Article(id=1284794230157586712, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, articleNumber=null, orderNo=null, doi=10.19912/j.0254-0096.tynxb.2025-0073, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736438400000, receivedDateStr=2025-01-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1784248414791, onlineDateStr=2026-07-17, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1784248414791, onlineIssueDateStr=2026-07-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1784248414791, creator=13701087609, updateTime=1784248414791, updator=13701087609, issue=Issue{id=1284794217658560734, tenantId=1146029695717560320, journalId=1283840536528293913, year='2026', volume='47', issue='6', pageStart='1', pageEnd='814', issueExtLink='null', onlineDate='null', pubDate='1783180800000', pubDateStr='2026-07-05', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1784248411812, creator='13701087609', updateTime=1784252840208, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1284812791785689442, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1284812791785689443, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=280, endPage=287, ext={EN=ArticleExt(id=1284794230463770906, articleId=1284794230157586712, tenantId=1146029695717560320, journalId=1283840536528293913, language=EN, title=LOSS-MINIMIZATION-BASED REACTIVE POWER OPTIMIZATION STRATEGY FOR WIND FARMS, columnId=null, journalTitle=Acta Energiae Solaris Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=When the grid dispatch center issues a reactive power command value, the wind farm needs to rationally allocate this command value to each wind turbine generator (WTG) to meet grid stability requirements. To achieve this objective, this paper proposes a loss-minimization-based reactive power optimization control strategy for onshore wind farms. An improved particle swarm optimization (PSO) algorithm is employed to optimize the reactive power reference value for each WTG, aiming to reduce total losses within the wind farm. These losses encompass generator losses, power converter losses, filter losses, transformer losses, and transmission line losses. To validate the effectiveness of the proposed strategy, a wind farm model with a 5×5 layout is established. Simulation studies compare the conventional reactive power control strategy with the proposed loss-minimization-based reactive power optimization control strategy under different scenarios. The simulation results demonstrate that the proposed optimization strategy significantly reduces power losses in the wind farm., authors=Liu Jun, Zhao Xuanbo, Ge Lei, Chen Zhengliang, authorsList=Liu Jun, Zhao Xuanbo, Ge Lei, Chen Zhengliang, authorCompany=School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1284794230375690521, articleId=1284794230157586712, tenantId=1146029695717560320, journalId=1283840536528293913, language=CN, title=基于损耗最小化的风电场无功优化策略, columnId=null, journalTitle=太阳能学报, columnName=null, runingTitle=null, highlight=null, articleAbstract=当电网调度中心下达无功指令值时,风电场需要将无功指令值合理分配给每台风电机组,从而满足电网稳定运行要求。为实现此目标,提出一种基于损耗最小化的陆上风电场无功优化运行策略,采用改进粒子群优化算法优化每台风电机组的无功功率参考值,以减少风电场的总损耗,包括发电机损耗、变流器损耗、滤波器损耗、变压器损耗和传输线路的损耗。为验证策略的有效性,设置5行5列布局的风电场模型,对常规的无功控制策略与基于损耗最小化的无功优化控制策略在不同场景下进行仿真研究,仿真结果表明该文所提无功优化运行策略能够显著减小风电场的功率损耗。, authors=刘军, 赵宣博, 葛磊, 陈正亮, authorsList=刘军, 赵宣博, 葛磊, 陈正亮, authorCompany=西安理工大学自动化与信息工程学院,西安 710048, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=olbnIFEUxxxqzw6dTdrCbA==, pdfFileSize=1333369, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=陕西省重点研发计划(2021GY-106); 西安市攻关项目(5025))}, authors=null, 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[10] AMARIS H, ALONSO M.Coordinated reactive power management in power networks with wind turbines and FACTS devices[J]. Energy conversion and management, 2011, 52(7): 2575-2586. [11] HE J, LI Q, MA J, et al.Research on capacity configuration method of concentrated reactive power compensator for wind farm LVRT capability[J]. The journal of engineering, 2017, 2017(13): 2428-2432. [12] ZHANG B H, HU W H, HOU P, et al.Review of reactive power dispatch strategies for loss minimization in a DFIG-based wind farm[J]. Energies, 2017, 10(7): 856. [13] KANNA B, SINGH S N.Towards reactive power dispatch within a wind farm using hybrid PSO[J]. International journal of electrical power & energy systems, 2015, 69: 232-240. [14] ZHAO B, GUO C X, CAO Y J.A multiagent-based particle swarm optimization approach for optimal reactive power dispatch[J]. IEEE transactions on power systems, 2005, 20(2): 1070-1078. [15] 李丽霞, 姚兴佳, 王晓东, 等. 