CN114977490A - New forms of energy electricity generation monitor platform - Google Patents
New forms of energy electricity generation monitor platform Download PDFInfo
- Publication number
- CN114977490A CN114977490A CN202210498309.2A CN202210498309A CN114977490A CN 114977490 A CN114977490 A CN 114977490A CN 202210498309 A CN202210498309 A CN 202210498309A CN 114977490 A CN114977490 A CN 114977490A
- Authority
- CN
- China
- Prior art keywords
- prediction
- data
- interface
- power
- submodule
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000005611 electricity Effects 0.000 title claims abstract description 5
- 238000012544 monitoring process Methods 0.000 claims abstract description 93
- 238000003860 storage Methods 0.000 claims abstract description 25
- 230000003993 interaction Effects 0.000 claims abstract description 22
- 238000010248 power generation Methods 0.000 claims description 74
- 238000004458 analytical method Methods 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 14
- 238000007619 statistical method Methods 0.000 claims description 12
- 238000009826 distribution Methods 0.000 claims description 11
- 238000007405 data analysis Methods 0.000 claims description 9
- 230000005684 electric field Effects 0.000 claims description 8
- 238000002955 isolation Methods 0.000 claims description 8
- 230000002441 reversible effect Effects 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 7
- 238000013500 data storage Methods 0.000 claims description 4
- 230000001276 controlling effect Effects 0.000 abstract description 2
- 230000001105 regulatory effect Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 20
- 238000007726 management method Methods 0.000 description 13
- 238000000034 method Methods 0.000 description 12
- 238000010586 diagram Methods 0.000 description 9
- 230000005855 radiation Effects 0.000 description 9
- 238000004422 calculation algorithm Methods 0.000 description 8
- 238000004088 simulation Methods 0.000 description 7
- 238000011161 development Methods 0.000 description 5
- 230000018109 developmental process Effects 0.000 description 5
- 230000007774 longterm Effects 0.000 description 5
- 230000000007 visual effect Effects 0.000 description 5
- 230000003203 everyday effect Effects 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 238000005096 rolling process Methods 0.000 description 4
- 238000012795 verification Methods 0.000 description 4
- 238000012937 correction Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000004146 energy storage Methods 0.000 description 3
- 238000003908 quality control method Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004140 cleaning Methods 0.000 description 2
- 238000010219 correlation analysis Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000007599 discharging Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 230000003442 weekly effect Effects 0.000 description 2
- 206010033799 Paralysis Diseases 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011017 operating method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000013341 scale-up Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 230000033772 system development Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00022—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission
- H02J13/00026—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using wireless data transmission involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00028—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment involving the use of Internet protocols
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Human Computer Interaction (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application discloses new forms of energy electricity generation monitor platform includes: the system comprises first-zone hardware, second-zone hardware, third-zone hardware and an extranet system; the first area hardware comprises a regulation center and a wind-solar power storage station; the regulating and controlling center is used for collecting the operation data of the wind and light power storage station; the second area hardware comprises a prediction server, a power grid dispatching transaction center, a dispatching data network switch and a workstation; the power grid dispatching transaction center carries out data interaction with the prediction server through a dispatching data network switch; the workstation is used for performing centralized prediction and monitoring; the centralized prediction comprises the prediction of meteorological resources and output correlation of different time dimensions and different area ranges; the three-area hardware comprises a meteorological server, and the extranet system comprises a numerical meteorological center; the meteorological server is used for acquiring meteorological data from the numerical meteorological center. The platform provided by the application fills the blank of the prior art, realizes the independent power prediction and the whole area prediction of the wind-solar power storage station, and has better monitoring performance and wider application range.
Description
Technical Field
The application relates to the technical field of new energy power generation, in particular to a new energy power generation monitoring platform.
Background
Wind energy and solar energy power generation have the characteristics of randomness, fluctuation and intermittence, the wind receiving and light power generation capacity of the traditional power grid is limited, and the safe and stable operation of the power grid can be influenced by large-scale access. The characteristics of the solar energy and wind energy resource enrichment area and the main load center in reverse distribution determine that the wind power development is mainly based on large-scale centralized development and long-distance high-voltage transportation, and the photovoltaic power generation is connected into a power grid, so that the characteristics of large-scale centralized access and distributed access are realized simultaneously. However, the energy storage technology is still in the primary stage at present, and in the prior art, a new energy power generation monitoring platform combining independent power prediction and integral regional prediction for a wind-solar energy power storage station is not provided, so that centralized power prediction of the wind-solar energy power storage station is realized.
Disclosure of Invention
The application aims to provide a new energy power generation monitoring platform to fill the blank of the existing new energy power generation monitoring platform and realize independent power prediction and integral area prediction of a wind-light power storage station.
In order to achieve the above object, the present application provides a new energy power generation monitoring platform, including:
the system comprises first-zone hardware, second-zone hardware, third-zone hardware and an extranet system;
the first area hardware comprises a regulation center and a wind-solar power storage station; the control center is used for acquiring the operation data of the wind-solar power storage station;
the second-area hardware comprises a prediction server, a power grid dispatching transaction center, a dispatching data network switch and a workstation; the power grid dispatching transaction center performs data interaction with the prediction server through the dispatching data network switch; the workstation is used for performing centralized prediction and monitoring; the centralized prediction comprises prediction of meteorological resources, regional output and correlation;
the three-zone hardware comprises a meteorological server, and the extranet system comprises a numerical meteorological center; the meteorological server is used for acquiring meteorological data from the numerical meteorological center.
Furthermore, the first area hardware and the second area hardware adopt a switch to perform data interaction, and the second area hardware and the third area hardware perform data interaction through a reverse isolation device.
Furthermore, firewalls are deployed between the hardware in the first area and the hardware in the second area, and between the hardware in the third area and the extranet system.
