Article(id=1317903102594892528, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=0, articleNumber=, orderNo=null, doi=10.19666/j.rlfd.202605123, pmid=, cstr=, oa=1, hot=null, price=null, onlineType=2, articleFormat=null, articleType=null, articleTypeStr=, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792142185115, onlineDateStr=2026-10-16, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=null, onlineIssueDateStr=null, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792142185109, creator=18991841707, updateTime=1792142188342, updator=18991841707, issue=null, startPage=, endPage=, ext={EN=ArticleExt(id=1317903226880504047, articleId=1317903102594892528, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Coordinated optimization strategy for agc and primary frequency regulation of thermal power units oriented to grid dispatching, columnId=null, journalTitle=Thermal Power Generation, columnName=, runingTitle=null, highlight=, articleAbstract=

[Objective] As the accelerated transition toward modern power systems with high-penetration renewable energy integration continuously weakens the equivalent rotational inertia of the grid, 1000 MW ultra-supercritical once-through boiler thermal power units face increasingly strict dispatch performance criteria. Due to their inherent thermodynamic lag and strong non-linear characteristics, these megawatt-class units frequently encounter severe command coupling conflicts and destructive energy clashes when executing automatic generation control and primary frequency regulation instructions simultaneously. To fundamentally resolve these operational bottlenecks, this research introduces a model-driven, coordinated optimization control strategy. 

[Methods] First, adopting a hybrid modeling concept, the intricate steam-water cycle of the boiler is spatially lumped to construct a highly efficient 3rd-order affine non-linear dynamic control model. To guarantee wide-range robustness, an objective-adaptive non-dominated sorting genetic algorithm is employed to perform the online calibration of unknown dynamic parameter matrices, specifically targeting pressure conversion coefficients, energy conversion variables, and thermal time constants. Capitalizing on this reduced-order model's internal boundary constraints, state reconstruction technologies are embedded in the control layer. Specifically, the transient reheat steam flow is extracted through a frequency-domain complementary filtering network to effectively eliminate volume-induced phase delays. Concurrently, the actual equivalent coal feed rate is reverse-calculated via a high-order Butterworth band-pass inversion algorithm to successfully strip away coal transportation delays. Furthermore, aligning strictly with the latest grid auxiliary service assessment rules, a comprehensive coordinated control logic strategy matrix is configured. This matrix features active main steam pressure-raising for energy storage at deep peak-shaving loads, adaptive variable-gain compensation algorithms for small frequency deviations, cross-interlocking protection mechanisms to prevent reverse actions during large frequency deviations, and a discrete micro-step decomposition module for continuous automatic generation control ramp commands. 

[Results] Field test data gathered from an industrial unit thoroughly verify the proposed strategy's exceptional efficacy. The reduced-order mathematical model exhibits remarkable tracking fidelity under wide-range load-varying conditions, maintaining an average main steam pressure prediction error of only 3.15%. Following the control logic upgrade, the initial mechanical response delay for primary frequency regulation was compressed to 2.65 seconds. This drove the monthly primary frequency regulation qualification rate from 62.4% to a stable 81.5%, safely surpassing the penalty-exemption baseline. Simultaneously, the comprehensive automatic generation control performance index registered a leap from 0.51 to 1.18, systematically eradicating power oscillations and inverse adjustments traditionally caused by thermodynamic inertia.

 [Conclusion] Balancing computational efficiency and physical fidelity, the proposed scheme establishes a practical engineering paradigm for 1000 MW units to deeply engage in the ancillary service market through pure software logic reconfiguration. It fundamentally breaks through the response bottlenecks of boiler-turbine coordination and significantly strengthens the unit's support capability for next-generation power systems.

, authors=null, authorsList=null, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=, copyrightStatement=, copyrightOwner=, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=mni56+FrolwPl2iMrvs0YA==, pdf=mni56+FrolwPl2iMrvs0YA==, pdfFileSize=null, pdfExtLink=, richHtmlUrl=, mobilePdfUrl=, reviewReport=, pdfFirstPage=, abstractGraph=, abstractGraphContent=, abstractVideo=null, citation=, cebUrl=, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1317903226867921134, articleId=1317903102594892528, tenantId=1146029695717560320, journalId=1210938733613449225, language=CN, title=适应电网调度的火电机组AGC与一次调频协同优化策略, columnId=null, journalTitle=热力发电, columnName=, runingTitle=null, highlight=, articleAbstract=

