基于风电机组可靠性的风电场平准化成本模型研究

doi:10.19912/j.0254-0096.tynxb.2020-1382

太阳能学报 ›› 2022, Vol. 43 ›› Issue (10): 304-311.DOI: 10.19912/j.0254-0096.tynxb.2020-1382

基于风电机组可靠性的风电场平准化成本模型研究

刘喜梅¹, 崔阳², 董建明^3,4, 王开让^3,4

1. 河北金融学院管理学院,保定 071051;
2. 电力规划设计总院（电力规划总院有限公司）,北京 100011;
3. 国网冀北电力有限公司电力科学研究院（华北电力科学研究院有限责任公司）,北京 100045;
4. 风光储并网运行技术国家电网公司重点实验室,北京 100045

收稿日期:2020-12-22 出版日期:2022-10-28 发布日期:2023-04-28
通讯作者: 刘喜梅（1985——）,女,博士,主要从事新能源技术经济评价、能源政策等方面的研究。meimeiliu126@163.com
基金资助:
国家科技支撑计划（2015BAA06B03）

RESEARCH ON LEVELIZED COST MODEL OF WIND FARMS BASED ON WIND TURBINE RELIABILITY

Liu Ximei¹, Cui Yang², Dong Jianming^3,4, Wang Kairang^3,4

1. School of Management, Hebei Finance University, Baoding 071051, China;
2. China Electric Power Planning &Engineering Institute（China Electric Power Planning & Engineering lnstitute Co., Ltd.）, Beijing 100011, China;
3. State Grid Jibei Electric Power Co., Ltd. Research Institute, North China Electric Power Research Institute Co., Ltd., Beijing 100045, China;
4. Grid-Connected Opeartion Technology for Wind-Solar-Storage Hybrid System State Grid Corporation Key Laboratory, Beijing 100045, China

Received:2020-12-22 Online:2022-10-28 Published:2023-04-28

摘要/Abstract

摘要： 考虑综合风电场总体运行成本、风电机组可靠性及风电场发电量等多个维度,从风电场全生命周期视角出发,建立基于风电机组可靠性的风电场平准化成本模型,并通过算例分析得出,提升风电机组可靠性可降低风电机组的故障维护成本,提高风电场运行小时数,进而降低风电场平准化成本。在此基础上测算当前阶段风电实现平价上网需达到的利用小时数,最后给出促进风电发展的合理化建议。

关键词: 风电成本, 风电机组, 可靠性, 风电运维, 平准化成本, 风电利用小时数

Abstract: As the reform of the electricity market continues to deepen, the wind power industry faces the dual pressures of “subsidy decline” and “reducing wind power cost”. The key to realizing wind on-grid price equal to the benchmark price of thermal power is to reduce the cost of wind power and improve its competitiveness in the power market. This paper comprehensively considers the overall operating cost of wind farms, the reliability of wind turbines, and the power generation of wind farms, establishes a Levelized Cost of Energy model for wind farms based on wind turbine reliability from the perspective of the full life cycle of wind farms. With the help of a quantitative analysis example, it is concluded that improving the reliability of the wind turbine reliability can reduce the fault maintenance cost and increase the operating hours of the wind farm, which achieve the goal of reducing the cost of Levelized Cost of wind power. On this basis, the wind power utilization hours meeting to on-grid price equal to the benchmark price of thermal power is estimated. Furthermore, the paper gives suggestions for promoting wind power development.

Key words: wind power cost, wind turbines, reliability, wind power operation and maintenance, levelized cost, wind power utilization hours

中图分类号:

TM761

刘喜梅, 崔阳, 董建明, 王开让. 基于风电机组可靠性的风电场平准化成本模型研究[J]. 太阳能学报, 2022, 43(10): 304-311.

Liu Ximei, Cui Yang, Dong Jianming, Wang Kairang. RESEARCH ON LEVELIZED COST MODEL OF WIND FARMS BASED ON WIND TURBINE RELIABILITY[J]. Acta Energiae Solaris Sinica, 2022, 43(10): 304-311.

