NL2033882B1 - Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction - Google Patents

Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction Download PDF

Info

Publication number
NL2033882B1
NL2033882B1 NL2033882A NL2033882A NL2033882B1 NL 2033882 B1 NL2033882 B1 NL 2033882B1 NL 2033882 A NL2033882 A NL 2033882A NL 2033882 A NL2033882 A NL 2033882A NL 2033882 B1 NL2033882 B1 NL 2033882B1
Authority
NL
Netherlands
Prior art keywords
data
new energy
prediction
energy power
comprehensive evaluation
Prior art date
Application number
NL2033882A
Other languages
Dutch (nl)
Other versions
NL2033882A (en
Inventor
Ji Yanqiu
Zhang Xu
Zhang Yuan
Lv Qingquan
He Chang'an
Zhang Yuanfeng
Sun Jianhua
Hu Diangang
Guo Taibei
Fu Jiayu
Gou Peijun
Wang Lu
Original Assignee
State Grid Gansu Electric Power Co
Gansu Tongxing Intelligent Tech Development Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by State Grid Gansu Electric Power Co, Gansu Tongxing Intelligent Tech Development Co Ltd filed Critical State Grid Gansu Electric Power Co
Priority to NL2033882A priority Critical patent/NL2033882B1/en
Publication of NL2033882A publication Critical patent/NL2033882A/en
Application granted granted Critical
Publication of NL2033882B1 publication Critical patent/NL2033882B1/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0611—Request for offers or quotes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0613—Third-party assisted
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Finance (AREA)
  • Accounting & Taxation (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Human Resources & Organizations (AREA)
  • Development Economics (AREA)
  • Health & Medical Sciences (AREA)
  • Tourism & Hospitality (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Game Theory and Decision Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention belongs to the technical field of software development and discloses a comprehensive evaluation method, system and medium for multi-source new energy power prediction. Real-time data is obtained from the storage resource pool, downloaded meteorological data is obtained from the meteorological service, and new energy power prediction is realized through algorithms and models. The system displays and compares the predicted manufacturer data of all access platforms, and ranks them according to different dimensions. Upload the prediction results to the unified path, filter the reported files, and finally upload and parse the files. The invention provides a multi-source new energy power prediction comprehensive evaluation system, which can satisfy the requirements of multiple manufacturers and new energy stations to manage, data query and analysis, and compare the prediction results on the system. The multi-source comprehensive evaluation method for new energy power prediction provided by the invention applies the advantages of multi-meteorological sources and high-performance computing resources to improve the accuracy of power prediction and meet the requirements of power grid for fine management of new energy stations.

