CN109934402B - Wind power plant centralized control center centralized wind power prediction system and design method thereof - Google Patents
Wind power plant centralized control center centralized wind power prediction system and design method thereof Download PDFInfo
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Abstract
The invention provides a centralized wind power prediction system of a centralized control center of a wind farm, which comprises the following components: (1) a data source; (2) a data platform layer; (3) applying a presentation layer; the centralized wind power prediction system adopts a micro-service software design mode, each module in the system is a micro-service which can be independently split and deployed, a Docker container technology and a container cloud platform used at the bottom layer are based on a continuous integration and continuous deployment technology on the container cloud platform, so that the rapid iterative updating of the system is realized, and the system is divided into a framework of a production control large area and a framework of an information management large area. The design method of the centralized wind power prediction system of the centralized control center of the wind power plant comprises the following steps: 1) Designing a network topology of a centralized wind power prediction system and a safety protection module of a power monitoring system; 2) The method comprises the steps of designing a prediction result acquisition and display module of a centralized wind power prediction system; 3) And designing an implementation strategy for the human intervention power prediction result.
Description
Technical Field
The invention belongs to a power system, and particularly relates to a wind power prediction system in a centralized control center of a wind power plant and a design method thereof.
Background
The state energy bureau issues a file of notification (national energy new energy [ 2011 ] No. 177) of a temporary method for wind farm power prediction and forecast management in 2011 month 6, and a wind power prediction system must be formally put into operation before 2012 month 7 of the wind farm is required, so that the configuration of the wind power prediction system at the wind farm side has become a mandatory requirement of the state.
Wind power generation enterprises face serious problems of 'wind curtailment and electricity limitation' and unfavorable external environments of 'gradual low' of comprehensive online electricity prices. In order to further reduce the power generation operation cost, in recent years, wind power enterprises build a centralized control operation center of a wind power plant based on the principle of 'unattended operation and less attended operation'.
The existing wind farm power prediction coefficient technical scheme is mature, and the structure of the gold wind technology wind farm power prediction system is shown in figure 1. The related power monitoring system safety protection mechanism of the station side wind power prediction system in the figure meets the requirements of national issuing and modifying Commission on the safety protection regulations of the power monitoring system (national issuing and modifying Commission No. 14 in 2014), and national energy agency on the safety protection scheme and evaluation criterion notification of the general scheme of the security protection of the printed power monitoring system (national energy safety No. 2015) and the like. The power prediction server is located in a safe II area, real-time operation data such as active power of a wind power plant, wind speed of the wind power plant and the like of the fan monitoring server are obtained through a protective wall between the I/II areas, and meteorological data, wind tower data and return power prediction assessment indexes in the meteorological downloading server are obtained through forward and reverse isolation devices in the II/III areas. And the power prediction server predicts the short-term and ultra-short-term wind power of the electric field by using an algorithm according to the data, and then reports the power data file to a power dispatching control center with the dispatching authority through a power dispatching data network.
A single power prediction system at a wind power plant station end cannot be directly applied to a centralized control center main station end, a wind power plant centralized control center does not currently have a centralized power prediction system of a main station belonging to the centralized control center, and power prediction data of all stations can be monitored at the centralized control center main station end. How to predict future active power of a governed wind power plant at a centralized control center side becomes urgent business demand in a centralized control operation mode, and a set of wind power plant centralized power prediction system is needed to be designed at the centralized control center side.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the system and the design method thereof overcome the defects of the prior art, predict the future active power of the administered wind farm at the centralized control center side, thereby meeting the operation requirement of a centralized control operation mode, realizing the centralized power prediction of new energy assets such as wind power generation, solar power generation, hydroelectric power generation and the like of the Tianrun centralized control center by using the new energy unified centralized power prediction system, facilitating the scientific and reasonable formulation of safe production operation plans of a power grid and each power station, reducing the production operation risk of the power station, continuously improving the power generation income of the power station, further improving the power generation planning of the power grid company on each power station, accurately completing the electric quantity transaction, and assisting the power generation enterprises in improving the operation and maintenance efficiency and the operation and management level.
To this end, an object of the present invention is to provide a wind power prediction system for a wind farm centralized control center, comprising:
(1) Data source: as the basic data source of the centralized power prediction system, the basic data are divided into wind farm data and photovoltaic electric field data according to electric field types, are divided into fan data, inverter data, measurement equipment data and booster station data according to equipment types, the data sources listed by the equipment classifications are displayed, the measurement equipment data comprise real-time monitoring data of wind speed and irradiance of two electric fields, the basic data are uploaded to a central end system through a unified data interface of a large data platform by a client, the weather and power prediction data of a power prediction manufacturer are the data sources of weather forecast early warning data and prediction power data of the centralized wind power prediction system of the wind farm centralized control center, and the data are directly uploaded to the central end of the centralized wind power prediction system of the wind farm centralized control center through the Internet;
(2) Data platform layer: for providing unified storage and calculation resources for the central end of the unified wind power prediction system of the wind power plant centralized control center, each service subsystem of the wind power prediction system is deployed on a data platform layer;
(3) Application display layer: the system is an interface of the centralized power prediction system, and a new energy user can realize query, monitoring and report work of all wind farm power prediction services through the interface.
Preferably, the data platform layer includes a unified data access service, a unified data storage pool, a unified computing resource pool, a data warehouse, and a unified data publishing service, where the data access service is based on a big data acquisition technology, and includes a stream data and batch data acquisition technology APACHE KAFKA, and a log and other unstructured data acquisition technologies logstack; the application display layer comprises weather forecast and early warning service, power forecast and early warning service and service management service, wherein the weather forecast and early warning service is divided into weather data display, weather disaster early warning and weather data comparison query, the power forecast and early warning service is divided into functions of forecast index display, forecast actual measurement data comparison, reporting state query, manual report supplement and the like, and the service management service comprises basic information query and management, user authority setting and management, a comprehensive query system, data archiving management, a free report system and a measurement equipment management system.
