[1] 张宁, 康重庆, 肖晋宇, 等. 风电容量可信度研究综述与展望[J]. 中国电机工程学报, 2015, 35(1): 82–94
ZHANG Ning, KANG Chongqing, XIAO Jinyu, et al. Review and prospect of wind power capacity credit[J]. Proceedings of the CSEE, 2015, 35(1): 82–94
[2] 孙笑雨, 于源, 孟垂懿, 等. 考虑大规模光伏和风电接入的主动配电网无功电源综合规划[J]. 智慧电力, 2020, 48(9): 16–22
SUN Xiaoyu, YU Yuan, MENG Chuiyi, et al. Comprehensive planning of reactive power supply for active distribution network accessed with large-scale photovoltaic and wind power[J]. Smart Power, 2020, 48(9): 16–22
[3] 杨修宇, 穆钢, 柴国峰, 等. 考虑灵活性供需平衡的源-储-网一体化规划方法[J]. 电网技术, 2020, 44(9): 3238–3246
YANG Xiuyu, MU Gang, CHAI Guofeng, et al. Source-storage-grid integrated planning considering flexible supply-demand balance[J]. Power System Technology, 2020, 44(9): 3238–3246
[4] 时智勇, 王彩霞, 李琼慧. “十四五”中国海上风电发展关键问题[J]. 中国电力, 2020, 53(7): 8–17
SHI Zhiyong, WANG Caixia, LI Qionghui. Key issues of China's offshore wind power development in the “14th five-year plan”[J]. Electric Power, 2020, 53(7): 8–17
[5] 高伟, 吴昌松, 乔光辉, 等. 风电产业研发资助政策的传导效果实证研究[J]. 中国软科学, 2017(11): 54–65
GAO Wei, WU Changsong, QIAO Guanghui, et al. The empirical study on the transmission effect of R & D funding policies in China's wind power industry[J]. China Soft Science, 2017(11): 54–65
[6] 高建刚, 马中东, 王丙毅. 基于结构方程模型的中国风能产业发展障碍因素研究[J]. 中国软科学, 2016(12): 24–36
GAO Jiangang, MA Zhongdong, WANG Bingyi. Research on the obstacles to the development of China's wind energy industry using SEM[J]. China Soft Science, 2016(12): 24–36
[7] LIU Y X, REN L Z, LI Y B, et al. The industrial performance of wind power industry in China[J]. Renewable and Sustainable Energy Reviews, 2015, 43: 644–655.
[8] RAADAL H L, VOLD B I, MYHR A, et al. GHG emissions and energy performance of offshore wind power[J]. Renewable Energy, 2014, 66: 314–324.
[9] WU Y N, LI Y, BA X, et al. Post-evaluation indicator framework for wind farm planning in China[J]. Renewable and Sustainable Energy Reviews, 2013, 17: 26–34.
[10] SHI R J, FAN X C, HE Y. Comprehensive evaluation index system for wind power utilization levels in wind farms in China[J]. Renewable and Sustainable Energy Reviews, 2017, 69: 461–471.
[11] 田鑫, 张健, 李雪亮, 等. 基于时序运行模拟的山东电网光伏发电消纳能力评估[J]. 电力系统保护与控制, 2020, 48(8): 34–43
TIAN Xin, ZHANG Jian, LI Xueliang, et al. Evaluating photovoltaic accommodation ability for the Shandong power system based on sequential operation simulation[J]. Power System Protection and Control, 2020, 48(8): 34–43
[12] 李俊, 王振宇, 向洁. 分布式蓄热电锅炉对弃风电量的消纳能力评估[J]. 电力科学与技术学报, 2021, 36(1): 185–191
LI Jun, WANG Zhenyu, XIANG jie. Study on ability of distributed electric boilers with thermal storage in abandoned wind power consumption[J]. Journal of Electric Power Science and Technology, 2021, 36(1): 185–191
[13] HULIO Z H, JIANG W. Assessment of the apparent performance characterization along with levelized cost of energy of wind power plants considering real data[J]. Energy Exploration & Exploitation, 2018, 36(6): 1708–1728.
[14] LIU J K, GAO C Y, REN J Z, et al. Wind resource potential assessment using a long term tower measurement approach: a case study of Beijing in China[J]. Journal of Cleaner Production, 2018, 174: 917–926.
[15] ZHANG J, ZHANG J W, CAI L, et al. Energy performance of wind power in China: a comparison among inland, coastal and offshore wind farms[J]. Journal of Cleaner Production, 2017, 143: 836–842.
[16] LO S F, WU C Y. Evaluating the performance of wind farms in China: an empirical review[J]. International Journal of Electrical Power & Energy Systems, 2015, 69: 58–66.
[17] 王宏钧. 基于熵权法和变权理论的风电机组发电性能评估模型[D]. 北京: 华北电力大学(北京), 2020.
WANG Hongjun. Evaluation model of power generation performance for wind turbine based on entropy weight method and contingeney theory[D]. Beijing: North China Electric Power University (Beijing) , 2020.
[18] ZHAO X G, WEI Z. The technical efficiency of China's wind power list enterprises: an estimation based on DEA method and micro-data[J]. Renewable Energy, 2019, 133: 470–479.
[19] 董福贵, 吴南南, 么峻, 等. 大规模风电并网背景下火电调峰行为演化博弈模型[J]. 中国电力, 2018, 51(9): 151–157
DONG Fugui, WU Nannan, YAO Jun, et al. Study on evolutionary game model of thermal power regulation in largescale wind power grid integration[J]. Electric Power, 2018, 51(9): 151–157
[20] REN G R, WAN J, LIU J F, et al. Spatial and temporal correlation analysis of wind power between different provinces in China[J]. Energy, 2020, 191: 116514.
[21] ANTONINI E, CALDEIRA K. Spatial constraints in large-scale expansion of wind power plants[J]. Proceedings of the National Academy of Sciences, 2021, 118(27): 118.
[22] 李勇, 檀楠楠. 我国医疗卫生资源配置效率的实证[J]. 统计与决策, 2021, 37(13): 80–83
LI Yong, TAN Nannan. An empirical study on the efficiency of allocation of medical and health resources in my country[J]. Statistics & Decision, 2021, 37(13): 80–83
[23] 赖一飞, 谢潘佳, 叶丽婷, 等. 我国区域科技创新效率测评及影响因素研究: 基于超效率SBM-Malmquist-Tobit模型[J]. 科技进步与对策, 2021, 38(13): 37–45
LAI Yifei, XIE Panjia, YE Liting, et al. Research on the efficiency and influencing factors of science and technology innovation in China: based on the super-efficiency SBM-malmquist-Tobit model[J]. Science & Technology Progress and Policy, 2021, 38(13): 37–45
[24] ANDERSON D. Energy efficiency and the economists: the case for a policy based on economic principles[J]. Annual Review of Energy and the Environment, 1995, 20: 495–511.
[25] 赵文会, 钟孔露, 毛璐, 等. 基于超效率DEA和Malmquist指数的三北地区风电经济效益评价[J]. 可再生能源, 2016, 34(3): 448–453
ZHAO Wenhui, ZHONG Konglu, MAO Lu, et al. Research on economic benefits of wind power in three northern regions based on the ultra-efficiency DEA and malmquist index[J]. Renewable Energy Resources, 2016, 34(3): 448–453
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