【目的】针对新能源并网导致电网惯量削弱,且火电机组执行自动发电控制和一次调频时频发冲突的痛点,本文以1000兆瓦超超临界直流炉火电机组为对象,提出一种模型驱动的机炉协同优化控制策略。

【方法】首先,基于物理集总汽水循环过程,建立三阶仿射非线性动态控制模型,并用自适应遗传算法在线辨识压力与能量转化系数等参数。其次,在控制底层引入状态重构技术,通过频域互补滤波提取暂态再热蒸汽流量,利用高阶逆向反演重构入炉煤等效热值。最后,对接考核细则,设计涵盖提压蓄能、变增益补偿、防冲突交叉闭锁及微阶梯分解的协调控制逻辑策略矩阵。

【结果】实机闭环投运表明,降阶模型变工况预测精度优异。优化后机组一次调频合格率稳超免考线,自动发电控制指标大幅跃升,改善了热惯性引发的功率振荡与能量对冲。

【结论】该方案兼顾计算效率与物理保真度,开辟了百万机组依靠纯软件逻辑重构深度参与辅助服务市场的工程实操范式,从底层突破了机炉协调响应瓶颈,显著增强了机组对新型电力系统的支撑能力。

, authors=null, authorsList=null, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=, copyrightStatement=, copyrightOwner=, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=sPngU8w7DilW0iF4OMPMVg==, pdf=sPngU8w7DilW0iF4OMPMVg==, pdfFileSize=null, pdfExtLink=, richHtmlUrl=, mobilePdfUrl=, reviewReport=, pdfFirstPage=, abstractGraph=, abstractGraphContent=, abstractVideo=null, citation=, cebUrl=, magXmlContent=null, mapNumber=null, fund=null)}, authors=null, keywords=null, refs=null, funds=null, companyList=null, figs=null, attaches=null, journal=Journal(id=1210938006006558725, delFlag=0, nameCn=热力发电, nameEn=Thermal Power Generation, nameHistory1=null, nameHistory2=null, issn=1002-3364, eissn=null, cn=61-1111/TM, coden=null, periodic=0, language=CN, oaType=null, ccby=null, superviseOffice=null, ownerOffice=null, pubOffice=null, editorOffice=null, officeType=null, aims=null, clcCode=null, officeProv=null, officeCity=null, officeAddr=null, officeZip=null, officeEmail=null, officePhone=null, editDirector=null, officeDirector=null, officeDirectorPhone=null, officeStaffNum=null, officeEmpNum=null, coverPicUrl=IcKGK23kpfWlBK6GqYtS5g==, journalPrice=null, startedYear=null, abbrevIsoEn=Thermal Power Generation, journalRemark=null, publicationField=null, createdTime=1766639718774, updatedTime=1784018130043, createdBy=18614031015, updatedBy=13041195026, firstLetterCn=R, firstLetterEn=R, subjectCode=Engineering, subjectName=null, subjectCodeEn=Engineering, subjectNameEn=null, picCn=IcKGK23kpfWlBK6GqYtS5g==, picEn=UzifuamzuAk3uXMVSOtdyA==, jcr=null, cjcr=null, exts=[JournalExt(id=1283828346035356554, language=CN, name=热力发电, nameHistory1=null, nameHistory2=null, managedBy=, sponsoredBy=, publishedBy=, editorOffice=, officeProv=null, officeCity=null, officeAddr=, officeZip=, editDirector=, officeDirector=null, officePhone=null, coverPicUrl=null, journalRemark=, submitArticleUrl=null, websiteUrl=, createdTime=1784018130072, updatedTime=1784018130072, createdBy=13041195026, updatedBy=13041195026, submissionGuidelinesUrl=, submissionAuthorUrl=https://rlfdauthor.cast.org.cn/webm, submissionEditorUrl=https://rlfdeditor.cast.org.cn/webm, submissionReviewUrl=https://rlfdauthor.cast.org.cn/webm, submissionCeEditorUrl=https://rlfdeditor.cast.org.cn/webm, submissionAeEditorUrl=https://rlfdeditor.cast.org.cn/webm, option={"copyright":""}), JournalExt(id=1283828346094076811, language=EN, name=Thermal Power Generation, nameHistory1=null, nameHistory2=null, managedBy=, sponsoredBy=, publishedBy=, editorOffice=, officeProv=null, officeCity=null, officeAddr=, officeZip=, editDirector=, officeDirector=null, officePhone=null, coverPicUrl=null, journalRemark=, submitArticleUrl=null, websiteUrl=, createdTime=1784018130086, updatedTime=1784018130086, createdBy=13041195026, updatedBy=13041195026, submissionGuidelinesUrl=, submissionAuthorUrl=https://rlfdauthor.cast.org.cn/webm, submissionEditorUrl=https://rlfdeditor.cast.org.cn/webm, submissionReviewUrl=https://rlfdauthor.cast.org.cn/webm, submissionCeEditorUrl=https://rlfdeditor.cast.org.cn/webm, submissionAeEditorUrl=https://rlfdeditor.cast.org.cn/webm, option={"copyright":""})], databaseList=null, tenantJournalId=1210938733613449225, websiteList=[Website(id=1210941118787744741, webName=null, webTitle=null, webDomain=null, webCopyrigh=null, webIpcNo=null, seoTitle=null, seoKeywords=null, seoDescription=null, tenantJournalId=null, journalId=1210938733613449225, journalNameCn=null, journalNameEn=null, grayFlag=null, tenantId=1146029695717560320, platformId=null, journalGroupId=null, journalGroupNameCn=null, journalGroupNameEn=null, type=1, domain=https://castjournals.cast.org.cn/joweb/rlfd/CN, language=CN, createTime=1766640460918, createBy=18614031015, updateTime=1766640511525, updateBy=18614031015, name=热力发电-中文, tplId=1146099689490845704, title=热力发电, delFlag=0, indexPage=/home, props=[WebsiteProps(id=1307280923934876518, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=articleTextType, value=kx, createTime=1789609660371, updateTime=1789609660371, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923905516387, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=banner, value=null, createTime=1789609660364, updateTime=1789609660364, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923960042345, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=grayFlag, value=0, createTime=1789609660377, updateTime=1789609660377, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923880350562, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=logo, value=https://castjournals.cast.org.cn/joweb/rlfd/CN/file/pic?fileId=ToFA0Lu4b/CNocENDvNjHA==, createTime=1789609660358, updateTime=1789609660358, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923976819563, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=minRunFlag, value=0, createTime=1789609660381, updateTime=1789609660381, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923926487909, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=picServerUrl, value=https://castjournals.cast.org.cn/joweb/rlfd/CN/file/pic, createTime=1789609660369, updateTime=1789609660369, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923968430954, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=silenceFlag, value=0, createTime=1789609660379, updateTime=1789609660379, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923913904996, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=staticResourcePath, value=https://castjournals.cast.org.cn/joweb/cast_kjdb_cn_619/, createTime=1789609660366, updateTime=1789609660366, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923943265127, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=themeColor, value=null, createTime=1789609660373, updateTime=1789609660373, creator=18614031015, updator=18614031015), WebsiteProps(id=1307280923951653736, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118787744741, code=themeStyle, value=.style-1 .main-menu ul>li { margin-right: 18px; }, createTime=1789609660375, updateTime=1789609660375, creator=18614031015, updator=18614031015)]), Website(id=1210941118926156777, webName=null, webTitle=null, webDomain=null, webCopyrigh=null, webIpcNo=null, seoTitle=null, seoKeywords=null, seoDescription=null, tenantJournalId=null, journalId=1210938733613449225, journalNameCn=null, journalNameEn=null, grayFlag=null, tenantId=1146029695717560320, platformId=null, journalGroupId=null, journalGroupNameCn=null, journalGroupNameEn=null, type=1, domain=https://castjournals.cast.org.cn/joweb/rlfd/EN, language=EN, createTime=1766640460950, createBy=18614031015, updateTime=1766640598724, updateBy=18614031015, name=热力发电-英文, tplId=1146101810881728533, title=Thermal Power Generation, delFlag=0, indexPage=/home, props=[WebsiteProps(id=1308830784610459877, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=articleTextType, value=kx, createTime=1789979175951, updateTime=1789979175951, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784581099746, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=banner, value=null, createTime=1789979175944, updateTime=1789979175944, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784631431400, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=grayFlag, value=0, createTime=1789979175956, updateTime=1789979175956, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784560128225, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=logo, value=https://castjournals.cast.org.cn/joweb/rlfd/CN/file/pic?fileId=ToFA0Lu4b/CNocENDvNjHA==, createTime=1789979175939, updateTime=1789979175939, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784644014314, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=minRunFlag, value=0, createTime=1789979175959, updateTime=1789979175959, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784602071268, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=picServerUrl, value=https://castjournals.cast.org.cn/joweb/rlfd/EN/file/pic, createTime=1789979175949, updateTime=1789979175949, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784639820009, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=silenceFlag, value=0, createTime=1789979175958, updateTime=1789979175958, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784593682659, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=staticResourcePath, value=https://castjournals.cast.org.cn/joweb/cast_kjdb_en_623/, createTime=1789979175947, updateTime=1789979175947, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784614654182, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=themeColor, value=null, createTime=1789979175953, updateTime=1789979175953, creator=18614031015, updator=18614031015), WebsiteProps(id=1308830784623042791, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1210941118926156777, code=themeStyle, value=.style-1 .main-menu ul>li { margin-right: 12px; }, createTime=1789979175954, updateTime=1789979175954, creator=18614031015, updator=18614031015)])], journalTitle=热力发电, weixinUrl=null, journalUrl=null, iacademicId=null, status=1, seqNo=null, journalTitleEn=Thermal Power Generation, journalPhotoCn=IcKGK23kpfWlBK6GqYtS5g==, journalPhotoEn=UzifuamzuAk3uXMVSOtdyA==, journalFirstLetter=R, journalRecommend=null, journalNew=null, journalCollection=null, jcrJf=null, cjcrJf=null, jcrJfStr=null, cjcrJfStr=null, submissionFirstDecision=null, sciSubjectClassification=null, casSubjectClassification=null, citeScore=null, totalCitationFrequency=null, icpCode=null, psCode=null, advertisingLicenseCode=null, copyrightInformation=null, country=null, option=, provinceCode=null, provinceName=null, collectFlag=false, interPubPlatform=, interPubPlatformUrl=null), detailUrlCn=https://castjournals.cast.org.cn/joweb/rlfd/CN/10.19666/j.rlfd.202605123, detailUrlEn=https://castjournals.cast.org.cn/joweb/rlfd/EN/10.19666/j.rlfd.202605123, pdfUrlCn=https://castjournals.cast.org.cn/joweb/rlfd/CN/PDF/10.19666/j.rlfd.202605123, pdfUrlEn=https://castjournals.cast.org.cn/joweb/rlfd/EN/PDF/10.19666/j.rlfd.202605123, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, previewStatus=0, delFlag=0, hasFullText=0, orderTime=1792142185115, fullTextJson=null, articleText=null, reference=null)
收藏切换
适应电网调度的火电机组AGC与一次调频协同优化策略
收藏切换
PDF下载
热力发电 | ,():
收起
收藏切换
热力发电 |
适应电网调度的火电机组AGC与一次调频协同优化策略
全屏
作者信息
通讯作者:
作者简介:
Coordinated optimization strategy for agc and primary frequency regulation of thermal power units oriented to grid dispatching
  • Affiliations
      Corresponding Author:
    doi: 10.19666/j.rlfd.202605123
    文章导航
    收藏切换