Further, the workstation comprises a monitoring terminal; the monitoring terminal comprises a data interface module, a basic function module and a high-level application module;
the data interface module comprises an interface service submodule, an interface system submodule, a centralized control system submodule and a power prediction system submodule;
the basic function module comprises a wind power region power prediction submodule, a photovoltaic region power prediction submodule and a data analysis submodule;
the advanced application module comprises a comparison analysis submodule, a panoramic monitoring submodule, a generating capacity prediction submodule and a statistical analysis submodule.
Further, the interface service sub-module comprises a service data interface and a power prediction curve interface;
the interface system submodule comprises a data analysis interface, a data storage interface, a data processing interface and a data processing interface;
the centralized control system submodule comprises an equipment information interface, a wind power plant real-time data interface and a photovoltaic power plant real-time data interface;
the power prediction system submodule comprises a meteorological data interface and a prediction data interface.
Furthermore, the wind power region power prediction submodule and the photovoltaic region power prediction submodule respectively comprise a corresponding ultra-short-term power prediction interface, a short-term power prediction interface and a medium-term region cluster power prediction interface;
the data analysis submodule comprises a power prediction data statistical analysis submodule, an electric field operation data statistical analysis submodule and a data weather forecast statistical analysis submodule.
Furthermore, the comparison analysis submodule comprises a power curve comparison interface, an irradiance curve comparison interface and a wind speed curve comparison interface;
the panoramic monitoring submodule comprises an area monitoring interface and an electric field monitoring interface;
the generating capacity prediction sub-module comprises a medium-term prediction interface and a medium-term prediction interface;
the statistic analysis sub-module comprises an integrity statistic interface, a power error statistic interface, a frequency distribution statistic interface and a reporting statistic interface.
Further, the monitoring terminal comprises a J2EE platform.
Further, the communication among the first area hardware, the second area hardware, the third area hardware and the extranet system adopts international industrial standard communication standard.
Further, the prediction server includes:
the main prediction server is used for carrying out data interaction with the power grid dispatching transaction center through the dispatching data network switch, carrying out data interaction with the regulation and control center through the switch, carrying out data interaction with the meteorological server through the reverse isolation device, and sending stored data to the workstation;
and the standby prediction server is connected with the main prediction server in parallel and is used for calling when the main prediction server is abnormal.
Compared with the prior art, the beneficial effects of this application lie in:
the application discloses new forms of energy electricity generation monitor platform includes: the system comprises first-zone hardware, second-zone hardware, third-zone hardware and an extranet system; the first area hardware comprises a regulation center and a wind-solar power storage station; the regulation and control center is used for collecting the operation data of the wind-solar power storage station; the second-area hardware comprises a prediction server, a power grid dispatching transaction center, a dispatching data network switch and a workstation; the power grid dispatching transaction center carries out data interaction with the prediction server through a dispatching data network switch; the workstation is used for performing centralized prediction and monitoring; the centralized prediction comprises the prediction of meteorological resources and output correlation of different time dimensions and different area ranges; the three-area hardware comprises a meteorological server, and the extranet system comprises a numerical meteorological center; the meteorological server is used for acquiring meteorological data from the numerical meteorological center. The platform provided by the application fills up the blank of the prior art, realizes independent power prediction and integral area prediction of the wind-light power storage station, and is better in monitoring performance and wider in application range.
Drawings
In order to more clearly illustrate the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic diagram of a hardware portion of a new energy power generation monitoring platform according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a new energy generation monitoring platform hardware portion according to another embodiment of the present application;
fig. 3 is a functional architecture diagram of a new energy power generation monitoring platform according to an embodiment of the present application;
fig. 4 is a schematic diagram of an architecture of a software portion of a new energy power generation monitoring platform according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
It should be noted that, in the prior art, a new energy power generation monitoring platform combining independent power prediction and integral regional prediction for a wind-solar power storage station is not provided, and centralized power prediction for the wind-solar power storage station is completed. In order to fill the technical gap, the application provides a new energy power generation monitoring platform to complete independent power prediction and integral regional prediction of the wind-light power storage station. The new energy power generation monitoring platform adopts a local deployment mode, the model algorithm server is deployed in a group center, the data management and statistics server is deployed in the intelligent combined regulation and control center, the regional prediction and unified management under various structures can be realized, and meanwhile, the power prediction and the power generation amount prediction from different dimensions of a region-station and different time lengths are supported. The method specifically comprises the steps of multi-dimensional 0-4 hour ultra-short term real-time power prediction from a power station to an area and 0-72 hour and 168 hour long term short term power prediction in the future; and predicting the power generation amount of the power station to the region in a multi-dimensional day (taking day as the minimum granularity and having the duration of 7 days), a month (taking the month as the minimum granularity and having the duration of 12 months) and a year (taking the year as the minimum granularity and having the duration of 1 year).
The group center can unify data cleaning, analysis, prediction, transaction assistance, data uploading and the like for new energy power stations, the power-assisted group side realizes that each power station is unattended, a set of prediction model is optimized all the time, and the prediction precision is promoted in a unified way, so that the operation and maintenance cost is reduced, the meteorological service cost is reduced, the efficiency is improved, the group is helped to effectively make a group scheduling plan, the wind and light abandoning is reduced, and the consumption of each power grid to clean energy is increased.
The new energy power generation monitoring platform supports power prediction based on charging and discharging regulation disturbance of the energy storage system, can evaluate and optimize deviation of actual power of a power station caused by charging and discharging of the energy storage system, and ensures that a prediction result can be correctly suitable for a normal operation state of the system.
Specifically, the design principle that the new energy power generation monitoring platform provided by the application follows includes the following contents:
(1) the new energy power generation monitoring platform is designed according to the principles of program modularization, interface standardization, clear and friendly interface and convenient and smooth connection.
