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Article(id=1236697123681530336, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236697118983909778, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202407138, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1719763200000, receivedDateStr=2024-07-01, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1772781171006, onlineDateStr=2026-03-06, pubDate=1745510400000, pubDateStr=2025-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772781171006, onlineIssueDateStr=2026-03-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772781171006, creator=13701087609, updateTime=1772781171006, updator=13701087609, issue=Issue{id=1236697118983909778, tenantId=1146029695717560320, journalId=1210938733613449225, year='2025', volume='54', issue='4', pageStart='1', pageEnd='185', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772781169887, creator=13701087609, updateTime=1772781423241, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1236698181698900007, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236697118983909778, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1236698181698900008, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1236697118983909778, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=77, endPage=84, ext={EN=ArticleExt(id=1236697124017074671, articleId=1236697123681530336, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Integrated monitoring scheme of renewable energies based on preprocessing data framework, columnId=1213164439017276071, journalTitle=Thermal Power Generation, columnName=Special topic on new energy power generation technology, runingTitle=null, highlight=null, articleAbstract=

The hardware equipment and monitoring systems used in various stages of production of renewable energy stations are provided by different manufacturers, resulting in the data format and communication protocols between various business systems can’t be standardized. This data non-uniformity makes the business systems can only run independently of each other, bringing a lot of inconvenience to the operation and maintenance and coordinated control of the field operation and maintenance personnel, and part of the system even falls into the situation of no one maintenance. Based on the data characteristics of renewable energy stations, an integrated monitoring scheme of renewable energy is proposed based on pre-processing data framework. By introducing the architectural design and workflow, a comprehensive data processing driver applicable to the integrated monitoring of renewable energies and data storage technology based on a hybrid architecture is proposed, the implementation of the data acquisition, standardization and storage ideas are described in detail, and application cases is combined to reflect the system performance improvement brought by this solution. This solution can be adapted to renewable energy monitoring needs of different scales, ensure the real-time and security of massive data processing under high concurrency processing scenarios, and significantly improve the data analysis capability of renewable energy stations, providing an important reference for the development and improvement of related systems.

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当前新能源场站在各个生产环节所使用的硬件及监控系统由不同厂家提供，导致各业务系统间的数据格式和通信规约无法统一。这种数据的不统一性使各业务系统只能相互独立运行，为现场运维人员的操作维护和协调控制带来了诸多不便，部分系统甚至因此陷入了无人维护的局面。针对新能源场站的数据特点，提出了一种基于前置数据处理框架的一体化监控方案，在介绍其架构设计和工作流程的基础上，提出新能源场站一体化监控适用的综合数据处理驱动和基于混合架构的场站数据存储技术，详述了数据的采集、标准化和存储的实现思路，并结合应用案例验证了此方案带来的系统性能提升。该方案可以适应不同规模的新能源监控需求，在高并发的处理场景下确保海量数据处理的实时性和安全性，并显著提升了新能源场站的数据分析能力，为相关系统的开发和改进提供了重要参考。

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张亦乐（1998），男，硕士研究生，主要研究方向为计算机软件及应用、自动化技术、电力工业，。

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张亦乐（1998），男，硕士研究生，主要研究方向为计算机软件及应用、自动化技术、电力工业，。

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张亦乐（1998），男，硕士研究生，主要研究方向为计算机软件及应用、自动化技术、电力工业，。

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Comparison of telemetry real-time data acquisition

, figureFileSmall=null, figureFileBig=null, tableContent=
控制器信号分散采集方案一体化采集方案方案时差/s
数值时刻数值时刻数值时刻
517:12:43517:12:46517:12:442
1017:14:211017:14:221017:14:220
2517:17:572517:17:582517:17:580
8917:19:018917:19:088917:19:026
25517:22:2525517:22:2825517:22:262
40317:23:1740317:23:1940317:23:181
8517:25:588517:26:028517:26:584
3917:26:503917:25:533917:26:512
1517:27:411517:27:441517:27:413
017:33:19017:33:22017:33:193
原控制系统和一体化监控系统的采集时差平均值2.3
), ArticleFig(id=1236707902279438355, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236697123681530336, language=CN, label=表1, caption=