Description

State Grid Gansu Electric Power Company, and
Gansu Tongxing Intelligent Technology Development CO., LTD. 22/110 PDNL
Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction
Technical Field
The invention belongs to the technical field of software development, in particular to a comprehensive evaluation method, system and medium for multi-source new energy power prediction.
Background Technology
At present, the traditional power prediction system is deployed on the field side, and the power prediction data is reported by the field side. Only one enterprise's equipment and system can be used in one electric field cycle. The service cost of switching enterprises is high and the cycle is long, so the system can only be upgraded on-site, and the service upgrade optimization cost is high and the cycle is long.
Additionally, the power prediction service level of each station is uneven. Due to the large number of manufacturers carrying out power prediction services in the market, the large number of station services, and the increasingly standardized and strict assessment standards, the technology research and development investment and service support level of power prediction by various prediction manufacturers vary greatly, and the market is chaotic.
Due to the uneven prediction level of various service providers, the accuracy of power prediction is not high, which increases the difficulty of power grid dispatch and cannot meet the requirements of power grid for fine management of new energy stations.
The data is scattered and the linkage is not strong. At present, the power prediction transmits data from multiple points of the new energy field station to the control center, and the data is scattered. Due to the stability of the channel on the source side of the network, the system barrier and the inconsistency of the standard specification at the field end, the linkage between the data is weak.
Through the above analysis, the problems and defects of the existing technology are as follows: (1) Traditional power prediction system switching enterprises have high service cost and long cycle, so the system can only be upgraded on-site, and service upgrade optimization has high cost and long cycle.
(2) Due to the uneven prediction level of various service providers, the accuracy of power prediction is not high, which increases the difficulty of power grid dispatch and cannot meet the requirements of power grid for fine management of new energy stations. (3) At the present stage, the power prediction data is scattered, and the channel stability of the source side of the network, the system barrier and the standard specification of the field end are not unified, resulting in the weak linkage between the data.
Description of the Invention
In view of the problems existing in the prior art, the invention provides a comprehensive evaluation method, system and medium for multi-source new energy power prediction.
The invention is realized as follows: a comprehensive evaluation method oriented to multi-source new energy power prediction. The comprehensive evaluation method oriented to multi-source new energy power prediction includes: obtaining real-time data from storage resource pool, obtaining downloaded meteorological data from meteorological service, and realizing new energy power prediction through algorithm and model; The system displays and compares the predicted manufacturer data of all access platforms, and ranks them according to different dimensions. Upload the prediction results to the unified path, filter the reported files, and finally upload and parse the files.
Further, the comprehensive evaluation method for multi-source new energy power prediction includes the following steps:
Step 1: Prediction: Obtaining meteorological data (the meteorological data is mainly forecast meteorological data, and the new small-scale forecast data is obtained by downscaling the original large-scale meteorological forecast data) and storing the meteorological data to the corresponding server. Then the meteorological data are used to achieve short-term prediction and ultra-short-term prediction through different algorithms and models. The short term includes the power forecast for the next 10 days, the time granularity of the forecast data is 15min, and the forecast period is daily. Ultra-short-term forecast data are rolling forecast every 15 minutes, and the forecast time interval is 16 points in total in the next 4 hours, with a time granularity of 15min. After the prediction is completed, the corresponding prediction point data is stored. If the accuracy of the corresponding prediction is defective, the accuracy of the data is corrected by dynamically adjusting the corresponding algorithm model in real time.
Step 2: Comparison: The prediction manufacturers complete their own power prediction data and upload the corresponding power prediction data to the comparison platform through the interface or file. After receiving the corresponding data, the platform will uniformly process the data of each manufacturer, mark the corresponding manufacturer label, and display and compare the data of all the prediction manufacturers through the platform display page.
Step 3: Report: After unified processing of the obtained prediction results of each forecast manufacturer, the platform displays all forecast manufacturers with normal data.
The report files are screened by users, and then uploaded and analyzed for storage.
Furthermore, in Step 1, each power prediction manufacturer deplores power prediction service and weather download service on the platform, and obtains real-time data from the storage resource pool of the big data platform respectively. Obtain the downloaded meteorological data from the meteorological service, integrate the forecast result data according to the file format required by the provincial survey through algorithm and model calculation, and send it to the unified reporting directory; Among them, real-time data obtained from the storage resource pool of the big data platform include active power, wind speed and irradiance data.
Furthermore, in Step 2, the system displays and compares the power prediction results, power grid assessment results, accuracy rate, reporting rate and order situation data of all the prediction manufacturers connected to the platform through the unified interface, and ranks them in different dimensions to achieve the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The system provides wind power and photovoltaic classification comparison, shows the comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and compares the gap between the predicted curve and the measured curve; According to the power prediction comparison of each forecast in the system, the new energy station selects and purchases power prediction service providers on the operation platform.
Furthermore, in Step 3, each power prediction manufacturer transmits the prediction result to the specified unified path through sftp. According to the manually entered order, the system filters the report file; Upload to Region Il of provincial investigation in a unified manner through 102 protocol for warehousing analysis.
Furthermore, the forecast results include short-term, ultra-short-term, inverter and weather station files.
Another purpose of the invention is to provide a comprehensive evaluation system for multi-source new energy power prediction by applying the comprehensive evaluation method for multi-source new energy power prediction. The comprehensive evaluation system for multi-source new energy power prediction comprises:
Prediction module, which is used to obtain real-time meteorological data and realize power prediction through algorithm and model;
Comparison module, which is used to display and compare the data of all the prediction manufacturers connected to the platform;
Report module, which is used to obtain prediction results, filter report files, and then enter the database for analysis.