双馈风电场新型无功优化分配策略研究[J]. 太阳能学报, 2017, 38(5): 1397-1404. LI L X, YAO X J, WANG X D, et al.An optimal reactive power dispatch strategy for interior-point method based wind farms[J]. Acta energiae solaris sinica, 2017, 38(5): 1397-1404. [16] ULLAH N R, BHATTACHARYA K, THIRINGER T.Wind farms as reactive power ancillary service providers: technical and economic issues[J]. IEEE transactions on energy conversion, 2009, 24(3): 661-672. [17] ZHANG B H, HOU P, HU W H, et al.A reactive power dispatch strategy with loss minimization for a DFIG-based wind farm[J]. IEEE transactions on sustainable energy, 2016, 7(3): 914-923. [18] 荣飞, 李培瑶, 周诗嘉. 双馈风电场损耗最小化的有功无功协调优化控制[J]. 电工技术学报, 2020, 35(3): 520-529. RONG F, LI P Y, ZHOU S J.Coordinated optimal control with loss minimization for active and reactive power of doubly fed induction generator-based wind farm[J]. Transactions of China Electrotechnical Society, 2020, 35(3): 520-529. [19] 刘军, 赵航, 刘安东. 基于机组分类的风电场有功功率分配方法研究[J]. 太阳能学报, 2023, 44(8): 396-403. LIU J, ZHAO H, LIU A D.Study on active power distribution method of wind farm based on unit classification[J]. Acta energiae solaris sinica, 2023, 44(8): 396-403. [20] 刘军, 武培东, 王启超, 等. 基于尾流重定向风电场输出功率与载荷的联合优化[J]. 太阳能学报, 2025, 46(2): 607-614. LIU J, WU P D, WANG Q C, et al.Joint optimization of wind farm output power and load based on wake redirection[J]. Acta energiae solaris sinica, 2025, 46(2): 607-614.)
太阳能学报
2026
, 47
(6) :
280
-287
基于损耗最小化的风电场无功优化策略
全屏
刘军, 赵宣博, 葛磊, 陈正亮
作者信息
西安理工大学自动化与信息工程学院,西安 710048
LOSS-MINIMIZATION-BASED REACTIVE POWER OPTIMIZATION STRATEGY FOR WIND FARMS
Liu Jun, Zhao Xuanbo, Ge Lei, Chen Zhengliang
Affiliations
School of Automation and Information Engineering, Xi'an University of Technology, Xi'an 710048, China
doi: 10.19912/j.0254-0096.tynxb.2025-0073
文章导航
当电网调度中心下达无功指令值时,风电场需要将无功指令值合理分配给每台风电机组,从而满足电网稳定运行要求。为实现此目标,提出一种基于损耗最小化的陆上风电场无功优化运行策略,采用改进粒子群优化算法优化每台风电机组的无功功率参考值,以减少风电场的总损耗,包括发电机损耗、变流器损耗、滤波器损耗、变压器损耗和传输线路的损耗。为验证策略的有效性,设置5行5列布局的风电场模型,对常规的无功控制策略与基于损耗最小化的无功优化控制策略在不同场景下进行仿真研究,仿真结果表明该文所提无功优化运行策略能够显著减小风电场的功率损耗。
风电场
/
无功优化控制策略
/
损耗最小化
/
尾流效应
/
永磁同步风电机组
When the grid dispatch center issues a reactive power command value, the wind farm needs to rationally allocate this command value to each wind turbine generator (WTG) to meet grid stability requirements. To achieve this objective, this paper proposes a loss-minimization-based reactive power optimization control strategy for onshore wind farms. An improved particle swarm optimization (PSO) algorithm is employed to optimize the reactive power reference value for each WTG, aiming to reduce total losses within the wind farm. These losses encompass generator losses, power converter losses, filter losses, transformer losses, and transmission line losses. To validate the effectiveness of the proposed strategy, a wind farm model with a 5×5 layout is established. Simulation studies compare the conventional reactive power control strategy with the proposed loss-minimization-based reactive power optimization control strategy under different scenarios. The simulation results demonstrate that the proposed optimization strategy significantly reduces power losses in the wind farm.
wind farm
/
reactive power optimization control strategy
/
loss minimization
/
wake effect
/
PMSG
刘军, 赵宣博, 葛磊, 陈正亮.
基于损耗最小化的风电场无功优化策略.
太阳能学报,
2026
, 47
(6)
: 280
-287
.
DOI: 10.19912/j.0254-0096.tynxb.2025-0073
Liu Jun, Zhao Xuanbo, Ge Lei, Chen Zhengliang.
LOSS-MINIMIZATION-BASED REACTIVE POWER OPTIMIZATION STRATEGY FOR WIND FARMS[J].
Acta Energiae Solaris Sinica ,
2026
, 47
(6)
: 280
-287
.