    【目的】针对新能源并网导致电网惯量削弱,且火电机组执行自动发电控制和一次调频时频发冲突的痛点,本文以1000兆瓦超超临界直流炉火电机组为对象,提出一种模型驱动的机炉协同优化控制策略。

    【方法】首先,基于物理集总汽水循环过程,建立三阶仿射非线性动态控制模型,并用自适应遗传算法在线辨识压力与能量转化系数等参数。其次,在控制底层引入状态重构技术,通过频域互补滤波提取暂态再热蒸汽流量,利用高阶逆向反演重构入炉煤等效热值。最后,对接考核细则,设计涵盖提压蓄能、变增益补偿、防冲突交叉闭锁及微阶梯分解的协调控制逻辑策略矩阵。

    【结果】实机闭环投运表明,降阶模型变工况预测精度优异。优化后机组一次调频合格率稳超免考线,自动发电控制指标大幅跃升,改善了热惯性引发的功率振荡与能量对冲。

    【结论】该方案兼顾计算效率与物理保真度,开辟了百万机组依靠纯软件逻辑重构深度参与辅助服务市场的工程实操范式,从底层突破了机炉协调响应瓶颈,显著增强了机组对新型电力系统的支撑能力。

    [Objective] As the accelerated transition toward modern power systems with high-penetration renewable energy integration continuously weakens the equivalent rotational inertia of the grid, 1000 MW ultra-supercritical once-through boiler thermal power units face increasingly strict dispatch performance criteria. Due to their inherent thermodynamic lag and strong non-linear characteristics, these megawatt-class units frequently encounter severe command coupling conflicts and destructive energy clashes when executing automatic generation control and primary frequency regulation instructions simultaneously. To fundamentally resolve these operational bottlenecks, this research introduces a model-driven, coordinated optimization control strategy. 

