含可再生能源的电力系统两阶段核心骨干网架优化策略
|
摘要
可再生能源是全球能源转型和低碳发展的重要解决方案,含高比例可再生能源是未来电力系统发展的必然趋势,而高比例可再生能源电力系统的核心骨干网架直接关系到系统在灾害条件下的生存性、可靠性和可再生能源的消纳率。分析了高比例可再生能源电力系统的核心骨干网架的特征。随后结合电力网络中不同类型节点的特点,基于拓扑特性和电气参数分别构建各类节点的重要度评价指标体系,并采用熵权-理想解法评价各类节点的相对重要度。根据节点的相对重要度,构建了两阶段核心骨干网架优化模型:第一阶段模型针对重要负荷节点进行网架优化;第二阶段模型针对电源节点进行优化,最终得到包含风电场、光伏电站和常规机组的核心骨干网架。修改后的含高比例可再生能源的IEEE-118节点系统的仿真结果表明,文中策略能够较全面地评估高比例可再生能源电力系统的各类节点的相对重要度,优化得到的核心骨干网架能够保障对重要负荷的供电,且具有较高的可再生能源渗透率与利用率。
Renewable energy is an important solution for global energy transformation and low carbon development. Interfacing with high proportion of renewable energy is an inevitable trend of future power systems. Core backbone network directly correlates to survivability, reliability and accommodation rate of renewable energy of power systems with high proportion of renewable energy. The characteristics of the core backbone network are analyzed based on the characteristics and operation requirements of power systems with high proportion of renewable energy. According to the characteristics of different types of nodes in power networks, the node importance evaluation indexes are presented respectively, and relative importance of each type of nodes is evaluated with entropy weight and technique for order preference by similarity to ideal solution method. Based on the relative importance of nodes, a two-stage core backbone network optimization model is proposed. The first stage of the model aims at optimizing critical load nodes; while the second stage aims at optimizing power source nodes, and then a core backbone network with wind farms, photovoltaic plants and conventional units is attained. Simulation results of the modified IEEE-118 bus system with high proportion of renewable energy show that the proposed strategy can comprehensively evaluate the relative importance of various types of nodes of power systems with high proportion of renewable energy and that the optimized core backbone network guarantees the power supply to critical loads and has ahigh penetration and utilization of renewable energy.
Renewable energy is an important solution for global energy transformation and low carbon development. Interfacing with high proportion of renewable energy is an inevitable trend of future power systems. Core backbone network directly correlates to survivability, reliability and accommodation rate of renewable energy of power systems with high proportion of renewable energy. The characteristics of the core backbone network are analyzed based on the characteristics and operation requirements of power systems with high proportion of renewable energy. According to the characteristics of different types of nodes in power networks, the node importance evaluation indexes are presented respectively, and relative importance of each type of nodes is evaluated with entropy weight and technique for order preference by similarity to ideal solution method. Based on the relative importance of nodes, a two-stage core backbone network optimization model is proposed. The first stage of the model aims at optimizing critical load nodes; while the second stage aims at optimizing power source nodes, and then a core backbone network with wind farms, photovoltaic plants and conventional units is attained. Simulation results of the modified IEEE-118 bus system with high proportion of renewable energy show that the proposed strategy can comprehensively evaluate the relative importance of various types of nodes of power systems with high proportion of renewable energy and that the optimized core backbone network guarantees the power supply to critical loads and has ahigh penetration and utilization of renewable energy.
引文
[1]杨文辉,毕天姝,黄少锋,等.基于电网生存性评估的关键线路识别方法[J].中国电机工程学报,2011,31(7):29-35.Yang Wenhui,Bi Tianshu,Huang Shaofeng,et al.An approach for critical lines identification based on the survivability of power grid[J].Proceedings of the CSEE,2011,31(7):29-35(in Chinese).
[2]潘旭东,吴军,刘涤尘,等.基于元件重要度的差异化规划核心骨干网架构建方法[J].电力系统自动化,2014,38(19):40-46.Pan Xudong,Wu Jun,Liu Dichen,et al.A method for constructing core backbone grid in differential planning based on importance degrees of components[J].Automation of Electric Power Systems,2014,38(19):40-46(in Chinese).
[3]董飞飞,刘涤尘,吴军,等.基于改进BBO优化算法和电网生存性的核心骨干网架构建[J].中国电机工程学报,2014,34(16):2659-2667.Dong Feifei,Liu Dichen,Wu Jun,et al.A method of constructing core backbone grid based on improved BBO optimization algorithm and survivability of power grid[J].Proceedings of the CSEE,2014,34(16):2659-2667(in Chinese).
