摘要
将分布式发电(DG)与集中供电相结合,清洁、高效利用能源,是电力工业重要的技术增长点。在未来智能电网中,改进的互联标准将使不同容量、不同类型的DG更加便利地接入配电网。分布式发电技术的应用必将给传统配电网规划带来深远变革。本文研究了含DG的配电网规划,主要成果包括:
(1)结合典型负荷日特性曲线,在变电站规划中考虑了DG削峰作用和不同类型负荷间的错峰效应,避免了传统方法可能出现的主变容量利用率不高和负荷分配不均衡的弊端;基于Voronoi图的遗传算法实现了变电站布点和供电范围的合理划分,为含DG的变电站规划提供了一种有效方法。
(2)从不同角度,构建了含DG的配电网规划模型。考虑安全约束的规划模型充分计及DG接入对配电网安全的影响,增强了配电网安全性能;考虑DG出力随机性的规划模型采用随机潮流和机会约束技术,为含多种可再生能源类型DG的配电网规划提供了新方法;考虑DG准入功率的多目标规划模型均衡协调了配电网投资成本与DG准入功率之间的关系,提高了配电网接纳DG的能力;DG与配电网联合规划模型以社会成本最小化为目标,并转换成一个双层规划问题,为在DSM(需求侧管理)和主动管理框架下优化配置DG资源探索了新途径。
(3)根据配电网拓扑结构特点,将常规配电网规划遗传算法改进为基于支撑树的遗传算法(St-GA),确保进化过程中每个规划方案均拓扑可行,提高了GA搜索效率;提出将多阶段配电网规划转化为搜索最优目标网架的策略,达到各阶段规划信息在目标网架中的融合,为研究多阶段配电网规划提供了新思路。
(4)引入配电网节点边际容量成本(LMCC),反映节点容量的充裕程度。基于节点边际容量成本的配电网扩容规划以DG单位扩容成本小于接入点的边际容量成本作为DG接入配电网的条件,既发挥了DG扩容作用,又避免了原有供电设备利用率降低,为评价DG接入的经济性提供了新工具。
Distributed generation (DG) is predicted to play an increasing role in the electric power system of the future. A large amount of DG capacity conneted to distribution network will bring about the great influence on operation and planning of conventional distribution network. Therefore, the study on distribution network planning with DG is one of the hotspots in the power engineering research field. This dissertion concentrates on some critical problems in this field and the main innocations are shown as follows:
(1) Combined with the typical load characteristic curve, a new method for substation planning with the consideration of DG for peak cutting is proposed to overcome the low utilization and unbalanced loading of main transformers in the conventional methods. Moreover, genetic algorithm based on Voronoi diagram can determine the optimal location, sizing and the service areas and provide an effective design method of substation planning.
(2) Planning models of the novel distributution network are established from the different viewpoints. The planning model considering safety constraints takes the risks as the result of DG connection into account and increases the safety capability of distribution netwrok; Based on chance-constrained programming, the planning model considering stochastic character of renewable DG output is presented to evaluate the distribution network investment risk due to DG connected to distribution network; The multi-objective planning model is built to explore the tradeoff between the maximum penetration level of DG and distribution network investment. The iterative algorithm based on linear programming is adopted to maximize the DG capacity in the given network, while the improvedε-constraints approach is used in the optimization decision on the pareto optimal set; The planning model of distribution network integrated with DG, which aims to minimize the social cost, is transformed into a bi-level planning and provide a noval measure to allocate DG source in the mode of demand side management (DSM) and active management.
(3) Spanning tree-based genetic algorithm (st-GA) to solve distribution network planning with DG is presented. St-GA with two specialized genetic operators can guarantee the topological feasibility and high heritability of each solution generated and overcome the deficiencies of existing GAs applied for distribution network planning. According to the topological characteristic of distribution network, the multistage distribution network planning can be transformed into a problem of searching the optimal target network with the minimum total costs in the whole planning horizon, which contains the message of each building stage for every candidate branch and its size.
(4) Locational marginal capacity cost (LMCC) is introduced to reflect the forward-looking cost of nodal capacity and the degree to which nodal capacity is utilized. On this basis, DG connection criterion that the unit capacity cost of DG is less than LMCC at its candidate node is obtained to avoid the lower utilization of the existing power supply facilities, which provides a new tool to envaluate DG connection from the point of the view of enlarging capacity with DG.