Preferably, the centralized power prediction system adopts a micro-service software design mode, each module in the system is a micro-service which can be independently split and deployed, a Docker container technology and a container cloud platform used at the bottom layer are used, and the rapid iterative updating of the system is realized based on a continuous integration and continuous deployment technology on the container cloud platform.
Preferably, the centralized power prediction system is divided into a framework of a production control large area and a framework of an information management large area, the production control large area is divided into a safe I area (control area) and a safe II area (non-control area), the safe I area directly realizes real-time monitoring of the power primary system, a power dispatching data network or a special channel is longitudinally used, the safe II area runs on line but does not have a control function, the power dispatching data network is used for being electrically connected with a service system or a functional module thereof in the control area, the centralized power prediction system is provided with a firewall, a power prediction server, an internal proxy server, forward isolation and reverse isolation in the production control large area and is used for equipment data acquisition, protocol adaptation, real-time monitoring, alarm management and data forwarding, and the server of the centralized power prediction system reports a result transmitted through the reverse isolation to a power grid according to a message format required by the power grid; the inner proxy server transmits the security zone data to the outer proxy through forward isolation; the information management area collects and stores data forwarded by the internal proxy by the server cluster, and performs reverse decryption, decompression, data unpacking, information model matching, stream calculation and data persistence on the data; acquiring data of other management information systems, and performing data cleaning, conversion, loading and persistence to form a clean energy big data lake crossing a plurality of data engines; the multi-copy set storage is provided, the high availability of the data is guaranteed, the query analysis service cluster provides an impromptu query service, a multidimensional data aggregation service, a parallelization analysis engine, an offline analysis service, data audit checking, quality evaluation and repair, a use trace record and the like of massive heterogeneous data, an interface is provided for data of a RESTful principle provided for upper-layer application, and the application server cluster acquires the data through the RESTful interface, performs service visualization display and provides a centralized power prediction application.
Preferably, the architecture of the production control large area includes:
(1) Data source: collecting fan, photovoltaic, booster station, energy storage equipment, photometry tower, anemometer tower and hydropower station equipment data, and supporting 104 protocol, 101 protocol, 103 protocol, modbus protocol and 61850 protocol set;
(2) Data acquisition and protocol adaptation layer: according to the protocol and configuration, connecting data source equipment, collecting data in real time, wherein the minimum collecting period is 1s, converting the collected data into an internally defined information model, and transmitting through a data transmission service according to an internal communication protocol;
(3) Data transmission layer: the collected data is encrypted and compressed, and then sent to one or more targets in a TCP (transmission control protocol) and UDP (user datagram protocol) mode, and after the target receives the data, the data is decompressed, decrypted and provided for corresponding services;
(4) Service layer: the data receiving service is used for rapidly receiving real-time data and providing the real-time data to the data analyzing service; the data analysis service is used for rapidly analyzing each piece of data in a multithreading way, and the data are corresponding to the information model of each device in the memory, so that the data are bound one by one; the data providing service provides an interface for the outside for the showing layer to call and provides real-time data of the equipment according to the information model; when the alarm information is received, the alarm information is immediately pushed to the display layer. The real-time data statistical analysis service performs statistical analysis on the real-time data stream according to predefined rules and data models, and stores the result into a corresponding information model in a memory or pushes the result to a presentation layer; and the device control and authority security management are used for checking the operation authority of the user and the soft five-prevention security of the instruction after receiving the control instruction sent by the presentation layer, sending the checked instruction to the data acquisition service, and sending the instruction to the device by the acquisition service.
(5) Presentation layer: the method comprises the steps of first interface display of a system, prediction analysis, weather forecast and early warning, comprehensive comparison, basic information and report management function interface display.
The invention also aims to provide a wind power prediction design method in the wind power plant centralized control center set, which comprises the following steps:
Step one, designing a network topology of a concentrated wind power prediction system and a safety protection module of a power monitoring system;
Step two, designing a prediction result acquisition and display module of a concentrated wind power prediction system;
And thirdly, designing an implementation strategy for human intervention power prediction results.
Preferably, the network topology of the concentrated wind power prediction system in the first step is a network topology structure of the concentrated wind power prediction system in a centralized control center mode, the network topology structure comprises a concentrated wind power prediction system, the whole system is a cross-region single network structure, and a concentrated power prediction server and an application workstation are in redundant configuration; the power monitoring system safety protection design adopts a mode of safety partition, network special, transverse isolation and longitudinal authentication, and the concentrated wind power prediction system spans a safety II area and a management information area on the safety partition, wherein equipment deployed in the safety II area is as follows: concentrated wind power prediction server and application workstation; the equipment for deploying the management information area is as follows: a weather download server; the network special-purpose network comprises a longitudinal wide area network between a centralized wind power system and a wind farm station end power prediction system, and a special channel of a leased communication operator is adopted; the boundary protection equipment for transversely isolating the safety II area from the management information area comprises the following components: a forward and reverse isolating device; the centralized wind power prediction server acquires fan monitoring information from a centralized control center monitoring server deployed in a safety I area, and boundary protection equipment is deployed in the safety I area and the safety II area as a firewall; the weather downloading server located in the management information large area accesses the cloud power prediction cluster server through the VPN special for the Internet to obtain numerical weather forecast and short-term power prediction data, and the management information large area and the Internet area deploy boundary protection equipment as a firewall; the longitudinal authentication comprises that the centralized wind power prediction system adopts a longitudinal encryption technology through a centralized control center private network, namely longitudinal encryption device equipment which is configured by a centralized control center end and a wind power station end in pairs, and the longitudinal encryption device configured by the wind power station end encrypts an IP service packet of a wind power prediction result of the wind power station end through an SM2 algorithm, and then sends the encrypted IP service packet to a centralized control master station, and the centralized control master station longitudinal encryption device decrypts the encrypted IP service packet and then sends the encrypted IP service packet to a centralized wind power prediction server.