[4]王浩磊,刘涤尘,吴军,等.基于改进二进制量子粒子群算法的核心骨干网架搜索[J].中国电机工程学报,2014,34(34):6127-6133.Wang Haolei,Liu Dichen,Wu Jun,et al.Core backbone network searching based on improved quantum binary particle swarm optimization[J].Proceedings of the CSEE,2014,34(34):6127-6133(in Chinese).
[5]洪运福.基于复杂网络的输电网差异化规划研究[D].北京:华北电力大学,2012.
[6]赵一婕,刘涤尘,吴军,等.基于线性判别分析与主成分分析的骨干网架生存性评估方法[J].电网技术,2014,38(2):388-394.Zhao Yijie,Liu Dichen,Wu Jun,et al.Survivability evaluation of backbone network based on linear discriminant analysis and principal component analysis[J].Power System Technology,2014,38(2):388-394(in Chinese).
[7]白建华,辛颂旭,刘俊,等.中国实现高比例可再生能源发展路径研究[J].中国电机工程学报,2015,35(14):3699-3705.Bai Jianhua,Xin Songxu,Liu Jun,et al.Roadmap of realizing the high penetration renewable energy in China[J].Proceedings of the CSEE,2015,35(14):3699-3705(in Chinese).
[8]鲁宗相,李海波,乔颖.含高比例可再生能源电力系统灵活性规划及挑战[J].电力系统自动化,2016,40(13):147-158.Lu Zongxiang,Li Haibo,Qiao Ying.Power system flexibility planning and challenges considering high proportion of renewable energy[J].Automation of Electric Power Systems,2016,40(13):147-158(in Chinese).
[9]Golshani A,Sun W,Zhou Q,et al.Incorporating wind energy in power system restoration planning[J].IEEE Transactions on Smart Grid,2018,PP(99):1-1.
[10]Zhao Y,Lin Z,Ding Y,et al.A model predictive control based generator start-up optimization strategy for restoration with microgrids as black-start resources[J].IEEE Transactions on Power Systems,2018,PP(99):1-1.
[11]廖萍,李兴源.风电场穿透功率极限计算方法综述[J].电网技术,2008,32(10):50-53.Liao Ping,Li Xingyuan.A survey on calculation methods of wind power penetration limit[J].Power System Technology,2008,32(10):50-53(in Chinese).
[12]董开松,胡殿刚,秦睿,等.考虑系统运行风险的风电穿透功率极限动态求解方法[J].高电压技术,2015,41(10):3422-3427.Dong Kaisong,Hu Diangang,Qin Rui,et al.Dynamic method for solving wind power penetration limit considering system operation risk[J].High Voltage Engineering,2015,41(10):3422-3427(in Chinese).
[13]徐岩,闫少波,史迪锋.基于近似线性规划法的弱电网光伏穿透功率极限计算[J].电力自动化设备,2014,34(4):128-132.Xu Yan,Yan Shaobo,Shi Difeng.Power penetration limit calculation based on approximate linear programming for PV power station in weak grid[J].Electric Power Automation Equipment,2014,34(4):128-132(in Chinese).
[14]张泽聪.抽取复杂网络中的骨干结构的方法研究[D].北京:北京邮电大学,2014.
[15]任卓明,邵凤,刘建国,等.基于度与聚集系数的网络节点重要性度量方法研究[J].物理学报,2013,62(12):128901.Ren Zhuoming,Shao Feng,Liu Jianguo,et al.Node importance measurement based on the degree and clustering coefficient information[J].Acta Physica Sinica,2013,62(12):128901(in Chinese).
[16]孙璞玉,张焰,罗雯清.考虑网架覆盖率与分散度的网架重构优化[J].电网技术,2015,39(1):271-278.Sun Puyu,Zhang Yan,Luo Wenqing.Optimization of backbone network reconfiguration considering network coverage rate and dispersion degree[J].Power System Technology,2015,39(1):271-278(in Chinese).
[17]Du Y,Gao C,Chen X,et al.A new closeness centrality measure via effective distance in complex networks[J].Chaos,2015,25(3):033112.
[18]Brockmann D,Helbing D.The hidden geometry of complex,network-riven contagion phenomena[J].Science,2013,342(6164):1337-1342.