Analysis and comprarision of the study cases proves the feasibility, effectivity and practicability of this dissertion.
引文
[1] El-Khattam W., Salama M. M. A. Distributed generation technologies, definitions and benefits[J]. Electric Power Systems Research, 2004, 71(2): 119-128.
[2] Püttgen Hans B., Macgregor Paul R., Lambert Frank C. Distributed generation: Semantic hype or the dawn of a new era? [J]. IEEE Power and Energy Magazine, 2003, 1(1): 22-29.
[3] Daly Peter A., Morrison Jay, Understanding the potential benefits of distributed generation on power delivery systems[C]. Rural electric power conference, 2001, A21-A213.
[4]赵豫,于尔铿.电力零售市场研究(六)分散式发电对电力系统的影响[J]..电力系统自动化, 2003, 27(15): 25-28.
[5]范明天.配电系统与分散发电集成研究的国际动态[J]..动力与电气工程师, 2008, 7(4): 23-27.
[6]陈海焱.含分布式发电的电力系统分析方法研究[D].华中科技大学博士学位论文, 2008.
[7]胡成志.分布式电源接入系统研究[D].重庆大学硕士学位论文, 2005.
[8] Wang Caisheng, Nehrir M. Hashem. Analytical approaches for optimal placement of distributed generation sources in power systems[J]. IEEE Transactions on Power Systems, 2004, 19(4): 2068-2076.
[9]王成山,陈恺,谢莹华.配电网扩展规划中分布式电源的选址和定容[J].电力系统及其自动化, 2006, 30(3): 38-43.
[10] Brown Richard E., Pan Jiuping, Feng Xiaoming, et al., Siting distributed generation to defer t&d expansion[C]. Proceedings of the ieee power engineering society transmission and distribution conference, 2001, 622-627.
[11] Celli G., Pilo F., Optimal distributed generation allocation in mv distribution networks[C]. IEEE power industry computer applications conference, 2001, 81-86.
[12]王成山,王赛一.市场条件下电力系统规划工作的探讨[J].电力系统自动化, 2005, 29(9): 82-86.
[13] Harrison Gareth P., Piccolo Antonio, Siano Pierluigi, et al. Hybrid ga and opf evaluation of network capacity for distributed generation connections[J]. Electric Power Systems Research, 2008, 78(3): 392-398.
[14]胡庶,吴耀武,娄素华,等.用户自备分布式发电与供电商的博弈[J].电力系统自动化, 2006, 30(20): 21-25.
[15] Harrison Gareth P., Piccolo Antonio, Siano Pierluigi, et al. Exploring the tradeoffs between incentives for distributed generation developers and dnos[J]. IEEE Transactions on Power Systems, 2007, 22(2): 821-828.
[16] Celli Gianni, Ghiani Emilio, Mocci Susanna, et al. A multiobjective evolutionary algorithm for the sizing and siting of distributed generation[J]. IEEE Transactions on Power Systems, 2005, 20(2): 750-757.
[17] Keane Andrew, O'Malley Mark. Optimal allocation of embedded generation on distribution networks[J]. IEEE Transactions on Power Systems, 2005, 20(3): 1640-1646.
[18] Liew S. N., Strbac G. Maximising penetration of wind generation in existing distribution networks[J]. IEE Proceedings: Generation, Transmission and Distribution, 2002, 149(3): 256-262.
[19] Griffin T., Tomsovic K., Secret D., et al., Placement of dispersed generations systems for reduced losses[C]. Proceedings of the hawaii international conference on system sciences, 2000, 104.
[20] Gil Hugo A., Joos Geza. Customer-owned back-up generators for energy management by distribution utilities[J]. IEEE Transactions on Power Systems, 2007, 22(3): 1044-1050.
[21] Bae In-Su, Kim Jin- O., Kim Jae-Chul, et al. Optimal operating strategy for distributed generation considering hourly reliability worth[J]. IEEE Transactions on Power Systems, 2004, 19(1): 287-292.
[22] Zhu Dan, Broadwater Robert P., Tam Kwa-Sur, 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.