    [Methods] First, adopting a hybrid modeling concept, the intricate steam-water cycle of the boiler is spatially lumped to construct a highly efficient 3rd-order affine non-linear dynamic control model. To guarantee wide-range robustness, an objective-adaptive non-dominated sorting genetic algorithm is employed to perform the online calibration of unknown dynamic parameter matrices, specifically targeting pressure conversion coefficients, energy conversion variables, and thermal time constants. Capitalizing on this reduced-order model's internal boundary constraints, state reconstruction technologies are embedded in the control layer. Specifically, the transient reheat steam flow is extracted through a frequency-domain complementary filtering network to effectively eliminate volume-induced phase delays. Concurrently, the actual equivalent coal feed rate is reverse-calculated via a high-order Butterworth band-pass inversion algorithm to successfully strip away coal transportation delays. Furthermore, aligning strictly with the latest grid auxiliary service assessment rules, a comprehensive coordinated control logic strategy matrix is configured. This matrix features active main steam pressure-raising for energy storage at deep peak-shaving loads, adaptive variable-gain compensation algorithms for small frequency deviations, cross-interlocking protection mechanisms to prevent reverse actions during large frequency deviations, and a discrete micro-step decomposition module for continuous automatic generation control ramp commands. 

    [Results] Field test data gathered from an industrial unit thoroughly verify the proposed strategy's exceptional efficacy. The reduced-order mathematical model exhibits remarkable tracking fidelity under wide-range load-varying conditions, maintaining an average main steam pressure prediction error of only 3.15%. Following the control logic upgrade, the initial mechanical response delay for primary frequency regulation was compressed to 2.65 seconds. This drove the monthly primary frequency regulation qualification rate from 62.4% to a stable 81.5%, safely surpassing the penalty-exemption baseline. Simultaneously, the comprehensive automatic generation control performance index registered a leap from 0.51 to 1.18, systematically eradicating power oscillations and inverse adjustments traditionally caused by thermodynamic inertia.

     [Conclusion] Balancing computational efficiency and physical fidelity, the proposed scheme establishes a practical engineering paradigm for 1000 MW units to deeply engage in the ancillary service market through pure software logic reconfiguration. It fundamentally breaks through the response bottlenecks of boiler-turbine coordination and significantly strengthens the unit's support capability for next-generation power systems.

    . 适应电网调度的火电机组AGC与一次调频协同优化策略. 热力发电, : - . DOI: 10.19666/j.rlfd.202605123
    . Coordinated optimization strategy for agc and primary frequency regulation of thermal power units oriented to grid dispatching[J]. Thermal Power Generation, : - . DOI: 10.19666/j.rlfd.202605123

    参考文献 引证文献
    排序方式:
    年第卷第期
    PDF下载
    156
    28
    引用本文
    BibTeX
    文章信息
    doi: 10.19666/j.rlfd.202605123
    • 首发时间:2026-10-16
    补充材料
    相关文章
    文章信息
    作者
    出版历史
    基金
    作者信息
    参考文献
    分享链接
    https://castjournals.cast.org.cn/joweb/rlfd/CN/10.19666/j.rlfd.202605123
    分享至
    全文二维码

    扫描看全文

    引用本文
    BibTeX
    本文的引用情况
    2种不同金属材料的力学参数
    科
    Family
    属数
    Number of
    genus
    种数
    Number of
    species
    占总种数比例
    Percentage of
    total species (%)
    属
    Genus
    种数
    Number of
    species
    占总种数比例
    Percentage of total
    species (%)
    鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
    小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
    多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
    红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
    小菇属 Mycena 11 5.26
    光柄菇属 Pluteus 5 2.39
    红菇属 Russula 17 8.13
    栓菌属 Trametes 5 2.39
    关闭全屏