参考文献

[1] 国家统计局. 中华人民共和国2020年国民经济和社会发展统计公报[EB/OL]. http://www.stats.gov.cn/tjsj/zxfb/ 202102/t20210227_1814154.html
[2] 王仲颖,时璟丽, 赵勇强.能源技术路线图-中国风电发展路线图2050[R]. 2011.
[3] ANASTASIA I, ANDREW A, FEARGAL B.Parametric capex, opex, and lcoe expressions for offshore wind farms based on global deployment parameters[J]. Energy sources, part B: economics, planning, and policy, 2018, 13(5): 281-290.
[4] MILLER L, CARRIVEAU R, HARPER S, et al.Evaluating the link between LCOE and PPA elements and structure for wind energy[J]. Energy strategy reviews, 2017, 16: 33-42.
[5] BRUCK M, SANDBORN P, GOUDARZI N.A levelized cost of energy (LCOE) model for wind farms that include power purchase agreements (PPAs)[J]. Renewable energy, 2018, 122: 131-139.
[6] ASHURI T, ZAAIJER M B, MARTINS J R R A, et al. Multidisciplinary design optimization of offshore wind turbines for minimum levelized cost of energy[J]. Renewable energy, 2014, 68: 893-905.
[7] DIAF S, DIAF D, BELHAMEL M, et al.A methodology for optimal sizing of autonomous hybrid PV/wind system[J]. Energy policy, 2007, 35(11): 5708-5718.
[8] LANTZ E, WISER R, HAND M.The past and future cost of wind energy[R]. National renewable energy laboratory, golden, CO, report No.NREL/TP-6A20-53510, 2012.
[9] HIRTH L, UECKERDT F, EDENHOFER O.Integration costs revisited-an economic framework for wind and solar variability[J]. Renewable energy, 2015, 74: 925-939.
[10] UECKERDT F, HIRTH L, LUDERER G, et al.System LCOE: what are the costs of variable renewables[J]. Energy, 2013, 63: 61-75.
[11] LIU Z F, ZHANG W H, ZHAO C H, et al.The economics of wind power in China and policy implications[J]. Energies, 2015, 8(2): 1529-1546.
[12] CORY K S, SCHWABE P.Wind levelized cost of energy: a comparison of technical and financing input variables[R]. National renewable energy laboratory, goladen, CO, 2009.
[13] GIELEN D.Renewable energy technologies: cost analysis series-wind power[R]. Volume 1: Power Sector Issue, 2012.
[14] LANTZ E, WISER R, HAND M.IEA wind task 26: the past and future cost of wind energy, work package 2[R]. National renewable energy laboratory (NREL), golden, CO, 2012.
[15] 刘喜梅, 白恺, 邓春, 等. 大型风电项目平准化成本模型研究[J]. 可再生能源, 2016, 34(12): 1853-1858.
LIU X M, BAI K, DENG C, et al.Research on levelized cost of energy model of large-scale wind power projects[J]. Renewable energy resources, 2016, 34(12): 1853-1858.
[16] TIMOTHY C.A levelized cost of energy analysis for a mechanical variable speed wind turbine[D]. Durham: Duke University, 2012.
[17] OUYANG X L, LIN B Q.Levelized cost of electricity (LCOE) of renewable energies and required subsidies in China[J]. Energy policy, 2014, 70: 64-73.
[18] PARRADO C, GIRARD A, SIMON F, et al.2050 LCOE (levelized cost of energy) projection for a hybrid PV (photovoltaic)-CSP (concentrated solar power) plant in the Atacama Desert, Chile[J]. Energy, 2016, 94: 422-430.
[19] PAWEL I.The cost of storage-how to calculate the levelized cost of stored energy (LCOE) and applications to renewable energy generation[J]. Energy procedia, 2014, 46: 68-77.
[20] HOANG T K, QUÉVAL L, BERRIAUD C, et al. Design of a 20-MW fully superconducting wind turbine generator to minimize the levelized cost of energy[J]. IEEE transactions on applied superconductivity, 2018, 28(4): 1-5.
[21] MIGNAN A, KARVOUNIS D, Broccardo M, et al.Including seismic risk mitigation measures into the levelized cost of electricity in enhanced geothermal systems for optimal siting[J]. Applied energy, 2019, 238: 831-850.
[22] 李垚, 朱才朝, 陶友传, 等. 风电机组可靠性研究现状与发展趋势[J]. 中国机械工程, 2017, 28(9): 1125-1133.
LI Y, ZHU C C, TAO Y C, et al.Research status and development tendency of wind turbine reliability[J]. China mechanical engineering, 2017, 28(9): 1125-1133.
[23] 王建. 全寿命周期成本理论在电力设备投资决策中的应用研究[D]. 重庆: 重庆大学, 2008.
WANG J.Research on electric equipment investment decision-making based on LCC theory[D]. Chongqing: Chongqing University, 2008.