(2) The new energy power generation monitoring platform adopts a fully-open system structure with network layering according to functions, tasks, management ranges and the like, and the advancement, maintainability, expandability, compatibility and application software portability of the new energy power generation monitoring platform in long-term operation in the future are ensured.
(3) The new energy power generation monitoring platform is deployed for safety protection, and meets the regulations of 'transverse isolation and longitudinal encryption'.
(4) The new energy power generation monitoring platform realizes, operates, maintains and manages functions of the wind power station prediction system in a centralized mode, gives full play to the maximum comprehensive utilization benefits in the aspects of power generation management, power trading and the like, and realizes remote optimization management and economic operation of each power station better.
(5) The new energy power generation monitoring platform network architecture needs to integrally consider unified access of a wind power plant and a photovoltaic power station, information transmission protocols, network communication and technical requirements.
(6) The new energy power generation monitoring platform provides standard interactive interface services with a power grid, a centralized control system and the like, and supports transmission protocols such as OPC, Modbus, IEC104, IEC102, IEC101 and FTP.
(7) The new energy power generation monitoring platform meets the requirement of hardware redundancy configuration, the normal operation of the system is not affected by the local fault of single hardware, the system has a seamless switching dual-computer hot standby function, the system configuration and the type selection fully consider the openness of the system on system hardware and software on the premise of ensuring the reliability of the whole system and the safety stability, real-time performance and practicability of equipment operation, and the characteristics of rapid development and short updating period of a computer are met.
(8) In order to meet the real-time requirement of the system and ensure that the system has good openness, the system hardware and software platform adopt products of manufacturers with mature operation experience and better qualification which strictly adhere to the current industrial standard.
(9) A software system developer of the new energy power generation monitoring platform compiles detailed system development reports and system operation manuals, and graphical interfaces are adopted for user operation and query.
(10) The new energy power generation monitoring platform is developed by adopting cross-platform language and can seamlessly run in Linux and Windows operating systems.
Referring to fig. 1, an embodiment of the present application provides a new energy power generation monitoring platform, including:
the system comprises first-zone hardware, second-zone hardware, third-zone hardware and an extranet system;
the first area hardware comprises a regulation center and a wind-solar power storage station; the regulating and controlling center is used for collecting the operation data of the wind and light power storage station;
the second-area hardware comprises a prediction server, a power grid dispatching transaction center, a dispatching data network switch and a workstation; the power grid dispatching transaction center carries out data interaction with the prediction server through a dispatching data network switch;
the workstation is used for performing centralized prediction and monitoring; the centralized prediction comprises the prediction of meteorological resources, regional output and correlation;
the three-area hardware comprises a meteorological server, and the extranet system comprises a numerical meteorological center; the meteorological server is used for acquiring meteorological data from the numerical meteorological center.
The first area hardware and the second area hardware adopt the switch to perform data interaction, and the second area hardware and the third area hardware perform data interaction through the reverse isolation device. Preferably, firewalls are deployed between the first zone hardware and the second zone hardware, and between the third zone hardware and the extranet system.
In an embodiment, the control center is mainly an intelligent combined control center, as shown in fig. 2, wherein the intelligent combined control center is wirelessly connected to the wind, light and power storage station and is used for collecting real-time operation data of subordinate power stations, and the wind, light and power storage station can remotely access the intelligent combined control center through WEB browsing.
In a preferred embodiment, the reverse isolation device is configured to exchange weather data between the area II hardware and the area III hardware, and upload a weather text file of the area III hardware from a weather forecast download server to the prediction main server of the area II hardware.
In a preferred embodiment, the I-zone hardware, the II-zone hardware, the III-zone hardware, and the internal and external communications between the server and the workstation in the extranet system use an international industry standard communications standard, and the server and the workstation are assigned according to function modules.
In a particular embodiment, the forecast servers include a primary forecast server, a backup forecast server, corresponding to "forecast server-primary" and "forecast server-backup" in fig. 2, respectively, and in particular,
the main prediction server is used for carrying out data interaction with the power grid dispatching transaction center through the dispatching data network switch, carrying out data interaction with the regulation and control center through the switch, carrying out data interaction with the meteorological server through the reverse isolation device, and sending the stored data to the workstation;
and the standby prediction server is connected with the main prediction server in parallel and is used for calling when the main prediction server is abnormal.
It can be understood that in practical applications, a server may have a failure condition, and once the server fails, the whole monitoring platform may be difficult to operate, and even enter a state of paralysis. In the embodiment, a dispatching data network switch exchanges data with a power grid dispatching transaction center, a prediction main server is connected with a standby prediction server in parallel, the prediction main server is used for performing related functions such as data acquisition, history storage, power prediction, result uploading and WEB publishing, and the standby prediction server is used for predicting that the main server is invalid; meanwhile, the prediction main server and the standby prediction server are connected with the workstation, and the workstation can monitor hardware equipment in each area through data uploaded by the prediction main server and the standby prediction server.