[19]刘巨,姚伟,文劲宇,等.大规模风电参与系统频率调整的技术展望[J].电网技术,2014,38(3):638-646.Liu Ju,Yao Wei,Wen Jinyu,et al.Prospect of technology for large-scale wind farm participating into power grid frequency regulation[J].Power System Technology,2014,38(3):638-646(in Chinese).
[20]Chang-Chien L R,Yin Y C.Strategies for operating wind power in a similar manner of conventional power plant[J].IEEE Transactions on Power Systems,2009,24(4):926-933.
[21]汪海蛟,江全元.应用于平抑风电功率波动的储能系统控制与配置综述[J].电力系统自动化,2014,38(19):126-135.Wang Haijiao,Jiang Quanyuan.An overview of control and configuration of energy storage system used for wind power fluctuation mitigation[J].Automation of Electric Power Systems,2014,38(19):126-135(in Chinese).
[22]袁小明,程时杰,文劲宇.储能技术在解决大规模风电并网问题中的应用前景分析[J].电力系统自动化,2013,37(1):14-18.Yuan Xiaoming,Cheng Shijie,Wen Jinyu.Prospects analysis of energy storage application in grid integration of large-scale wind power[J].Automation of Electric Power Systems,2013,37(1):14-18(in Chinese).
[23]Marion B,Adelstein J,Boyle K,et al.Performance parameters for grid-connected PV systems[C]//Proc of the 31st IEEE Photovoltaics Specialists Conference and Exhibition,2005,Lake Buena Vista,FL,USA:1601-1606.
[24]李芬,陈正洪,蔡涛,等.并网光伏系统性能精细化评估方法研究[J].太阳能学报,2013,34(6):974-983.Li Fen,Chen Zhenghong,Cai Tao,et al.Refinement assessment method of grid-connected PV system performance[J].Acta Energiae Solaris Sinica,2013,34(6):974-983(in Chinese).
[25]曹清山,郑梦莲,丁一,等.新电改背景下基于多属性决策的电力客户评估和选择研究[J].电网技术,2018,42(1):117-125.Cao Qingshan,Zheng Menglian,Ding Yi,et al.Multi-attribute decision making model for customer evaluation and selection in electricity market[J].Power System Technology,2018,42(1):117-125(in Chinese).
[26]Li X,Wang K,Liu L,et al.Application of the entropy weight and TOPSIS method in safety evaluation of coal mines[J].Procedia Engineering,2011,26(4):2085-2091.
[27]卢锦玲,张津,丁茂生.含风电的电力系统调度经济性评价[J].电网技术,2016,40(8):2258-2264.Lu Jinling,Zhang Jin,Ding Maosheng.Economic evaluation of power system dispatch integrated with wind power[J].Power System Technology,2016,40(8):2258-2264(in Chinese).
[28]彭显刚,林利祥,翁奕珊,等.基于模糊综合评判和综合赋权的抗灾型配电网骨干网架规划[J].电力系统自动化,2015,39(12):172-178.Peng Xiangang,Lin Lixiang,Weng Yishan,et al.Decision-making method for anti-disaster distribution network backbone upgrade based on fuzzy comprehensive evaluation and comprehensive weights[J].Automation of Electric Power Systems,2015,39(12):172-178(in Chinese).
[29]李晨懿,杨家莉,徐永海,等.模糊综合评价在电压暂降源识别中的应用[J].电网技术,2017,41(3):1022-1028.Li Chenyi,Yang Jiali,Xu Yonghai,et al.Application of comprehensive fuzzy evaluation method on recognition of voltage sag disturbance sources[J].Power System Technology,2017,41(3):1022-1028(in Chinese).
[30]郑莹,王建新,陈建二.Steiner Tree问题的研究进展[J].计算机科学,2011,38(10):16-22.Zheng Ying,Wang Jianxin,Chen Jianer.Survey of steiner tree problem[J].Computer Science,2011,38(10):16-22(in Chinese).
[31]Karaboga D,Basturk B.A powerful and efficient algorithm for numerical function optimization:artificial bee colony(ABC)algorithm[J].Journal of Global Optimization,2007,39(3):459-471.
[2]潘旭东,吴军,刘涤尘,等.基于元件重要度的差异化规划核心骨干网架构建方法[J].电力系统自动化,2014,38(19):40-46.Pan Xudong,Wu Jun,Liu Dichen,et al.A method for constructing core backbone grid in differential planning based on importance degrees of components[J].Automation of Electric Power Systems,2014,38(19):40-46(in Chinese).