Preferably, the design objective of the second step includes: the short-term power prediction result of the wind farm managed by the concentrated wind power prediction system is from Jin Fenghui cloud power prediction cluster servers; the ultra-short term wind power prediction result is calculated by a wind power plant power prediction model through a numerical weather forecast obtained by a centralized power prediction server.
Preferably, the prediction result obtaining and displaying module of the centralized wind power prediction system designed in the second step can realize centralized picture display of a station, centralized prediction data total addition display, result display of a wind power plant reporting scheduling end, comparison of centralized prediction results and station end prediction results, centralized power prediction result data evaluation, short-term data correction, planned shutdown management, reporting management, electric quantity management, equipment management, error analysis and data statistics and report forms.
Preferably, the implementation strategy of the manual intervention power prediction result in the step three is used for manually correcting the short-term wind power prediction result of the wind power plant in the wind power system in a centralized manner when a central control center operator finds that the power prediction of the wind power plant end has a problem, and sending the correction result back to the power prediction server of the plant end, and sending the substitution result to a power grid dispatching end; and when the central control center operator knows that the shutdown of the fans is caused by the fault reasons of the equipment of the fans or the hard constraint of the upper-level outgoing channel, the shutdown wind turbine generator is excluded from the power prediction mode.
The invention has the beneficial effects that:
The wind power station centralized control center master station realizes centralized display of wind power prediction results of the administered wind power station; the centralized power prediction system based on the wind power centralized control center is a technical means for effectively improving the power prediction accuracy of the wind power plant; the centralized power prediction system based on the wind power centralized control center can be used for guiding a wind power plant to participate in power spot transaction and reducing the wind power prediction accuracy rate assessment of two rules.
The above, as well as additional objectives, advantages, and features of the present invention will become apparent to those skilled in the art from the following detailed description of a specific embodiment of the present invention when read in conjunction with the accompanying drawings.
Drawings
Some specific embodiments of the invention will be described in detail hereinafter by way of example and not by way of limitation with reference to the accompanying drawings. The same reference numbers will be used throughout the drawings to refer to the same or like parts or portions. It will be appreciated by those skilled in the art that the drawings are not necessarily drawn to scale. The objects and features of the present invention will become more apparent in view of the following description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a schematic diagram of an overall architecture of a centralized power prediction system according to an embodiment of the present invention;
FIG. 2 is a diagram of a large data platform of a gold-phoenix technological new energy foundation meteorological asset according to an embodiment of the present invention;
FIG. 3 is a data flow diagram of a golden phoenix scientific and technological new energy foundation meteorological asset big data platform according to an embodiment of the invention;
FIG. 4 is a system hub interface function list according to an embodiment of the present invention;
FIG. 5 is a list of system single-field interface functions according to an embodiment of the present invention;
FIG. 6 is a summary interface for a centralized power prediction system in accordance with an embodiment of the present invention;
FIG. 7 is a system weather forecast information interface in accordance with an embodiment of the present invention;
FIG. 8 is a block diagram of a wind power prediction system for a single station of a wind farm according to an embodiment of the present invention;
FIG. 9 is a network topology of a concentrated wind power prediction system according to an embodiment of the present invention;
FIG. 10 is a main monitoring screen of a concentrated wind power prediction system according to an embodiment of the present invention;
FIG. 11 is an overview of wind farm centralized power forecast data, in accordance with an embodiment of the present invention;
FIG. 12 is a graph of wind farm power forecast data evaluation in accordance with an embodiment of the present invention;
FIG. 13 is a diagram of a power prediction result data correction interface in accordance with an embodiment of the present invention;
FIG. 14 is a plan shutdown correction interface diagram in accordance with an embodiment of the present invention;
FIG. 15 is a graph of predicted electrical results according to an embodiment of the present invention;
FIG. 16 is a graph comparing historical predicted power to actual power generation in accordance with an embodiment of the present invention;
FIG. 17 is a diagram showing the measured data of a anemometer tower according to an embodiment of the present invention;
FIG. 18 is an explanatory diagram of the wind rose of the wind tower according to the embodiment of the present invention;
FIG. 19 is a diagram showing a geographical distribution of a wind turbine according to an embodiment of the present invention;
FIG. 20 is a diagram showing wind power error results according to an embodiment of the present invention.
Detailed Description
Prior to proceeding with the description of the embodiments, the industry terminology in the art to which this relates is described as follows:
(1) Wind farm: the power station is composed of a group of wind turbines or wind turbine groups (comprising a unit transformer), a collecting line, a main step-up transformer and other equipment.
(2) Numerical weather forecast: according to the actual condition of the atmosphere, under the condition of a certain initial value and a certain side value, a large-scale computer is used for carrying out numerical calculation, a fluid mechanics and thermodynamic equation set for describing the weather evolution process is solved, and the atmosphere movement state and weather phenomenon of a certain period in the future are predicted.
(3) Wind power prediction: the method comprises the steps of establishing a prediction model of wind power plant output power by using data such as historical power, historical wind speed, topography, numerical weather forecast, wind power plant running state and the like of the wind power plant, and predicting future active power of the wind power plant by using wind speed, power or numerical weather forecast data as input of the model and combining equipment state and running working conditions of the wind power plant.
(4) Short-term wind power prediction: the active power of the wind power plant from the next day zero for 3 days is predicted, and the time resolution is 15min.
(5) Ultra-short-term wind power prediction: and predicting the active power of the wind farm for 0-4 hours in the future, wherein the time resolution is not less than 15min.
(6) Centralized control operation: and a production operation mode for monitoring a plurality of wind power stations accessing the platform through the centralized monitoring platform.
1. System overall architecture
The centralized power prediction system adopts a micro-service software design mode, each module in the system is a micro-service which can be independently split and independently deployed, and the rapid iterative development of the system can be realized based on the continuous integration and continuous deployment technology on the container cloud platform by combining the dock container technology and the container cloud platform used by the bottom layer, so that the system can realize the upgrade of several times to tens of times per day, and the rapid and stable online of new business is ensured.
The centralized power prediction system is divided into three layers from the system context point of view, as shown in fig. 1:
(1) Data source
The data source is the underlying data source for the centralized power prediction system.
The basic data can be classified into wind farm data and photovoltaic farm data according to the types of electric fields, and can be classified into fan data, inverter data, measurement equipment data and booster station data according to the types of equipment, and the data sources listed by the equipment classification are shown in fig. 1. The measurement equipment data comprise real-time monitoring data of two electric fields such as wind speed, irradiance and the like. The basic data is uploaded to the central system through the unified data interface of the big data platform by the client. In addition, the weather and power prediction data of the power prediction manufacturer are data sources of weather prediction early warning data and predicted power data of the system, and the data are directly uploaded to the central end of the system through the Internet.
(2) Data platform layer
The data platform layer provides unified storage and calculation resources for the central end of the unified centralized power prediction system, and all service subsystems of the centralized power prediction system are deployed on the data platform layer.
The layer comprises unified data access service, unified data storage pool, unified computing resource pool, data warehouse and unified data release service.
The data access service is based on a big data acquisition technology (including but not limited to a stream data and batch data acquisition technology APACHE KAFKA, a log and other unstructured data acquisition technologies logstack and the like), and the advantages of using the technologies are that on one hand, the interface format of all data acquisition can be standardized, the rapid introduction of new data sources is supported, on the other hand, a local caching mechanism can be provided, when the network of a main station end and a central end is abnormal, all data cannot be lost, historical data of 7 days can be stored in a cache at most, and system operation and maintenance personnel can have network inspection and system repair time of 7 days.
(3) Application presentation layer
The application display layer is an interface of the centralized power prediction system, and a new energy user can realize the work of inquiring, monitoring, reporting and the like of all wind power plant power prediction services through the interface.
The application display layer is also divided into 3 major business categories, namely weather forecast and early warning, power forecast and business management. The weather forecast and early warning business comprises weather data display, weather disaster early warning, weather data comparison query, power forecast business comprises functions of forecast index display, forecast actual measurement data comparison, reporting state query, manual report supplement and the like, and the business management business comprises basic information query and management, user authority setting and management, a comprehensive query system, data archiving management, a free report system, a measurement equipment management system and the like.
First, a production control large area architecture
The production area is divided into a safe I area (control area) and a safe II area (non-control area). The safety I area is an important link of power production, directly realizes real-time monitoring of a power primary system, and longitudinally uses a power dispatching data network or a special channel, which is an important point and core of safety protection. The safe II area is an essential link of power production, runs on line but does not have a control function, and uses a power dispatching data network to be closely connected with a service system or a functional module thereof in the control area.
According to the safety protection regulation of the secondary power system, the system mainly comprises the following components in a production control area: firewall, power prediction server, internal proxy server, forward quarantine, reverse quarantine, etc. The method is mainly responsible for equipment data acquisition, protocol adaptation, real-time monitoring, alarm management and data forwarding. The power prediction server reports the result of the centralized power prediction transmitted by reverse isolation to the power grid according to the message format required by the power grid; the inner proxy server primarily transmits the secure zone data to the outer proxy via forward quarantine.
1. Data source:
The system can collect equipment such as fans, photovoltaics, booster stations, energy storage equipment, photometry towers, anemometry towers, hydropower stations and the like, and can support protocol sets such as 104 protocols, 101 protocols, 103 protocols, modbus protocols, 61850 and the like.
2. Data acquisition and protocol adaptation layer:
according to the protocol and configuration, connecting data source equipment, collecting data in real time, wherein the minimum collecting period is 1s, converting the collected data into an internally defined information model, and transmitting through a data transmission service according to an internal communication protocol.
3. Data transmission layer:
And encrypting and compressing the acquired data, transmitting the encrypted and compressed data to one or more targets in a TCP (transmission control protocol), UDP (user datagram protocol) mode and the like, decompressing and decrypting the data after the target receives the data, and providing the data for corresponding services.
4. Service layer:
the data receiving service is used for rapidly receiving real-time data and providing the real-time data to the data analyzing service;
The data analysis service is used for rapidly analyzing each piece of data in a multithreading way, and the data are corresponding to the information model of each device in the memory, so that the data are bound one by one;
The data providing service provides an interface for the outside for the showing layer to call and provides real-time data of the equipment according to the information model; when the alarm information is received, the alarm information is immediately pushed to the display layer.
And the real-time data statistical analysis service performs statistical analysis on the real-time data stream according to predefined rules and data models, and stores the result into a corresponding information model in the memory or pushes the result to the presentation layer.
And the device control and authority security management are used for checking the operation authority of the user and the soft five-prevention security of the instruction after receiving the control instruction sent by the presentation layer, sending the checked instruction to the data acquisition service, and sending the instruction to the device by the acquisition service.
5. Presentation layer:
The method comprises the steps of displaying a first interface of a system, predicting and analyzing, weather forecast and early warning, comprehensive comparison, basic information, report management and other functional interfaces.
(II) information management district architecture
The information management area collects and stores data forwarded by the internal agent by the server cluster, and carries out reverse decryption, decompression, data unpacking, information model matching, stream calculation and data persistence on the data; acquiring data of other management information systems, and performing data cleaning, conversion, loading and persistence to form a clean energy big data lake crossing a plurality of data engines; and providing multi-copy set storage, and ensuring high availability of data. The query analysis service cluster provides an impromptu query service, a multidimensional data aggregation service, a parallelization analysis engine, an offline analysis service, data audit verification, quality evaluation repair, a trace record and the like for massive heterogeneous data, and provides an interface for data of RESTful principle for upper-layer application. The application server cluster acquires data through a RESTful interface, performs service visual display and provides centralized power prediction application.
Referring to FIG. 2, a golden wind technology base meteorological asset big data platform graph and the golden wind technology base meteorological asset big data platform data graph of FIG. 3 can centralize a prediction method executed by a power prediction system, which comprises the following steps:
(1) Multiple meteorological source advantage:
The gold wind technology utilizes the concept of an open platform, and not only increases the investment of internal research and development capability, but also provides an open platform for the outside on the aspect of optimizing and improving weather forecast data, and provides scientific research experiments and business weather forecast data; each wind field guarantees at least 3 sets of weather forecast data sources, so that intelligent comparison with wind measuring tower data is realized, and preferential switching is realized.
(2) High performance computing resource advantage
Besides the cooperation of domestic and foreign meteorological data, the gold-wind technology combines excellent high-performance computing resources at home and abroad to conduct weather mode forecasting, set forecasting and the like, and by adopting a hybrid cloud computing scheme, super computing exceeding 100 trillion times can be applied to production practice based on the powerful cloud power of a public cloud cluster computer, and the high-performance computing resources mainly used and cooperated at present are as follows:
(III) comprehensive display system scheme
The overall architecture adopts a B/S architecture, and the front end is based on the technologies of WebGIS, HTML5, dynamic flow field animation and the like; the backend adopts the technologies of Restful API, django and the like.
The user operation adopts an interactive hierarchical mode, and the user can click the concerned wind power plant and fan on the map to acquire the historical, real-time and forecast data of the wind power plant and fan.
The system provides the functions of prediction, actual measurement data comparison, short-term and ultra-short-term accuracy query, report log monitoring, capacity forecast monitoring and the like.
The online states of the wind measuring towers and the light measuring towers, the current wind speed or irradiance are monitored, the wind rose diagram of each connected wind measuring tower is displayed, and the actual measurement meteorological data of the current day and each historical layer height can be inquired.
The system comprises a centralized end interface and a single electric field interface, wherein the function list of the centralized end interface is shown in fig. 4, and the function list of the single electric field interface is shown in fig. 5.
1. System overview interface and weather display interface
The overview interface is developed based on WebGIS, and shows the positions of all electric fields accessed by the system and the information required on the map. Referring to the system overview interface of figure 6 and the weather forecast information interface of figure 7,
2. Centralized end interface
The centralized terminal interface is mainly divided into six modules: reporting statistics, comparing the generated energy of the month, analyzing the accuracy of power prediction, comparing the power prediction, monitoring the measuring equipment on line, and counting the generated energy in the future.
(1) Reporting statistics
The report statistics module is mainly used for monitoring the report state of each report file, and the secondary interface can inquire the historical report state of the access electric field.
(2) Comparison of the amount of generated electricity in this month
The module displays the comparison of the actual power generation amount, the theoretical power generation amount and the predicted power generation amount in each day of the month, and the second-level interface supports the query of the power generation amount in the historical time period.
(3) Accuracy contrast
The main interface displays the short-term and ultra-short-term accuracy comparison of yesterday station and the central terminal, and the secondary interface supports the short-term and ultra-short-term accuracy comparison of the query history.
(4) Power prediction data comparison
The main interface displays yesterday station prediction, central end prediction and actual measurement curves, and the secondary interface can inquire the history of daily access to the station prediction and actual measurement curves.
(5) Future power generation statistics
The main interface shows the predicted power statistics for each electric field for the next 3 days.
(6) Wind tower status monitoring
The main interface monitors the on-line and off-line states of the wind measuring towers or the light measuring towers of all stations in real time, and displays the real-time wind speed or irradiance. The secondary interface can inquire the wind rose diagram of the access station in the historical time period.
3. Single electric field interface
The interface of the centralized terminal can be jumped to a single electric field interface to monitor and inquire the predicted data, statistical data, equipment state and other conditions of a certain designated electric field.
The main functions are as follows:
1) Reporting assessment
The reporting evaluation comprises a prediction evaluation and a reporting evaluation, and the interface function is to inquire the comparison of the predicted power and the measured power data of the historical time period and the comparison of the weather prediction data and the measured data of weather such as wind speed, irradiance, temperature, humidity and the like.
2) Report management
The module comprises historical report states and historical report data, can inquire the historical report states such as success and failure of each file type, and can inquire the comparison condition of the historical report data and the actual measurement data.
A) Power management
The predicted and measured electricity amounts for the historical time period and the predicted electricity amounts for several days in the future can be queried.
B) Device management
The equipment management comprises monitoring of real-time data of the anemometer tower or the irradiator, provides the functions of inquiring and deriving the history of the measuring equipment, and can intuitively see the wind rose diagram of the anemometer tower in the inquiring time period.
C) Error analysis
The error analysis module provides short-term and ultra-short-term statistical index query including indexes such as accuracy, root mean square error, correlation coefficient and the like according to the day and month, and supports data export.
D) Data statistics and reporting
The data statistics shows the indexes of the accuracy rate, the qualification rate and the reporting rate in a histogram mode, and can inquire the showing condition of each index in a period of time of the history. And providing report form display of the statistical data.
4. System core features and advantages
The key value of the centralized power prediction system is weather data and prediction system, massive fan data, power generation modeling and prediction algorithm and professional service.
The centralized power prediction system takes the key value as the center, takes the client requirement as the guide, and has the characteristics of multi-weather set preparation, big data prediction and learning optimization and affiliated professional service through years of investment, development and market practice.
5. Resources required for construction
1) Desired data points
1. Prediction data and actual measurement data (real-time data of fans, anemometers, inverters and weather stations) of each station.
2. Each station reports the log.
3. Each electric field is limited to a 15 minute threshold bit (the necessary amount for high-precision prediction).
4. Basic information of each power station comprises longitude, latitude, the number of devices, the type of the devices and the like, and templates are used as main information.
2) Platform design
1. Software platform design
The bottom layer of the centralized power prediction platform uses a container technology, so that a set of container cloud management platform needs to be deployed in a safe three-zone. The scheme selects Alauda EE container cloud products provided by clever sparrow cloud.
Alauda EE essentially provides the following techniques:
Cluster management: hosts are added or deleted according to the requirements, and the scheduling system supports Kubernetes, mesos and Swarm of the main stream.
Mirror warehouse: the private mirror warehouse service is provided, and the functions of mass storage, group management, mirror synchronization, version management and mirror scanning are satisfied.
Application and service management: the cloud native application functions such as complete application construction, arrangement, elastic expansion, gray level release and the like are provided, and full life cycle management of services or applications is supported.
DevOps: and providing complete DevOps period management, including development, test and operation and maintenance links. And provides complete CI/CD process automation management.
And (3) network management: the container network layer is defined and managed to support the creation, configuration and deletion of load balancing. In addition to supporting the Host and Bridge network models of the Docker native, flannel, IPVlan and MacVlan are also supported.
And (3) storage management: supporting multiple types of distributed storage solutions, including GlusterFS and NFS, through management of storage volumes, the need for container data persistence is fulfilled.
Monitoring and alarming: and the system supports multi-level and multi-dimensional monitoring alarms of clusters, hosts, platform components, applications, containers and the like, and provides a self-defined centralized monitoring instrument panel.
The embodiment relates to a wind power prediction design method in a centralized control center of a wind power plant, which comprises the following steps:
Network topology of concentrated wind power prediction system and safety protection design of power monitoring system
The network topology diagram of the concentrated wind power prediction system is shown in fig. 9, and the devices in the dashed line frame form the concentrated wind power prediction system, and the whole system is in a cross-region single network structure, wherein the concentrated power prediction server and the application workstation are in redundant configuration.
The centralized wind power prediction system belongs to an application system in the power monitoring system, and meets the basic safety protection principle of the power monitoring system of safety partition, network special, transverse isolation and longitudinal authentication, and spans a safety II area and a management information area on the safety partition, and the centralized wind power prediction system is contained in a broken line frame of the figure 1.
(1) Safety zone
The devices deployed in the security II zone are: concentrated wind power prediction server and application workstation;
The equipment for deploying the management information area is as follows: a weather download server;
(2) Network-specific use
The centralized control center gathers a longitudinal wide area network between the wind power system and the wind power station end power prediction system, and adopts a special channel for renting a communication operator.
(3) Lateral isolation
The boundary protection equipment of the safety II area and the management information area is as follows: a forward and reverse isolating device;
In addition, the centralized wind power prediction server acquires fan monitoring information from a centralized control center monitoring server deployed in a safety I area, and boundary protection equipment is deployed in the safety I area and the safety II area as a firewall;
The weather downloading server located in the management information area accesses Jin Fenghui the cloud power prediction cluster server through the special VPN of the Internet to obtain numerical weather prediction and short-term power prediction data, and the management information area and the Internet area deploy boundary protection equipment as a firewall;
(4) Longitudinal authentication
The centralized wind power prediction system adopts a longitudinal encryption technology through a centralized control center private network, namely longitudinal encryption device equipment which is configured by the centralized control center end and the wind power station end in pairs, and the longitudinal encryption device configured by the wind power station end encrypts a wind power prediction result IP service packet of the wind power station end through an SM2 algorithm, and then sends the encrypted service packet to a centralized control main station, and the centralized control main station longitudinal encryption device decrypts the encrypted service packet and then sends the encrypted service packet to a centralized wind power prediction server.
Prediction result acquisition and display of concentrated wind power prediction system
The short-term power prediction result of the wind farm managed by the concentrated wind power prediction system is from Jin Fenghui cloud power prediction cluster servers; the ultra-short term wind power prediction result is calculated by a wind power plant power prediction model through a numerical weather forecast obtained by a centralized power prediction server.
The centralized wind power prediction system can realize centralized picture display of a station, centralized prediction data total display, wind power plant report scheduling end result display, centralized prediction result and station end prediction result comparison, centralized power prediction result data evaluation, short-term data correction, planned shutdown management, report management, electric quantity management, equipment management, error analysis and data statistics and report forms, and display interfaces are shown in fig. 9 to 20.
Through the display interface, operation and maintenance personnel of the centralized control center can comprehensively master wind power prediction results of the managed wind power plant, the obtained short-term and ultra-short-term wind power prediction results are completely independent of a wind power plant station end power prediction system, and the short-term and ultra-short-term wind power prediction results can be used for guiding centralized control operation of the wind power plant, wind power generation capacity prediction and can be used as a power generation capacity basis for participating in daily spot transaction.
Implementation strategy for human intervention power prediction result
When the central control center operator finds the problem of power prediction of a certain wind power station end, the set of central wind power prediction system can be utilized to artificially correct the short-term wind power prediction result of the wind power station in the central wind power system, the corrected result is returned to the power station end power prediction server, and the replacement result is sent to the power grid dispatching end, so that the power prediction accuracy is improved, the examination of two rules is reduced, and the modified interface is shown in figure 4.
When the central control center operator knows that the fans are stopped due to the failure reasons of the equipment or the hard constraint of the upper-level outgoing channel, the set of central wind power prediction system can be utilized to exclude the stopped wind turbines from the power prediction mode, so that the number of the wind turbines in the power prediction model is ensured to be consistent with the number of the actual grid-connected wind turbines capable of generating, the power prediction accuracy is improved, and the modification interface is shown in fig. 12.
The system designed by adopting the design method of the embodiment performs centralized power prediction, and provides a high-precision unified new energy power prediction function for the power grid dispatching center, and the construction targets of the system are as follows:
1) Station high-precision prediction for realizing power grid centralized end
A, accurately predicting the wind speed and the power of a region, a wind power plant and the position coordinates of each fan from 0 hour to 72 hours in the future according to an advanced weather prediction model of a gold wind technology big data weather prediction center and a weather downscaling mode which is independently optimized and researched and developed;
b, based on the running state of each wind farm field fan and the historical meteorological and power relation of each fan under the control of the power grid, establishing a prediction power model of each fan position, and carrying out high-precision regional power prediction, wind farm power prediction and power prediction of each position in a centralized manner at the power grid end;
c, based on historical data and meteorological data of inverters of all photovoltaic power stations governed by the power grid, centralizing the photovoltaic power stations at the power grid end
High-precision irradiance prediction and power prediction of all photovoltaic power stations in the whole grid and under the jurisdiction;
d, based on the access data of an upstream water condition detection sensor of a hydropower station under the electric network and the analysis of historical meteorological element resources, water condition monitoring and meteorological prediction are intensively carried out at the electric network end;
e, providing prediction of loss electric quantity of 24 hours in future from power grid and each new energy power station
2) Interface friendly
A, providing a friendly visual interface, and inquiring the forecast wind speed, the forecast power, the actual wind speed and the actual power of a power grid, an area and an electric field at a centralized side even at any time period of each coordinate point;
and b, providing a friendly visual interface to uniformly inquire the transverse comparison analysis results of each level.
3) Unified and instant reporting at all levels
A, supporting unified configuration, unified forecast and forecast result display of a power grid level region and a new energy station;
b, unifying and reporting the time required by each provincial power grid from the power grid end or station end on time
And reporting the required wind, light power prediction data and wind field operation data.
While the present invention has been described with reference to the particular illustrative embodiments, it is not to be restricted by the embodiments but only by the appended claims. It will be appreciated by those skilled in the art that changes and modifications may be made to the embodiments of the invention without departing from the scope and spirit thereof.
Claims (2)
1. A wind power prediction system in a centralized control center of a wind farm, comprising:
(1) Data source: as the basic data source of the centralized power prediction system, the basic data are divided into wind farm data and photovoltaic electric field data according to electric field types, are divided into fan data, inverter data, measurement equipment data and booster station data according to equipment types, the data sources listed by the equipment classifications are displayed, the measurement equipment data comprise real-time monitoring data of wind speed and irradiance of two electric fields, the basic data are uploaded to a central end system through a unified data interface of a large data platform by a client, the weather and power prediction data of a power prediction manufacturer are the data sources of weather forecast early warning data and prediction power data of the centralized wind power prediction system of the wind farm centralized control center, and the data are directly uploaded to the central end of the centralized wind power prediction system of the wind farm centralized control center through the Internet;
(2) Data platform layer: for providing unified storage and calculation resources for the central end of the unified wind power prediction system of the wind power plant centralized control center, each service subsystem of the wind power prediction system is deployed on a data platform layer;
(3) Application display layer: the system is an interface of a centralized power prediction system, and a new energy user can realize query, monitoring and report work of all wind farm power prediction services through the interface;
The data platform layer comprises unified data access service, a unified data storage pool, a unified computing resource pool, a data warehouse and unified data release service, wherein the data access service is based on a big data acquisition technology, and comprises a stream data and batch data acquisition technology APACHE KAFKA and a log unstructured data acquisition technology Logstar; the application display layer comprises weather forecast and early warning service, power forecast and early warning service and service management service, wherein the weather forecast and early warning service is divided into weather data display, weather disaster early warning and weather data comparison query, the power forecast and early warning service is divided into forecast index display, forecast actual measurement data comparison, reporting state query and manual report supplementing functions, and the service management service comprises basic information query and management, user authority setting and management, comprehensive query system, data archiving management, free report system and measurement equipment management system;
The centralized power prediction system adopts a micro-service software design mode, each module in the system is independently split and deployed micro-service, a Docker container technology and a container cloud platform used at the bottom layer are used, and the rapid iterative updating of the system is realized based on a continuous integration and continuous deployment technology on the container cloud platform;
The centralized power prediction system is divided into a framework of a production control large area and a framework of an information management large area, the production control large area is divided into a safe I area and a safe II area, the safe I area is a control area, the safe II area is a non-control area, the safe I area directly realizes real-time monitoring of a power primary system, a power dispatching data network or a special channel is longitudinally used, the safe II area runs on line but does not have a control function, the power dispatching data network is used, the centralized power prediction system is electrically connected with a service system or a functional module thereof in the control area, a firewall, a power prediction server, an internal proxy server, forward isolation and reverse isolation are arranged in the production control large area, and the system is used for equipment data acquisition, protocol adaptation, real-time monitoring, alarm management and data forwarding, and the server of the centralized power prediction system reports a result of the centralized power prediction transmitted through reverse isolation to a power grid according to a message format required by a power grid; the inner proxy server transmits the security zone data to the outer proxy through forward isolation; the information management area collects and stores data forwarded by the internal proxy by the server cluster, and performs reverse decryption, decompression, data unpacking, information model matching, stream calculation and data persistence on the data; acquiring data of other management information systems, and performing data cleaning, conversion, loading and persistence to form a clean energy big data lake crossing a plurality of data engines; providing multi-copy set storage, ensuring high availability of data, providing impromptu query service, multidimensional data aggregation service, parallelization analysis engine, offline analysis service, data audit check, quality evaluation repair and use trace record of massive heterogeneous data by a query analysis service cluster, providing an interface for data of a RESTful principle for upper-layer application, acquiring data by an application server cluster through the RESTful interface, performing service visualization display, and providing a centralized power prediction application;
the architecture of the production control large area comprises:
(1) Data source: collecting fan, photovoltaic, booster station, energy storage equipment, photometry tower, anemometer tower and hydropower station equipment data, and supporting 104 protocol, 101 protocol, 103 protocol, modbus protocol and 61850 protocol set;
(2) Data acquisition and protocol adaptation layer: according to the protocol and configuration, connecting data source equipment, collecting data in real time, wherein the minimum collecting period is 1s, converting the collected data into an internally defined information model, and transmitting through a data transmission service according to an internal communication protocol;
(3) Data transmission layer: the collected data is encrypted and compressed, and then sent to one or more targets in a TCP (transmission control protocol) and UDP (user datagram protocol) mode, and after the target receives the data, the data is decompressed, decrypted and provided for corresponding services;
(4) Service layer: the data receiving service is used for rapidly receiving real-time data and providing the real-time data to the data analyzing service; the data analysis service is used for rapidly analyzing each piece of data in a multithreading way, and the data are corresponding to the information model of each device in the memory, so that the data are bound one by one; the data providing service provides an interface for the outside for the showing layer to call and provides real-time data of the equipment according to the information model; when receiving the alarm information, immediately pushing the alarm information to a display layer; the real-time data statistical analysis service performs statistical analysis on the real-time data stream according to predefined rules and data models, and stores the result into a corresponding information model in a memory or pushes the result to a presentation layer; the device control and authority security management, which receives the control instruction sent by the display layer, checks the operation authority of the user and the soft five-prevention security of the instruction, issues the checked instruction to the data acquisition service, and then sends the instruction to the device by the acquisition service;
(5) Presentation layer: the method comprises the steps of first interface display of a system, prediction analysis, weather forecast and early warning, comprehensive comparison, basic information and report management function interface display.
2. A method of designing a wind power collection prediction system for a wind farm central control center according to claim 1, comprising the steps of:
Step one, designing a network topology of a concentrated wind power prediction system and a safety protection module of a power monitoring system;
Step two, designing a prediction result acquisition and display module of a concentrated wind power prediction system;
step three, designing an implementation strategy of a human intervention power prediction result;
The network topology of the concentrated wind power prediction system is a network topology structure of the concentrated wind power prediction system in a centralized control center mode, the concentrated wind power prediction system comprises a concentrated wind power prediction system, the whole system is of a cross-region single network structure, and a concentrated power prediction server and an application workstation are in redundant configuration; the power monitoring system safety protection design adopts a mode of safety partition, network special, transverse isolation and longitudinal authentication, and the concentrated wind power prediction system spans a safety II area and a management information area on the safety partition, wherein equipment deployed in the safety II area is as follows: concentrated wind power prediction server and application workstation; the equipment for deploying the management information area is as follows: a weather download server; the network special-purpose network comprises a longitudinal wide area network between a centralized wind power system and a wind farm station end power prediction system, and a special channel of a leased communication operator is adopted; the boundary protection equipment for transversely isolating the safety II area from the management information area comprises the following components: a forward and reverse isolating device; the centralized wind power prediction server acquires fan monitoring information from a centralized control center monitoring server deployed in a safety I area, and boundary protection equipment is deployed in the safety I area and the safety II area as a firewall; the weather downloading server located in the management information large area accesses the cloud power prediction cluster server through the VPN special for the Internet to obtain numerical weather forecast and short-term power prediction data, and the management information large area and the Internet area deploy boundary protection equipment as a firewall; the longitudinal authentication comprises that a centralized wind power prediction system adopts a longitudinal encryption technology through a centralized control center private network, namely longitudinal encryption device equipment which is configured by a centralized control center end and a wind power station end in pairs, and the longitudinal encryption device which is configured by the wind power station end encrypts a wind power prediction result IP service packet of the wind power station end through an SM2 algorithm, and then the service packet is sent to a centralized control master station, and the centralized control master station longitudinal encryption device decrypts the service packet and then sends the service packet to a centralized wind power prediction server;
The design targets of the second step include: the short-term power prediction result of the wind farm managed by the concentrated wind power prediction system is from Jin Fenghui cloud power prediction cluster servers; the ultra-short term wind power prediction result is calculated by a wind power plant power prediction model through a numerical weather forecast obtained by a centralized power prediction server;
The prediction result acquisition and display module of the centralized wind power prediction system designed in the second step can realize centralized picture display of a station, centralized prediction data total addition display, wind power plant report scheduling end result display, comparison of centralized prediction results and station end prediction results, centralized power prediction result data evaluation, short-term data correction, planned shutdown management, report management, electric quantity management, equipment management, error analysis and data statistics and report forms;
The implementation strategy of the manual intervention power prediction result in the step three is used for manually correcting the short-term wind power prediction result of the wind power plant in the wind power collection system and sending the correction result back to the station power prediction server and sending the substitution result to the power grid dispatching end when a central control center operator finds that the power prediction of the station end of the wind power plant has a problem; and when the central control center operator knows that the shutdown of the fans is caused by the fault reasons of the equipment of the fans or the hard constraint of the upper-level outgoing channel, the shutdown wind turbine generator is excluded from the power prediction mode.
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