In one embodiment, the workstation comprises a monitoring terminal; the function modules that can be implemented by the monitoring terminal include a data interface module, a basic function module and a high-level application module, as shown in fig. 3. Specifically, the contents of the respective functional modules are as follows:
the data interface module comprises an interface service submodule, an interface system submodule, a centralized control system submodule and a power prediction system submodule; wherein,
the interface service sub-module comprises a service data interface and a power prediction curve interface;
the interface system submodule comprises a data analysis interface, a data storage interface, a data processing interface and a data processing interface;
the centralized control system submodule comprises an equipment information interface, a wind power plant real-time data interface and a photovoltaic power plant real-time data interface;
the power prediction system submodule comprises a meteorological data interface and a prediction data interface; wherein,
the interface service submodule, the power prediction system submodule and the interface system submodule carry out bidirectional data interaction, and the centralized control system submodule respectively carries out unidirectional data interaction with the interface service submodule and the interface system submodule;
the basic function module comprises a wind power region power prediction submodule, a photovoltaic region power prediction submodule and a data analysis submodule;
the wind power region power prediction submodule and the photovoltaic region power prediction submodule respectively comprise corresponding ultra-short-term power prediction interfaces, short-term power prediction interfaces and middle-term region cluster power prediction interfaces;
the data analysis submodule comprises a power prediction data statistical analysis submodule, an electric field operation data statistical analysis submodule and a data weather forecast statistical analysis submodule;
the advanced application module comprises a comparison analysis submodule, a panoramic monitoring submodule, a power generation amount prediction submodule and a statistical analysis submodule; wherein,
the comparison analysis sub-module comprises a power curve comparison interface, an irradiance curve comparison interface and a wind speed curve comparison interface;
the panoramic monitoring submodule comprises an area monitoring interface and an electric field monitoring interface;
the power generation amount prediction sub-module comprises a medium-term prediction interface and a medium-term prediction interface;
the statistic analysis sub-module comprises an integrity statistic interface, a power error statistic interface, a frequency distribution statistic interface and a reporting statistic interface.
In one embodiment, the monitoring terminal includes a J2EE platform, and a software system of the monitoring platform is deployed on the platform. Fig. 4 provides a schematic diagram of an architecture of a software system in the J2EE platform, and as shown in fig. 2, a part of the software system is built on the J2EE platform, and the system is divided into a resource layer, a storage layer, a control layer, and a presentation layer by using a design idea of providing service support in a hierarchical manner. The system defines a clear functional interface for each layer, and realizes modular interface realization in the layer. The realization of layering and module modularization ensures that the system has the flexibility to the maximum extent, thereby being capable of making quick response to the change of business requirements and ensuring that the system has good expansibility.
In order to help understand the functions that can be realized by the new energy power generation monitoring platform provided in the foregoing embodiments of the present application, in a certain embodiment, based on the monitoring platform, a corresponding operating method is also provided, including:
1) and (3) data acquisition:
the new energy power generation monitoring platform collects short-term and ultra-short-term prediction data from a station end, collects actual measurement data from a centralized control end of the intelligent combined control center and transmits the actual measurement data to the master station center, and a communication protocol supports IEC104, IEC102, Modbus-Rtu, Tcp-Modbus, FTP and SFTP.
2) And (3) data storage is carried out:
2.1) storing 15min numerical weather forecast data at all times during the operation of the new energy power generation monitoring platform;
2.2) storing the operation data, the anemometer tower data and the meteorological station data at all times during the operation of the new energy power generation monitoring platform, and converting the operation data, the anemometer tower data and the meteorological station data into 15min actual power and 5min anemometer tower data and meteorological station data;
2.3) storing all prediction results of the short-term power prediction executed each time;
2.4) storing all prediction results of ultra-short term power prediction executed in a rolling way every 15 min;
3) carrying out intelligent data cleaning:
3.1) historical data quality control and pretreatment:
the original data in the intelligent combined regulation and control center centralized control end system has a plurality of data with important attributes, if the missing values and the error values are simply discarded, the effect of data mining can be seriously influenced, and the real effectiveness of the original data is also changed. Such as misestimating the annual average wind speed of a wind farm, a photovoltaic power plant, underestimating or overestimating the output of a wind farm, etc. Data quality control is a prerequisite for correctly evaluating the operation condition of the new energy electric field. The data abnormal state generally has four forms: the method is characterized in that missing, constant, wrong and verification are not passed, research on missing, dead, wrong and verification which do not pass through a verification algorithm is carried out on operation data of a wind power plant and a photovoltaic power station, and the method comprises but is not limited to calculation of absolute errors of adjacent data points, reasonable range of meteorological data, meteorological stations, logical correlation of wind measuring tower layer heights, correlation verification of different fans and the like.
3.2) historical data repair based on big data architecture:
wind speed, wind direction and power data acquired by single machine data and wind speed, wind direction, temperature, humidity and pressure data of all layers acquired by anemometer tower data are missing, and missing numbers within 4 continuous points are supplemented by the nearest normal points in adjacent time; and if the number of the defects exceeds 4 continuous points, synchronously supplementing the wind measuring data of the adjacent fans in the same time period. And (4) data errors of wind speed, power and the wind measuring tower are repaired by adopting a substitution, nonlinear correction or meteorological simulation method.
4) Performing high-precision meteorological resource simulation:
the new energy power generation monitoring platform selects typical areas and time periods in a unified area, and adopts different parameterization scheme settings for simulation based on a mesoscale atmospheric mode. And comparing the simulation result with the actual measurement data of the meteorological points, analyzing the influence of different parameterization schemes on the accuracy of the simulation result of different meteorological elements, selecting the parameterization scheme suitable for the meteorological element numerical simulation of the group area, and providing a basis for the parameterization scheme selection of the high-precision numerical weather forecasting system.
5) Calculating the correlation of the regional output:
when a meteorological model is initialized, the new energy power generation monitoring platform performs correlation analysis (correlation coefficient calculation and correlation degree analysis) on the photoelectric actual output of each meteorological point and each dimensional area according to various area dimensions (group-area-power station) by using meteorological elements (wind speed, wind direction, irradiance and the like) of meteorological points and area output historical data and combining the group area terrain.
And according to the result of the correlation analysis, researching a reference weather point (a reference power station) of each area, selecting a correlation index, and combining the correlation index to obtain the reference weather point.
And (3) searching a proper power prediction algorithm in regions by using the reference weather point meteorological elements (wind speed, wind direction, irradiance and the like) and the region output historical data of each region, and establishing a reasonable power prediction model of each region.