遥测实时数据采集对比

, figureFileSmall=null, figureFileBig=null, tableContent=
控制器信号分散采集方案一体化采集方案方案时差/s
数值时刻数值时刻数值时刻
517:12:43517:12:46517:12:442
1017:14:211017:14:221017:14:220
2517:17:572517:17:582517:17:580
8917:19:018917:19:088917:19:026
25517:22:2525517:22:2825517:22:262
40317:23:1740317:23:1940317:23:181
8517:25:588517:26:028517:26:584
3917:26:503917:25:533917:26:512
1517:27:411517:27:441517:27:413
017:33:19017:33:22017:33:193
原控制系统和一体化监控系统的采集时差平均值2.3
), ArticleFig(id=1236707902392684570, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236697123681530336, language=EN, label=Tab.2, caption=

Time delay of remote control commands in integrated monitoring system

, figureFileSmall=null, figureFileBig=null, tableContent=
指令发送时刻指令接收时刻时延/s
16:38:31.47916:38:32.0270.548
16:40:16.72216:40:17.3880.666
16:41:15.89216:41:16.3880.496
16:42:15.50716:42:16.0090.502
16:43:18.06816:43:18.7090.641
16:44:36.78716:44:37.5300.743
16:45:29.91716:45:30.5300.613
16:46:36.11616:46:36.6900.574
16:48:28.85216:48:29.4910.639
16:49:23.83816:49:24.2910.453
时延平均值0.588
), ArticleFig(id=1236707902463987743, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236697123681530336, language=CN, label=表2, caption=

一体化监控系统遥控指令控制时延

, figureFileSmall=null, figureFileBig=null, tableContent=
指令发送时刻指令接收时刻时延/s
16:38:31.47916:38:32.0270.548
16:40:16.72216:40:17.3880.666
16:41:15.89216:41:16.3880.496
16:42:15.50716:42:16.0090.502
16:43:18.06816:43:18.7090.641
16:44:36.78716:44:37.5300.743
16:45:29.91716:45:30.5300.613
16:46:36.11616:46:36.6900.574
16:48:28.85216:48:29.4910.639
16:49:23.83816:49:24.2910.453
时延平均值0.588
), ArticleFig(id=1236707902568845354, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236697123681530336, language=EN, label=Tab.3, caption=

Time delay of remote control commands in conventional monitoring system

, figureFileSmall=null, figureFileBig=null, tableContent=
指令发送时刻指令接收时刻时延/s
15:14:57.04015:14:58.0881.048
15:16:43.44315:16:46.0082.565
15:17:56.35215:17:57.4491.097
15:19:21.88515:19:23.8091.924
15:19:59.22415:20:01.0901.886
15:20:40.47915:20:42.0501.571
15:21:17.57415:21:20.3312.757
15:21:54.94815:21:56.6901.742
15:23:29.74815:23:31.7311.983
15:24:10.16115:24:12.6912.530
时延平均值2.210
), ArticleFig(id=1236707902648537133, tenantId=1146029695717560320, journalId=1210938733613449225, articleId=1236697123681530336, language=CN, label=表3, caption=

传统监控系统遥控指令控制时延

, figureFileSmall=null, figureFileBig=null, tableContent=
指令发送时刻指令接收时刻时延/s
15:14:57.04015:14:58.0881.048
15:16:43.44315:16:46.0082.565
15:17:56.35215:17:57.4491.097
15:19:21.88515:19:23.8091.924
15:19:59.22415:20:01.0901.886
15:20:40.47915:20:42.0501.571
15:21:17.57415:21:20.3312.757
15:21:54.94815:21:56.6901.742
15:23:29.74815:23:31.7311.983
15:24:10.16115:24:12.6912.530
时延平均值2.210
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基于前置数据处理框架的新能源一体化监控方案
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张亦乐 1 , 胡波 1 , 张津 1 , 宋美艳 1 , 皇晓军 2 , 李家港 1 , 薛建中 1
热力发电 | 新能源发电技术专题 2025,54(4): 77-84
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热力发电 | 新能源发电技术专题 2025, 54(4): 77-84
基于前置数据处理框架的新能源一体化监控方案
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张亦乐1 , 胡波1, 张津1, 宋美艳1, 皇晓军2, 李家港1, 薛建中1
作者信息
  • 1.西安热工研究院有限公司，陕西　西安　710054
  • 2.华能陕西新能源分公司，陕西　西安　710077

    • 张亦乐（1998），男，硕士研究生，主要研究方向为计算机软件及应用、自动化技术、电力工业，。

Integrated monitoring scheme of renewable energies based on preprocessing data framework
Yile ZHANG1 , Bo HU1, Jin ZHANG1, Meiyan SONG1, Xiaojun HUANG2, Jiagang LI1, Jianzhong XUE1
Affiliations
  • 1.Xi’an Thermal Power Research Institute Co., Ltd., Xi’an 710054, China
  • 2.Huaneng Renewables Co., Ltd. Shaanxi Branch, Xi’an 710077, China
出版时间: 2025-04-25 doi: 10.19666/j.rlfd.202407138
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摘要
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当前新能源场站在各个生产环节所使用的硬件及监控系统由不同厂家提供，导致各业务系统间的数据格式和通信规约无法统一。这种数据的不统一性使各业务系统只能相互独立运行，为现场运维人员的操作维护和协调控制带来了诸多不便，部分系统甚至因此陷入了无人维护的局面。针对新能源场站的数据特点，提出了一种基于前置数据处理框架的一体化监控方案，在介绍其架构设计和工作流程的基础上，提出新能源场站一体化监控适用的综合数据处理驱动和基于混合架构的场站数据存储技术，详述了数据的采集、标准化和存储的实现思路，并结合应用案例验证了此方案带来的系统性能提升。该方案可以适应不同规模的新能源监控需求，在高并发的处理场景下确保海量数据处理的实时性和安全性，并显著提升了新能源场站的数据分析能力，为相关系统的开发和改进提供了重要参考。

数据采集  /  规约解析  /  数据存储

The hardware equipment and monitoring systems used in various stages of production of renewable energy stations are provided by different manufacturers, resulting in the data format and communication protocols between various business systems can’t be standardized. This data non-uniformity makes the business systems can only run independently of each other, bringing a lot of inconvenience to the operation and maintenance and coordinated control of the field operation and maintenance personnel, and part of the system even falls into the situation of no one maintenance. Based on the data characteristics of renewable energy stations, an integrated monitoring scheme of renewable energy is proposed based on pre-processing data framework. By introducing the architectural design and workflow, a comprehensive data processing driver applicable to the integrated monitoring of renewable energies and data storage technology based on a hybrid architecture is proposed, the implementation of the data acquisition, standardization and storage ideas are described in detail, and application cases is combined to reflect the system performance improvement brought by this solution. This solution can be adapted to renewable energy monitoring needs of different scales, ensure the real-time and security of massive data processing under high concurrency processing scenarios, and significantly improve the data analysis capability of renewable energy stations, providing an important reference for the development and improvement of related systems.

data acquisition  /  communication protocol parsing  /  data storage
张亦乐, 胡波, 张津, 宋美艳, 皇晓军, 李家港, 薛建中. 基于前置数据处理框架的新能源一体化监控方案. 热力发电, 2025 , 54 (4) : 77 -84 . DOI: 10.19666/j.rlfd.202407138
Yile ZHANG, Bo HU, Jin ZHANG, Meiyan SONG, Xiaojun HUANG, Jiagang LI, Jianzhong XUE. Integrated monitoring scheme of renewable energies based on preprocessing data framework[J]. Thermal Power Generation, 2025 , 54 (4) : 77 -84 . DOI: 10.19666/j.rlfd.202407138
正文
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新能源高比例接入电网是新型电力系统的重要特征之一[1]，新型电力系统同时提出挖掘历史数据价值、推动数字化革命的新需求[2]。而实现电力系统的数字化、智能化转型，其前提是电力系统能够具备较高的感知水平，实现对数据的可观、可测、可控[3]。
新能源场站目前按功能设计可将设备划分为多个子系统[4]，如光伏场站设备可分为逆变器/汇流箱/箱变监控、AGC、AVC、五防、升压站和功率预测等。由于不同功能类型的设备供应厂家不同，各功能模块所采取的数据标准和通信规约也不同[5]，因此场站不得不依赖使用厂商提供的软件系统完成对数据的处理。各功能子系统之间独立地采集与运行使得运维信息在场站内部呈现碎片化分布[6]，这不仅使不同子系统间的数据无法统一应用，也为场站人员日常的监控操作和设备维护带来了很大不便，从而给新能源场站对数据的处理和分析造成了诸多限制[7-8]。
此外随着包含风光水火储多种电源类型的大型清洁能源基地的不断建设，针对多源电力系统的协调控制策略被提出[9-10]。完成基于多能互补策略的可控能源协同调度，需要消除子系统间的阻塞，实现一体化的信息处理系统。
文献[11]提出了“就地设备——就地SCADA监控系统——区域集控中心”的三级远程集中监控系统架构。文献[12]提出了采集上传与遥控下发相互独立、采集一体机通过电力通信专网传输至集控服务器的远程监控系统架构。文献[13]基于云边协同技术提出将场站侧数据统一采集到集团侧的物联网关，统一使用中心平台进行对数据的治理、应用和持久化的方案。上述一体化监控平台都是通过在现场部署通信管理机收集报文并再转发至远程集控中心实现对数据和命令的处理。此类方案并没有摆脱对现场各个子控制系统的依赖，造成了新能源场站对解析和处理数据能力的缺乏，也令监控实时性受限于场站与集控中心通信的网络带宽。
为了应对在集控侧实现一体化监控的不足，文献[14-15]分别提出了2种部署在新能源场站侧的全景监控系统，二者都以独立控制终端与现场设备进行销户，通过通信转换方式实现一体化监控，此种基于硬件的一体化监控模式不仅增加了场站的建设成本，而且不具备可拓展性。文献[16]提出面向光伏场站监控的通信机制，以光伏发电方阵实现数据获取和解析，其数据来源只能局限于光伏组件、汇流箱、逆变器和变压器，无法实现对其他设备的数据采集。
针对上述新能源场站侧一体化监控系统存在的问题，本文提出了基于前置数据处理框架的新能源一体化监控方案，能够有效降低系统成本，在具备较好可拓展性的基础上实现对全部设备的一体化监控。
1　架构设计
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传统的新能源场站监控系统如图1所示，每个子控制系统配置运行在1台上位机中，以独立采集的方式实现与设备的信息交互，设备与控制系统间的一一对应关系通过通信管理机或直接接线的方式实现。
为了减少监控所需的设备数量，降低系统成本增加可拓展性，并且减少协议因经过通信管理机转发所造成的额外传输时延，本文提出了以前置数据处理框架代替原本分散的各设备SCADA系统，直接与设备层进行数据交互。此前置数据处理框架由综合数据处理驱动和基于混合架构的场站数据存储组成，综合数据处理驱动负责维护和管理数据通信通道、根据各设备产生数据的特点实时采集并解析数据以及将数据分发给高级应用并接收返回结果；基于混合架构的场站统一存储负责接收解析后的标准化数据、向高级应用提供数据接口以及保存历史数据。图2为本文所提新能源一体化监控系统。由图2可见，前置数据处理框架在整个一体化监控系统中需要发挥现场设备和高级应用之间交互的桥梁作用。即向上提供经过标准化处理后的实时数据并进行统一存储，向下根据接收到的应用消息生成对应指令报文。具体而言，数据采集与解析的流程为综合数据处理驱动通过并行的多路通道与场站设备建立连接，设备数据经数据通道传入规约框架调用抽象模型进行标准化处理，然后由场站统一存储获取并保存，以供高级应用使用；指令执行的流程为高级应用向综合数据处理驱动发送请求消息，规约框架调用对应的抽象模型生成规约信息经由数据通道发送至设备。图3为应用前置数据处理框架的一体化监控系统的数据流。
2　综合数据处理驱动
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2.1　可分组的多路冗余通信通道
新能源场站的设备总量大，通信点数多。以光伏场站为例，国内已建成的地面光伏电站大多为几十兆瓦以上的规模，每10 MW的装机容量对应的测点数量为10 000个左右，单点最大采集频率不小于100帧/s。对新能源场站的全部数据实现集中采集使综合数据处理驱动的数据吞吐量大幅增加，为了保证在此高并发场景下的数据可靠性和实时性，本文提出了可分组的多路冗余通信通道。此通信通道采用多进程和多线程相结合的方式，即每路通信对应1台设备，其通信运行载体以线程实现，多个通信通道组成通信组以进程方式运行。系统会在启动后自动加载定义好的通信进程，各进程根据通信通道的所属进程号属性值找到并加载对应的通信线程。
本文提出的可分组的多路冗余通信通道可以实现各路通信互不干扰，保证了各通信通道运行的可靠性，还满足了大容量吞吐能力要求。相较于单通道单进程方式，该方式有效降低了系统资源的消耗，从而实现在相同硬件配置下支持更多的通信负载。同时因为分组基于通信通道自身属性，使得通信通道可以在通信组间灵活地进行分配。此设计不仅通过均衡各通信进程的负载保证了实时性，还可以在检测到通信进程心跳故障时将其工作迅速地分配给其他通信组以避免出现数据的丢失，提高了系统的可靠性。
为保证单个通信通道数据的可靠性，本文为其设计了冗余工作模式。具体做法为对于多个数据来源相同的通信通道，有2种通信方式供用户配置选择：1）互为主备，根据通道状态选择通信质量最佳的数据送至规约框架进行解析；2）互相独立，将所有通道采集的数据都送给规约框架，完成标准化解析后通过对数据内容的判优来决定当前数据的选择。
2.2　基于多层抽象单元的规约框架
新能源场站数据的来源较多，以多协议并存方式完成数据传输，较常使用的协议有Modbus TCP/RTU、IEC104、IEC61850、DLT645等。因为不同通信规约的差异可能会很大[17]（如Modbus与IEC104），加之各种规约还有预留的专用类型，如IEC103规约只有类型标识符为1~31是兼容范围，32~255都是可自定义的专用范围，这就使得场站中各子系统间的数据在格式、语义和表达形式等方面存在诸多差异。为了兼容各种类型的数据和指令，统一数据的封装和表达形式[18]，本文提出了基于抽象单元的规约框架，能够透明地对各类规约实现标准化，向高级应用提供统一的数据格式并且保证系统具备较好的可扩展性。
2.2.1　数据兼容
对于从设备层获取到的数据，需要解决的是规约不统一带来的解析方法杂乱问题。由于用户一般只会关注与业务相关的数据内容，对通信层的报文原文不感兴趣，因此本文选择将数据采集与解析相结合，即通信通道接收到报文后立即调用对应的规约抽象单元，将报文内容统一为ASDU形式。
通信通道与抽象单元的匹配方式为用户手动配置，为了避免因为输入错误导致的模式不匹配，系统会在抽象单元加载完成后对设备发送复位命令，若对其复位确认响应报文无法正确解析，则会停止后续解析任务并告警。初始化完成后还需要进行时间同步，具体流程为汇聚控制器向监测设备发送时间设定命令ASDU，这条命令包含了发送报文第一位瞬间的实时时间，监测装置根据收到的时间、时间设定命令的帧长和传输速度修正自身时间，在监测设备据此调整好时钟信息并回复确认报文后，此抽象模型才会进入常态化工作模式。
将各类不定长的报文从通信通道传递至抽象单元，利用堆栈的方式在大量数据高并发的场景下很可能会产生溢出问题，而使用内存缓冲区又很容易因为读写速度的不一致导致新的报文内容覆盖还未被接收的旧报文。针对上述问题，本文提出以带有读写锁的动态数组来实现报文接收缓冲区，在保证报文内容接收完整的前提下将时间开销控制在可接受范围内。
2.2.2　指令兼容
对于从高级应用下发到设备层的指令，需要解决的是不同协议间执行模式不一致的问题，如对于遥控指令，有的协议会先判断当前状态是否和指令内容一致再决定是否执行，有的协议则直接对开关量进行调整。针对上述问题，本文总结了工控领域主流规约的执行机制，设计了指令抽象单元，以类继承的方式向规约抽象模型中的各个函数提供实质内容。同时规约抽象模型可以分为应用层协议和传输层协议，同一层级的规约抽象模型以统一接口完成数据的接收与发送。
对功能模块抽象化实现了对所需功能以动态链接库的形式进行加载，使主流程代码可以得到复用，在保证系统兼容性基础上提高了可扩展性[19]。将抽象单元分为指令执行、应用层协议和传输层协议3级，通过组合运行方式减少了各模型库的单元数量，避免了因为模型库臃肿影响系统运行效率。
3　基于混合架构的场站数据存储
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新能源场站对数据的使用需求可以分为可视化监控和控制策略计算等实时性请求和持久化存储2类。若对数据先执行实时请求后进行持久化存储，则需要将大量的堆空间用于存储常量，会对监控系统的运行产生影响。而将数据先进行持久化存储后执行实时性请求，除了会降低系统的实时性，还可能会在高并发场景下造成监控系统读空值或读错值的情况。
此外，与常规电源相比，新能源场站在故障过程中呈强受控性特征，且分析与控制策略多样[20]，因此很多情况下对单一设备会使用多源数据融合分析。图4为变压器绝缘状态监测多源数据融合分析流程。由图4可见，变压器的绝缘状况通过局部放电、油色谱和温度3个参数均可得到反映，单一参数监测可能会因设备故障或受环境影响而使检测结果不准确，所以需要结合3个参数进行综合分析来提高评价的精确度[21]。
为了解决实时性请求和持久化处理串行执行所带来的问题，并且满足高级应用对于多源数据的需求，本文提出了基于混合架构的数据存储模式，该模式既能满足各类业务对数据的存储要求，又能提供灵活的数据获取方式支持对大数据的应用。
3.1　基于并行数据管道的内存映射
无论是实现实时性请求与持久化操作并发地读取数据，还是消除高级应用之间的数据屏障，都需要系统对实时数据提供一个开放的读取方式。而共享内存作为一种标准的程序间大量数据通信的方式，能够在对通信双方约束较少的同时保证高效率的进程间通信[22]，因此成为了存储实时数据的最佳适配方案。
由于高级应用和监控画面对实时数据的单次获取量较大，为了保证在多个请求并发的情况下系统能够完成实时响应，本文提出了基于并行数据管道的内存映射，对数据的访问速度能够达到指针级水平，这样实现了对目标数据的快速定位。
新能源场站的发电机组数量较多，而单设备所能产生的数据量并不高。基于此特点，为每台终端设备（即1个通信通道）分配1条子管道，对多个子管道并行处理可以提高系统的时效性。子管道的运行相互独立，通过管道索引与通信组相互对应，子管道的索引区由可变数量的区块构成，每个区块指向数据区的1条数据。子管道的数据区可以看作1个只读队列和1个读写队列，分别用于信息的上传与下发。图5为实时库数据管道的存储结构。
3.2　基于混合架构的历史数据存储
新能源场站的数据采集频率在不同设备间的差异较大，对数据持久化存储的模式需要根据采样频率和数据类型作出区分：采样频率为毫秒级和秒级的数据数量巨大，为了降低对其存储和查询的时间开销，以时间序列数据库进行保存；而分钟级的历史数据其整体数据量在Petabytes（PB）以内，单表记录数在10亿条以内，使用关系型数据库保存；对于非结构化的报表、画面、断面和视频等内容以文件服务器进行保存。
因为对历史数据保存是以周期性同步实时内存块的方式实现，所以当发生网络中断或数据服务器故障时历史数据会丢失。为了保证系统可靠性，本文设计了实时数据缓存机制，即规定周期内未发生对内存区内实时数据持久化操作，则使用本地缓存记录当前实时数据，并在恢复正常时写入历史数据库，确保历史数据在其缓存范围内不发生丢失。
4　项目应用效果
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4.1　可靠性与兼容性
华能共和世能光伏电站，简称世能电站，2013年并网发电，装机容量30 MW，具有101 760块295 W多晶硅太阳能电池组件和60台500 kW逆变器，2023年4月28日正式投运了本文所提方案的一体化监控系统（华能睿渥S316）。
该一体化监控系统在世能电站的可存储测点数达10万点，历史数据存储压缩率不小于10倍，CPU负荷率控制在10%之内，系统可用率达99.8%以上，测试和投运期间均未发生数据错误，保障了系统可靠性，为场站控制提供了良好的数据基础。
此外，世能电站的一体化监控范围包含了光伏子阵、升压站、本地气象站、公用测控装置、AGC/AVC控制器、保护测控装置、工程安全监控和审计系统，兼容协议范围包含CDT、MODBUS、IEC61850、IEC101、IEC103、IEC104。而由南能电气提供的世能电站原监控系统，对上述7个功能系统分别配置了1台上位机来完成日常运维，以及3台通信管理机用于接收并向服务器转发数据。相较于原控制系统，本文所提监控方案实现了对各类设备的集中监控，大大提高了系统的兼容性，减少了对通信管理机和上位机的使用，降低了对各设备厂商所提供监控系统的依赖，每年可为世能电站节约维护成本约20万元。
4.2　实时性
在数据采集方面，本文以使用IEC104协议进行遥测为例，使用本文所提的一体化方案和世能电站原控制系统连接同一个控制器，将控制器的变量数设定为1 000个，通过控制器上送的报警信息来记录开关量值变化的时间。测试对比结果见表1。
在指令控制方面，本文以IEC61850协议进行遥控为例，使用本文提出的一体化方案和世能电站原控制系统连接2个相同的控制器，将上位机中发送指令的操作记录时间和控制器接收到指令的时间差值作为时延进行对比测试。一体化监控系统的遥控指令控制测试结果见表2，世能电站原控制系统的遥控指令控制测试结果见表3。
本文所提出的一体化监控方案相较于传统的监控系统消除了通信规约管理机转发数据这一中间步骤，使得该一体化监控方案从测试数据来看，在数据采集和指令控制的实时性方面都有着70%以上的性能提升。
5　结语
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为了解决新能源场站数据的多源性和异构性问题，实现统一的数据管理和设备控制，本文提出了一种基于前置数据处理框架的新能源一体化监控方案。通过创新的多路通信机制，实现了对新能源场站全部数据的统一采集；利用多层级的抽象单元，完成了对数据的解析和指令的执行；采用混合存储架构，提供了对数据的统一访问方式。面对数量庞大且形式复杂的新能源场站数据，本方案确保了数据处理的可靠性和实时性，维持了良好的系统兼容性和可扩展性，并且在实际项目应用中取得了良好的成效，对于推动新能源场站侧的监控系统向更高效、更智能的方向发展具有重要的技术参考和实际应用价值。
基金
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  • 西安热工研究院有限公司发展基金项目(TV-24-TYK03)
文献
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doi: 10.19666/j.rlfd.202407138
  • 接收时间：2024-07-01
  • 首发时间：2026-03-06
  • 出版时间：2025-04-25
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  • 收稿日期：2024-07-01
基金
Development Fund Project of Xi’an Thermal Power Research Institute Co., Ltd.(TV-24-TYK03)
西安热工研究院有限公司发展基金项目(TV-24-TYK03)
作者信息
    1.西安热工研究院有限公司，陕西　西安　710054
    2.华能陕西新能源分公司，陕西　西安　710077
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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
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