1 Scope
This standard specifies the technical requirements for forecasting data requirements, forecasting system software requirements, hardware requirements and performance indicators of the photovoltaic power plant power forecasting system.
This standard applies to grid-connected photovoltaic power stations.
2 normative references
The following documents are indispensable for the application of this document. For dated references, only the dated version applies to this document. For undated references, the latest version (including all amendments) applies to this document.
Technical Regulations for GB/T 19964 Photovoltaic Power Station Intervention Power System
Technical requirements for real-time monitoring of solar energy resources in GB/T 30153 photovoltaic power stations
3 Terms and Definitions
The following terms and definitions apply to this document.
3.1
Photovoltaic power station photovoltaicta (PV) power station
Utilizing the photovoltaic effect of photovoltaic cells, power generation systems that convert solar radiation energy directly into electrical energy generally include transformers, inverters, and photovoltaic arrays, as well as associated auxiliary facilities.
3.2
Numerical Weather Prediction
According to the actual conditions of the atmosphere, under certain initial values ​​and boundary conditions, numerical calculations are performed by large-scale computers to solve equations describing fluid dynamics and thermodynamics in the process of weather evolution, and to predict atmospheric motion conditions and weather phenomena in the future.
3.3
Photovoltaie power forecasting
According to meteorological conditions, statistical laws and other technologies and means, forecast the active power of photovoltaic power stations.
3.4
Irradiance irradiance
The ratio of the radiant flux impinging on the bin to the area of ​​the bin, in units of W/m2.
3.5
Total irradiance global irradiance
Also known as total irradiance, it refers to the total solar radiant flux per unit area of ​​the silly brother on the incident and horizontal surface, in units of W/m2.
3.6
Direct irradiance direct irradiance
Radiant flux per unit area of ​​8° of the half-cone angle from the sky-sun disk and its surroundings to the irradiation point, in units of W/m2.
3.7
Scattered irradiance diffuse irradiance
In addition to the contribution of out-of-direct irradiance, the radiant flux per unit area from the entire sky is given in W/m2.
3.8
Total radiation exposure global iadiant exposure
The total amount of total radiation irradiance over a given time period, in units of Jm2.
3.9
Sunshine duration
The direct solar radiation irradiance is greater than or equal to 120W/m2 of the comprehensive time, also known as the actual hours.
3.10
Data availability
The ratio of the number of deviations of the collected data from the real data to the number of all collected data is less than 5%.
3.11
Forecast system monthly availability prediction systerm ratio
In each month, the ratio of fault-free running time to total time is predicted.
4 forecast data requirements
4.1 Basic requirements
The data required for photovoltaic power station power should include at least numerical weather forecast data, real-time meteorological data, real-time power data, operational status, planned maintenance information, and so on.
4.2 Data Acquisition
4.2.1 Numerical weather forecast data should meet the following requirements:
a) It should include at least the numerical weather forecast data for the next 3 days from the next day, with a time resolution of 15 min;
b) The data should include at least parameters such as total radiation irradiance, cloud cover, air temperature, humidity, wind speed, wind direction, and pressure;
c) At least two numerical weather forecast data are provided daily.
4.2.2 Real-time weather data should meet the following requirements:
a) The technical indicators of the real-time meteorological information acquisition equipment shall meet the requirements of GB/T 30153;
b) Real-time meteorological data shall include total radiation irradiance (horizontal and tilt), ambient temperature, humidity, wind speed, wind direction, etc. It shall include parameters such as direct irradiance, scattered irradiance, and air pressure;
c) The transmission time interval should not exceed 5 min;
d) The availability of collected data should be greater than 95%.
4.2.3 The real-time power data and equipment operation status (including PV module temperature) shall be taken from the PV power station computer monitoring system, and the collection time interval shall not exceed 5 minutes.
4.2.4 The collection of all data should be completed automatically and can be added manually by manual input.
4.2.5 The time delay of all real-time data should not exceed 1 min.
4.3 Data Processing
4.3.1 All data should be tested for completeness and plausibility, supplemented and corrected for missing and abnormal data.
4.3.2 The data integrity check should satisfy:
a) The amount of data should equal the number of data expected to be recorded;
b) The time sequence of the data should be in line with the expected start and end times, and the middle should be continuous.
4.3.3 Data Rationality Testing should meet:
a) Examine limit values ​​for power, numerical weather forecast, and measured meteorological data.
b) Perform correlation tests on the data based on the relationship between measured weather data and power data.
4.3.4 Missing test and abnormal data should be handled according to the following requirements:
a) previous power data complements missing or abnormal power data;
b) Replace less than zero power data with zero;
c) Meteorological data that are missing or abnormal can be corrected by other meteorological elements according to the principle of correlation; data from previous moments that do not have corrective conditions are replaced;
d) All corrected data are recorded with special identifiers and can be queried;
e) All missing and abnormal data can be manually supplemented or corrected.
4.4 Data Storage
Data storage should meet the following requirements:
a) The data collected in real time shall be taken as the original original data and backed up, and no changes shall be made to the original data;
b) Numerical weather forecast data at all times during storage system operation;
c) Power data, real-time meteorological data at all times during the operation of the storage system;
d) store all the prediction results of the short-term power prediction performed each time;
e) store all predictions of ultra-short-term power projections performed every 15 minutes;
f) Predict all the prediction results before and after correction of the curve after manual correction;
g) All data is kept for at least 10 years.