6) Carrying out intelligent training on the regional centralized prediction model:
in the meteorological modeling process of the new energy power generation monitoring platform, a photovoltaic power station with better prediction quality and higher correlation degree with regional output is selected in a region to serve as a representative photovoltaic power station and a wind power plant, then a scale-up algorithm model of the output condition of the representative photovoltaic power station and the wind power plant and the overall output condition of the region is established, and finally, the regional output prediction is obtained based on the output prediction of the representative wind power plant and the photovoltaic power station.
7) And (3) predicting the medium-term and long-term power generation capacity:
the new energy power generation monitoring platform carries out long-term power generation amount prediction and medium-short term power generation amount prediction on the station.
7.1) long-term power generation capacity (year, month) prediction function: the prediction software can realize that a new energy station annual and monthly power generation prediction model is established based on historical multi-year meteorological simulation data and historical power generation data, the power generation of a future year and a rolling month is predicted, and the time resolution is 24 hours.
7.2) medium-short term power generation (week and day) prediction function: the prediction software can realize the purpose that a week power generation amount prediction model of the new energy field is established based on the weather forecast data, historical and current power generation amount data and month power generation amount prediction data of seven days in the future, the power generation amount of one week in the future is predicted, the time resolution is 24 hours, and the prediction is performed once in a rolling mode every day.
7.3) regional power generation capacity prediction function: the prediction software can realize the generation capacity prediction based on a single electric field and a power station, establish a generation capacity prediction model of the whole network and the regional wind field station, and predict annual, monthly and weekly generation capacity data of the whole network and the regional wind field station.
And 7.4) the prediction software can be used for establishing a secondary correction prediction model by comprehensively considering the influence factors of the prediction result according to the basic data and the actually measured historical data, and forming the functions of analysis, correction and the like of the prediction result of each power generation capacity.
8) And (3) implementing panoramic monitoring:
the new energy power generation monitoring platform provides a web interface panoramic monitoring function for users in a unified mode, real-time data operation conditions are checked from headquarters, areas and power stations in real time in a multi-angle mode, different interface contents are checked through login of different user authorities, and corresponding data and curves are displayed.
The panoramic monitoring interface can check the real-time power and predicted power data curves in the whole area of the headquarters, compare and check corresponding real-time meteorological data, perform short-term and ultra-short-term (1-24 points) precision ranking on the power stations under the headquarters, the ranking sequence is approximately small, the prediction conditions of the power stations every day are updated in real time, and operation and maintenance personnel can conveniently know the precision ranking of all the power stations in the headquarters in time.
9) And (3) carrying out regional monitoring:
the new energy power generation monitoring platform monitors the overall operation profile of the power station in the group area range for a user in a unified manner, from the aspect of the area, the real-time output condition and the prediction information of the area-new energy station can be monitored in real time, and the installed capacity, the grid-connected power, the meteorological information, the running number of the fans/inverters, the meteorological states (cloudy, sunny and snow) and the PM2.5 numerical value in the area can be refreshed in real time.
The macroscopic graph shows the following information:
A. actual power, station-side predicted power and center-side predicted power of the area range;
B. weather information of weather stations/anemometers in the regional range and forecast weather information of the center terminal.
10) And (3) carrying out site monitoring:
the new energy power generation monitoring platform unifies that a user can finely track the overall operation condition of the power station, from the perspective of a floor type station, the real-time output condition and the prediction information of the station can be monitored in real time, and the installed capacity, the grid-connected power, the meteorological information and the operation quantity of the fans/inverters can be refreshed in real time.
And the wind turbines of the photovoltaic power station inverter and the wind power plant are finely monitored, and the running power and the generated energy information are displayed in real time.
The macroscopic graph shows the following information:
A. actual power, station-side predicted power and center-side predicted power;
B. weather information of a weather station/a wind measuring tower and forecast weather information of a center terminal.
11) And (3) performing regional cluster prediction:
the new energy power generation monitoring platform acquires meteorological resource information through the services of a meteorological data center in a unified mode, uploads real-time data by combining meteorological monitoring equipment of each power station, calculates power prediction data of each power station in an area and power prediction data of the area where the power station belongs through a power prediction algorithm, and comprises power predictions of the levels of ultra-short-term prediction, medium-term prediction and the like.
11.1) the cluster power prediction of the short-term area can be carried out, the photoelectric output power in the area from 00 hours to 72 hours on the next day can be predicted, and the time resolution is 15 minutes.
11.2) ultra-short-term region cluster power prediction can be carried out, so that the photoelectric output power in a region 0-4 hours in the future can be predicted, the rolling time is 15 minutes, and the time resolution is 15 minutes.
11.3) the cluster power prediction of the middle-period area can be carried out, the photoelectric output power in the area of 0-7 days in the future can be predicted, and the time resolution is 1 hour.
11.4) setting the time range:
A. the short-term power prediction can predict 7 days from the time zero of the next day, the time can be configured, the theoretical power prediction and the capability power prediction are carried out, and the time resolution is at least 15 min;
B. the function of uploading predicted data files for multiple times (at least four times) every day is achieved, the times are configurable, and multiple predicted results can be stored, inquired and exported;
C. the ultra-short term power prediction can predict the capability power prediction of 15min-6h in the future, and the time resolution is not less than 15 min;
D. power prediction under the condition of expanding a wind power plant/photovoltaic power station is supported;
E. the method supports the processing method of the missing data and the abnormal data in the prediction model, and rolls back to trace the value data.
11.5) performing a predictive comparative analysis:
the prediction comparison analysis mainly uses a curve graph to form a comparison center end prediction result and a station end prediction result, can freely switch between a histogram and the curve graph, and compares the difference between the prediction result and the actual result in a visual mode.
The main functional points are as follows:
A. comparing the actual power with the predicted power;
B. transversely comparing meteorological information including actual irradiance, wind speed, wind direction, temperature, humidity and pressure with predicted meteorological information;
C. performing transverse comparison according to any time dimension;
D. a comparison result may be derived.
11.6) weather comparison analysis:
the prediction comparison analysis mainly uses a curve graph to form a comparison center end prediction result and a station end prediction result, can freely switch between a histogram and the curve graph, and compares the difference between the prediction result and the actual result in a visual mode.