[23] Teng Jen-Hao, Luor Tain-Syh, Liu Yi-Hwa, Strategic distributed generator placements for service reliability improvements[C]. Proceedings of the ieee power engineering society transmission and distribution conference, 2002, 719-724.
[24] Celli G., Pilo F. Mv network planning under uncertainties on distributed generation penetration[C]. Proceedings of 2001 IEEE Power Engineering Society Summer Meeting, 2001.
[25] Celli G., Ghiani E., Mocci S. A multi-objective formulation for the optimal sizing and siting of embedded generation in distribution networks[C]. 2003 IEEE Power Tech ConferenceProceedings, Bologna, 2003.
[26] Dugan Roger C., McDermott Thomas E., Ball Greg J. Planning for distributed generation. IEEE Industry Applications Magazine[J], 2001, 7(2): 80-88.
[27] Favuzza Salvatore, Graditi Giorgio, Ippolito Mariano Giuseppe, et al. Optimal electrical distribution systems reinforcement planning using gas micro turbines by dynamic ant colony search algorithm[J]. IEEE Transactions on Power Systems, 2007, 22(2): 580-587.
[28] S.W.Hadley, T.K.Stovall. Customer-owned utilities and distributed energy: Potentials and benefits[S]. Oak Ridge National Laboratory, Tennessee, February, 2006: 50-70.
[29]王敏,丁明.分布式发电及其效益[J].合肥工业大学学报(自然科学版), 2004, 27(4): 354-358.
[30]王敏,丁明.含分布式电源的配电系统规划[J].电力系统及其自动化学报, 2004, 16(6): 5-8.
[31]高笑,赵宏伟,冯璞.基于分布式发电的配网规划初探[J].江苏电机工程, 2005, 24(2): 9-11.
[32] Mori H.,Iimura, Y. Application of parallel tabu search to distribution network expansion planning with distributed generation[C]. 2003 IEEE Power Tech Conference Proceedings, 2003: 580-587.
[33] Farrag M. A., El-Metwally M. M., El-Bages M. S. New model for distribution system planning[J]. International Journal of Electrical Power and Energy System, 1999, 21(7): 523-531.
[34]康庆平,周雷.一个实用的配电网优化规划方法[J].电网技术, 1994, 18(6): 39-43.
[35] Boulaxis Nicholas G., Papadopoulos Michael P. Optimal feeder routing in distribution system planning using dynamic programming technique and gis facilities[J]. IEEE Transactions on Power Delivery, 2002, 17(1): 242-247.
[36] Ramirez-Rosado Ignacio J., Gonen Turan. Pseudodynamic planning for expansion of power distribution systems[J]. IEEE Transactions on Power Systems, 1991, 6(2): 245-254.
[37] Peponis G. J., Papadopoulos M. P. New dynamic, branch exchange method for optimal distribution system planning[J]. IEE Proceedings: Generation, Transmission and Distribution, 1997, 144(3): 333-339.
[38] Aoki K., Nara K., Satoh T., et al. New approximate optimization method for distribution system planning[J]. IEEE Transactions on Power Systems, 1990, 5(1): 126-132.
[39] Nara K., Satoh T., Kuwabara H., et al. Distribution systems expansion planning by multi-stage branch exchange[J]. IEEE Transactions on Power Systems, 1992, 7(1): 208-214.
[40] Diaz-Dorado Eloy, Cidras Jose, Miguez Edelmiro. Application of evolutionary algorithms for the planning of urban distribution networks of medium voltage[J]. IEEE Transactions on Power Systems, 2002, 17(3): 879-884.
[41] L. Gregory, T. Shmuel M., E. David. Genetic algorithm for open-loop distribution system design[J]. Electric Power Systems Research, 1995, 32(2): 81-87.
[42]倪秋龙,黄民翔.基于支路交换的模拟退火算法在配电网规划中的应用[J].电力系统及其自动化学报, 2000, 12(4): 31-35.
[43]顾洁,陈章潮,包海龙.混合遗传-模拟退火算法在电网规划中的应用[J].上海交通大学学报, 1999, 33(4): 485-487.
[44]贾德香,唐国庆,韩净.基于改进模拟退火算法的电网无功优化[J].继电器2004, 32(4): 32-35.
[45]王志刚,杨丽徙.基于蚁群算法的配电网网架优化规划方法[J].电力系统及其自动化学报, 2002, 14(6): 73-76.
[46]翟海保,程浩忠,陈春霖.基于改进蚁群算法的输电网络扩展规划[J].中国电力, 2003, 36(21): 49-52.
[47]黄训诚,庄奕琪,耿阿囡.基于改进蚁群算法的配电网优化规划[J].西安交通大学学报, 2007, 41(6): 727-731.
[48]孙薇,商伟,牛东晓.改进蚁群优化算法在配电网网架规划中的应用[J].电网技术2006, 30(15): 85-89.
[49]徐珍霞,顾洁.粒子群优化算法在配电网网架优化规划中的应用[J].继电器, 2006, 34(6): 29-33.
[50]张宪,苑津莎,杨薛明,等.基于粒子群算法的配电网网架规划[J].华北电力大学学报2006, 33(3): 14-17.
[51]杨期余,潘力强.应用于城网规划中的新算法-tabu搜索[J].电力自动化设备, 2001, 21(12): 9-12.
[52]陈根军,唐国庆.基于禁忌搜索与蚁群最优结合算法的配电网规划[J].电网技术, 2005, 29(2): 23-27.
[53] Haghifam M. R., Shahabi M. Optimal location and sizing of hv/mv substations in uncertainty load environment using genetic algorithm[J]. Electric Power Systems Research, 2002, 63(1): 37-50.
[54] Masud E. An interactive procedure for sizing and timing distribution substations using optimization techniques[J]. IEEE Transactions on Power Apparatus and Systems, 1974, 93(5): 1281-1286.
[55] Thompson G.L., Wall D.L. A branch and bound model for choosing optimal substation locations. IEEE Transactions on Power Apparatus and Systems[J], 1981, 100(5): 2683-2688.
[56] Hongwei Dai, Yixin Yu, Chunhua Huang, et al. Optimal planning of distribution substation locations and sizes - model and algorithm[J]. International Journal of Electrical Power and Energy System, 1996, 18(6): 353-357.
[57]王成山,魏海洋,肖峻,等.变电站选址定容两阶段优化规划方法[J].电力系统自动化, 2005, 29(4): 62-66.
[58]王成山,刘涛,谢莹华.基于混合遗传算法的变电站选址定容[J].电力系统自动化, 2006, 30(6): 30-35.
[59] M.S. Sepasian, S. Hossein, Foroud Akbari, et al. A new approach for substation expansion planning[J]. IEEE Transactions on Power Systems, 2006, 21(2): 997-1004.
[60]刘自发,张建华.基于改进多组织粒子群体优化算法的配电网络变电站选址定容[J].中国电机工程学报, 2007, 27(01): 105-111.
[61]林济铿,李鸿路,罗萍萍,等.统一考虑变电站和网架优化的配电网综合规划[J].电力系统自动化, 2006, 30(19): 42-46.
[62] Held Martin, Williamson Robert B. Creating electrical distribution boundaries using computational geometry[J]. IEEE Transactions on Power Systems, 2004, 19(3): 1342-1347.
[63]葛少云,李慧,刘洪.基于加权voronoi图的变电站优化规划[J].电力系统自动化, 2007, 31(3): 29-34.
[64]杨丽徙,朱向前,陈根永.基于voronoi图的变电站优化规划方法[J].电力系统及其自动化学报, 2006, 18(5): 22-25.
[65] Sergio Haffner, Alves Fernando, Alberto Luis. Multistage model for distribution expansion planning with distributed generation - part i: Problem formulation[J]. IEEE Transactions on Power Delivery, 2008, 23(2): 915-923.
[66] Sergio Haffner, Alves Fernando, Alberto Luis. Multistage model for distribution expansion planning with distributed generation-part ii: Numerical results. [J] IEEE Transactions on Power Delivery, 2008, 23(2): 924-929.
[67]国家电网公司.城市电力网规划设计导则[S].国家电网企业标准Q/GDW 156-2006,北京, 2006.
[68] Vovos Panagis N., Bialek Janusz W. Direct incorporation of fault level constraints in optimal power flow as a tool for network capacity analysis[J]. IEEE Transactions on Power Systems, 2005, 20(4): 2125-2134.