基于风电机组可靠性的风电场平准化成本模型研究

RESEARCH ON LEVELIZED COST MODEL OF WIND FARMS BASED ON WIND TURBINE RELIABILITY

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	石嫄嫄, 和庆冬, 吴衍剑, 杜君峰, 张敏. 基于多失效模式的海上浮式风电机组结构可靠性研究[J]. 太阳能学报, 2022, 43(9): 236-241.
[2]	花志锋, 赵荣珍. 风电齿轮箱行星轮系的齿面摩擦与齿根裂纹耦合效应计算方法[J]. 太阳能学报, 2022, 43(9): 287-293.
[3]	曹洁, 张玉林, 王进花, 余萍. 基于VMD和SVPSO-BP的滚动轴承故障诊断[J]. 太阳能学报, 2022, 43(9): 294-301.
[4]	张振海, 王维庆, 王海云, 曹源. 基于改进小波包的风电机组齿轮箱复合故障特征提取研究[J]. 太阳能学报, 2022, 43(9): 331-336.
[5]	李雄威, 徐家豪, 李庚达, 崔青汝, 伍权. 一种新修正的风电机组尾流分析模型[J]. 太阳能学报, 2022, 43(8): 260-265.
[6]	齐咏生, 单成成, 高胜利, 刘利强, 董朝轶. 基于AEWT-KELM的风电机组轴承故障诊断策略[J]. 太阳能学报, 2022, 43(8): 281-291.
[7]	李进友, 李媛, 冯冰, 邢作霞, 许增金. 基于随机组合赋权模糊评价的风电机组健康状态评估[J]. 太阳能学报, 2022, 43(8): 340-351.
[8]	刘颖明, 陈亮, 王晓东, 谢洪放. 数据驱动的风电机组偏航参数适应性优化[J]. 太阳能学报, 2022, 43(8): 366-372.
[9]	郭珊珊, 韩巧丽, 王一博, 李明, 刘丹. 实度对低风速风电机组风轮气动性能影响研究[J]. 太阳能学报, 2022, 43(8): 373-381.
[10]	黄玲玲, 李锁, 符杨, 王振帅. 基于风电机组状态的超短期海上风电功率预测[J]. 太阳能学报, 2022, 43(8): 391-398.
[11]	刘杰, 杨娜, 谭玉涛, 孙兴伟. 基于WD-LSTM的风电机组叶片结冰状态评测[J]. 太阳能学报, 2022, 43(8): 399-408.
[12]	张榴晨, 张亚, 茆美琴. 基于任务剖面的单相Boost型功率解耦光伏逆变器寿命预测[J]. 太阳能学报, 2022, 43(7): 109-114.
[13]	毕玉, 朱才朝, 谭建军, 宋海蓝, 杜雪松. 齿根裂纹对风电齿轮箱高速级动态特性影响分析及其故障模式识别[J]. 太阳能学报, 2022, 43(7): 284-292.
[14]	黄德胜, 张旭方, Sørensen John Dalsgaard. 兆瓦级风力机结构系统可靠性分析的样本分数阶矩最大熵方法[J]. 太阳能学报, 2022, 43(7): 293-301.
[15]	李密密, 戴巨川, 陈换过, 杨书仪, 李建涛. 基于光纤传感的风电机组叶片应变传递特性研究[J]. 太阳能学报, 2022, 43(7): 375-384.