The main functional points are as follows:
A. comparing the actual power with the predicted power;
B. transversely comparing meteorological information including actual irradiance, wind speed, wind direction, temperature, humidity and pressure with predicted meteorological information;
C. performing transverse comparison according to any time dimension;
D. a comparison result may be derived.
11.7) reporting a prediction result:
and the prediction result data of the new energy power generation monitoring platform is reported to the provincial dispatching and local dispatching interface, so that the prediction data can be uploaded to the dispatching automation system in real time.
The main functional points are as follows:
A. and displaying the scheduling files, the requirement indexes, the statistical indexes and the assessment method of each area.
B. Communication method configuration, communication data configuration, communication channel configuration and data cycle configuration.
C. The reporting protocol meets IEC102, FTP and SFTP power prediction scheduling end communication protocols.
D. According to the requirements of each regional power grid company, the reported contents not only comprise: the system comprises the contents of station basic information, operation information, overhaul capacity, installed capacity, commissioning capacity, maximum output, short-term forecast data, ultra-short-term forecast data, meteorological station actual measurement data, numerical weather forecast data and the like.
E. All reported data can be exported according to date.
The main performance points are as follows:
A. the system can report at least a 96-point prediction curve of the next day (from zero hour) to a power prediction system of a superior scheduling mechanism according to the requirements of a scheduling department.
B. If the power prediction curve of 0-72 hours from the time zero of the next day should be reported on weekends, the future 6h ultra-short-term prediction curve is reported every 15min, and the time resolution is not less than 15 min.
C. And data and numerical weather forecast information of the station weather station are transmitted to the superior scheduling in real time, and the time resolution is not more than 15 min.
11.8) meteorological monitoring:
A. monitoring the wind speed:
and displaying the weather forecast wind speed of the station and the wind speed 5, 10 and 15 minute average values of the wind measuring tower and the weather station in the target time period, respectively displaying the wind speed of the wind measuring tower, the weather wind speed of the substation and the predicted wind speed, and providing various visual modes for viewing a curve chart and a table.
B. Monitoring wind direction:
and displaying photovoltaic weather forecast, a wind measuring tower and a wind direction rose diagram of the weather station in the target time period, and switching randomly between dimensions. And displaying a rose diagram according to the selected condition, wherein when the station is selected, the rose diagram displays the wind direction of the selected station, and a rose diagram is generated in one day.
C. Monitoring temperature, humidity and pressure:
and displaying photovoltaic weather forecast, the temperature, humidity and pressure data of the anemometer tower and the meteorological station in a target time period, inquiring the temperature, humidity and pressure of the station, and displaying the substation prediction data, the main station prediction data and the measured data by each curve graph with the time resolution of 15 minutes.
D. Irradiance monitoring:
and displaying the photovoltaic weather forecast and the irradiance data of the weather stations in the target time period, wherein the irradiance data comprises total radiation, direct radiation and scattered radiation, and displaying the total radiation (main station prediction), the total radiation (substation prediction), the total radiation (weather station), the direct radiation (weather station) and the scattered radiation (weather station) of the selected weather stations.
12) And (4) integrity statistics:
and counting the integrity of data uploading according to multiple dimensions such as grid-connected power data, anemometer tower data, weather forecast data, meteorological station data and the like in a target time period, transversely displaying and analyzing the data through the total number, normal number, abnormal number and lost number of the data, and providing multiple graphic visualization modes.
13) Power error statistics:
the error statistics comprises short-term error statistics and ultra-short-term (1-24 prediction points) error statistics, real power data and predicted power data of a certain time period are displayed, the real power data and the predicted power data are displayed in a curve form for comparison, and the Root Mean Square Error (RMSE), the Equivalent Root Mean Square Error (ERMSE), the average absolute error (MAE) and the correlation coefficient of the time period are calculated and displayed.
14) Reporting data statistics:
the system can count the uploading rate of the prediction result in real time, display the integrity rate of each power station uploaded to the scheduling prediction file every day, display the number, the station, the time, the type (short-term prediction E file, ultra-short-term prediction E file, weather station E file, numerical weather forecast), the number and the integrity rate (%) in percentage.
15) And (3) frequency distribution statistics:
the platform uniformly counts the frequency distribution of data items such as grid-connected power, wind speed and wind direction of a wind measuring tower, wind speed and wind direction of a fan, total irradiance of a meteorological station, numerical meteorological forecast wind speed, irradiance and wind direction. The anemometry tower data supports anemometry data statistics of multiple story heights. And counting results, namely dividing the statistics form by a numerical range by taking days as a unit, and counting the numerical number of each range so as to obtain a frequency distribution statistical result of the whole. The comparison statistics can be carried out aiming at the statistical result, and the quality sequencing can be carried out on the power stations in the region;
16) and (4) alarm monitoring:
files and operation parameters are generated by predicting the manager station in real time based on the graphical interface, the operation problems of the station are found in time by grasping the working states of the front-end station and the rear-end station in time, and the abnormal station is accurately positioned.
The alarm is displayed in a graphical mode, different alarm types are distinguished by different colors, and alarm pushing is generated at the granularity of 15 minutes.
Wherein, the warning monitoring range includes: a short-term forecast E file, a short-term forecast generating file, an ultra-short-term forecast E file, an ultra-short-term forecast generating file, a numerical weather forecast E file and a numerical weather forecast generating file.
17) Monitoring the running state of the system in real time:
the real-time statistics of the collected and non-collected quantity of the collection interface condition is supported, the running conditions of the server resource utilization rate and the database resource utilization rate are monitored in real time, and a graphical visual interface is provided.