Another purpose of the invention is to provide a computer device, which comprises a memory and a processor, and the memory stores a computer program, which, when executed by the processor, enables the processor to perform the steps of the comprehensive evaluation method for multi-source new energy power prediction.
Another purpose of the present invention is to provide a computer readable storage medium containing a computer program which, when executed by the processor, enables the processor to perform the steps of the comprehensive evaluation method for power prediction of multi-source new energy sources.
Another purpose of the invention is to provide an information data processing terminal, which is used to realize the comprehensive evaluation system for multi-source new energy power prediction.
Combined with the above technical scheme and the technical problem solved, the advantages and positive effects of the technical scheme to be protected by the invention are as follows:
The comprehensive evaluation method for multi-source new energy power prediction of the invention provides an innovative centralized prediction mode, so that as long as the prediction manufacturer pays attention to the prediction algorithm, the platform manufacturer mainly pays attention to the system maintenance, so that unified use and unified management can be realized only by maintaining a set of systems. Realize the comparative display of all power prediction data and indicators, multi-dimensional comparative analysis of power prediction data, centralized management of power prediction manufacturers, and in-depth mining of power prediction data. The invention can also adapt to the needs of business and technological development in the next few years. At the same time, the maturity of products and technologies should be taken into account as much as possible to ensure the overall stability of the basic platform.
The comprehensive evaluation system for multi-source new energy power prediction provided by the invention adopts the micro-service software design mode, and each module in the system is a micro-service that can be independently separated and deployed.
Combined with the Docker container technology and container cloud platform used at the bottom, the continuous integration and continuous deployment technology based on the container cloud platform can realize the rapid iterative development of the system. The system can be upgraded several to dozens of times a day to ensure the rapid and stable online of new services.
The power prediction service and meteorological download service are deployed on the platform of each power prediction manufacturer of the invention, and real-time data (active 5 power, wind speed, irradiation, etc.) are obtained from the storage resource pool of the big data platform respectively, and downloaded meteorological data are obtained from the meteorological service. Through the calculation of algorithms and models, the predicted result data are integrated in accordance with the required file format. And send it to the unified reporting directory.
The invention displays and compares the power prediction results, power grid assessment results, accuracy rate, reporting rate, order situation and other data of all the prediction manufacturers connected to the platform through a unified interface, and ranks them in different dimensions, so as to realize the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The classification comparison of wind power and photovoltaic is also provided to show the comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and to visually compare the gap between the predicted curve and the measured curve.
The invention improves the accuracy of prediction. Simple and centralized deployment allows forecasting vendors to devote more human and material resources to the key goal of improving forecast accuracy. There is no need to worry about the quality of measured data affecting the accuracy of prediction, no need to worry about the complex network from the electric field to the power grid affecting the timely reporting of prediction data, no need to spend time and energy to the electric field site to deal with a simple or complex problem, no need to worry about the hardware limitations affecting the complex calculation of data.
The invention reduces the number of interfaces between the power grid system and the
Internet and improves the network security of the power grid system. Based on the current centralized monitoring system of the power grid to obtain real-time data of the electric field, and an external network outlet of the power grid to obtain meteorological data of all stations, the corresponding prediction function can be realized. By controlling the destination address, port, protocol and other strategies of the external network outlet at the power grid end, coupled with logical and physical isolation, the invention ensures the security and control of the Internet outlet of the power grid, which is sufficient to ensure the security of the entire power grid network.
The invention provides a multi-source new energy power prediction comprehensive evaluation system, which can satisfy the requirements of multiple manufacturers and new energy stations to manage, data query and analysis, and compare the prediction results on the system. The multi-source comprehensive evaluation method of new energy power prediction applies the advantages of multi-meteorological sources and high-performance computing resources to improve the accuracy of power prediction and meet the requirements of power grid for fine management of new energy stations.
The expected benefits and commercial value of the technical scheme of the invention after transformation are as follows: for new energy power generation enterprises, it can save a large amount of hardware, software, network and other costs required by the procurement of forecasting system. This can save the workload of the station personnel on duty to maintain each system. For the prediction manufacturer, it can save the labor cost and time cost that must go to the site to deploy and maintain the prediction system. For the power grid, the platform should be provided for the use of forecasting manufacturers and electric field owners, and reasonable service fees should be charged from it, so as to continuously promote the upgrading and improvement of centralized forecasting and provide more perfect forecasting services.
Additionally, the invention has the following advantages: 1. Portal integration
There are multiple services provided by multiple manufacturers in the power prediction application service ecosystem. A unified directory is used to display multiple power prediction services. 2. Common platform architecture
Without much hardware and software dependence, virtual machines and containerization enable secure, reliable, fast response, elastic scaling of computing resources and one-click deployment. 3. Other advantages (1) Innovative centralized prediction mode, benefiting the electric field, prediction manufacturers, power grid and other parties, and improving the accuracy of the overall new energy prediction. (2) Prediction manufacturers mainly focus on prediction algorithms, while platform manufacturers mainly focus on system maintenance. This can realize that we only need to maintain a set of systems, can achieve unified use, unified management. This avoids the decentralized deployment and maintenance of the traditional prediction system, and there will be many network hidden dangers in each electric field, which has obvious management benefits.
Brief Description of the Drawings
In order to more clearly explain the technical scheme of the implementation methods of the invention, a brief introduction will be made to the attached drawings required in the implementation methods of the invention in the following. Obviously, the attached drawings described below are only some implementation methods of the invention. For ordinary technicians in the art, other attached drawings can be obtained according to these attached drawings without paying creative labor.