[3]董飞飞,刘涤尘,吴军,等.基于改进BBO优化算法和电网生存性的核心骨干网架构建[J].中国电机工程学报,2014,34(16):2659-2667.Dong Feifei,Liu Dichen,Wu Jun,et al.A method of constructing core backbone grid based on improved BBO optimization algorithm and survivability of power grid[J].Proceedings of the CSEE,2014,34(16):2659-2667(in Chinese).
[4]王浩磊,刘涤尘,吴军,等.基于改进二进制量子粒子群算法的核心骨干网架搜索[J].中国电机工程学报,2014,34(34):6127-6133.Wang Haolei,Liu Dichen,Wu Jun,et al.Core backbone network searching based on improved quantum binary particle swarm optimization[J].Proceedings of the CSEE,2014,34(34):6127-6133(in Chinese).
[5]洪运福.基于复杂网络的输电网差异化规划研究[D].北京:华北电力大学,2012.
[6]赵一婕,刘涤尘,吴军,等.基于线性判别分析与主成分分析的骨干网架生存性评估方法[J].电网技术,2014,38(2):388-394.Zhao Yijie,Liu Dichen,Wu Jun,et al.Survivability evaluation of backbone network based on linear discriminant analysis and principal component analysis[J].Power System Technology,2014,38(2):388-394(in Chinese).
[7]白建华,辛颂旭,刘俊,等.中国实现高比例可再生能源发展路径研究[J].中国电机工程学报,2015,35(14):3699-3705.Bai Jianhua,Xin Songxu,Liu Jun,et al.Roadmap of realizing the high penetration renewable energy in China[J].Proceedings of the CSEE,2015,35(14):3699-3705(in Chinese).
[8]鲁宗相,李海波,乔颖.含高比例可再生能源电力系统灵活性规划及挑战[J].电力系统自动化,2016,40(13):147-158.Lu Zongxiang,Li Haibo,Qiao Ying.Power system flexibility planning and challenges considering high proportion of renewable energy[J].Automation of Electric Power Systems,2016,40(13):147-158(in Chinese).
[9]Golshani A,Sun W,Zhou Q,et al.Incorporating wind energy in power system restoration planning[J].IEEE Transactions on Smart Grid,2018,PP(99):1-1.
[10]Zhao Y,Lin Z,Ding Y,et al.A model predictive control based generator start-up optimization strategy for restoration with microgrids as black-start resources[J].IEEE Transactions on Power Systems,2018,PP(99):1-1.
[11]廖萍,李兴源.风电场穿透功率极限计算方法综述[J].电网技术,2008,32(10):50-53.Liao Ping,Li Xingyuan.A survey on calculation methods of wind power penetration limit[J].Power System Technology,2008,32(10):50-53(in Chinese).
[12]董开松,胡殿刚,秦睿,等.考虑系统运行风险的风电穿透功率极限动态求解方法[J].高电压技术,2015,41(10):3422-3427.Dong Kaisong,Hu Diangang,Qin Rui,et al.Dynamic method for solving wind power penetration limit considering system operation risk[J].High Voltage Engineering,2015,41(10):3422-3427(in Chinese).
[13]徐岩,闫少波,史迪锋.基于近似线性规划法的弱电网光伏穿透功率极限计算[J].电力自动化设备,2014,34(4):128-132.Xu Yan,Yan Shaobo,Shi Difeng.Power penetration limit calculation based on approximate linear programming for PV power station in weak grid[J].Electric Power Automation Equipment,2014,34(4):128-132(in Chinese).
[14]张泽聪.抽取复杂网络中的骨干结构的方法研究[D].北京:北京邮电大学,2014.
[15]任卓明,邵凤,刘建国,等.基于度与聚集系数的网络节点重要性度量方法研究[J].物理学报,2013,62(12):128901.Ren Zhuoming,Shao Feng,Liu Jianguo,et al.Node importance measurement based on the degree and clustering coefficient information[J].Acta Physica Sinica,2013,62(12):128901(in Chinese).
[16]孙璞玉,张焰,罗雯清.考虑网架覆盖率与分散度的网架重构优化[J].电网技术,2015,39(1):271-278.Sun Puyu,Zhang Yan,Luo Wenqing.Optimization of backbone network reconfiguration considering network coverage rate and dispersion degree[J].Power System Technology,2015,39(1):271-278(in Chinese).