18) Managing the system configuration:
the configuration management of the system mainly comprises system information management functions of managing system user distribution, managing menus, managing logs, managing regional power station information and the like.
18.1) user information management:
the platform can classify the operation authority of the system according to requirements, and define different user groups which are divided into an administrator user group and an on-duty operator user group, wherein the administrator user group comprises a system administrator, and the on-duty operator user group comprises an operation operator and a browsing user. Each end user group is given a specific right, and users belonging to the same user group have the same right.
When a user logs in the system, the platform needs to select the user group and the user name where the user is located, and the user can log in the system to perform related operations after password authentication.
The number of platform login users is not limited, and the platform login users can be customized by a system administrator, but when the platform is on duty, the platform login users need to log in by using their own job numbers.
18.2) operation authority management:
if the platform comprises a system administrator built-in group, only the identity of the system administrator can have operation permission on any operation item; the user can be managed: including user definition, assigning users to groups, configuring operation authority items of each group, and the like. The system management system is used for carrying out detailed itemization aiming at the system operation function, a system administrator can carry out authorization and recovery operation on each user group by each operation authority item, and the authority distribution operation is flexible, convenient and safe.
Support the operation authority management that becomes more meticulous, can carry out independent setting to the operation of all interfaces and the permission of looking over, based on the two-dimensional authority management of role and node, the user can have different roles at different node levels, and different roles have corresponded different permissions, can configure the operation alone and look over the permission to every function, include:
the method provides a customized authority management system, supports the addition of new accounts and the distribution of authorities, supports the change of the authorities of the existing accounts, and distributes and changes the revision authorities of the prediction curves and the distribution and changes of system configuration authorities.
In summary, the new energy power generation monitoring platform provided by the application realizes development of a high-precision meteorological numerical mode and a power prediction model based on Kalman filtering by combining regional geographical climate characteristics, regional characteristics of a power generation group and training of meteorological element live data and an intelligent algorithm model, constructs a high-resolution regional centralized prediction system, displays meteorological resources and future time-space changes in a region in an imaging manner, completes development of a regional new energy power prediction model by combining power station equipment fault information, and provides support for theoretical output of power stations in the group region, short-term and ultra-short-term (0-4 hours in the future) prediction of single-station and centralized power generation benefits and management in the group region. Therefore, the embodiment of the application can achieve at least the following beneficial effects:
(1) according to the geographical climate characteristics, calculating regional high-precision meteorological resources, and realizing the imaging display of macroscopic regional high-precision solar radiation data;
(2) carrying out classification research on regions by using a landform and climate network method, and carrying out region division on different meteorological elements and meteorological resources;
(3) aiming at algorithm optimization of regional wind and light power centralized accurate prediction models, intelligently matching whole-field modeling, partition modeling and single-machine modeling according to different terrains;
(4) selecting a reference meteorological point with high correlation with regional photoelectric output by combining regional climate and characteristics, establishing a nonlinear relation algorithm model of regional output and reference meteorological points (reference photovoltaic power stations) with different dimensions, and supporting application of reference meteorological points (reference photovoltaic power stations) and multi-dimensional regional photoelectric output prediction;
(5) establishing a power generation amount prediction model of the whole network and regional wind power plants/photovoltaic power stations based on power generation amount prediction of the power stations, and predicting annual, monthly and weekly power generation amount data of the whole network and regional wind power plants/photovoltaic power stations;
(6) the existing acquisition resources are fully utilized, data quality control and pretreatment restoration are developed, the integrity and accuracy of service data are realized, the data quality is improved, groups can conveniently and accurately evaluate the station absorption capacity, and support is provided for optimizing the station production plan;
(7) and a friendly visual graphical interface is provided, and data such as predicted power, actual power, irradiation, wind speed, wind direction, temperature, humidity, pressure and the like in short-term and ultra-short-term arbitrary time of the region-station dimension can be freely switched.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and there may be other divisions in actual practice, for example, multiple units or page components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. The utility model provides a new forms of energy electricity generation monitor platform which characterized in that includes:
the system comprises first-zone hardware, second-zone hardware, third-zone hardware and an extranet system;
the first area hardware comprises a regulation center and a wind-solar power storage station; the control center is used for acquiring the operation data of the wind-solar power storage station;
the second-zone hardware comprises a prediction server, a power grid dispatching transaction center, a dispatching data network switch and a workstation; the power grid dispatching transaction center carries out data interaction with the prediction server through the dispatching data network switch; the workstation is used for performing centralized prediction and monitoring; the centralized prediction comprises prediction of meteorological resources and output correlation of different time dimensions and different area ranges;
the three-zone hardware comprises a meteorological server, and the extranet system comprises a numerical meteorological center; the meteorological server is used for acquiring meteorological data from the numerical meteorological center.
2. The new energy power generation monitoring platform according to claim 1, wherein the first area hardware and the second area hardware adopt a switch for data interaction, and the second area hardware and the third area hardware perform data interaction through a reverse isolation device.
3. The new energy power generation monitoring platform according to claim 1, wherein a firewall is deployed between the first area hardware and the second area hardware, and between the third area hardware and the extranet system.
4. The new energy power generation monitoring platform according to claim 1, wherein the workstation comprises a monitoring terminal; the monitoring terminal comprises a data interface module, a basic function module and a high-level application module;
the data interface module comprises an interface service submodule, an interface system submodule, a centralized control system submodule and a power prediction system submodule;
the basic function module comprises a wind power region power prediction submodule, a photovoltaic region power prediction submodule and a data analysis submodule;
the advanced application module comprises a comparison analysis submodule, a panoramic monitoring submodule, a power generation amount prediction submodule and a statistical analysis submodule.
