A. Llinca, et al. Optimization of diesel engine performances for hybrid wind-disel system with compressed air energy storage[J]. Energy,2011,36(5):3079-3091.
[92]孙增圻.智能控制理论与技术[M].北京：清华大学出版社,2008.
[93]李士勇.智能控制·神经控制和智能控制理论[M].黑龙江：哈尔滨工业大学出版社,2006.
[94]诸静.模糊控制原理与应用[M].北京：机械工业出版社,1999.
[95]李晓丹.模糊PID控制器的设计研究[D].天津：天津大学,2005.
[96]陶永华.新型PID控制及应用[M].北京：机械工业出版社,2002.
[97]金以慧.过程控制[M].北京：清华大学出版社,1993.
[98]何衍庆.控制分析、设计和应用[M].北京：化学工业出版社,2003.
[99]王伟,张晶涛.PID参数先进整定方法综述[J].自动化学报,2000,26(3)：347-353.
[100]互晚霞,于玲玲,戴义保.控制器参数快速整定的新方法[J].自动化与仪器仪表,1996,67(5)：13-16.
[101]韩晓泉.模糊控制在光电跟踪伺服系统中的应用研究[D].北京：中国科学院研究生院,2005.
[102]王童谣,胡建易.模糊PID自整定算法在PLC中的实现[J].辽宁科技大学学报,2010,33(2)：149-152.
[103]张庆永.液驱混合动力车辆液压系统研究[D].南京：南京理工大学,2009.
[104]覃强.模糊PID温度控制方案的仿真优选及其实现[D].北京：中国科学院研究生院,2002.
[105]龙祖强.变论域模糊控制器的若干重要问题研究[D].长沙：中南大学,2011.
[106]龙祖强.变论域模糊控制器的万能逼近性及其逼近条件[J].中南大学学报,2012,43(8)：3046-3052.
[107]S. Srivastava, V. Sukumar, P. S. Bhasin. et al. A laboratory testbed for embedded fuzzy control[J]. IEEE Transactions on Education,2011,54(1):14-23.
[108]C. S. Tseng, B. S. Chen. Robust fuzzy observser-based fuzzy control design for nonlinear discrete-time systems with persistent bounded disturbances [J]. IEEE Transaction on Fuzzy System,2009,17(3):711-723.
[109]M. Hayati, A. M. Rashidi, A. Rezaei. Prediction of grain size of nanocrysralline nickel coatings using adaptive neuro-fuzzy inference system[J]. Solid State Sciences,2011,13:163-167.
[110]M. K. Giiven, K. M. Passino. Avoiding exponential parameter groth in fuzzy systems[J]. IEEE Transactions on Fuzzy System,2001,9(1):194-199.
[111]汪培庄,李洪兴.Fuzzy计算机的设计思想(Ⅰ)[J].北京师范大学学报,1995,31(2)：189-196.
[112]汪培庄,李洪兴.Fuzzy计算机的设计思想(Ⅱ)[J].北京师范大学学报,1995,31(3)：303-307.
[113]汪培庄,李洪兴.Fuzzy计算机的设计思想(Ⅲ)[J].北京师范大学学报,1995,31(3)：308-312.
[114]汪培庄,李洪兴.Fuzzy计算机的设计思想(Ⅳ)[J].北京师范大学学报,1995,31(4)：434-439.
[115]李洪兴.Fuzzy控制的本质与一类高精度fuzzy控制器的设计[J].控制理论与应用,1997,14(6)：868-872.
[116]李洪兴,苗志宏,王加银.非线性系统的变论域稳定自适应模糊控制[J].中国科学,E辑,2002,32(2)：211-223.
[117]李洪兴.变论域自适应模糊控制器[J].中国科学,E辑,1999,29(1)：32-42.
[118]文生平,赵国平,蔡康雄.一种变论域模糊控制自适应算法[J].控制理论与应用,2009,26(3)：265-268.
[119]郑宏,徐红兵,朱贵平.变论域自适应模糊控制在航机发电中的应用[J].控制理论与应用,2008,25(2)：253-256.
[120]朱岩,郭军平.变论域自适应模糊PID方法的研究与仿真[J].空军工程大学学报,2005,6(5)：11-14.
[121]李力,邹砚湖.海底采矿车路径跟踪的变论域模糊控制[J].中南大学学报,2012,43(2)：489-196.
[122]周建军,张漫,汪懋华,等.基于模糊控制的农用车辆路线跟踪[J].农业机械学报,2009,40(4)：151-156.
[123]高淑芝,高宪文,朱志承.基于变论域模糊PID的汽提塔温度控制方法[J].东北大学学报,2010,31(10)：1369-1372.
[124]黄冬梅,程树康,李军.变论域自组织模糊PID控制在逆变电源中的应用[J].电力自动化设备,2007,27(11)：45-47.
[125]潘永平,王钦若.变论域自适应模糊PID控制器设计[J].电气自动化,2007,29(3)：9-12.
[126]揭海宝,康积涛,李平.基于变论域模糊PID控制的同步发电机[J].电力自动化设备,2011,31(6)：101-104.
[127]黄悦华,徐阳,周星辰.基于变论域模糊控制的无刷双馈风力发电系统空载并网控制[J].电力自动化设备,2012,32(2)：99-103.
[128]朱颖合,薛凌云,黄伟.基于自组织调整因子的模糊PID控制器设计[J].系统仿真学报,2011,23(12)：2732-2737.
[129]李洪兴.模糊控制的插值机理[J].中国科学,E辑,1998,28(3)：259-267.
[130]G. Pagliarini, S. Rainieri. Modeling of a thermal energy storage system coupled with combined heat and power generation for the heating requirements of a University Campus[J]. Appled Thermal Engineering,2010,30(10):1255-1261.
[131]W. F. Su, S. J. Huang. C. E. Lin. Economic analysis for demand-side hybrid photovoltaic and battery energy storage system[J]. IEEE Transactions on Industry Application,2001,37(1):2051-2057.
[132]J. T. Alt, M. D. Aaderson, R. G Jungst. Assessment of utility side cost saving from battery energy storage. IEEE Transactions on Power System,1997,12(3): 1112-1120.
[133]T. Y. Lee, N. M. Chen. Determination optimal contract capacity and optimal sizes of battery energy storage systems for time-of-use rates industrial customers[J]. IEEE Transaction on Energy Conversion,1995,10(3):562-568.
[134]A. Oudalov, R. Cherkaoui, A. Beguin. Sizing and optimal operation of battery energy storage system for peak shaving application[C].2007 IEEE Lausanne Power Tech conference, July 1st-July 5th, Switzerland,2007.
[135]C. Bueno, J. A. Carta. Technical-economic analysis of wind-powered pumped hydro storage system. Part II:model application to the island of EI Hierro[J]. Solar Energy,2005,78(3):396-405.
[136]C. Bueno, J. A. Carta. Technical-economic analysis of wind-powered pumped hydro storage system. Part I:model development[J]. Solar Energy,2005,78(3): 382-395.
[137]J. P. Deane, B.P.O Gallachoir, E. J. McKeogh. Techno-economic review of existing and new pumped hydro energy storage plant[J]. Renew and Sustainable Energy Review,2010,14(4):1293-1302.
[138]E. Fertig, J. Apt. Economics of compressed air energy storage to integrate wind power:a case study in ERCOT[J]. Energy Policy,2011,35(5):2330-2342.
[139]N. K. C. Nair, N. Garimella. Battery energy storage systems:assessment for small scale renewable energy integration[J]. Energy and Building,2010,37(11): 2124-2130.
[140]A. M. Khudhair, M. M. Farid. A review on energy conservation in building applications with thermal storage by latent heat using phase change materials[J]. Energy Conversion and Management,2004,45(2):263-275.
[141]A. Ucar, M. Inalli. Thermal and economic comparisons of solar heating systems with seasonal storage used in building heating[J]. Renewable Energy,2008, 33(12):2532-2539.
[142]B. A. Habeebullah. Economic feasibility of thermal energy storage system[J]. Energy and Builds,2007,39(3):355-363.
[143]G. Tzamalis, E.I. Zoulias, E. Stamatakis, et al. Techno-economic analysis of an autonomous power system integrating hydrogen technology as energy storage medium[J]. Renewable Energy,2007,39(3):118-124.
[144]J. K. Kaldellis, D. S. Vlachou, G Korbakis. Techno-economic evaluation of small hydro power plants in Greece:a complete sensitivity analysis[J]. Energy Policy,2005,33(15):1969-1985.
[145]M. Kapsali, J. K. Kaldellis. Combining hydro and variable wind power generation by means of pumped-storage under economically viable terms[J]. Applied Energy,2010,87(11):1969-1985.
[146]Z. W. Shi, B. Zhang, X. Y. Zheng, et al. Engineering economics[M]. Beijing, China:Science Press,2009.
[147]J. Eyer, G Corey. Energy Storage for the Electricity Grid:Benefits and Markets Potential Assessment Guide[C]. New Mexico, USA:Sandia Corporation,2010.
[148]State Administration of Taxation. (2007) Provisional Regulations on Value Added Tax of the People's Republic of China[EB/OL]. Averable: http://202.108.90.130/n6669073/n6669088/6888727.html.
[149]State Administration of Taxation. (2003) Notice of the state administration of taxation concerning the follow-up management issues after conceling corporate income tax approving projects[EB/OL]. http://www.chinatax.gov.cn/n8136506/ n8136563/n8193451/n8193571/n8194571/8253239.html.
[150]中国南方电网.(2009)国家电力监管委员会关于印发《东北区域电力市场初期运营规则(暂行)》的通知[EB/OL].http://www.gd.csg.cn/fzyd/flfg/200912/t20091207_36564.html.
[151]李红军,李成仁,王卫军.当前抽水蓄能电站电价疏导问题分析[J].能源技 术经济,2010,22(9)：38-42.
[152]陈允鹏.发展抽水蓄能电站是电网调峰和经济运行的选择[J].中国能源,2005,25(8)：31-34.
[153]C. X. Wang, B. S. He, S. Y. Sun, et al. Application of a low pressure economizer for waste heat recovery from the exhaust flue gas in a 600 MW power plant[J]. Energy,2012,48(1):196-202.
[154]J. C. Cui, D. H. Liu, W. L. Liang, et al. Analysis on economic and environmental benefit of pumped-storage station[J]. Electric Power,2007,40(1):1-6.
[155]D. H. Liu, Y. P. Yang, K. Yang, et al. Research on the production cost of coal-fired power generating unit with consideration of environmental costs [J]. Electric Power,2005,38(9):24-28.
[156]National Development and Reform Commission. China's policies and actions for addressing climate change-the annual report 2010[R]. Beijing, China: Government Press,2010.
[157]N. Zhang, R. X. Cai. The proper order of magnitude of penalty for pollutant emission[J]. Proceedings of CSEE,1997,17(4):286-288.
[158]中国市场调查研究中心.(2012)2011-2012年中国液压设备行业现状分析与前景预测报告[EB/OL].http://www.cmir.com.cn/report/qjyc/100918.shtml.
[159]X. H. Yan, X. H. Zhang, H. S. Chen, et al. Techno-economic and social analysis of energy storage for commercial buildings [J]. Energy Conversion and Management,78(2014):125-136.
[160]国家统计局.(2011)2010年国民经济和社会发展统计公报[EB/OL].http://www.stats.gov.cn/tjsj/tjgb/ndtjgb/qgndtjgb/201102/t20110228_30025.html
[161]国家统计局.(2012)2011年国民经济和社会发展统计公报[EB/OL].http://www.stats.gov.cn/tjsj/tjgb/ndtjgb/qgndtjgb/201202/t20120222_30026.html.
[162]国家统计局.(2013)2012年国民经济和社会发展统计公报[EB/OL].http://www.stats.gov.cn/tjsj/tj gb/ndtjgb/qgndtjgb/201302/t20130221_30027.html
[163]J. McNell, J. Previtali, M. Krarti. A simplified method to predit energy cost saving in office buildings using a hybrid desiccant, absorption chiller, and natural gas turbine cogeneration systems with thermal storage [C]. Proceedings of energy sustainability, California, USA, Jun 27th-June 30th,2007.
[164]严晓辉,陈海生,张雪辉等.国际储能产业政策解读与我国储能产业政策分析[J].中国能源,2011,33(11)：28-33.