DOI: 10.19912/j.0254-0096.tynxb.2025-0073
参考文献
引证文献
[1] GB/T 19963—2011, 风电场接入电力系统技术规定[S]. GB/T 19963—2011, Technical rule for connecting wind farm to power system[S]. [2] TAPIA G, TAPIA A, OSTOLAZA J X.Proportional-integral regulator-based approach to wind farm reactive power management for secondary voltage control[J]. IEEE transactions on energy conversion, 2007, 22(2): 488-498. [3] MOHSENI-BONAB S M, RABIEE A. Optimal reactive power dispatch: a review, and a new stochastic voltage stability constrained multi-objective model at the presence of uncertain wind power generation[J]. IET generation, transmission & distribution, 2017, 11(4): 815-829. [4] RAMIREZ J M, GONZALEZ J M, RUBEN T O.An investigation about the impact of the optimal reactive power dispatch solved by DE[J]. International journal of electrical power & energy systems, 2011, 33(2): 236-244. [5] MARTINEZ-ROJAS M, SUMPER A, GOMIS-BELLMUNT O, et al.Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search[J]. Applied energy, 2011, 88(12): 4678-4686. [6] ABOU EL ELA A A, ABIDO M A, SPEA S R. Differential evolution algorithm for optimal reactive power dispatch[J]. Electric power systems research, 2011, 81(2): 458-464. [7] ZHANG B H, HU W H, HOU P, et al.Reactive power dispatch for loss minimization of a doubly fed induction generator based wind farm[C]//2014 17th International Conference on Electrical Machines and Systems (ICEMS). Hangzhou, China, 2015: 1373-1378. [8] 杨铎烔, 俞靖一, 葛俊, 等. 海上风电场自适应多目标无功优化控制策略[J]. 电力工程技术, 2024, 43(3): 121-129. YANG D D, YU J Y, GE J, et al.Adaptive multi-objective reactive power optimization control strategy for offshore wind farms[J]. Jiangsu electrical engineering, 2024, 43(3): 121-129. [9] 胡畔, 丁凯, 江克证, 等. 计及无功资源调配成本的风电场优化技术[J]. 可再生能源, 2024, 42(4): 522-529. HU P, DING K, JIANG K Z, et al.Reactive power optimization technology for wind farms considering the reactive power resources allocation cost[J]. Renewable energy resources, 2024, 42(4): 522-529. [10] AMARIS H, ALONSO M.Coordinated reactive power management in power networks with wind turbines and FACTS devices[J]. Energy conversion and management, 2011, 52(7): 2575-2586. [11] HE J, LI Q, MA J, et al.Research on capacity configuration method of concentrated reactive power compensator for wind farm LVRT capability[J]. The journal of engineering, 2017, 2017(13): 2428-2432. [12] ZHANG B H, HU W H, HOU P, et al.Review of reactive power dispatch strategies for loss minimization in a DFIG-based wind farm[J]. Energies, 2017, 10(7): 856. [13] KANNA B, SINGH S N.Towards reactive power dispatch within a wind farm using hybrid PSO[J]. International journal of electrical power & energy systems, 2015, 69: 232-240. [14] ZHAO B, GUO C X, CAO Y J.A multiagent-based particle swarm optimization approach for optimal reactive power dispatch[J]. IEEE transactions on power systems, 2005, 20(2): 1070-1078. [15] 李丽霞, 姚兴佳, 王晓东, 等. 双馈风电场新型无功优化分配策略研究[J]. 太阳能学报, 2017, 38(5): 1397-1404. LI L X, YAO X J, WANG X D, et al.An optimal reactive power dispatch strategy for interior-point method based wind farms[J]. Acta energiae solaris sinica, 2017, 38(5): 1397-1404. [16] ULLAH N R, BHATTACHARYA K, THIRINGER T.Wind farms as reactive power ancillary service providers: technical and economic issues[J]. IEEE transactions on energy conversion, 2009, 24(3): 661-672. [17] ZHANG B H, HOU P, HU W H, et al.A reactive power dispatch strategy with loss minimization for a DFIG-based wind farm[J]. IEEE transactions on sustainable energy, 2016, 7(3): 914-923. [18] 荣飞, 李培瑶, 周诗嘉. 双馈风电场损耗最小化的有功无功协调优化控制[J]. 电工技术学报, 2020, 35(3): 520-529. RONG F, LI P Y, ZHOU S J.Coordinated optimal control with loss minimization for active and reactive power of doubly fed induction generator-based wind farm[J]. Transactions of China Electrotechnical Society, 2020, 35(3): 520-529. [19] 刘军, 赵航, 刘安东. 基于机组分类的风电场有功功率分配方法研究[J]. 太阳能学报, 2023, 44(8): 396-403. LIU J, ZHAO H, LIU A D.Study on active power distribution method of wind farm based on unit classification[J]. Acta energiae solaris sinica, 2023, 44(8): 396-403. [20] 刘军, 武培东, 王启超, 等. 基于尾流重定向风电场输出功率与载荷的联合优化[J]. 太阳能学报, 2025, 46(2): 607-614. LIU J, WU P D, WANG Q C, et al.Joint optimization of wind farm output power and load based on wake redirection[J]. Acta energiae solaris sinica, 2025, 46(2): 607-614.
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doi: 10.19912/j.0254-0096.tynxb.2025-0073
接收时间:2025-01-10
首发时间:2026-07-17
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2种不同金属材料的力学参数
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