Figure 1 is the flow chart of the comprehensive evaluation method for multi-source new energy power prediction provided by the implementation method of the invention.
Specific Implementation Methods
In order to make the purpose, technical scheme and advantages of the invention more clearly, the invention is further explained in the following implementation methods. It should be understood that the specific implementation method described herein are intended only to explain the invention and are not intended to qualify it.
In view of the problems existing in the prior art, the invention provides a comprehensive evaluation method, system and medium for multi-source new energy power prediction. The following is a detailed description of the invention combined with the attached figure.
In order to enable those skilled in the art to fully understand how the invention is implemented, this part is an explanatory illustrative implementation method of the technical scheme of the claim.
As shown in Figure 1, the comprehensive evaluation method for multi-source new energy power prediction provided by the implementation method of the invention comprises the following steps:
S101. Prediction: Obtain real-time meteorological data and realize power prediction through algorithms and models;
S102. Comparison: Display and comparison of the data of all the prediction manufacturers connected to the platform;
S103. Report: Obtain the prediction results and filter the report files, and then carry out warehousing analysis.
The comprehensive evaluation system for multi-source new energy power prediction provided by the implementation method of the invention comprises: 1. Business architecture implementation
Using the micro-service software design mode, each module in the system is a micro- service that can be independently separated and deployed. Combined with the Docker container technology and container cloud platform used at the bottom, the continuous integration and continuous deployment technology on the container cloud platform can realize the rapid iterative development of the system, and the system can be upgraded several to dozens of times a day. Ensure the rapid and stable launch of new business. 2. System architecture implementation
It is divided into three corresponding services: (1) Prediction function
Each power prediction manufacturer deploys power prediction service and meteorological download service on the platform, and obtains real-time data (active power, wind speed, irradiance and other data) from the storage resource pool of the big data platform respectively.
Obtain the downloaded meteorological data from the meteorological service, integrate the forecast result data according to the file format required by the provincial survey and send it to the unified reporting directory through the calculation of algorithm and model. (2) Comparison function
The system displays and compares the power prediction results, power grid assessment results, accuracy rate, reporting rate and order situation of all forecast manufacturers connected to the platform through a unified interface, and ranks them in different dimensions. This can realize the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The system provides classification comparison of wind power and photovoltaic, shows the comparison of short-term and ultra- short-term accuracy of different models for all power stations under each type, and visually compares the gap between the predicted curve and the measured curve. The new energy station can choose its own power prediction service provider on the operation platform according to the power prediction comparison of each forecast in the system. (3) Reporting function
Each power prediction manufacturer will send the prediction results (short-term, ultra- short-term, inverter, weather station and other files) to the specified unified path through sftp.
The system filters the report documents according to the manually entered order. Upload to
Region Il of provincial investigation in a unified manner through 102 protocol for warehousing analysis.
The comprehensive evaluation system for multi-source new energy power prediction provided by the implementation method of the invention comprises:
Prediction module, which is used to obtain real-time meteorological data and realize power prediction through algorithm and model;
Comparison module, which is used to display and compare the data of all the prediction manufacturers connected to the platform;
Report module, which is used to obtain prediction results, filter report files, and then enter the database for analysis.
On the application server provided on site, the relevant applications are deployed in the way of micro-services, and the implementation of the scheme is completed in accordance with the three steps of prediction, comparison and reporting. In the prediction module, the connected prediction manufacturer obtains real-time and historical meteorological data, as well as historical actual power data through the platform, predicts the corresponding short- term and ultra-short-term data according to the algorithm model, and calculates whether the accuracy meets the requirements by comparing with the actual data. If the deviation is large, the data is corrected by constantly adjusting the algorithm model. The corresponding prediction accuracy requirements have been met.
The platform will display and compare the power prediction results, power grid assessment results, accuracy and reporting rates of all the connected prediction manufacturers, and rank them in different dimensions. So as to realize the unified comparison and evaluation of the prediction results of different power prediction manufacturers. The platform also provides classification comparison of wind power and photovoltaic, showing the comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and intuitively comparing the gap between the predicted curve and the measured curve. According to the above data display, the new energy station can purchase its own power prediction service provider from the platform.
Each power prediction manufacturer in the reporting module will send the prediction results (short-term, ultra-short-term, inverter, weather station and other files) to the specified path through sftp. The user enters the order through the system and filters the corresponding report file. It is uploaded to Region II of provincial investigation through 102 protocol for warehousing analysis.
It should be noted that the implementation methods of the present invention can be realized by hardware, software or a combination of software and hardware. The hardware part can be implemented by special logic; The software component can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or specially designed hardware. A person of ordinary skill in the art can understand that the above devices and methods can be implemented using computer executable instructions and/or included in the processor control code, For example, such code is provided on carrier media such as disks, CD, or DVD-ROM, programmable memory such as read-only memory (firmware), or data carriers such as optical or electronic signal carriers. The devices of the present invention and their modules may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors. It can also be implemented by a combination of the above hardware circuits and software such as firmware.
The above is only the specific implementation of the invention, but the protection scope of the invention is not limited to this. Any modification, equivalent replacement and improvement made by any skilled person familiar with the technical field within the technical scope disclosed by the invention and within the spirit and principle of the invention shall be covered within the scope of protection of the invention.