5. The new energy power generation monitoring platform of claim 4,
the interface service sub-module comprises a service data interface and a power prediction curve interface;
the interface system sub-module comprises a data analysis interface, a data storage interface, a data processing interface and a data processing interface;
the centralized control system submodule comprises an equipment information interface, a wind power plant real-time data interface and a photovoltaic power plant real-time data interface;
the power prediction system submodule comprises a meteorological data interface and a prediction data interface.
6. The new energy power generation monitoring platform of claim 4,
the wind power region power prediction submodule and the photovoltaic region power prediction submodule respectively comprise a corresponding ultra-short-term power prediction interface, a short-term power prediction interface and a middle-term region cluster power prediction interface;
the data analysis submodule comprises a power prediction data statistical analysis submodule, an electric field operation data statistical analysis submodule and a data weather forecast statistical analysis submodule.
7. The new energy power generation monitoring platform of claim 4,
the comparison analysis sub-module comprises a power curve comparison interface, an irradiance curve comparison interface and a wind speed curve comparison interface;
the panoramic monitoring submodule comprises an area monitoring interface and an electric field monitoring interface;
the generating capacity prediction sub-module comprises a medium-term prediction interface and a medium-term prediction interface;
the statistic analysis sub-module comprises an integrity statistic interface, a power error statistic interface, a frequency distribution statistic interface and a reporting statistic interface.
8. The new energy generation monitoring platform of claim 4, wherein the monitoring terminal comprises a J2EE platform.
9. The new energy power generation monitoring platform according to claim 1, wherein communication among the first zone hardware, the second zone hardware, the third zone hardware and the extranet system is based on international industry standard communication standards.
10. The new energy generation monitoring platform of claim 2, wherein the prediction server comprises:
the main prediction server is used for carrying out data interaction with the power grid dispatching transaction center through the dispatching data network switch, carrying out data interaction with the regulation and control center through the switch, carrying out data interaction with the meteorological server through the reverse isolation device, and sending stored data to the workstation;
and the standby prediction server is connected with the main prediction server in parallel and is used for calling when the main prediction server is abnormal.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210498309.2A CN114977490A (en) | 2022-05-09 | 2022-05-09 | New forms of energy electricity generation monitor platform |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210498309.2A CN114977490A (en) | 2022-05-09 | 2022-05-09 | New forms of energy electricity generation monitor platform |
Publications (1)
Publication Number | Publication Date |
---|---|
CN114977490A true CN114977490A (en) | 2022-08-30 |
Family
ID=82981563
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210498309.2A Pending CN114977490A (en) | 2022-05-09 | 2022-05-09 | New forms of energy electricity generation monitor platform |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114977490A (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115225415A (en) * | 2022-09-21 | 2022-10-21 | 南京华盾电力信息安全测评有限公司 | Password application platform for new energy centralized control system and monitoring and early warning method |
CN116633018A (en) * | 2023-05-31 | 2023-08-22 | 国家电网有限公司 | Power industry fault power failure full-flow management and control platform |
CN116661831A (en) * | 2023-07-21 | 2023-08-29 | 国能日新科技股份有限公司 | Automatic upgrading system and method for power generation station algorithm |
-
2022
- 2022-05-09 CN CN202210498309.2A patent/CN114977490A/en active Pending
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115225415A (en) * | 2022-09-21 | 2022-10-21 | 南京华盾电力信息安全测评有限公司 | Password application platform for new energy centralized control system and monitoring and early warning method |
CN115225415B (en) * | 2022-09-21 | 2023-01-24 | 南京华盾电力信息安全测评有限公司 | Password application platform for new energy centralized control system and monitoring and early warning method |
CN116633018A (en) * | 2023-05-31 | 2023-08-22 | 国家电网有限公司 | Power industry fault power failure full-flow management and control platform |
CN116661831A (en) * | 2023-07-21 | 2023-08-29 | 国能日新科技股份有限公司 | Automatic upgrading system and method for power generation station algorithm |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN114977490A (en) | New forms of energy electricity generation monitor platform | |
CN102736593B (en) | Integrated platform system for remote management and control of wind power field cluster | |
CN203324773U (en) | Wind farm centralized control system | |
CN102193555B (en) | Panoramic-state monitoring system for centralized control centers | |
CN106952032A (en) | A kind of equipment manufacture big data management system | |
CN102156467B (en) | Steel production planning-based energy forecasting method | |
CN106228278A (en) | Photovoltaic power prognoses system | |
WO2011041741A2 (en) | Microgrid model based automated real time simulation for market based electric power system optimization | |
CN104182902A (en) | Monitoring method based on centralized operation and maintenance system of dispatching data network | |
KR101927759B1 (en) | optimum control system for photovoltaic energy generation system | |
CN105449849A (en) | Wind farm integrated monitoring system | |
CN110533348A (en) | Wisdom power consumption management cloud platform | |
CN101923685A (en) | System and method for deciding power shedding load based on line breaking fault rate prediction | |
CN111461567A (en) | Mass distributed new energy low-cost management system based on mobile Internet of things | |
CN115173550A (en) | Distributed photovoltaic power generation real-time monitoring method and system | |
CN113610253A (en) | Operation and maintenance management type photovoltaic station control system based on CS version | |
CN114915029A (en) | Distributed photovoltaic power station remote online intelligent monitoring platform | |
CN113762911A (en) | Manufacturing method of comprehensive energy service platform based on distributed architecture | |
CN112712191A (en) | Energy utilization method for deep fusion of energy Internet | |
CN116633018A (en) | Power industry fault power failure full-flow management and control platform | |
Jain et al. | Overview of Energy Management Systems for Microgrids and Smart Grid | |
CN110416996A (en) | A kind of distributed photovoltaic cluster power prediction system based on cloud platform | |
CN116933952B (en) | Park low-carbon energy scheduling system based on visualization of Internet of things | |
Meliones et al. | A web-based three-tier control and monitoring application for integrated facility management of photovoltaic systems | |
CN105939025A (en) | Wind power prediction system of dispatching main station end |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |