CN118100449A - Micro-grid configuration management system based on data center platform - Google Patents
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Abstract
The invention discloses a micro-grid configuration management system based on a data center table, and relates to the technical field of micro-grid configuration management. The micro-grid configuration management system based on the data center comprises: the system comprises a data acquisition module, a data processing module and an analysis module; wherein, the data acquisition module: the micro-grid parameter data acquisition device is used for carrying out real-time monitoring on the micro-grid and acquiring the micro-grid parameter data through the data center; and a data processing module: the method comprises the steps of obtaining a micro-grid configuration degree evaluation index according to micro-grid parameter data; and an analysis module: and the system is used for analyzing the configuration situation of the micro-grid according to the micro-grid configuration degree evaluation index and carrying out micro-grid configuration management. According to the invention, the configuration condition of the micro-grid is analyzed according to the micro-grid configuration degree evaluation index, so that the micro-grid configuration is managed rapidly and efficiently according to the configuration condition of the micro-grid, and the problem that the configuration management state of the micro-grid is difficult to be determined efficiently and accurately by analyzing related data of the micro-grid is solved.
Description
Technical Field
The invention relates to the technical field of micro-grid configuration management, in particular to a micro-grid configuration management system based on a data center platform.
Background
The micro-grid is a novel power system, integrates distributed energy sources, energy storage equipment, loads and control devices, and has the characteristics of flexibility, reliability, sustainability and the like. The micro-grid comprises links of power generation, power utilization, energy storage, scheduling and the like. With the rapid development of new energy sources, micro-grids are an important energy source form, and the position and the function of the micro-grids in an energy source structure are increasingly prominent. As the scale of the micro-grid is continuously enlarged, how to effectively manage and configure various devices in the micro-grid, and improve the operation efficiency and stability of the system becomes a problem to be solved urgently. The data center is a centralized data management platform within an organization that aims to integrate data from different data sources and provide consistent, processed data for use by various business applications and analysis tasks within the organization. Data center often contains components such as data storage, data processing, data management, and data services to support the entire lifecycle of the data.
The existing micro-grid configuration management system is used for checking and recording data of equipment configured by the micro-grid by arranging staff periodically, comparing the recorded data with normal data of the equipment to judge whether configuration management is needed and carrying out subsequent management operation, so that the micro-grid configuration management function is realized.
For example, bulletin numbers: the method for configuring the small hydropower capacity in the micro-grid disclosed in the CN110956554B patent publication comprises the following steps: firstly, constructing a data set of the warehouse-in flow of a small hydropower station; then, calculating and determining the mean value and variance of annual warehouse-in flow, monthly warehouse-in flow, daily warehouse-in flow and time period warehouse-in flow of the small hydropower stations in the micro-grid according to the normal distribution rule by adopting a probability analysis method; then, calculating and determining the probability of the annual, monthly, daily and time period warehousing flow rate of the small hydropower stations in the micro-grid according to the normal distribution rule by adopting a probability analysis method, and calculating the average value of the warehousing flow rates of the small hydropower stations in the micro-grid; and finally, calculating the capacity of the small hydroelectric generator set of the small hydropower station.
For example, bulletin numbers: the CN111445107B patent publication discloses a multi-objective optimization configuration method for a combined cooling heating power type micro-grid, which comprises the following steps: the energy supply equipment model of the CCHP system and the energy flow diagram thereof are constructed, cold energy and heat energy are converted into electric energy in a unified mode to be scheduled, the energy cost of each kilowatt hour generated by various equipment in different time periods is analyzed from the aspects of the running cost and the maintenance cost of the equipment, and the scheduling flow diagram of the energy output by each equipment in the CCHP system is determined according to the size relation of the energy cost; constructing an objective function configured by the CCHP system, solving constraint conditions of the function, and determining an evaluation index for solving an objective function value of the system; the best configuration scheme is found by improving the PSO algorithm under the condition that the evaluation index is met.
However, in the process of implementing the technical scheme of the embodiment of the application, the application discovers that the above technology has at least the following technical problems:
In the prior art, as the types and the number of the related configurations of the power distribution network are too many, the positions to be checked and the data to be checked are too many when the configuration management of the micro-grid is carried out, the process of analyzing the configuration state of the micro-grid is complex and complicated, the analysis process consumes long time and has low analysis efficiency, and the problem that the configuration management state of the micro-grid is difficult to be effectively and accurately determined by analyzing the related data of the micro-grid exists.
Disclosure of Invention
The embodiment of the application solves the problem that the micro-grid configuration management state is difficult to be effectively and accurately determined by analyzing the related data of the micro-grid in the prior art by providing the micro-grid configuration management system based on the data center, and realizes the effective and accurate determination and management of the micro-grid configuration management state according to the related data of the micro-grid.
The embodiment of the application provides a micro-grid configuration management system based on a data center, which comprises the following steps: the system comprises a data acquisition module, a data processing module and an analysis module; wherein, the data acquisition module: the micro-grid parameter data acquisition device is used for carrying out real-time monitoring on the micro-grid and acquiring the micro-grid parameter data through the data center; the data processing module: the method comprises the steps of obtaining a micro-grid configuration degree evaluation index according to micro-grid parameter data, wherein the micro-grid configuration degree evaluation index is used for reflecting the good degree of micro-grid configuration; the analysis module: and the system is used for analyzing the configuration situation of the micro-grid according to the micro-grid configuration degree evaluation index and carrying out micro-grid configuration management.
Further, the specific analysis process for obtaining the evaluation index of the configuration degree of the micro-grid according to the parameter data of the micro-grid is as follows: acquiring micro-grid parameter data through a data center table, wherein the micro-grid parameter data comprise energy use degree data, wind power generation equipment state data, pollution treatment state data and micro-grid reliability degree data; analyzing the micro-grid parameter data to obtain micro-grid configuration monitoring index data, wherein the micro-grid configuration monitoring index data comprises an energy use degree evaluation index, a wind power generation equipment state evaluation index, a pollution treatment state evaluation index and a micro-grid reliability degree evaluation index; obtaining a micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data; the energy use degree evaluation index is used for describing data for comprehensively evaluating the energy use degree of the micro-grid through the data of the corresponding power generation amount of wind power generation of the micro-grid, the data of the corresponding power generation amount of photovoltaic power generation of the micro-grid and the data of the corresponding power generation amount of gas power generation of the micro-grid; the wind power generation equipment state evaluation index is used for representing data for evaluating the state good degree of the micro-grid wind power generation equipment through the wind power generation equipment aging degree data, the wind power generation equipment maintenance time and the wind power generation equipment maintenance cost data; the pollution treatment state evaluation index is used for comprehensively evaluating the data of the pollution treatment state of the micro-grid through the expense data of carbon monoxide treatment by the micro-grid, the expense data of nitrogen oxide treatment by the micro-grid and the expense data of sulfide treatment by the micro-grid; the micro-grid reliability evaluation index is used for expressing data reflecting the reliability of the micro-grid through micro-grid power generation efficiency data, micro-grid energy storage efficiency data and micro-grid power generation capacity data.
Further, the specific analysis process for acquiring the micro-grid parameter data through the data center table is as follows; the data center station ingests data from a data source; storing the ingested data in a data storage system of a data center station; the data center station cleans the ingested data; performing data conversion on the data after data cleaning, wherein the data conversion comprises data mapping, data aggregation and data remodeling; the data center station carries out data management on the ingested data, wherein the data management comprises data access control, data dictionary management, data metadata management and data quality monitoring; and obtaining the data processed by the data center, namely obtaining the micro-grid parameter data.
Further, the specific analysis process for obtaining the evaluation index of the micro-grid configuration degree according to the micro-grid configuration monitoring index data is as follows: acquiring micro-grid configuration monitoring index data, indicating that the micro-grid configuration monitoring index data is abnormal when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is larger than a first threshold value or the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is smaller than a second threshold value, and recalculating the micro-grid configuration monitoring index data; when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is not greater than a first threshold value and the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is not less than a second threshold value, the micro-grid configuration monitoring index data is normal; and comprehensively analyzing the normal micro-grid configuration monitoring index data to obtain a micro-grid configuration degree evaluation index.
Further, the specific analysis process of the energy use degree evaluation index is as follows: acquiring energy use degree data and carrying out data cleaning and pretreatment; normalizing the energy use degree data; acquiring all the micro-grid total power generation amount data in the energy use degree data, sequentially arranging the micro-grid total power generation amount data in sequence from large to small, extracting micro-grid total power generation amount data of the first rank of the micro-grid total power generation amount data, taking the micro-grid total power generation amount data as micro-grid total power generation amount maximum value data, extracting micro-grid total power generation amount data of the last rank of the micro-grid total power generation amount data, and taking the micro-grid total power generation amount data as micro-grid total power generation amount minimum value data; and analyzing the energy use degree data to obtain an energy use degree evaluation index.
Further, the specific analysis process of the state evaluation index of the wind power generation equipment is as follows: acquiring state data of wind power generation equipment and performing data conversion and pretreatment; comparing the ageing degree data of the wind power generation equipment in the state data of the wind power generation equipment with the ageing degree standard value data of the wind power generation equipment, comparing the maintenance time of the wind power generation equipment with the maintenance standard time of the wind power generation equipment, comparing the maintenance cost data of the wind power generation equipment with the maintenance cost standard value data of the wind power generation equipment, and analyzing the comparison result to obtain a state evaluation index of the wind power generation equipment.
Further, the specific analysis process of the pollution treatment state evaluation index is as follows: acquiring pollution processing state data, and normalizing the data in the pollution processing state data to the same level; comparing the carbon monoxide expenditure data processed by the micro-grid in the pollution processing state data with the carbon monoxide volume data processed by the micro-grid, and then comparing the carbon monoxide expenditure data with the standard expenditure data of the carbon monoxide processed by the micro-grid in unit volume to obtain a first comparison result; comparing the expenditure data of the nitrogen oxides processed by the micro-grid with the volume data of the nitrogen oxides processed by the micro-grid, and then comparing the expenditure data with the standard expenditure data of the nitrogen oxides processed by the micro-grid in unit volume to obtain a second comparison result; comparing the sulfide expenditure data processed by the micro-grid with the sulfide object volume data processed by the micro-grid, and then comparing the sulfide expenditure data with the standard expenditure data of the sulfide in unit volume processed by the micro-grid to obtain a third comparison result; and analyzing the first comparison result, the second comparison result and the third comparison result to obtain a pollution treatment state evaluation index.
Further, the specific acquisition method of the micro-grid configuration degree evaluation index comprises the following steps: acquiring the number data of the micro-grids, and numbering the micro-grids; acquiring a preset time period, and numbering the preset time period according to the time period; acquiring micro-grid configuration monitoring index data; constructing a micro-grid configuration degree evaluation index calculation formula; the specific micro-grid configuration degree evaluation index calculation formula is as follows: in the above, the ratio of/> Expressed asThe micro-grid is at theA microgrid configuration level evaluation index for a preset period of time,，Expressed as the total number of micro-grids,，Expressed as a total number of preset time periods,Expressed asThe micro-grid is at theEnergy use degree evaluation index for each preset time period,Expressed asThe micro-grid is at theWind energy plant status assessment index for a predetermined period of time,Expressed asThe micro-grid is at thePollution treatment state evaluation index for each preset period,Expressed asThe micro-grid is at theMicro-grid reliability evaluation index for preset time period,Expressed as the weight proportion of the energy use degree evaluation index in the micro-grid configuration degree evaluation index,Expressed as weight proportion of wind power generation equipment state evaluation index in micro-grid configuration degree evaluation index,Expressed as the weight proportion of pollution treatment state evaluation index in micro-grid configuration degree evaluation index,Expressed as the weight proportion of the microgrid reliability degree evaluation index in the microgrid configuration degree evaluation index.
Further, the specific method for obtaining the energy use degree evaluation index comprises the following steps: acquiring the number data of the micro-grids, and numbering the micro-grids; acquiring a preset time period, and numbering the preset time period according to the time period; the method comprises the steps of performing multiple data acquisition in a preset time period, and numbering the data acquisition times; constructing an energy use degree evaluation index calculation formula; the specific energy use degree evaluation index calculation formula is as follows: In which, in the process, Expressed asThe micro-grid is at theAn energy use degree evaluation index for a preset period of time,，Expressed as the total number of micro-grids,，Expressed as a total number of preset time periods,Expressed asThe micro-grid is at theFirst/>, of the preset time periodCorresponding generating capacity data of wind power generation of micro-grid during secondary data acquisition，Expressed as total number of data acquisitions,，Expressed asThe micro-grid is at theFirst/>, of the preset time periodPhotovoltaic power generation corresponding to generated energy data of micro-grid during secondary data acquisition,Expressed asThe micro-grid is at theFirst/>, of the preset time periodCorresponding generated energy data of gas power generation of micro-grid during secondary data acquisition,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid total power generation data,/>, during secondary data acquisitionExpressed asThe micro-grid is at theMicro-grid total power generation maximum value data of preset time period,Expressed asThe micro-grid is at theMicro-grid total power generation minimum value data of preset time period,Representing the weight proportion of corresponding power generation amount data of wind power generation belonging to micro-grid in energy use degree evaluation index,Representing the weight proportion of the photovoltaic power generation corresponding power generation data of the micro-grid in the energy use degree evaluation index,And the weight proportion of the generated energy data corresponding to the gas power generation of the micro-grid in the energy use degree evaluation index is shown.
Further, the specific analysis process of analyzing the configuration situation of the micro grid according to the evaluation index of the configuration degree of the micro grid and performing configuration management of the micro grid is as follows: acquiring a micro-grid configuration degree evaluation index of the micro-grid in a preset time period, acquiring a configuration degree evaluation threshold, and when the micro-grid configuration degree evaluation index is larger than the configuration degree evaluation threshold, indicating that the micro-grid configuration is in a reasonable state in the preset time period, and not carrying out early warning reminding; when the micro-grid configuration degree evaluation index is not larger than the configuration degree evaluation threshold, the micro-grid configuration is in an unreasonable state in a preset time period, early warning and reminding are carried out, and micro-grid configuration management is carried out.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. The method comprises the steps of monitoring a micro-grid in real time, acquiring micro-grid parameter data through a data center table, analyzing the micro-grid parameter data to obtain micro-grid configuration monitoring index data, and obtaining a micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data, so that the micro-grid configuration condition is analyzed according to the micro-grid configuration degree evaluation index, further, the purposes of efficiently and accurately determining and managing the micro-grid configuration management state through analyzing the micro-grid related data are achieved, and the problem that in the prior art, the micro-grid configuration management state is difficult to be efficiently and accurately determined through analyzing the micro-grid related data is effectively solved.
2. The micro-grid configuration monitoring index data such as the energy use degree evaluation index, the wind power generation equipment state evaluation index, the pollution treatment state evaluation index, the micro-grid reliability degree evaluation index and the like are obtained by carrying out data processing and analysis on the micro-grid parameter data, so that the accuracy and the reliability of the micro-grid configuration monitoring index data are higher, the micro-grid configuration degree evaluation index is obtained by analyzing the micro-grid configuration monitoring index data, the micro-grid configuration degree evaluation index is considered more comprehensively, and further the micro-grid configuration condition is analyzed in more detail according to the micro-grid configuration degree evaluation index.
3. And analyzing the configuration condition of the micro-grid according to the configuration degree evaluation index of the micro-grid, so that a worker can timely perform configuration management on the micro-grid according to the configuration condition of the micro-grid, and further the power generation loss caused by unreasonable configuration of the micro-grid is reduced.
Drawings
Fig. 1 is a schematic structural diagram of a micro-grid configuration management system based on a data center platform according to an embodiment of the present application;
fig. 2 is a flowchart of obtaining a micro-grid configuration degree evaluation index in the micro-grid configuration management system based on a data center platform according to an embodiment of the present application;
Fig. 3 is a block diagram of a micro-grid configuration degree evaluation index obtained in the micro-grid configuration management system based on a data center platform according to an embodiment of the present application.
Detailed Description
The embodiment of the application solves the problem that the related data of the micro grid is difficult to analyze in the prior art so as to efficiently and accurately determine the configuration management state of the micro grid by providing the micro grid configuration management system based on the data center, monitors the micro grid in real time through the data acquisition module and acquires the parameter data of the micro grid through the data center; obtaining a micro-grid configuration degree evaluation index according to the micro-grid parameter data through a data processing module; the analysis module analyzes the configuration condition of the micro-grid according to the micro-grid configuration degree evaluation index and carries out micro-grid configuration management, so that the analysis of related data of the micro-grid is realized, and the micro-grid configuration management state is effectively and accurately defined and managed.
The technical scheme in the embodiment of the application aims to solve the problem that the configuration management state of the micro-grid is difficult to be effectively and accurately defined by analyzing the related data of the micro-grid, and the overall thought is as follows:
Real-time monitoring is carried out on the micro-grid through a data acquisition module, and micro-grid parameter data are acquired through a data center; obtaining a micro-grid configuration degree evaluation index according to the micro-grid parameter data through a data processing module, wherein the method specifically comprises the following steps: acquiring micro-grid parameter data such as energy use degree data, wind power generation equipment state data, pollution treatment state data, micro-grid reliability degree data and the like through a data center table, analyzing the micro-grid parameter data to obtain micro-grid configuration monitoring index data such as an energy use degree evaluation index, a wind power generation equipment state evaluation index, a pollution treatment state evaluation index, a micro-grid reliability degree evaluation index and the like, and obtaining a micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data; the analysis module analyzes the configuration condition of the micro-grid according to the micro-grid configuration degree evaluation index and carries out micro-grid configuration management, so that the effect of efficiently and accurately determining and managing the configuration management state of the micro-grid through analysis of related data of the micro-grid is achieved.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
As shown in fig. 1, a schematic structural diagram of a micro-grid configuration management system based on a data center table according to an embodiment of the present application is provided, where the micro-grid configuration management system based on a data center table according to an embodiment of the present application includes: the system comprises a data acquisition module, a data processing module and an analysis module; wherein, the data acquisition module: the micro-grid parameter data acquisition device is used for carrying out real-time monitoring on the micro-grid and acquiring the micro-grid parameter data through the data center; and a data processing module: the method comprises the steps of obtaining a micro-grid configuration degree evaluation index according to micro-grid parameter data, wherein the micro-grid configuration degree evaluation index is used for reflecting the good degree of micro-grid configuration; and an analysis module: and the system is used for analyzing the configuration situation of the micro-grid according to the micro-grid configuration degree evaluation index and carrying out micro-grid configuration management.
Further, the specific analysis process for obtaining the micro-grid configuration degree evaluation index according to the micro-grid parameter data is as follows: acquiring micro-grid parameter data through a data center table, wherein the micro-grid parameter data comprise energy use degree data, wind power generation equipment state data, pollution treatment state data and micro-grid reliability degree data; analyzing the micro-grid parameter data to obtain micro-grid configuration monitoring index data, wherein the micro-grid configuration monitoring index data comprises an energy use degree evaluation index, a wind power generation equipment state evaluation index, a pollution treatment state evaluation index and a micro-grid reliability degree evaluation index; obtaining a micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data; the energy use degree evaluation index is used for describing data for comprehensively evaluating the energy use degree of the micro-grid through the corresponding power generation amount data of the wind power generation of the micro-grid, the corresponding power generation amount data of the photovoltaic power generation of the micro-grid and the corresponding power generation amount data of the gas power generation of the micro-grid; the wind power generation equipment state evaluation index is used for representing data for evaluating the state good degree of the micro-grid wind power generation equipment through the wind power generation equipment aging degree data, the wind power generation equipment maintenance time and the wind power generation equipment maintenance cost data; the pollution treatment state evaluation index is used for comprehensively evaluating the data of the pollution treatment state of the micro-grid through the expense data of carbon monoxide treatment by the micro-grid, the expense data of nitric oxide treatment by the micro-grid and the expense data of sulfide treatment by the micro-grid; the micro-grid reliability evaluation index is used for expressing data reflecting the reliability of the micro-grid through micro-grid power generation efficiency data, micro-grid energy storage efficiency data and micro-grid power generation capacity data.
In this embodiment, as shown in fig. 2, a flowchart of a micro-grid configuration degree evaluation index is obtained in the micro-grid configuration management system based on a data center provided in the embodiment of the present application, and data integration, data conversion, data cleaning and preprocessing are performed on micro-grid parameter data such as energy usage degree data, wind power generation equipment status data, pollution processing status data, and micro-grid reliability degree data, so that accuracy of the micro-grid parameter data is higher, and more accurate micro-grid configuration monitoring index data is facilitated.
Further, the specific analysis process for acquiring the micro-grid parameter data through the data center table is as follows; the data center station ingests data from a data source; storing the ingested data in a data storage system of a data center station; the data center station cleans the ingested data; performing data conversion on the data after data cleaning, wherein the data conversion comprises data mapping, data aggregation and data remodeling; the data center station carries out data management on the ingested data, wherein the data management comprises data access control, data dictionary management, data metadata management and data quality monitoring; and obtaining the data processed by the data center, namely obtaining the micro-grid parameter data.
In this embodiment, the specific process of processing data by the data center station generally includes the following steps: data intake: the data center ingests data from various data sources including relational databases, non-relational databases, external systems, APIs, log files, spreadsheets, and the like. The data intake includes real-time data streaming, bulk data importation, or a combination of both. And (3) data storage: the ingested data needs to be stored in a suitable data storage system, including relational databases, column store databases, noSQL databases, data warehouse or data lake, etc. The data store should be able to support large amounts of data and fast queries. Data cleaning: the data center cleans the ingested data to ensure the quality and consistency of the data. Cleaning includes handling missing values, correcting errors, removing duplicate records, normalizing data formats, and the like. Data conversion: the cleaned data needs to be converted for analysis and reporting, including data mapping, data aggregation, data remodeling, calculating derived metrics, and the like. Data conversion may be accomplished through ETL (extract, convert, load) processes or using data stream processing tools. Data integration: the data center integrates data from different sources to create a unified view. Data management: the data center station implements a data management strategy to ensure the quality, safety and compliance of the data. Including data access control, data dictionary management, data metadata management, data quality monitoring, and the like.
The purpose of the data center is to simplify data management, improve data availability and efficiency, and support data-driven decision making. Through centralized management and data processing, the data center can ensure that different departments and teams in an organization can access accurate, consistent and timely data, so that the accuracy of the power grid parameter data is higher.
Further, the specific analysis process for obtaining the micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data is as follows: acquiring micro-grid configuration monitoring index data, indicating that the micro-grid configuration monitoring index data is abnormal when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is larger than a first threshold value or the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is smaller than a second threshold value, and recalculating the micro-grid configuration monitoring index data; when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is not greater than a first threshold value and the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is not less than a second threshold value, the micro-grid configuration monitoring index data is normal; and comprehensively analyzing the normal micro-grid configuration monitoring index data to obtain a micro-grid configuration degree evaluation index.
In the present embodiment, when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is greater than the first threshold, i.e.、、AndOr when the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is smaller than the second threshold value, namely、、AndRepresenting that the micro-grid configuration monitoring index data is abnormal, and recalculating the micro-grid configuration monitoring index data;
when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is not greater than the first threshold value and the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is not less than the second threshold value, namely And、And is also provided with、AndAndAndAnd indicating that the micro-grid configuration monitoring index data is normal.
Further, the specific analysis process of the energy use degree evaluation index is as follows: acquiring energy use degree data and carrying out data cleaning and pretreatment; normalizing the energy use degree data; acquiring all the micro-grid total power generation amount data in the energy use degree data, sequentially arranging the micro-grid total power generation amount data in sequence from large to small, extracting micro-grid total power generation amount data of the first rank of the micro-grid total power generation amount data, taking the micro-grid total power generation amount data as micro-grid total power generation amount maximum value data, extracting micro-grid total power generation amount data of the last rank of the micro-grid total power generation amount data, and taking the micro-grid total power generation amount data as micro-grid total power generation amount minimum value data; and analyzing the energy use degree data to obtain an energy use degree evaluation index.
In this embodiment, by cleaning and preprocessing the energy usage degree data, the error rate of the energy usage degree data is reduced, which is beneficial to obtaining an energy usage degree evaluation index with higher accuracy. The energy use degree data are normalized, so that the energy use degree data are in the same magnitude and range, and more accurate calculation is facilitated.
Further, the specific analysis process of the state evaluation index of the wind power generation equipment is as follows: acquiring state data of wind power generation equipment and performing data conversion and pretreatment; comparing the ageing degree data of the wind power generation equipment in the state data of the wind power generation equipment with the ageing degree standard value data of the wind power generation equipment, comparing the maintenance time of the wind power generation equipment with the maintenance standard time of the wind power generation equipment, comparing the maintenance cost data of the wind power generation equipment with the maintenance cost standard value data of the wind power generation equipment, and analyzing the comparison result to obtain a state evaluation index of the wind power generation equipment.
In the embodiment, the wind power generation equipment state data is more accurate by converting and preprocessing the wind power generation equipment state data, so that the wind power generation equipment state evaluation index with higher accuracy can be calculated, and the accuracy of the subsequent calculation process can be improved.
Further, the specific analysis process of the pollution treatment state evaluation index is as follows: acquiring pollution processing state data, and normalizing the data in the pollution processing state data to the same level; comparing the carbon monoxide expenditure data processed by the micro-grid in the pollution processing state data with the carbon monoxide volume data processed by the micro-grid, and then comparing the carbon monoxide expenditure data with the standard expenditure data of the carbon monoxide processed by the micro-grid in unit volume to obtain a first comparison result; comparing the expenditure data of the nitrogen oxides processed by the micro-grid with the volume data of the nitrogen oxides processed by the micro-grid, and then comparing the expenditure data with the standard expenditure data of the nitrogen oxides processed by the micro-grid in unit volume to obtain a second comparison result; comparing the sulfide expenditure data processed by the micro-grid with the sulfide object volume data processed by the micro-grid, and then comparing the sulfide expenditure data with the standard expenditure data of the sulfide in unit volume processed by the micro-grid to obtain a third comparison result; and analyzing the first comparison result, the second comparison result and the third comparison result to obtain a pollution treatment state evaluation index.
In this embodiment, data storage, data organization and data cleaning are performed on the pollution treatment state data, so that erroneous data in the pollution treatment state data are removed, the accuracy of the pollution treatment state data is higher, and a more accurate pollution treatment state evaluation index is obtained. The data in the pollution processing state data is standardized to the same magnitude, which is beneficial to more accurately calculating.
Further, the specific acquisition method of the micro-grid configuration degree evaluation index comprises the following steps: acquiring the number data of the micro-grids, and numbering the micro-grids; acquiring a preset time period, and numbering the preset time period according to the time period; acquiring micro-grid configuration monitoring index data; constructing a micro-grid configuration degree evaluation index calculation formula; the specific micro-grid configuration degree evaluation index calculation formula is as follows: In which, in the process, Expressed asThe micro-grid is at theA microgrid configuration level evaluation index for a preset period of time,，Expressed as the total number of micro-grids,，Expressed as a total number of preset time periods,Expressed asThe micro-grid is at theEnergy use degree evaluation index for each preset time period,Expressed asThe micro-grid is at theWind energy plant status assessment index for a predetermined period of time,Expressed asThe micro-grid is at thePollution treatment state evaluation index for each preset period,Expressed asThe micro-grid is at theMicro-grid reliability evaluation index for preset time period,Expressed as the weight proportion of the energy use degree evaluation index in the micro-grid configuration degree evaluation index,Expressed as weight proportion of wind power generation equipment state evaluation index in micro-grid configuration degree evaluation index,Expressed as the weight proportion of pollution treatment state evaluation index in micro-grid configuration degree evaluation index,Expressed as the weight proportion of the microgrid reliability degree evaluation index in the microgrid configuration degree evaluation index.
In the present embodiment of the present invention, in the present embodiment,AndThe range of the values of (2) is 0-1, and The sum is equal to 1. As shown in fig. 3, in the micro-grid configuration management system based on the data center provided by the embodiment of the application, a structure diagram of a micro-grid configuration degree evaluation index is obtained, wherein the larger the micro-grid configuration degree evaluation index is, the better the state of micro-grid configuration is, and the less configuration management is needed for the micro-grid; the smaller the microgrid configuration degree evaluation index, the worse the state of the microgrid configuration is, and the more the microgrid is required to be configured and managed. The micro-grid configuration degree evaluation index is obtained by analyzing four aspects of the energy use degree evaluation index, the wind power generation equipment state evaluation index, the pollution treatment state evaluation index and the micro-grid reliability degree evaluation index, so that the micro-grid configuration degree evaluation index is more comprehensively considered.
The microgrid configuration level evaluation index may also be obtained by other methods, such as data analysis: by collecting historical operation data of the micro-grid, such as power generation amount, load consumption, equipment efficiency and the like, a characteristic parameter reflecting the configuration degree of the micro-grid is found out by applying a data mining and analyzing technology, and then the configuration degree evaluation index of the micro-grid is obtained through analysis.
Further, the specific acquisition method of the energy use degree evaluation index comprises the following steps: acquiring the number data of the micro-grids, and numbering the micro-grids; acquiring a preset time period, and numbering the preset time period according to the time period; the method comprises the steps of performing multiple data acquisition in a preset time period, and numbering the data acquisition times; constructing an energy use degree evaluation index calculation formula; the specific energy use degree evaluation index calculation formula is as follows: In which, in the process, Expressed asThe micro-grid is at theAn energy use degree evaluation index for a preset period of time,，Expressed as the total number of micro-grids,，Expressed as a total number of preset time periods,Expressed asThe micro-grid is at theFirst/>, of the preset time periodCorresponding generating capacity data of wind power generation of the micro-grid during secondary data acquisition, wherein the corresponding generating capacity data of the wind power generation represents generating capacity data generated by wind power generation in the micro-grid,，Expressed as total number of data acquisitions,，Expressed asThe micro-grid is at theFirst/>, of the preset time periodPhotovoltaic power generation corresponding generated energy data of the micro-grid during secondary data acquisition, wherein the generated energy data corresponding to the photovoltaic power generation represents generated energy data generated by photovoltaic power generation in the micro-grid,Expressed asThe micro-grid is at theFirst/>, of the preset time periodThe micro-grid belongs to the corresponding generated energy data of the gas power generation when the secondary data is acquired, the corresponding generated energy data of the gas power generation represents the generated energy data of the gas power generation in the micro-grid,Expressed asThe micro-grid is at theFirst/>, of the preset time periodThe total power generation amount data of the micro-grid during secondary data acquisition represents the total power generation amount data generated by all kinds of power generation in the micro-grid,Expressed asThe micro-grid is at theThe maximum value data of the total power generation amount of the micro-grid in a preset time period represent the maximum power generation amount data in the total power generation amount data of the micro-grid, and the maximum power generation amount data of the total power generation amount data of the micro-grid is/are shown in the maximum power generation amount data of the micro-gridExpressed asThe micro-grid is at theMinimum value data of total power generation of the micro-grid in a preset time period, wherein the minimum value data of the total power generation of the micro-grid represents minimum power generation data in the data of the total power generation of the micro-grid,Representing the weight proportion of corresponding power generation amount data of wind power generation belonging to micro-grid in energy use degree evaluation index,Representing the weight proportion of the photovoltaic power generation corresponding power generation data of the micro-grid in the energy use degree evaluation index,And the weight proportion of the generated energy data corresponding to the gas power generation of the micro-grid in the energy use degree evaluation index is shown.
In the present embodiment of the present invention, in the present embodiment,AndThe range of the values of the (E) is 0-1, and the. The larger the energy use degree evaluation index is, the better the energy use effect of the micro-grid is, and the micro-grid configuration management is not needed; the smaller the energy use degree evaluation index is, the worse the energy use effect of the micro-grid is, and the more the micro-grid configuration management is needed.
The micro-grid is provided with sensors and is arranged on various power generation equipment, such as an impeller of a wind driven generator, the surface of a photovoltaic panel or the combustion chamber of a fuel/natural gas generator, and the sensors are used for monitoring parameters such as output power, rotating speed and temperature of a generator set in real time to obtain corresponding generated energy of different parts, namely obtaining corresponding generated energy data of wind power generation of the micro-grid, corresponding generated energy data of photovoltaic power generation of the micro-grid, corresponding generated energy data of gas power generation of the micro-grid and total generated energy data of the micro-grid, and comparing the total generated energy data of the micro-grid to obtain maximum value data of the total generated energy of the micro-grid and minimum value data of the total generated energy of the micro-grid. The generated energy can also be obtained by other methods, the current, the voltage and the running time of the equipment are obtained, the current, the voltage and the running time are subjected to data processing, error and repeated data are removed, the accuracy and the reliability of the current, the voltage and the running time are improved, the current and the voltage after the data processing are subjected to multiplication to obtain power, and the power and the running time are subjected to multiplication to obtain the generated energy.
The power function is used in the calculation process of the energy use degree evaluation index to simplify the calculation process of the energy use degree evaluation index, the readability of the calculation formula of the energy use degree evaluation index is improved, and the inverse secant function is used to simplify the expression of the calculation formula of the energy use degree evaluation index.
The energy use degree evaluation index can also be obtained by other methods, for example, by monitoring equipment installed in the micro-grid, collecting data such as the generated energy, the load consumption, the energy conversion efficiency and the like of the micro-grid in real time, comparing the data of the micro-grid with micro-grids with the same type and the same scale, and obtaining the energy use degree evaluation index through analysis.
Further, the specific analysis process of analyzing the configuration condition of the micro-grid and performing configuration management of the micro-grid according to the evaluation index of the configuration degree of the micro-grid is as follows: acquiring a micro-grid configuration degree evaluation index of the micro-grid in a preset time period, acquiring a configuration degree evaluation threshold, and when the micro-grid configuration degree evaluation index is larger than the configuration degree evaluation threshold, indicating that the micro-grid configuration is in a reasonable state in the preset time period, and not carrying out early warning reminding; when the micro-grid configuration degree evaluation index is not larger than the configuration degree evaluation threshold, the micro-grid configuration is in an unreasonable state in a preset time period, early warning and reminding are carried out, and micro-grid configuration management is carried out.
In the present embodiment, when the microgrid configuration level evaluation index is greater than the configuration level evaluation threshold, that isWhen the micro-grid configuration is in a reasonable state in a preset time period, the micro-grid configuration is not warned; when the microgrid configuration level assessment index is not greater than the configuration level assessment threshold, i.e.And when the micro-grid configuration is in an unreasonable state in a preset time period, carrying out early warning reminding and carrying out micro-grid configuration management.
The method comprises the steps of performing configuration management on a micro-grid, wherein when the generated energy of the micro-grid exceeds the load electric quantity, the surplus electric quantity is regulated and controlled or the load of the micro-grid is increased; when the generated energy of the photovoltaic power generation does not reach the standard, starting the wind power generation equipment to enable the generated energy of the clean energy to reach the standard; and when the micro-grid energy storage device is full of electric quantity and still has more unused generated energy, the energy storage device is increased.
Further, the number of wind power generation equipment of the micro-grid is obtained, and the wind power generation equipment is numbered; constructing a wind power generation equipment state evaluation index calculation formula; the wind power plant state assessment index may be obtained using the following ways including, but not limited to: predicting a state of the device using the historical data and a machine learning algorithm; collecting data in real time through sensors and other monitoring equipment, and evaluating equipment states by combining a plurality of indexes such as efficiency, capacity utilization rate, reliability and the like; the state evaluation index can also be obtained by a calculation formula, and the specific calculation formula of the state evaluation index of the wind power generation equipment is as follows: In which, in the process, Expressed asThe micro-grid is at theA wind power plant status assessment index for a predetermined period of time,Expressed asFirst/>, of the individual micro-gridThe individual wind energy power generation equipment is at theFirst/>, of the preset time periodWind power generation equipment aging degree data during secondary data acquisition, wherein the wind power generation equipment aging degree data represents data reflecting aging degree of wind power generation equipment in a micro-grid,，Expressed as the total number of wind power plants,Expressed asFirst/>, of the individual micro-gridThe individual wind energy power generation equipment is at theWind power plant aging degree standard value data of each preset time period, wherein the wind power plant aging degree standard value data represent data reflecting the maximum aging degree of the wind power plant in the micro-grid,Expressed asFirst/>, of the individual micro-gridThe individual wind energy power generation equipment is at theFirst/>, of the preset time periodMaintenance time of wind power generation equipment during secondary data acquisition, wherein the maintenance time of the wind power generation equipment represents time data of maintenance of the wind power generation equipment in the micro-grid,Expressed asFirst/>, of the individual micro-gridThe individual wind energy power generation equipment is at theWind power generation equipment maintenance standard time length of each preset time period, wherein the wind power generation equipment maintenance standard time length represents standard maintenance time length data limited by wind power generation equipment in a micro-grid,Denoted as the firstFirst/>, of the individual micro-gridThe individual wind energy power generation equipment is at theFirst/>, of the preset time periodWind power generation equipment maintenance cost data during secondary data acquisition, wherein the wind power generation equipment maintenance cost data represents the amount data of maintenance cost of wind power generation equipment in a micro-grid,Expressed asFirst/>, of the individual micro-gridThe individual wind energy power generation equipment is at theWind power plant maintenance cost standard value data representing standard amount data of maintenance cost of wind power plant in micro-grid for each preset time period,Expressed as the weight proportion of the ageing degree data of the wind power generation equipment in the state evaluation index of the wind power generation equipment,Representing the weight proportion of the maintenance time of the wind power generation equipment in the state evaluation index of the wind power generation equipment as the maintenance time of the wind power generation equipmentRepresented as the weight proportion of the maintenance cost data of the wind power generation equipment in the state evaluation index of the wind power generation equipment,Expressed as natural constants; the pollution treatment state evaluation index may be obtained using the following means including, but not limited to: evaluating the effect of the pollution process by data collected by an environmental monitoring station; evaluating a pollution treatment state by analyzing performance indexes (such as removal rate, treatment capacity, etc.) of the pollution treatment device; the pollution treatment state evaluation index can also be obtained by a calculation formula, and the specific calculation formula of the pollution treatment state evaluation index is as follows: In which, in the process, Expressed asThe micro-grid is at thePollution treatment state evaluation index for each preset period,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid processing carbon monoxide expenditure data during secondary data acquisition, wherein the micro-grid processing carbon monoxide expenditure data represents expenditure amount data of carbon monoxide generated by micro-grid processing,Expressed asThe micro-grid is at theFirst/>, of the preset time periodCarbon monoxide volume data processed by the micro-grid during secondary data acquisition, wherein the carbon monoxide volume data processed by the micro-grid represents total volume data of carbon monoxide processed by the micro-grid,Expressed asThe micro-grid is at theThe micro-grid processing unit volume carbon monoxide standard expense data of each preset time period represents standard amount data required to be spent for the micro-grid processing unit volume carbon monoxide, and the micro-grid processing unit volume carbon monoxide standard expense data is/areExpressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid processing nitrogen oxide expense data during secondary data acquisition, wherein the micro-grid processing nitrogen oxide expense data represents expense amount data of nitrogen oxides generated by micro-grid processing,Expressed asThe micro-grid is at the firstFirst/>, of the preset time periodThe nitrogen oxide volume data processed by the micro-grid during secondary data acquisition represents the total volume data of nitrogen oxides processed by the micro-grid,Expressed asThe micro-grid is at theThe micro-grid processing unit volume nitrogen oxide standard expense data of each preset time period, wherein the micro-grid processing unit volume nitrogen oxide standard expense data represent standard amount data required to be spent for micro-grid processing unit volume nitrogen oxide, and the standard amount data is/are recorded in the micro-grid processing unit volume nitrogen oxide standard expense dataExpressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid processing sulfide expenditure data during secondary data acquisition, wherein the micro-grid processing sulfide expenditure data represents expenditure amount data of sulfide generated by micro-grid processing,Expressed asThe micro-grid is at theFirst/>, of the preset time periodSulfide volume data processed by the micro-grid during secondary data acquisition, wherein the sulfide volume data processed by the micro-grid represents total volume data of sulfide processed by the micro-grid,Expressed asThe micro-grid is at theMicro-grid processing unit volume sulfide standard expense data of each preset time period, wherein the micro-grid processing unit volume sulfide standard expense data represents standard amount data required to be spent for micro-grid processing unit volume sulfide, and the micro-grid processing unit volume sulfide standard expense data is/areExpressed as the weight proportion of the carbon monoxide expenditure data of the micro-grid treatment in the pollution treatment state evaluation index,Expressed as the weight proportion of the nitrogen oxide expenditure data of the micro-grid treatment in the pollution treatment state evaluation index,Representing the weight proportion of sulfide expenditure data of micro-grid treatment in a pollution treatment state evaluation index; the microgrid reliability assessment index may be obtained using the following means, including but not limited to: evaluating the reliability of the micro-grid by analyzing past accident records and fault rates of the micro-grid; determining the reliability of the micro-grid by evaluating the spare capacity and the redundant design of the micro-grid; the reliability evaluation index of the micro-grid can also be obtained by a calculation formula, and the specific calculation formula of the reliability evaluation index of the micro-grid is as follows: In which, in the process, Expressed asThe micro-grid is at theA microgrid reliability evaluation index for a preset period of time,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid power generation efficiency data during secondary data acquisition, wherein the micro-grid power generation efficiency data represents data reflecting micro-grid power generation efficiency,，Expressed asThe micro-grid is at theMicro-grid power generation efficiency standard data of each preset time period, wherein the micro-grid power generation efficiency standard data represent data reflecting the micro-grid standard power generation efficiency,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid energy storage efficiency data during secondary data acquisition, wherein the micro-grid energy storage efficiency data represents data reflecting micro-grid energy storage efficiency,Expressed asThe micro-grid is at theMicro-grid energy storage efficiency standard data of a preset time period, wherein the micro-grid energy storage efficiency standard data represents data reflecting the micro-grid standard energy storage efficiency,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid generating capacity data during secondary data acquisition, wherein the micro-grid generating capacity data represent micro-grid total generating capacity data,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid supply end electricity demand data during secondary data acquisition, wherein the micro-grid supply end electricity demand data represents electricity generation data required by a supply end using a micro-grid,Expressed asThe micro-grid is at theMicro-grid supply end electricity demand maximum value data of preset time period, wherein the micro-grid supply end electricity demand maximum value data represents maximum electricity generation amount data required by a supply end using a micro-grid,Expressed asThe micro-grid is at theMinimum electric quantity data of a micro-grid supply end in a preset time period, wherein the minimum electric quantity data of the micro-grid supply end represents minimum electric quantity data required by a supply end using the micro-grid,Expressed as the weight proportion of the micro-grid power generation efficiency data in the micro-grid reliability evaluation index,Expressed as the weight proportion of the energy storage efficiency data of the micro-grid in the reliability degree evaluation index of the micro-grid,And the weight proportion of the micro-grid power generation amount data in the micro-grid reliability degree evaluation index is expressed.
In the present embodiment of the present invention, in the present embodiment,AndThe range of the values of the (E) is 0-1, and the. And counting the total running time of the wind power generation equipment from starting and the total shutdown time of the wind power generation equipment due to faults or maintenance through an equipment running log and a monitoring video, comparing the ratio of the former to the latter to obtain the total running time of the wind power generation equipment from starting and the standard shutdown time of the corresponding wind power generation equipment due to faults or maintenance, obtaining the ratio of the latter to the former to obtain the standard wind power generation equipment aging degree data, obtaining the maintenance time of the wind power generation equipment through observing and counting the monitoring video, determining the maintenance standard time of the wind power generation equipment through consulting a wind power generation equipment specification, obtaining the maintenance cost data of the wind power generation equipment through checking a micro-grid financial statement, and obtaining the maintenance cost standard data of the wind power generation equipment through checking a financial planning statement.
The data are transformed by using the logarithmic function in the calculation process of the state evaluation index of the wind power generation equipment, so that the data are more in line with normal distribution, the analysis is easier, and the growth rate and the change rate of the logarithmic function can be researched by analyzing the slope of the image of the logarithmic function.
AndThe range of the values of the (E) is 0-1, and the. The method comprises the steps of obtaining the amount data of the micro-grid, which is required to be spent for processing the carbon monoxide in unit volume under the normal operation condition in a preset time period, and taking the amount data as the standard expense data of the micro-grid for processing the carbon monoxide in unit volume; and the standard expense data of the nitrogen oxide in the unit volume processed by the micro-grid and the standard expense data of the sulfide in the unit volume processed by the micro-grid can be obtained by the same method. And obtaining carbon monoxide expenditure data processed by the micro-grid, nitrogen oxide expenditure data processed by the micro-grid and sulfide expenditure data processed by the micro-grid by consulting the micro-grid pollution processing related financial statement, and obtaining carbon monoxide volume data processed by the micro-grid, nitrogen oxide volume data processed by the micro-grid and sulfide volume data processed by the micro-grid by measuring the volumes of carbon monoxide, nitrogen oxide and sulfide processed by the pollution processing by the flowmeter. /(I)
The hyperbolic cosine function is used in the calculation formula of the pollution treatment state evaluation index, the image of the hyperbolic cosine function is a smooth curve, and no peak or break point exists, so that the pollution treatment state evaluation index is more visual in analysis and visualization, and the image of the hyperbolic cosine function has two horizontal asymptotes, which is beneficial to understanding the long-term behavior of the hyperbolic cosine function.
AndThe range of the values of the (E) is 0-1, and the. The method comprises the steps of evaluating the power generation efficiency through a thermal performance test, such as an ISO fuel efficiency test, obtaining micro-grid power generation efficiency data, performing the thermal performance test under the condition of micro-grid standard operation to obtain micro-grid power generation efficiency standard data, obtaining the ratio of the energy actually released by micro-grid energy storage equipment to the stored energy through an electric energy meter or a power meter, taking the ratio of the energy actually released by the micro-grid energy storage equipment to the stored energy under the condition of standard as micro-grid energy storage efficiency data, obtaining micro-grid power generation amount data and micro-grid supply end power demand data through the electric energy meter, comparing the micro-grid supply end power demand data to obtain micro-grid supply end power demand maximum data and micro-grid supply end power demand minimum data.
The hyperbolic sine function is used in the calculation process of the reliability evaluation index of the micro-grid, so that the change speed of data is improved, and the change of the reliability evaluation index of the micro-grid can be more intuitively analyzed.
The larger the wind power generation equipment state evaluation index is, the better the state of the wind power generation equipment is, and the less micro-grid configuration management is needed; the smaller the wind power generation equipment state evaluation index is, the worse the wind power generation equipment state is, and the more the micro-grid configuration management is needed.
The larger the pollution treatment state evaluation index is, the higher the pollution treatment level is, and the micro-grid configuration management is not needed; the smaller the pollution treatment state evaluation index, the lower the pollution treatment level, and the more necessary the micro grid configuration management is.
The larger the reliability evaluation index of the micro-grid is, the higher the reliability of the micro-grid power generation and storage is, and the less the micro-grid configuration management is needed; the smaller the reliability evaluation index of the micro-grid is, the lower the reliability of the micro-grid power generation and storage is, and the more the micro-grid configuration management is needed.
The technical scheme provided by the embodiment of the application at least has the following technical effects or advantages: relative to the bulletin number: according to the micro-grid small water and electricity capacity configuration method disclosed by the CN110956554B patent publication, the micro-grid configuration monitoring index data such as the energy use degree evaluation index, the wind power generation equipment state evaluation index, the pollution treatment state evaluation index and the micro-grid reliability degree evaluation index are obtained by carrying out data processing and analysis on the micro-grid parameter data, so that the accuracy and the reliability of the micro-grid configuration monitoring index data are higher, and the micro-grid configuration degree evaluation index is obtained by analyzing the micro-grid configuration monitoring index data, so that the micro-grid configuration degree evaluation index is considered more comprehensively, and further the micro-grid configuration condition is analyzed in more detail according to the micro-grid configuration degree evaluation index; relative to the bulletin number: according to the cooling, heating and power combined supply type micro-grid multi-target optimal configuration method disclosed by the CN111445107B, the micro-grid configuration condition is analyzed according to the micro-grid configuration degree evaluation index, so that a worker can timely perform configuration management on the micro-grid according to the micro-grid configuration condition, and further the power generation loss caused by unreasonable micro-grid configuration is reduced.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of systems, apparatuses (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (9)
1. A data center based microgrid configuration management system comprising: the system comprises a data acquisition module, a data processing module and an analysis module;
Wherein, the data acquisition module: the micro-grid parameter data acquisition device is used for carrying out real-time monitoring on the micro-grid and acquiring the micro-grid parameter data through the data center;
the data processing module: the method comprises the steps of obtaining a micro-grid configuration degree evaluation index according to micro-grid parameter data, wherein the micro-grid configuration degree evaluation index is used for reflecting the good degree of micro-grid configuration;
The analysis module: the system is used for analyzing the configuration situation of the micro-grid according to the micro-grid configuration degree evaluation index and carrying out micro-grid configuration management;
The specific analysis process for obtaining the micro-grid configuration degree evaluation index according to the micro-grid parameter data comprises the following steps:
Acquiring micro-grid parameter data through a data center table, wherein the micro-grid parameter data comprise energy use degree data, wind power generation equipment state data, pollution treatment state data and micro-grid reliability degree data;
Analyzing the micro-grid parameter data to obtain micro-grid configuration monitoring index data, wherein the micro-grid configuration monitoring index data comprises an energy use degree evaluation index, a wind power generation equipment state evaluation index, a pollution treatment state evaluation index and a micro-grid reliability degree evaluation index;
obtaining a micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data;
the energy use degree evaluation index is used for describing data for comprehensively evaluating the energy use degree of the micro-grid through the data of the corresponding power generation amount of wind power generation of the micro-grid, the data of the corresponding power generation amount of photovoltaic power generation of the micro-grid and the data of the corresponding power generation amount of gas power generation of the micro-grid;
the wind power generation equipment state evaluation index is used for representing data for evaluating the state good degree of the micro-grid wind power generation equipment through the wind power generation equipment aging degree data, the wind power generation equipment maintenance time and the wind power generation equipment maintenance cost data;
the pollution treatment state evaluation index is used for comprehensively evaluating the data of the pollution treatment state of the micro-grid through the expense data of carbon monoxide treatment by the micro-grid, the expense data of nitrogen oxide treatment by the micro-grid and the expense data of sulfide treatment by the micro-grid;
the micro-grid reliability evaluation index is used for expressing data reflecting the reliability of the micro-grid through micro-grid power generation efficiency data, micro-grid energy storage efficiency data and micro-grid power generation capacity data.
2. The micro-grid configuration management system based on the data center as set forth in claim 1, wherein the specific analysis process of acquiring the micro-grid parameter data through the data center is that;
the data center station ingests data from a data source;
storing the ingested data in a data storage system of a data center station;
the data center station cleans the ingested data;
performing data conversion on the data after data cleaning, wherein the data conversion comprises data mapping, data aggregation and data remodeling;
The data center station carries out data management on the ingested data, wherein the data management comprises data access control, data dictionary management, data metadata management and data quality monitoring;
And obtaining the data processed by the data center, namely obtaining the micro-grid parameter data.
3. The micro-grid configuration management system based on the data center as set forth in claim 1, wherein the specific analysis process for obtaining the micro-grid configuration degree evaluation index according to the micro-grid configuration monitoring index data is as follows:
Acquiring micro-grid configuration monitoring index data, indicating that the micro-grid configuration monitoring index data is abnormal when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is larger than a first threshold value or the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is smaller than a second threshold value, and recalculating the micro-grid configuration monitoring index data;
when the ratio of the micro-grid configuration monitoring index data to the maximum value of the micro-grid configuration monitoring index data is not greater than a first threshold value and the ratio of the micro-grid configuration monitoring index data to the minimum value of the micro-grid configuration monitoring index data is not less than a second threshold value, the micro-grid configuration monitoring index data is normal;
and comprehensively analyzing the normal micro-grid configuration monitoring index data to obtain a micro-grid configuration degree evaluation index.
4. The data center-based microgrid configuration management system according to claim 1, wherein the specific analysis process of the energy use level evaluation index is as follows:
acquiring energy use degree data and carrying out data cleaning and pretreatment;
Normalizing the energy use degree data;
Acquiring all the micro-grid total power generation amount data in the energy use degree data, sequentially arranging the micro-grid total power generation amount data in sequence from large to small, extracting micro-grid total power generation amount data of the first rank of the micro-grid total power generation amount data, taking the micro-grid total power generation amount data as micro-grid total power generation amount maximum value data, extracting micro-grid total power generation amount data of the last rank of the micro-grid total power generation amount data, and taking the micro-grid total power generation amount data as micro-grid total power generation amount minimum value data;
And analyzing the energy use degree data to obtain an energy use degree evaluation index.
5. The micro-grid configuration management system based on a data center as claimed in claim 1, wherein the specific analysis process of the wind power generation equipment state evaluation index is as follows:
Acquiring state data of wind power generation equipment and performing data conversion and pretreatment;
Comparing the ageing degree data of the wind power generation equipment in the state data of the wind power generation equipment with the ageing degree standard value data of the wind power generation equipment, comparing the maintenance time of the wind power generation equipment with the maintenance standard time of the wind power generation equipment, comparing the maintenance cost data of the wind power generation equipment with the maintenance cost standard value data of the wind power generation equipment, and analyzing the comparison result to obtain a state evaluation index of the wind power generation equipment.
6. The data center-based microgrid configuration management system according to claim 1, wherein the specific analysis process of the pollution treatment state evaluation index is as follows:
acquiring pollution processing state data, and normalizing the data in the pollution processing state data to the same level;
Comparing the carbon monoxide expenditure data processed by the micro-grid in the pollution processing state data with the carbon monoxide volume data processed by the micro-grid, and then comparing the carbon monoxide expenditure data with the standard expenditure data of the carbon monoxide processed by the micro-grid in unit volume to obtain a first comparison result;
comparing the expenditure data of the nitrogen oxides processed by the micro-grid with the volume data of the nitrogen oxides processed by the micro-grid, and then comparing the expenditure data with the standard expenditure data of the nitrogen oxides processed by the micro-grid in unit volume to obtain a second comparison result;
comparing the sulfide expenditure data processed by the micro-grid with the sulfide object volume data processed by the micro-grid, and then comparing the sulfide expenditure data with the standard expenditure data of the sulfide in unit volume processed by the micro-grid to obtain a third comparison result;
and analyzing the first comparison result, the second comparison result and the third comparison result to obtain a pollution treatment state evaluation index.
7. The micro-grid configuration management system based on the data center as set forth in claim 1, wherein the specific obtaining method of the micro-grid configuration degree evaluation index is as follows:
acquiring the number data of the micro-grids, and numbering the micro-grids;
acquiring a preset time period, and numbering the preset time period according to the time period;
Acquiring micro-grid configuration monitoring index data;
Constructing a micro-grid configuration degree evaluation index calculation formula;
the specific micro-grid configuration degree evaluation index calculation formula is as follows:
，
In the method, in the process of the invention, Expressed asThe micro-grid is at theMicro-grid configuration degree evaluation index of each preset time period,，Expressed as the total number of micro-grids,，Expressed as a total number of preset time periods,Expressed asThe micro-grid is at theEnergy use degree evaluation index for each preset time period,Expressed asThe micro-grid is at theWind energy plant status assessment index for a predetermined period of time,Expressed asThe micro-grid is at thePollution treatment state evaluation index for each preset period,Expressed asThe micro-grid is at theMicro-grid reliability evaluation index for preset time period,Expressed as the weight proportion of the energy use degree evaluation index in the micro-grid configuration degree evaluation index,Expressed as weight proportion of wind power generation equipment state evaluation index in micro-grid configuration degree evaluation index,Expressed as the weight proportion of pollution treatment state evaluation index in micro-grid configuration degree evaluation index,Expressed as the weight proportion of the microgrid reliability degree evaluation index in the microgrid configuration degree evaluation index.
8. The micro grid configuration management system based on the data center as set forth in claim 1, wherein the specific acquisition method of the energy use degree evaluation index is as follows:
acquiring the number data of the micro-grids, and numbering the micro-grids;
acquiring a preset time period, and numbering the preset time period according to the time period;
The method comprises the steps of performing multiple data acquisition in a preset time period, and numbering the data acquisition times;
constructing an energy use degree evaluation index calculation formula;
the specific energy use degree evaluation index calculation formula is as follows:
，
In the method, in the process of the invention, Expressed asThe micro-grid is at theAn energy use degree evaluation index for a preset period of time,，Expressed as the total number of micro-grids,，Expressed as a total number of preset time periods,Expressed asThe micro-grid is at theFirst/>, of the preset time periodCorresponding generating capacity data of wind power generation of micro-grid during secondary data acquisition，Expressed as total number of data acquisitions,，Expressed asThe micro-grid is at theFirst/>, of the preset time periodPhotovoltaic power generation corresponding to generated energy data of micro-grid during secondary data acquisition,Expressed asThe micro-grid is at theFirst/>, of the preset time periodCorresponding generated energy data of gas power generation of micro-grid during secondary data acquisition,Expressed asThe micro-grid is at theFirst/>, of the preset time periodMicro-grid total power generation data,/>, during secondary data acquisitionExpressed asThe micro-grid is at theMicro-grid total power generation maximum value data of preset time period,Expressed asThe micro-grid is at theMicro-grid total power generation minimum value data of preset time period,Representing the weight proportion of corresponding power generation amount data of wind power generation belonging to micro-grid in energy use degree evaluation index,Representing the weight proportion of the photovoltaic power generation corresponding power generation data of the micro-grid in the energy use degree evaluation index,And the weight proportion of the generated energy data corresponding to the gas power generation of the micro-grid in the energy use degree evaluation index is shown.
9. The micro-grid configuration management system based on the data center as set forth in claim 1, wherein the specific analysis process of analyzing the micro-grid configuration condition according to the micro-grid configuration degree evaluation index and performing the micro-grid configuration management is as follows:
Acquiring a micro-grid configuration degree evaluation index of the micro-grid in a preset time period, acquiring a configuration degree evaluation threshold, and when the micro-grid configuration degree evaluation index is larger than the configuration degree evaluation threshold, indicating that the micro-grid configuration is in a reasonable state in the preset time period, and not carrying out early warning reminding;
when the micro-grid configuration degree evaluation index is not larger than the configuration degree evaluation threshold, the micro-grid configuration is in an unreasonable state in a preset time period, early warning and reminding are carried out, and micro-grid configuration management is carried out.
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