5 Prediction System Software Requirements
5.1 Basic requirements
5.1.1 Based on the specific characteristics of photovoltaic power stations, combined with historical and measured data of photovoltaic power stations, appropriate prediction methods are used to build prediction models, and photovoltaic power plant power forecasting systems are established on this basis.
5.1.2 Photovoltaic power forecasting system software should include numerical weather forecasting module, real-time meteorological information processing module, short-term forecasting module, ultra-short-term forecasting module, system man-machine interface, database, and data exchange interface.
5.2 Predict Software Configuration Requirements
5.2.1 The forecasting system should be equipped with a general-purpose, mature commercial relational database for the storage of data, models and parameters.
5.2.2 Predictive system software should be implemented on a unified support platform with a uniform style man-machine interface.
5.2.3 Predictive system software should be divided into modules. Failure of a single functional module does not affect the operation of the entire predictive system.
5.2.4 The predictive system should be scalable to support the development of users and third-party applications.
5.2.5 Predictive systems should use rights management mechanisms to ensure the security of system operations.
5.3 Forecast Module Requirements
5.3.1 Short-term power forecasts should meet the following requirements:
a) It should be able to predict the output power of the photovoltaic power station from the next day from midnight to the next 72 hours with a time resolution of 15 min;
b) The short-term forecast input includes data such as numerical weather forecast, so as to obtain the predicted power;
c) Short-term forecasting should consider the influence of maintenance and fault lamps on the output power of photovoltaic power stations;
d) The predictive model should be scalable to meet the power forecast for newly built, built, and expanded photovoltaic power stations;
e) It is advisable to use a variety of prediction methods to establish a prediction model to form an optimal predictive test chlorine;
f) For short-term prediction based on the number of NWP releases, the word calculation time should be less than 5 minutes.
5.3.2 Ultra-short-term power forecasts should meet the following requirements:
a) It can predict the output power of the photovoltaic power station in the future 15min ~ 4h with a time resolution of 15min;
b) The input of the ultra-short-term prediction model shall include measured power data, measured meteorological data, and equipment status data;
c) It is advisable to use actual measured data for analysis to determine cloud cover of PV power stations and to realize prediction of ultra-short-term power fluctuations;
d) The ultra-short-term forecast should be performed once every 15 minutes, and the forecast results should be dynamically updated. The word calculation time should be less than 5 minutes.
5.4 man-machine interface requirements
5.4.1 The photovoltaic power station output monitoring page should be available to display the layout of photovoltaic power stations in a map format. At least the actual power, predicted power, and meteorological meteorological elements should be displayed at the same time. The data update time should not exceed 5 minutes.
5.4.2 should have a photovoltaic power station output curve display page, should also display the system prediction curve, the actual power curve should be updated dynamically and update time should not exceed 5min.
5.4.3 should have historical data curve query page, at least provide daily, weekly and other time curve display, page query response time should be less than 1min.
5.4.4 Should provide statistical data analysis page, provide a variety of visualization methods such as pie charts, column charts, tables.
5.4.5 The system page should adopt a uniform style, and the page layout is reasonable, which is convenient for the operating personnel.
5.5 Data Statistics Requirements
5.5.1 Statistics of photovoltaic power station operating parameters, measured meteorological data, and prediction errors should be available.
5.5.2 The statistics of operating parameters shall include the amount of electricity generated, the effective generation time, the maximum output and the time of occurrence, the number of hours of utilization and the average load rate.
5.5.3 The meteorological data statistics shall include the average value of all meteorological elements and the total radiant tonnage, sunshine hours, etc.
5.5.4 Prediction Error Statistical indicators should at least include root mean square error, average absolute error, correlation coefficient, maximum prediction error, and pass rate. For the calculation of error index, see Appendix A.
5.5.5 The time range of participation statistics should be arbitrarily selected, and the night time can be automatically excluded based on the sunrise and sunset times of the photovoltaic power station location.
5.5.6 The statistical calculation time of each index should be less than 1min.
6 Hardware Requirements
6.1 Photovoltaic power plant power prediction system hardware includes at least a numerical weather forecast server, a system application server, a physical isolation device, and a man-machine workstation. A database server, a network switching device, and a hardware firewall may be selected as required.
6.2 The mainstream server should be used to support cluster, RAID, and other technical features. It supports dual-channel independent power input and should adopt redundant configuration.
6.3 workstations should adopt the graphics workstations of mainstream hardware manufacturers, should have good reliability and scalability.
6.4 The physical isolation device shall be tested and certified by the national designated department.
6.5 Select necessary devices such as switches, firewalls, and routers as required.
6.6 Photovoltaic power plant power forecasting system shall be operated in the safety secondary area II of the power system and interface with the dispatching planning system.
7 performance indicators
7.1 The monthly average root-mean-square error of the short-term forecast of photovoltaic power generation period (excluding the controlled period) shall be less than 0.15, and the monthly qualification rate shall be greater than 80%; the monthly average root mean square error of the ultra-short-term prediction shall be less than 0.10. The passing rate should be greater than 85%.
7.2 The CPU load rate of all computers under normal conditions is less than 30% within 5 min and the peak load rate is less than 50%.
7.3 The system server MTBF should not be less than 30000h.
7.4 The monthly availability of the forecast system should be greater than 99%.
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