Claims (8)

ConclusiesConclusions 1. Uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen, met het kenmerk, dat real-time data worden verkregen uit de pool van opslagsystemen, dat gedownloade meteorologische data worden verkregen van de meteorologische dienst, en dat voorspelling van nieuw energievermogen wordt gerealiseerd door middel van algoritmes en modellen, waarbij het systeem de voorspelde data van de verschaffers van alle toegangsplatformen toont en vergelijkt en deze volgens verschillende dimensies rangschikt, waarbij de voorspelde resultaten naar het uniforme pad worden geüpload, de gerapporteerde bestanden worden gefilterd en de bestanden tenslotte worden geüpload en geparseerd.1. Comprehensive evaluation method for predicting new energy power from multiple sources, characterized in that real-time data is obtained from the pool of storage systems, downloaded meteorological data is obtained from the meteorological service, and prediction of new energy power is realized through algorithms and models, where the system displays and compares the predicted data from the providers of all access platforms and arranges them according to different dimensions, uploading the predicted results to the unified path, filtering the reported files and finally sorting the files uploaded and parsed. 2. Uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen volgens conclusie 1, met het kenmerk, dat de methode de volgende stappen omvat: Stap 1. Voorspelling: Verkrijg meteorologische data in realtime en realiseer voor- spelling van het energievermogen door middel van algoritmes en modellen; Stap 2. Vergelijking: toon en vergelijk de data van alle voorspellingsverschaffers die met het platform zijn verbonden; Stap 3. Rapportage: verkrijg de resultaten van de voorspellingen, screen de rappor- terende bestanden en voer vervolgens een warehouse analyse uit.2. Comprehensive evaluation method for predicting new energy power from multiple sources according to claim 1, characterized in that the method includes the following steps: Step 1. Forecast: Obtain meteorological data in real time and realize energy power prediction by means of algorithms and models; Step 2. Comparison: display and compare the data from all forecast providers connected to the platform; Step 3. Reporting: obtain the results of the predictions, screen the reporting files and then perform a warehouse analysis. 3. Uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen volgens conclusie 2, met het kenmerk, dat in stap 1 iedere verschaffer van voorspellingen van energievermogen een voorspellingsdienst voor energievermogen en een downloaddienst voor het weer op het platform inzet, resp. real-time data verkrijgt uit de pool van opslagsystemen van het big data-platform, waarbij de gedownloade meteoro- logische data worden verkregen van de meteorologische dienst, de data van de voorspelde resultaten worden geïntegreerd door middel van algoritme- en modelberekening volgens het bestandsformat dat door de provinciale inspectie is vereist en deze naar de uniforme rapportage directory worden gestuurd, waarbij de real-time data die uit de pool van opslag- systemen van het big data-platform zijn verkregen, onder meer data van actief energie- vermogen, windsnelheid en straling omvatten.3. Comprehensive evaluation method for predicting new energy power from multiple sources according to claim 2, characterized in that in step 1 each provider of energy power predictions deploys an energy power prediction service and a weather download service on the platform, respectively. obtains real-time data from the pool of storage systems of the big data platform, obtaining the downloaded meteorological data from the meteorological service, integrating the data of the forecast results through algorithm and model calculation according to the file format provided required by the provincial inspection and sent to the uniform reporting directory, where the real-time data obtained from the pool of storage systems of the big data platform, including data of active energy power, wind speed and include radiation. 4. Uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen volgens conclusie 2, met het kenmerk, dat in stap 2 het systeem de resultaten van de voorspelling van het energievermogen, de beoordelingsresultaten van het elektriciteitsnet, de mate van nauwkeurigheid, de rapportagesnelheid en de data van de ordersituatie van alle voorspellingsverschaffers die via een uniforme interface met het platform zijn verbonden, weergeeft en vergelijkt, en deze in verschillende dimensies rang- schikt, waarbij een uniforme vergelijking en evaluatie van de voorspellingsresultaten van de verschillende verschaffers van vermogensvoorspellingen wordt gerealiseerd, waarbij het systeem een vergelijking van windenergie en fotovoltaïsche classificatie biedt, en een vergelijking van korte termijn- en ultrakorte termijn-nauwkeurigheid van verschillende modellen voor alle krachtcentrales onder elk type toont, en de ruimte tussen de voorspelde curve en de gemeten curve vergelijkt; waarbij het nieuwe energiestation volgens de vergelijking van de energievoorspellingen van iedere voorspelling in het systeem, dienstverleners van energievoorspellingen op het uitvoeringsplatform selecteert en koopt.4. Comprehensive evaluation method for predicting new energy power from multiple sources according to claim 2, characterized in that in step 2 the system evaluates the results of the energy power prediction, the assessment results of the power grid, the degree of accuracy, the reporting rate and displays and compares the order situation data of all forecast providers connected to the platform through a uniform interface, and arranges them in different dimensions, realizing a uniform comparison and evaluation of the forecast results of the different asset forecast providers, wherein the system provides a comparison of wind energy and photovoltaic classification, and shows a comparison of short-term and ultra-short-term accuracy of different models for all power stations under each type, and compares the space between the predicted curve and the measured curve; wherein, according to the comparison of the energy forecasts of each forecast in the system, the new energy station selects and purchases energy forecast service providers on the execution platform. 5. Uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen volgens conclusie 2, met het kenmerk, dat in stap 3 elke verschaffer van vermogensvoorspelling een vermogensvoorspellingsdienst en een weerdownloaddienst op het platform inzet, en real-time data verkrijgt van respectievelijk de opslagresourcepool van het big data-platform, waarbij de gedownloade meteorologische data worden verkregen van de meteorologische dienst, de voorspellingsresultaatdata worden geïntegreerd door middel van algoritme- en modelberekening volgens het bestandsformaat dat door de provinciale inspectie is vereist en deze naar de uniforme rapportagedirectory worden gestuurd, waarbij real-time data die uit de pool van opslagsystemen van het big data-platform zijn verkregen, onder meer data van actief energievermogen, windsnelheid en straling omvatten.5. A comprehensive evaluation method for predicting new energy power from multiple sources according to claim 2, characterized in that in step 3, each power forecasting provider deploys a power forecasting service and a weather download service on the platform, and obtains real-time data from the storage resource pool respectively the big data platform, obtaining the downloaded meteorological data from the meteorological department, integrating the forecast result data through algorithm and model calculation according to the file format required by the provincial inspection, and sending it to the unified reporting directory, where real -time data obtained from the pool of storage systems of the big data platform, including data of active energy power, wind speed and radiation. 6. Uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen volgens conclusie 5, met het kenmerk, dat de voorspellingsresultaten korte termijn-, ultrakorte termijn-, omvormer- en weerstation-bestanden omvatten.A comprehensive evaluation method for predicting new energy power from multiple sources according to claim 5, characterized in that the prediction results include short-term, ultra-short-term, inverter and weather station files. 7. Uitgebreid evaluatiesysteem voor het voorspellen van nieuw energievermogen uit meerdere bronnen onder toepassing van de uitgebreide evaluatiemethode voor het voor- spellen van nieuw energievermogen uit meerdere bronnen volgens conclusie 1, met het kenmerk, dat het systeem omvat: - Voorspellingsmodule om real-time meteorologische data te verkrijgen en voor- spelling van het energievermogen te realiseren door middel van algoritmes en modellen; - Vergelijkingsmodule om de data van alle met het platform verbonden voorspellings- verschaffers weer te geven en te vergelijken;7. Comprehensive evaluation system for predicting new energy power from multiple sources using the comprehensive evaluation method for predicting new energy power from multiple sources according to claim 1, characterized in that the system comprises: - Forecasting module for real-time meteorological obtain data and predict energy capacity by means of algorithms and models; - Comparison module to display and compare the data from all forecast providers connected to the platform; - Rapportagemodule om voorspellingsresultaten te verkrijgen en, rapportage- bestanden te filteren, en vervolgens in de database in te voeren voor analyse.- Reporting module to obtain forecast results and, filter reporting files, and then enter into the database for analysis. 8. Door een computer leesbaar opslagmedium, dat een computerprogramma opslaat, met het kenmerk, dat wanneer het computerprogramma door de processor wordt uitge- voerd, de processor de stappen uitvoert van de uitgebreide evaluatiemethode voor het voorspellen van nieuw energievermogen uit meerdere bronnen, zoals beschreven in één van de conclusies 1- 6.8. A computer-readable storage medium storing a computer program, characterized in that when the computer program is executed by the processor, the processor performs the steps of the extended evaluation method for predicting new energy from multiple sources, as described in one of claims 1-6.
NL2033882A 2022-12-30 2022-12-30 Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction NL2033882B1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
NL2033882A NL2033882B1 (en) 2022-12-30 2022-12-30 Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
NL2033882A NL2033882B1 (en) 2022-12-30 2022-12-30 Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction

Publications (2)

Publication Number Publication Date
NL2033882A NL2033882A (en) 2023-04-07
NL2033882B1 true NL2033882B1 (en) 2023-09-06

Family

ID=85872902

Family Applications (1)

Application Number Title Priority Date Filing Date
NL2033882A NL2033882B1 (en) 2022-12-30 2022-12-30 Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction

Country Status (1)

Country Link
NL (1) NL2033882B1 (en)

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3580719A4 (en) * 2017-02-13 2020-09-16 Griddy Holdings LLC Methods and systems for an automated utility marketplace platform
CN109639880B (en) * 2018-11-08 2021-02-02 维沃移动通信有限公司 Weather information display method and terminal equipment

Also Published As

Publication number Publication date
NL2033882A (en) 2023-04-07

Similar Documents

Publication Publication Date Title
US10734811B2 (en) System and method for optimal control of energy storage system
CN102855525B (en) A kind of resident's load prediction analytic system and method
CN102084569B (en) Method and system for managing a power grid
CN103514514A (en) On-line monitoring method for electricity marketing business data
CN111754023A (en) Edge-cloud-cooperated user load prediction control and transaction system and implementation method thereof
CN110889466B (en) Transformer area line loss analysis method based on line loss classifier
CN105631604A (en) Platform used for environmental health management
CN103366311A (en) Data fusion processing method based on transformer substation multi-system
CN106391482A (en) Parcel sorting machine control method and system based on cloud computing
CN109558991B (en) Commodity channel quantity recommendation method, device, equipment and storage medium based on vending machine
CN103929759A (en) Method and system for optimizing mobile network based on medical histories
CN106097161A (en) Water affairs management system and data processing method thereof
CN105787665A (en) System for providing environment management service
US20230342699A1 (en) Systems and methods for modeling and analysis of infrastructure services provided by cloud services provider systems
NL2033882B1 (en) Comprehensive Evaluation Method, System and Medium for Multi-source New Energy Power Prediction
CN108921733B (en) Property information processing system based on cloud storage
Abolghasemi et al. How to predict and optimise with asymmetric error metrics
CN102137449A (en) Business process method and system for business support system
CN115016902B (en) Industrial flow digital management system and method
CN114997574A (en) Power distribution station area elastic resource management method and device based on service middling station
Yuan Intelligent logistics management application relying on the internet of things
CN105787666A (en) System for providing health management service
CN116881106B (en) Method, device, storage medium and equipment for analyzing and managing capacity operation of service system
Zhang et al. Design and development of big data cloud platform for cattle and sheep IoT breeding based on SaaS
US20240202752A1 (en) Distributed energy resources management system software platform