[69]陈海焱,陈金富,杨雄平,等.配电网中计及短路电流约束的分布式发电规划[J].电力系统自动化, 2006, 30(21): 16-21.
[70]裴玮,鹍盛,孔力,等.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.
[71]陈海焱,段献忠,陈金富.计及配网静态电压稳定约束的分布式发电规划模型与算法[J].电网技术, 2006, 30(21): 11-14.
[72]刘健,毕鹏翔,董海鹏.复杂配电网简化分析与优化[M],北京:中国电力出版社,2002.
[73] Miguez Edelmiro, Cidras Jose, Diaz-Dorado Eloy, et al. An improved branch-exchange algorithm for large-scale distribution network planning[J]. IEEE Transactions on Power Systems, 2002, 17(4): 931-936.
[74] Rivas-Davalos F., Irving M.R. An efficient genetic algorithm for optimal large-scale power distribution network planning[C]. Proceedings of 2003 IEEE Power Tech Conference, June. 23-26, 2003.
[75] Carvalho P. M. S., Ferreira L. A. F. M., Barruncho L. M. F. On spanning-tree recombination in evolutionary large-scale network problems - application to electrical distribution planning[J]. IEEE Transactions on Evolutionary Computation, 2001, 5(6): 623-630.
[76]王天华,王平洋,范明天.用演化算法求解多阶段配电网规划问题[J].中国电机工程学报, 2000, 20(3): 34-38.
[77]陈章潮,唐德光.城市电力网规划与改造[M].中国电力出版社, 1998.
[78]上海市电力公司.上海中低压电网技术原则及典型设计[S],2006.
[79] Narsingh D. Graph theory with applications to engineering and computer science[M]. Prentice-Hall Inc., 1974.
[80] Carrano E. G., Cardoso R. T. N., Takahashi R. H. C., et al. Power distribution network expansion scheduling using dynamic programming genetic algorithm[J]. IET Generation, Transmission and Distribution, 2008, 2(3): 444-455.
[81] Balouktsis Anastasios, Chassapis Dimitrios, Karapantsios Thodoris D. A nomogram method for estimating the energy produced by wind turbine generators[J]. Solar Energy, 2002, 72(3): 251-259.
[82] Bowden G. J., Barker P. R., Shestopal V. O., et al. Weibull distribution function and wind power statistics[J]. Wind Engineering, 1983, 7(2): 85-98.
[83] Carta J. A., Ramirez P. Analysis of two-component mixture weibull statistics for estimation of wind speed distributions[J]. Renewable Energy, 2007, 32(3): 518-531.
[84] Karaki S. H., Chedid R. B., Ramadan R. Probabilistic performance assessment of autonomous solar-wind energy conversion systems[J]. IEEE Transactions on Energy Conversion, 1999, 14(3): 766-772.
[85] Abouzahr Imad, Ramakumar R. Loss of power supply probability of stand-alone photovoltaic systems: A closed form solution approach[J]. IEEE Transactions on Energy Conversion, 1991, 6(1): 1-11.
[86] Charytoniuk W., Chen M. S., Kotas P., et al. Demand forecasting in power distribution systems using nonparametric probability density estimation[J]. IEEE Transactions on Power Systems, 1999, 14(4): 1200-1206.
[87]杨宁,文福拴.计及风险约束的多阶段输电系统规划方法[J].电力系统自动化, 2005, 29(4): 28-33.
[88]王锡凡,王秀丽.电力系统的随机潮流分析[J].西安交通大学学报, 1988, 22(3): 87-97.
[89]郑海峰.计及分布式发电的配电系统随机潮流计算[D].天津大学硕士学位论文, 2006.
[90] Zhang Pei, Lee Stephen T. Probabilistic load flow computation using the method of combined cumulants and gram-charlier expansion[J]. IEEE Transactions on Power Systems, 2004, 19(1): 676-682.
[91]王锡凡.电力系统优化规划[M].北京:水利电力出版, 1990.
[92]张节潭,程浩忠,姚良忠,等.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.
[93] Tian W. D., Sutanto D., Lee Y. B., et al. Cumulant based probabilistic power system simulation using laguerre polynomials[J]. IEEE Transactions on Energy Conversion, 1989, 4(4): 567-574.
[94]谢建民,邱毓昌,张治源.风力发电机优化选型与云南省风力发电场规划研究[J].电力建设, 2001, 22(5): 27-31.
[95] K.Jeith, Hedgecock J., R.Gregory. Technical guide to the connection of generation to the distribution network[S]. DTI New & Renewable Energy Programm K/EL/00318/REP/URN 03/1631, London, UK, 2004.
[96] Calderaro V., Piccolo A., Siano P., Maximizing dg penetration in distribution networks by means of ga based reconfiguration[C], Transmission and Distribution Conference and Exposition, 2005, 1-5.
[97] S. Lundberg, T. Thiringer, T. Petru. Electrical limiting factors for wind energy installations in weak grids[J]. International Journal of Renewable Energy Engineering, 2001, 3(2): 17-22.
[98] L.Z. Yao, G. Strbac, X.P. Zhang. A concurrent optimal power flow for enforcement of system solvability, voltage and thermal constraints[C]. Proc. 13th Power System Computation Conference in Trondheim, 1999: 351-357.
[99]崔逊学.多目标进化算法及其应用[M].北京:国防工业出版社, 2006.
[100]王寅初译.多目标决策分析及其在工程和经济中的应用[M].北京:航空工业出版社, 1987.
[101]张节潭,程浩忠,姚良忠,等.主动管理在含有分布式电源的配电网中的应用[J].电力科学与技术学报, 2008, 23(1): 18-23.
[102]胡庶,吴耀武,娄素华,等.用户自备分布式发电与供电商的博弈[J].电力系统自动化, 2005, 30(20): 21-25.
[103]高军彦,麻秀范,凡鹏飞.计及分布式发电的配电网协调规划整体框架与模型[J].电网与清洁能源, 2008, 24(4): 12-16.
[104] D.Z. Ray, E.M. Carlos, G. Deqiang. Available: Http://www.Pserc.Cornell.Edu/matpower.
[105] Rivera Rodriguez Gabriel A., O'Neill-Carrillo Efrain, Economic assessment of distributed generation using life cycle costs and environmental externalities[C], Transmission and Distribution Conference and Exposition, 2005, 412-419.
[106] Pipattanasomporn Manisa, Willingham Michael, Rahman Saifur. Implications of on-site distributed generation for commercial/industrial facilities[J]. IEEE Transactions on Power Systems, 2005, 20(1): 206-212.
[107] Zhang Jietan, Cheng Haozhong, Wang Chun. Technical and economic impacts of active management on distribution network[J]. International Journal of Electrical Power and Energy Systems, 2009, 31(2-3): 130-138.
[108] Dugan R. C., McDermott T. E., Ball G. J., et al. Planning for distributed generation[J]. IndustryApplications Magazine, IEEE, 2001, 7(2): 80-88.
[109] Brown R. E., Pan J., Feng X., et al. Siting distributed generation to defer t&d expansion[C]. Transmission and Distribution Conference and Exposition, 2001 IEEE/PES, 2001, 2.
[110] Orans R. Area-specific marginal costing for electric utilities: A case study of transmission and distribution costs[D]. Ph.D. dissertation Stanford, CA: Stanford Univ., 1989.
[111] Li Xin, Zielke Garry K. One-year deferral method for estimating avoided transmission and distribution costs[J]. IEEE Transactions on Power Systems, 2005, 20(3): 1408-1413.
[112] Woo C. K., Orans Ren, Horii Brian, et al. Area- and time-specific marginal capacity costs of electricity distribution[J]. Energy, 1994, 19(12): 1213-1218.
[113] Heffner Grayson, Woo C. K., Horii Brian, et al. Variations in area- and time-specific marginal capacity costs of electricity distribution[J]. IEEE Transactions on Power Systems, 1998, 13(2): 560-565.
[114] Li Furong, Tolley David L. Long-run incremental cost pricing based on unused capacity[J]. IEEE Transactions on Power Systems, 2007, 22(4): 1683-1689.
[115] K.Jeith, Hedgecock J., R.Gregory. technical guide to the connection of generation to the distribution network[S]. DTI New & Renewable Energy Programm K/EL/00318/REP/URN 03/1631, London, UK, 2004.