[17]Du Y,Gao C,Chen X,et al.A new closeness centrality measure via effective distance in complex networks[J].Chaos,2015,25(3):033112.
[18]Brockmann D,Helbing D.The hidden geometry of complex,network-riven contagion phenomena[J].Science,2013,342(6164):1337-1342.
[19]刘巨,姚伟,文劲宇,等.大规模风电参与系统频率调整的技术展望[J].电网技术,2014,38(3):638-646.Liu Ju,Yao Wei,Wen Jinyu,et al.Prospect of technology for large-scale wind farm participating into power grid frequency regulation[J].Power System Technology,2014,38(3):638-646(in Chinese).
[20]Chang-Chien L R,Yin Y C.Strategies for operating wind power in a similar manner of conventional power plant[J].IEEE Transactions on Power Systems,2009,24(4):926-933.
[21]汪海蛟,江全元.应用于平抑风电功率波动的储能系统控制与配置综述[J].电力系统自动化,2014,38(19):126-135.Wang Haijiao,Jiang Quanyuan.An overview of control and configuration of energy storage system used for wind power fluctuation mitigation[J].Automation of Electric Power Systems,2014,38(19):126-135(in Chinese).
[22]袁小明,程时杰,文劲宇.储能技术在解决大规模风电并网问题中的应用前景分析[J].电力系统自动化,2013,37(1):14-18.Yuan Xiaoming,Cheng Shijie,Wen Jinyu.Prospects analysis of energy storage application in grid integration of large-scale wind power[J].Automation of Electric Power Systems,2013,37(1):14-18(in Chinese).
[23]Marion B,Adelstein J,Boyle K,et al.Performance parameters for grid-connected PV systems[C]//Proc of the 31st IEEE Photovoltaics Specialists Conference and Exhibition,2005,Lake Buena Vista,FL,USA:1601-1606.
[24]李芬,陈正洪,蔡涛,等.并网光伏系统性能精细化评估方法研究[J].太阳能学报,2013,34(6):974-983.Li Fen,Chen Zhenghong,Cai Tao,et al.Refinement assessment method of grid-connected PV system performance[J].Acta Energiae Solaris Sinica,2013,34(6):974-983(in Chinese).
[25]曹清山,郑梦莲,丁一,等.新电改背景下基于多属性决策的电力客户评估和选择研究[J].电网技术,2018,42(1):117-125.Cao Qingshan,Zheng Menglian,Ding Yi,et al.Multi-attribute decision making model for customer evaluation and selection in electricity market[J].Power System Technology,2018,42(1):117-125(in Chinese).
[26]Li X,Wang K,Liu L,et al.Application of the entropy weight and TOPSIS method in safety evaluation of coal mines[J].Procedia Engineering,2011,26(4):2085-2091.
[27]卢锦玲,张津,丁茂生.含风电的电力系统调度经济性评价[J].电网技术,2016,40(8):2258-2264.Lu Jinling,Zhang Jin,Ding Maosheng.Economic evaluation of power system dispatch integrated with wind power[J].Power System Technology,2016,40(8):2258-2264(in Chinese).
[28]彭显刚,林利祥,翁奕珊,等.基于模糊综合评判和综合赋权的抗灾型配电网骨干网架规划[J].电力系统自动化,2015,39(12):172-178.Peng Xiangang,Lin Lixiang,Weng Yishan,et al.Decision-making method for anti-disaster distribution network backbone upgrade based on fuzzy comprehensive evaluation and comprehensive weights[J].Automation of Electric Power Systems,2015,39(12):172-178(in Chinese).
[29]李晨懿,杨家莉,徐永海,等.模糊综合评价在电压暂降源识别中的应用[J].电网技术,2017,41(3):1022-1028.Li Chenyi,Yang Jiali,Xu Yonghai,et al.Application of comprehensive fuzzy evaluation method on recognition of voltage sag disturbance sources[J].Power System Technology,2017,41(3):1022-1028(in Chinese).
[30]郑莹,王建新,陈建二.Steiner Tree问题的研究进展[J].计算机科学,2011,38(10):16-22.Zheng Ying,Wang Jianxin,Chen Jianer.Survey of steiner tree problem[J].Computer Science,2011,38(10):16-22(in Chinese).
[31]Karaboga D,Basturk B.A powerful and efficient algorithm for numerical function optimization:artificial bee colony(ABC)algorithm[J].Journal of Global Optimization,2007,39(3):459-471.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |