CN115269652B - Dual-carbon electric power balance optimization system and method - Google Patents
Dual-carbon electric power balance optimization system and method Download PDFInfo
- Publication number
- CN115269652B CN115269652B CN202210899692.2A CN202210899692A CN115269652B CN 115269652 B CN115269652 B CN 115269652B CN 202210899692 A CN202210899692 A CN 202210899692A CN 115269652 B CN115269652 B CN 115269652B
- Authority
- CN
- China
- Prior art keywords
- data
- module
- optimization
- carbon
- power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000005457 optimization Methods 0.000 title claims abstract description 98
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 89
- 238000000034 method Methods 0.000 title claims abstract description 25
- 238000006243 chemical reaction Methods 0.000 claims abstract description 70
- 239000010410 layer Substances 0.000 claims abstract description 70
- 238000012545 processing Methods 0.000 claims abstract description 44
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 37
- 230000005540 biological transmission Effects 0.000 claims abstract description 28
- 239000002346 layers by function Substances 0.000 claims abstract description 8
- 230000008569 process Effects 0.000 claims abstract description 6
- 238000003860 storage Methods 0.000 claims description 47
- 238000007726 management method Methods 0.000 claims description 40
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 36
- 238000013500 data storage Methods 0.000 claims description 34
- 230000010354 integration Effects 0.000 claims description 23
- 230000008054 signal transmission Effects 0.000 claims description 22
- 238000010248 power generation Methods 0.000 claims description 18
- 238000001514 detection method Methods 0.000 claims description 15
- 238000003745 diagnosis Methods 0.000 claims description 15
- 238000006073 displacement reaction Methods 0.000 claims description 15
- 238000007405 data analysis Methods 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 10
- 238000013499 data model Methods 0.000 claims description 8
- 230000008439 repair process Effects 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000003993 interaction Effects 0.000 claims description 5
- 239000003245 coal Substances 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims description 3
- 230000001360 synchronised effect Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 2
- 238000011065 in-situ storage Methods 0.000 claims 1
- 238000009420 retrofitting Methods 0.000 claims 1
- 238000012216 screening Methods 0.000 claims 1
- 239000000872 buffer Substances 0.000 description 12
- 230000000903 blocking effect Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000009977 dual effect Effects 0.000 description 6
- 230000006835 compression Effects 0.000 description 4
- 238000007906 compression Methods 0.000 description 4
- 238000004880 explosion Methods 0.000 description 4
- 238000013480 data collection Methods 0.000 description 2
- 230000006698 induction Effects 0.000 description 2
- 230000006798 recombination Effects 0.000 description 2
- 238000005215 recombination Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006386 neutralization reaction Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24552—Database cache management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Data Mining & Analysis (AREA)
- Computational Linguistics (AREA)
- Human Resources & Organizations (AREA)
- Fuzzy Systems (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Primary Health Care (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Software Systems (AREA)
- General Health & Medical Sciences (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a double-carbon electric power balance optimization system and a double-carbon electric power balance optimization method, relates to the technical field of micro-grid power, and aims to solve the problems of micro-grid power caused by overlarge flow in the process of data acquisition and output and carbon discharge during data acquisition. The double-carbon power balance optimizing system and method are characterized in that an electric power data system converts original data into conversion data, meanwhile, comparison decision is carried out between the conversion data and safety numerical data, so that data flow is subjected to decentralized processing, the data optimizing system carries out further flow optimization on the converted data through a capability layer module, a functional layer module, a model layer module, a data layer module and a physical layer module, and a distributed power coordination module carries out grouping control on integrated conversion electric energy data through a master-slave control module, a peer-to-peer control module and a layer control module and effectively controls and balances micro-grid power through data transmission flow.
Description
Technical Field
The invention relates to the technical field of micro-grid power, in particular to a double-carbon electric power balance optimization system and method.
Background
The "two-carbon" strategy advocates a green, environment-friendly, low-carbon lifestyle, i.e., short for carbon peak and carbon neutralization. The following problems often occur in existing power conversion and harvesting:
1. When the data of water, wind and light are collected, the data are usually transmitted without completing the data conversion of the water, wind and light, and the data are inaccurate or lost during the transmission
2. In the data transmission process, no further flow optimization is performed, so that flow is accumulated during the transmission of the flow, and the power of the micro-grid is caused to flow explosion.
3. When the data is optimized, the balance coordination processing is not performed on the whole data, so that the final micro-grid power is accumulated due to the unbalance of the data.
4. When the self-heat energy source is utilized for power conversion, the risk of overhigh carbon discharge in the power conversion process occurs, the overhigh carbon discharge can cause atmospheric pollution, ecological balance is also caused, and a double-carbon detection system is absent in the existing power balance optimizing system.
Disclosure of Invention
The invention aims to provide a double-carbon electric power balance optimization system and a double-carbon electric power balance optimization method, wherein an electric power data system converts original water, wind and light acquisition data into water, wind and light conversion data in a classified mode, and meanwhile, comparison decision is carried out on the data of safety values in the water, wind and light conversion data, so that data flow is subjected to decentralized processing, the data optimization system carries out further flow optimization on the converted data through a capacity layer module, a functional layer module, a model layer module, a data layer module and a physical layer module, the flow of the data during transmission is not accumulated, the flow explosion of the power of a micro-grid is avoided, the distributed power coordination module carries out grouping control on integrated water, wind and light conversion electric energy data through a master-slave control module, a peer-to-peer control module and a layer control module, and the micro-grid power is effectively controlled and balanced through the flow of data transmission, so that the problems in the background technology are solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
A double-carbon electric power balance optimization system and method are characterized in that: the system comprises an acquisition terminal, a server, an optimization platform and a management terminal, wherein the acquisition terminal, the server, the optimization platform and the management terminal are respectively transmitted through data signals;
The acquisition terminal is used for uniformly acquiring and storing the acquired water, wind and light original data and classifying the original data;
the server performs optimized storage on different types of data based on the acquisition terminal;
The optimization platform integrates the optimized data based on the server, and performs data balance integration after integration;
the management terminal is used for displaying the completed data on the display device in a document form;
the optimizing platform 3 comprises an optimizing balance system 31 and a double-carbon processing system 32, and the optimizing balance system 31 and the double-carbon processing system 32 are in data interaction;
the optimization balancing system 31 is configured to balance and optimize the received data;
the two-carbon processing system 32 converts power supply data in the data based on the optimizing balance system 31 into carbon displacement data, and optimizes the converted data through the optimizing balance system 31 after conversion;
The dual carbon treatment system 32 includes a power supply A/D conversion module 321, a dual carbon calculation module 322, a carbon displacement comparison module 323, and a storage module 324
The power supply is an a/D conversion module 321 that converts received analog signal data into digital signal data based on the optimization balancing system 31;
The two-carbon calculation module 322 converts all the power data in the digital signal data into coal consumption data based on the power supply being the A/D conversion module 321, and calculates the carbon emission amount by multiplying the carbon emission coefficient of the region;
The carbon displacement comparison module 323 compares the calculated carbon displacement data with the qualified value data based on the two-carbon calculation module 322 and screens out abnormal data;
The storage module 324 stores the anomaly data based on the carbon displacement comparison module 323.
Preferably, an electric power data system is arranged in the acquisition terminal, the electric power data system comprises a data acquisition module, a data conversion module, a data detection module and a data integration module, and the data integration module performs unified integration on the data which is detected in a safety value and is detected outside the safety value after decision making based on the data detection module;
The data acquisition module is used for acquiring different types of data separately;
the data conversion module is used for carrying out different power conversion on different data based on the data acquired by the data acquisition module;
the data detection module performs further detection processing based on the power value converted by the data conversion module;
The data integration module is used for sorting and storing different data in different categories.
Preferably, the data acquisition module comprises a photovoltaic data acquisition module, a wind data acquisition module and a photovoltaic data acquisition module;
The water voltage data acquisition module is used for acquiring and storing water energy data;
the wind voltage data acquisition module is used for acquiring and storing wind energy data;
the photovoltaic data acquisition module is used for acquiring and storing the light energy data.
Preferably, the data conversion module comprises a photovoltaic power generation conversion module, a wind power generation conversion module and a photovoltaic power generation conversion module;
The water energy is converted into electric energy by the water power generation conversion module based on the data acquisition module;
the wind power generation conversion module is used for converting wind energy into electric energy based on the data acquisition module;
the photovoltaic power generation conversion module converts light energy into electric energy based on the data acquisition module.
Preferably, the data detection module comprises a data comparison module, a data diagnosis module and a data decision module;
the data comparison module performs classification comparison on the collected data of each group transmitted by the data conversion module and the set safety value data;
the data diagnosis module diagnoses based on the data which is not in the safety value in the data comparison module;
the data decision module performs decision cutting based on the data category diagnosed in the data diagnosis module.
Preferably, a data optimization system is arranged in the server, and the data optimization system comprises a data synchronization module, a data optimization module, a data analysis module, a data storage module and a data guiding module;
the data synchronization module receives the synchronization information of the data at fixed time according to a preset interval based on the acquisition terminal;
the data optimization module carries out multi-step evaluation on the data based on the data synchronization module;
the data analysis module performs excellent analysis on the evaluated data based on the data optimization module;
the data storage module is used for storing the data after the data analysis is completed based on the data analysis module;
the data guiding module is used for guiding various data according to the categories in the next step;
And a storage management module is further performed in the server for the data storage module, and the storage management module performs storage management for the data storage module, including:
Acquiring state information of the data storage module, analyzing the state information to determine the residual storage space of the data storage module, modifying the storage module according to the residual storage space,
And monitoring the data storage module through the state information, analyzing whether an occlusion channel exists in the data storage module in the state information,
When the state information is analyzed that the blocking channel exists in the data storage module, automatic repair is carried out on a storage area corresponding to the blocking channel, and if the automatic repair fails, reminding is carried out on the blocking channel.
Preferably, the data optimization module comprises a capability layer module, a function layer module, a model layer module, a data layer module and a physical layer module;
the capacity layer module is used for energy-saving operation mode, daily operation mode and large-flow scheduling;
the functional layer module is used for digital simulation, analysis and diagnosis;
the model layer module is used for a data model and a data driving model, and the data model and the data driving model form a dynamic model;
The data layer module is used for carrying out multidimensional data operation on inherent data and real-time acquisition data;
the physical layer module is used for data operation of physical entities and logic rules.
Preferably, the optimized balance system comprises a distributed power supply data receiving module, a distributed power supply coordination module and a power supply grid-connected module;
the distributed power supply data receiving module receives the data of each category in a distributed mode based on the server;
the distributed power coordination module performs coordination processing based on the distributed data received by the distributed power data receiving module;
the power grid-connected module is used for combining and integrating the whole distributed data based on the distributed power coordination module;
the distributed power coordination module comprises a master-slave control module, a peer-to-peer control module and a layer control module;
the master-slave control module provides voltage and frequency references for distributed power supplies in the micro-grid based on the distributed power supply data receiving module;
The peer-to-peer control module controls each distributed power supply according to the local information of the access system point voltage and the frequency based on the distributed power supply data receiving module;
The layer control module predicts the power generation power and the load demand of the distributed power supply based on the distributed power supply data receiving module.
Preferably, the data signal transmission includes: a transmitting end and a receiving end;
the sending end and the receiving end are respectively arranged in the acquisition terminal, the server, the optimization platform and the management terminal according to the requirements of the acquisition terminal, the server, the optimization platform and the management terminal,
The sending end generates data signals according to the data to be transmitted in the acquisition terminal, the server, the optimization platform and the management terminal according to the requirements of the acquisition terminal, the server, the optimization platform and the management terminal, adjusts and processes the data signals by combining compensation data, and then the signal transmitting device transmits the processed data signals to the receiving end of the target position;
the receiving end of the target position receives the processed data signal sent by the transmitting device, performs signal processing on the processed data signal to obtain processed data signal restoration information, and extracts data to be transmitted from the processed data signal restoration information to obtain data signal transmission data;
When the signal transmitting device transmits the processed data signal to the receiving end of the target position, the signal transmitting device performs signal transmission energy estimation according to the processed data signal and the receiving end of the target position and then transmits the processed data signal according to the estimated energy;
the estimated data is determined by the following formula:
In the above-mentioned formula(s), Representing the estimated energy of signal emission; representing the estimated power of signal transmission; A reception power of a reception end indicating a target position; Representing a constant; representing the distance between the transmitting end and the receiving end of the target position; The loss representing the transmission parameters includes: antenna loss, transmission line loss, etc.; Representing the antenna gain of the transmitting end; Representing the antenna gain at the receiving end; Indicating the wavelength of the processed data signal.
The invention provides another technical scheme, a method for optimizing a double-carbon electric power balance system and a method thereof, which comprises the following steps:
The first step: firstly, collecting all groups of energy data of water, wind and light through a collecting terminal, converting the energy data into electric energy after the collection is completed, and detecting and integrating all groups of converted data after the conversion is completed;
and a second step of: the server synchronously integrates all groups of conversion data integrated by the acquisition terminal, and further optimizes the data after synchronous integration;
and a third step of: the optimization platform performs balance coordination on the optimized data in the server;
fourth step: and the management terminal displays the balanced and coordinated data in the optimization platform in the form of a document.
Compared with the prior art, the invention has the beneficial effects that:
1. The invention provides a dual-carbon power balance optimization system and a method, wherein a data acquisition module is used for acquiring different types of data separately, the real-time acquisition of the data acquisition module is realized by depending on an acquisition total system, the real-time acquisition total system is realized by an independent processor timing module, the data interval of real-time messages can be set according to the need under the condition that the acquired highest data flow is not exceeded, the data integration module establishes four types of threads of an acquisition thread, a compression thread, a recombination thread and a network transmission thread on the data of a data conversion module, and initializes three types of data buffers of an acquisition buffer zone, a compression buffer zone and a transmission buffer zone, the data buffer zone is used for integrating the data, the data buffer zone guarantees the mutex of multi-thread access in a locking mode, and meanwhile, a high-performance data diagnosis module provides powerful computing capacity for a power data system, realizes real-time processing and local storage of important data, and greatly improves the functions and operation processing capacity of the power data system.
2. The invention provides a double-carbon electric power balance optimization system and a method, wherein a data optimization module performs effective optimization processing on electric energy data of converted water, wind and light, a solution for solving a certain type of specific problems in specific application data is combined into a professional knowledge system through collocation of a capability layer module, the formed modes are integrated into a professional knowledge system after induction summarization, self-adaptive adjustment is realized to a certain extent, the formed modes are enabled to enable the data transmitted simultaneously to follow common transmission rules, the data model and the data driving model are mutually kept at certain uniformity, a model layer module is used for the data model and the data driving model to form a dynamic model, the capability of self-adjusting the data is provided, inherent data provide the data layer module with data existing in a physical space and multi-mode multi-type operation data acquired by various sensors in real time, and the physical layer module is used for data operation of physical entities and logic rules and also comprises various operation logic rules existing inside the physical entities and among the physical entities, data transmission flows and the like.
3. The invention provides a double-carbon electric power balance optimizing system and a method, a distributed power coordination module performs grouping control on integrated water, wind and light converted electric energy data through a master-slave control module, a peer-to-peer control module and a layer control module, and the micro-grid power is effectively controlled and balanced through the flow of data transmission.
4. The invention provides a double-carbon electric power balance optimization system and a double-carbon electric power balance optimization method, wherein a double-carbon processing system can calculate carbon displacement data calculated by electric energy data of different energy sources acquired in an acquisition terminal, the calculated data is compared with data in a qualified range in a national policy, and after the comparison, unqualified data of carbon emission is checked, so that the corresponding acquired energy sources can be further controlled, the data interaction of the balance system and the double-carbon processing system is optimized, and when the data of the double-carbon processing system is formed, the data in the double-carbon processing system can be optimized through the balance system.
Drawings
FIG. 1 is a schematic diagram of the overall topology of the present invention;
FIG. 2 is a schematic diagram of the overall system of the present invention;
FIG. 3 is a schematic diagram of a power data system module according to the present invention;
FIG. 4 is a schematic diagram of a data optimization system module according to the present invention;
FIG. 5 is a schematic diagram of an optimized balance system module of the present invention;
FIG. 6 is a schematic diagram of a dual carbon processing system module according to the present invention.
In the figure: 1. a collecting terminal; 11. a power data system; 111. a data acquisition module; 1111. a water volt data acquisition module; 1112. a photovoltaic data acquisition module; 1113. a photovoltaic data acquisition module; 112. a data conversion module; 1121. a photovoltaic power generation conversion module; 1122. a wind-to-voltage power generation conversion module; 1123. a photovoltaic power generation conversion module; 113. a data detection module; 1131. a data comparison module; 1132. a data diagnosis module; 1133. a data decision module; 114. a data integration module; 2. a server; 21. a data optimization system; 211. a data synchronization module; 212. a data optimization module; 2121. a capability layer module; 2122. a functional layer module; 2123. a model layer module; 2124. a data layer module; 2125. a physical layer module; 213. a data analysis module; 214. a data storage module; 215. a data guiding module; 3. optimizing a platform; 31. optimizing a balance system; 311. a distributed power data receiving module; 312. a distributed power coordination module; 3121. a master-slave control module; 3122. a peer-to-peer control module; 3123. a layer control module; 313. a power grid-connected module; 32. a dual carbon treatment system; 321. a power supply data A/D conversion module; 322. a two-carbon calculation module; 323. a carbon displacement comparison module; 324. a storage module; 4. and managing the terminal.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1 and 6, a dual-carbon power balance optimization system and method includes an acquisition terminal 1, a server 2, an optimization platform 3 and a management terminal 4, wherein the acquisition terminal 1, the server 2, the optimization platform 3 and the management terminal 4 respectively transmit data signals; the acquisition terminal 1 is used for uniformly acquiring and storing the acquired water, wind and light original data and effectively classifying the original data; the server 2 performs optimized storage on different types of data based on the acquisition terminal 1; the optimization platform 3 integrates the optimized data based on the server 2, and performs data balance integration after integration; the management terminal 4 is used for displaying the completed data on a display device in a document form, and the optimization platform 3 comprises an optimization balance system 31 and a double-carbon processing system 32, and the optimization balance system 31 and the double-carbon processing system 32 are in data interaction; the optimization balancing system 31 is used for performing balance optimization on the received data; the double-carbon processing system 32 converts power supply data in the data into carbon displacement data based on the optimizing balance system 31, and optimizes the converted data through the optimizing balance system 31 after conversion; the dual carbon treatment system 32 includes a power supply A/D conversion module 321, a dual carbon calculation module 322, a carbon displacement comparison module 323, and a storage module 324; the power supply is an a/D conversion module 321 that converts received analog signal data into digital signal data based on the optimization balancing system 31; the two-carbon calculation module 322 converts all the power data in the digital signal data into coal consumption data based on the power supply being the a/D conversion module 321, calculates the carbon emission amount by multiplying the carbon emission coefficient of the region; the carbon displacement comparison module 323 compares the calculated carbon displacement data with the qualified value data based on the two-carbon calculation module 322 and screens out abnormal data; the storage module 324 stores abnormal data based on the carbon discharge comparison module 323, carbon discharge data calculated by electric energy data of different energy sources collected in the collection terminal 1 can be calculated through the double-carbon processing system 32, the calculated data is compared with data in a qualified range in a national policy, unqualified data of carbon discharge is checked after comparison, corresponding collected energy sources can be further controlled, data interaction of the balance system 31 and the double-carbon processing system 32 is optimized, and after the data of the double-carbon processing system 32 is formed, the data in the double-carbon processing system 32 can be optimized through the optimization balance system 31.
Referring to fig. 2-3, the collecting terminal 1 is provided with a power data system 11, the power data system 11 includes a data collecting module 111, a data converting module 112, a data detecting module 113 and a data integrating module 114, the data integrating module 114 performs unified integration on the data after decision cutting in the safety value and out of the safety value based on the data detecting module 113, the data integration module 114 creates four types of threads, namely an acquisition thread, a compression thread, a recombination thread and a network transmission thread, of the data conversion module 112, and initializes an acquisition buffer area, a compression buffer area, Three types of data buffers of the buffer area are sent, the data buffers are used for integrating data among the multithread, and the data buffers ensure mutex of multithread access in a locking mode; the data acquisition module 111 is used for acquiring different types of data separately; the real-time acquisition of the data acquisition module 111 is realized by depending on an acquisition total system, the real-time acquisition total system is realized by an independent processor timing module, the data interval of real-time messages can be set according to the need under the condition that the data interval does not exceed the acquired highest data flow, and the data conversion module 112 converts different data into different power based on the data acquired by the data acquisition module 111; the data detection module 113 performs further detection processing based on the power value converted by the data conversion module 112; the data integration module 114 is used for sorting and storing different data according to categories; The data acquisition module 111 includes a photovoltaic data acquisition module 1111, a photovoltaic data acquisition module 1112, and a photovoltaic data acquisition module 1113; the water voltage data acquisition module 1111 is used for acquiring and storing water energy data; the wind voltage data acquisition module 1112 is used for acquiring and storing wind energy data; the photovoltaic data acquisition module 1113 is used for acquiring and storing the light energy data; the data conversion module 112 includes a photovoltaic power conversion module 1121, a wind power conversion module 1122, and a photovoltaic power conversion module 1123; the photovoltaic power conversion module 1121 converts water energy into electric energy based on the data collection module 111; the wind power generation conversion module 1122 converts wind energy into electric energy based on the data acquisition module 111; the photovoltaic power conversion module 1123 converts light energy into electric energy based on the data collection module 111; the data detection module 113 includes a data comparison module 1131, a data diagnosis module 1132, and a data decision module 1133; the data comparison module 1131 performs classification comparison on the collected data of each group transmitted by the data conversion module 112 and the set safety value data; the data diagnosis module 1132 diagnoses based on the data in the data comparison module 1131 that is not within the safe value; the high-performance data diagnosis module 1132 provides strong computing capacity for the power data system, realizes real-time processing and local storage of important data, and greatly improves the function and operation processing capacity of the power data system; The data decision module 1133 performs decision cutting based on the data type diagnosed in the data diagnosis module 1132, the power data system 11 converts the original water, wind and light collecting data into water, wind and light conversion data according to the data type, and meanwhile, the comparison decision is performed between the water, wind and light conversion data and the safety value data, so that the data flow is subjected to decentralized processing, the data optimization system 21 performs further flow optimization on the converted data through the capability layer module 2121, the functional layer module 2122, the model layer module 2123, the data layer module 2124 and the physical layer module 2125, so that the flow of the data during transmission is not piled up, the power of the micro-grid is not allowed to flow explosion.
Referring to fig. 2 and 4, a data optimization system 21 is disposed in the server 2, where the data optimization system 21 includes a data synchronization module 211, a data optimization module 212, a data analysis module 213, a data storage module 214, and a data guiding module 215; the data synchronization module 211 receives a synchronization message of data at regular intervals based on the acquisition terminal 1; the data optimization module 212 performs multi-step evaluation on the data based on the data synchronization module 211; the data analysis module 213 performs a fine analysis on the evaluated data based on the data optimization module 212; the data storage module 214 performs data analysis on the completed storage work based on the data analysis module 213; the data guiding module 215 is used for guiding the various data in different categories to the next step; the data optimization module 212 includes a capability layer module 2121, a function layer module 2122, a model layer module 2123, a data layer module 2124, and a physical layer module 2125; the capability layer module 2121 is used for energy-saving operation mode, daily operation mode and large-flow scheduling, and a solution for solving a certain specific problem in specific application data through the collocation of the capability layer module 2121 is integrated into a professional knowledge system after induction summarization, and the formed mode is subjected to self-adaptive adjustment to a certain extent; the functional layer module 2122 is used for digital simulation, analysis diagnosis and decision autonomy, and the functional layer module 2122 enables the data transmitted simultaneously to follow a common transmission rule and keep certain uniformity mutually; the model layer module 2123 is used for a data model and a data driving model, and the data model and the data driving model form a dynamic model and have the capability of self-adjusting data; the data layer module 2124 is used for performing multidimensional data operation on intrinsic data and real-time collected data, wherein the intrinsic data provides the data existing in a physical space for the data layer module 2124 and multi-mode and multi-type operation data collected by various sensors in real time; the physical layer module 2125 is configured to perform data operation on physical entities and logic rules, including physical entities and logic rules, and also includes various existing logic rules such as operation logic, data transmission flow, and the like existing inside the physical entities and between the physical entities.
Referring to fig. 2 and 5, the optimization balancing system 31 includes a distributed power data receiving module 311, a distributed power coordination module 312, and a power grid connection module 313; the distributed power supply data receiving module 311 receives data of each category in a distributed manner based on the server 2; the distributed power coordination module 312 performs coordination processing based on the distributed data received by the distributed power data receiving module 311; the power grid-connected module 313 merges and integrates the overall distributed data based on the distributed power coordination module 312; the distributed power coordination module 312 includes a master-slave control module 3121, a peer-to-peer control module 3122, and a peer-to-peer control module 3123; the master-slave control module 3121 provides voltage and frequency references to other distributed power sources in the micro-grid based on the distributed power source data receiving module 311, where the master-slave control module 3121 refers to that when the micro-grid is in the island operation mode, one of the distributed power sources adopts constant voltage and constant frequency control, the other distributed power sources can adopt constant power control, the distributed power source controller adopting V/F control is called a master controller, and the other distributed power source controllers are called slave controllers; the peer-to-peer control module 3122 controls each distributed power source according to the local information of the access system point voltage and the frequency based on the distributed power source data receiving module 311, the peer-to-peer control module 3122 means that all the distributed power sources in the micro-grid have equal status in control, and no control relationship of master and slave exists between the controllers, for the control mode, the policy selection of the distributed power source controllers is critical, and one common method is Droop control; the layer control module 3123 predicts the power generated by the distributed power source and the load demand based on the distributed power source data receiving module 311, and the layer control module 3123 is generally provided with a central controller for sending control information to the distributed power sources in the micro-grid. The central controller firstly predicts the power generation and load demand of the distributed power supply, then makes a corresponding plan, adjusts the operation plan according to the information such as voltage, current and power acquired in real time, and the distributed power supply coordination module 312 performs grouping control on the integrated electric energy data converted from water, wind and light through the master-slave control module 3121, the peer-to-peer control module 3122 and the layer control module 3123 and performs effective control and balance on the micro-grid power through the flow of data transmission.
The server 2 further performs a storage management module for the data storage module 214, where the storage management module is configured to perform storage management for the data storage module 214, and includes:
Acquiring state information of the data storage module 214, analyzing the state information to determine the residual storage space of the data storage module 214, modifying the storage module 214 according to the residual storage space, deleting data stored in the storage module 214 according to time sequence when the residual storage space is smaller, or accessing new storage hardware into the storage module 214 to increase the storage space of the storage module;
Meanwhile, the state information is also monitored on the data storage module 214, the storage condition of the storage module can be embodied by analyzing the state information, specifically, whether an occlusion channel exists in the data storage module 214 is analyzed in the state information, when the occlusion channel exists in the data storage module 214, an abnormal repair system is utilized to automatically repair a storage area corresponding to the occlusion channel, and if the automatic repair fails, the occlusion channel is reminded, so that a worker can further process according to reminding.
The management of the data storage module 214 is realized through the storage management module, so that the improvement on the storage space of the data storage module 214 is timely carried out, the situation that the data storage cannot be completed or the normal operation of the server 2 is affected due to the fact that the residual storage space in the data storage module 214 is smaller is avoided, and the staff can timely process the storage area corresponding to the blocking channel in the data storage module 214 by reminding the blocking channel, so that the maintenance of the data storage module 214 is facilitated, and the staff can be effectively reduced only when the abnormal repair system carries out automatic repair failure on the storage area corresponding to the blocking channel during reminding the blocking channel.
The data signal transmission includes: a transmitting end and a receiving end; the sending end and the receiving end are respectively arranged in the acquisition terminal 1, the server 2, the optimization platform 3 and the management terminal 4 according to the requirements of the acquisition terminal 1, the server 2, the optimization platform 3 and the management terminal 4, the sending end respectively generates data signals for the data to be transmitted in the acquisition terminal 1, the server 2, the optimization platform 3 and the management terminal 4 according to the requirements of the acquisition terminal 1, the server 2, the optimization platform 3 and the management terminal 4, the data signals are adjusted and processed by combining with compensation data, the processed data signals are transmitted to the receiving end of a target position by a signal transmitting device,
The adjusting and processing here includes: filtering processing, transformation processing, enhancement processing, and the like; the target location herein refers to the requirements of the acquisition terminal 1, the server 2, the optimization platform 3, and the management terminal 4, where the requirements of the acquisition terminal 1, the server 2, the optimization platform 3, and the management terminal 4 are set in the acquisition terminal 1, the server 2, the optimization platform 3, and the management terminal 4, respectively, and the receiving end of the target location receives the processed data signal sent by the transmitting device, performs signal processing on the processed data signal to obtain processed data signal restoration information, and extracts data to be transmitted from the processed data signal restoration information to obtain data signal transmission data, where the signal processing includes: noise reduction processing, main signal recognition processing, and the like; when the signal transmitting device transmits the processed data signal to the receiving end of the target position, the signal transmitting device performs signal transmitting energy prediction according to the processed data signal and the receiving end of the target position, and then transmits the processed data signal according to the predicted energy, wherein the predicted data is determined by the following formula:
In the above-mentioned formula(s), Representing the estimated energy of signal emission; representing the estimated power of signal transmission; A reception power of a reception end indicating a target position; Representing a constant; representing the distance between the transmitting end and the receiving end of the target position; The loss representing the transmission parameters includes: antenna loss, transmission line loss, etc.; Representing the antenna gain of the transmitting end; Representing the antenna gain at the receiving end; Indicating the wavelength of the processed data signal.
According to the data signal transmission method, the data signal transmission and reception can be targeted and carried out during data signal transmission through the sending end and the receiving end, so that the data signal transmission can be carried out orderly, signal transmission confusion is avoided, the coordination among the acquisition terminal 1, the server 2, the optimization platform 3 and the management terminal 4 is guaranteed to realize orderly water, wind and light micro-grid power balance optimization, the receiving end receives the data signal loss through adjustment and processing, the error of the receiving end receiving the data signal is reduced, the influence on the data signal in the transmission process is eliminated through the data signal restoration information carried out by the receiving end, the accuracy of the data signal transmission data obtained by the receiving end is improved, and in addition, the signal transmission energy is also estimated during the data signal transmission through the signal transmission device at the sending end, so that the data signal transmission is carried out according to the estimated transmission energy, the data signal cannot be successfully received by the receiving end, and the success rate of the data signal transmission is improved.
A method of a two-carbon electric power balance optimization system, comprising the steps of:
The first step: firstly, collecting all groups of energy data of water, wind and light through a collecting terminal 1, converting the energy data into electric energy after the collection is completed, detecting and integrating all groups of converted data after the conversion is completed, and integrating the optimized data based on a server 2 by an optimizing platform 3, and balancing and integrating the data after the integration; the management terminal 4 is used for displaying the completed data on the display device in a document form;
And a second step of: the server 2 synchronously integrates all the groups of conversion data integrated by the acquisition terminal 1, the data are further optimized after the synchronous integration, and the data optimization system 21 further optimizes the flow of the converted data through the capability layer module 2121, the function layer module 2122, the model layer module 2123, the data layer module 2124 and the physical layer module 2125, so that the flow of the data during transmission is not accumulated, and the power of the micro-grid is not subjected to flow explosion;
and a third step of: the optimization platform 3 performs balance coordination on the optimized data in the server 2, the distributed power coordination module 312 performs grouping control on the integrated water, wind and light converted electric energy data through the master-slave control module 3121, the peer-to-peer control module 3122 and the layer control module 3123, and the micro-grid power is effectively controlled and balanced through the flow of data transmission;
Fourth step: the management terminal 4 presents the data balanced and coordinated in the optimization platform 3 in the form of a document.
In summary, the power data system 11 converts the original water, wind and light collected data into water, wind and light converted data according to the classification, and performs comparison decision with safety value data in the water, wind and light converted data at the same time, so that the data traffic is distributed, the data optimizing system 21 performs further traffic optimization on the converted data through the capability layer module 2121, the function layer module 2122, the model layer module 2123, the data layer module 2124 and the physical layer module 2125, so that the traffic of the data during transmission is not accumulated, the power of the micro grid is not exploded, the distributed power coordination module 312 performs packet control on the integrated water, wind and light converted electric energy data through the master-slave control module 3121, the peer control module 3122 and the peer control module 3123, and the traffic of the data transmission effectively controls and balances the micro grid power.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should be covered by the protection scope of the present invention by making equivalents and modifications to the technical solution and the inventive concept thereof.
Claims (6)
1. A double-carbon electric power balance optimizing system is characterized in that: the system comprises an acquisition terminal (1), a server (2), an optimization platform (3) and a management terminal (4), wherein the acquisition terminal (1), the server (2), the optimization platform (3) and the management terminal (4) are respectively transmitted through data signals;
The acquisition terminal (1) is used for uniformly acquiring and storing the acquired water, wind and light original data and classifying the original data;
The server (2) performs optimized storage on different types of data based on the acquisition terminal (1);
the optimization platform (3) integrates the optimized data based on the server (2), and performs data balance integration after integration;
the management terminal (4) is used for displaying the completed data on the display device in a document form;
the optimization platform (3) comprises an optimization balance system (31) and a double-carbon processing system (32), and the optimization balance system (31) and the double-carbon processing system (32) are in data interaction;
the optimization balancing system (31) is used for carrying out balance optimization on received data;
the double-carbon processing system (32) converts power supply data in the data into carbon displacement data based on the optimized balance system (31), and the converted data is optimized through the optimized balance system (31);
The dual-carbon treatment system (32) comprises a power supply A/D conversion module (321), a dual-carbon calculation module (322), a carbon discharge comparison module (323) and a storage module (324);
The power supply is an A/D conversion module (321) for converting received analog signal data into digital signal data based on an optimized balance system (31);
The two-carbon calculation module (322) converts all electric power data in the digital signal data into coal consumption data based on the power supply A/D conversion module (321), and calculates the carbon emission amount by multiplying the carbon emission coefficient of the area;
The carbon displacement comparison module (323) is used for comparing the calculated carbon displacement data with the qualified value data based on the double-carbon calculation module (322) and screening out abnormal data;
the storage module (324) stores abnormal data based on the carbon displacement comparison module (323);
The data signal transmission includes: a transmitting end and a receiving end;
The sending end and the receiving end are respectively arranged in the acquisition terminal (1), the server (2), the optimization platform (3) and the management terminal (4) according to the requirements of the acquisition terminal (1), the server (2), the optimization platform (3) and the management terminal (4),
The sending end generates data signals according to the data to be transmitted in the acquisition terminal (1), the server (2), the optimization platform (3) and the management terminal (4) aiming at the requirements of the acquisition terminal (1), the server (2), the optimization platform (3) and the management terminal (4), adjusts and processes the data signals by combining with compensation data, then the signal transmitting device transmits the processed data signals to the receiving end of a target position,
The receiving end of the target position receives the processed data signal sent by the transmitting device, performs signal processing on the processed data signal to obtain processed data signal restoration information, and extracts data to be transmitted from the processed data signal restoration information to obtain data signal transmission data;
When the signal transmitting device transmits the processed data signal to the receiving end of the target position, the signal transmitting device performs signal transmission energy estimation according to the processed data signal and the receiving end of the target position and then transmits the processed data signal according to the estimated energy;
the estimated data is determined by the following formula:
W＝P+10lg{4.5×(l/s)2}
In the above formula, W represents estimated energy of signal emission; p represents the estimated power of signal transmission; p represents the receiving power of the receiving end of the target position; pi represents a constant; l represents the distance between the transmitting end and the receiving end of the target position; e i denotes a loss of transmission parameters, the parameters of which include: antenna loss, transmission line loss, etc.; z 1 represents the antenna gain at the transmitting end; z 2 represents the antenna gain at the receiving end; s represents the wavelength of the processed data signal;
a data optimization system (21) is arranged in the server (2), and the data optimization system (21) comprises a data synchronization module (211), a data optimization module (212), a data analysis module (213), a data storage module (214) and a data guiding module (215);
the data synchronization module (211) receives the synchronization information of the data at regular intervals based on the acquisition terminal (1);
The data optimization module (212) carries out multi-step evaluation on the data based on the data synchronization module (211);
The data analysis module (213) performs excellent analysis on the evaluated data based on the data optimization module (212);
the data storage module (214) is used for storing the data after the data analysis is completed based on the data analysis module (213);
The data guiding module (215) is used for guiding various data in the next step according to the categories;
-a storage management module is further provided in the server (2) for the data storage module (214), the storage management module being provided for storage management of the data storage module (214) and comprising:
Acquiring status information of the data storage module (214), analyzing the status information to determine a remaining storage space of the data storage module (214), retrofitting the storage module (214) according to the remaining storage space,
While also monitoring the data storage module (214) by means of the status information in which it is analyzed whether an occlusion channel is present in the data storage module (214),
When the state information is analyzed to have an occlusion channel in the data storage module (214), automatically repairing a storage area corresponding to the occlusion channel, and prompting the occlusion channel if the automatic repair fails;
the data optimization module (212) comprises a capability layer module (2121), a function layer module (2122), a model layer module (2123), a data layer module (2124) and a physical layer module (2125);
The capability layer module (2121) is used for energy-saving operation mode, daily operation mode and large-flow scheduling;
the functional layer module (2122) is used for digital simulation, analysis and diagnosis;
the model layer module (2123) is used for a data model and a data driving model, and the data model and the data driving model form a dynamic model;
The data layer module (2124) is used for carrying out multidimensional data operation on inherent data and real-time collected data;
the physical layer module (2125) is used for data operation of physical entities and logical rules;
the optimization balancing system (31) comprises a distributed power supply data receiving module (311), a distributed power supply coordination module (312) and a power supply grid-connected module (313);
the distributed power supply data receiving module (311) receives data of each type in a distributed mode based on the server (2);
The distributed power coordination module (312) performs coordination processing based on the distributed data received by the distributed power data receiving module (311);
the power grid-connected module (313) is used for combining and integrating the whole distributed data based on the distributed power coordination module (312);
The distributed power coordination module (312) comprises a master-slave control module (3121), a peer-to-peer control module (3122) and a peer-to-peer control module (3123);
the master-slave control module (3121) provides voltage and frequency references to distributed power sources in the microgrid based on the distributed power data reception module (311);
The peer-to-peer control module (3122) controls each distributed power source according to in-situ information of access system point voltage and frequency based on the distributed power source data receiving module (311);
the layer control module 3123 predicts the distributed power generation power and the load demand amount based on the distributed power data receiving module 311.
2. A two-carbon electric power balance optimization system as recited in claim 1, wherein: the power data system (11) is arranged in the acquisition terminal (1), the power data system (11) comprises a data acquisition module (111), a data conversion module (112), a data detection module (113) and a data integration module (114), and the data integration module (114) performs unified integration on data which are detected in a safety value and are detected outside the safety value after decision making based on the data detection module (113);
The data acquisition module (111) is used for acquiring different types of data separately;
The data conversion module (112) is used for carrying out different power conversion on different data based on the data acquired by the data acquisition module (111);
The data detection module (113) performs further detection processing based on the power value converted by the data conversion module (112);
the data integration module (114) is used for sorting and storing different data in different categories.
3. A two-carbon electric power balance optimization system as recited in claim 2, wherein: the data acquisition module (111) comprises a photovoltaic data acquisition module (1111), a photovoltaic data acquisition module (1112) and a photovoltaic data acquisition module (1113);
the water volt data acquisition module (1111) is used for acquiring and storing water energy data;
The wind power data acquisition module (1112) is used for acquiring and storing wind power data;
the photovoltaic data acquisition module (1113) is used for acquiring and storing the light energy data.
4. A two-carbon electric power balance optimization system as recited in claim 2, wherein: the data conversion module (112) comprises a photovoltaic power generation conversion module (1121), a wind power generation conversion module (1122) and a photovoltaic power generation conversion module (1123);
the water-based power generation conversion module (1121) converts water energy into electric energy based on the data acquisition module (111);
the wind power generation conversion module (1122) converts wind energy into electric energy based on the data acquisition module (111);
The photovoltaic power conversion module (1123) converts light energy into electrical energy based on the data acquisition module (111).
5. A two-carbon electric power balance optimization system as recited in claim 2, wherein: the data detection module (113) comprises a data comparison module (1131), a data diagnosis module (1132) and a data decision module (1133);
the data comparison module (1131) performs classification comparison on the acquired data of each group transmitted by the data conversion module (112) and the set safety value data;
the data diagnosis module (1132) diagnoses based on the data which is not in the safety value in the data comparison module (1131);
The data decision module (1133) makes decision cuts based on the data categories diagnosed in the data diagnosis module (1132).
6. A method for implementing the two-carbon electric power balance optimization system according to any one of claims 1-5, wherein: the method comprises the following steps:
The first step: collecting all groups of energy data of water, wind and light through a collecting terminal (1), converting the energy data into electric energy after the collection is completed, and detecting and integrating all groups of converted data after the conversion is completed;
and a second step of: the server (2) synchronously integrates the data of each group of conversion data integrated by the acquisition terminal (1), and optimizes the data after synchronous integration;
and a third step of: the optimization platform (3) performs balance coordination on the optimized data in the server (2);
Fourth step: the management terminal (4) displays the balanced and coordinated data in the optimization platform (3) in the form of a document.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210899692.2A CN115269652B (en) | 2022-07-28 | 2022-07-28 | Dual-carbon electric power balance optimization system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210899692.2A CN115269652B (en) | 2022-07-28 | 2022-07-28 | Dual-carbon electric power balance optimization system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115269652A CN115269652A (en) | 2022-11-01 |
| CN115269652B true CN115269652B (en) | 2024-08-20 |
Family
ID=83772489
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210899692.2A Active CN115269652B (en) | 2022-07-28 | 2022-07-28 | Dual-carbon electric power balance optimization system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115269652B (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114092027A (en) * | 2021-10-13 | 2022-02-25 | 中国电力科学研究院有限公司 | Carbon flow master station management system, management method and demand side carbon management system |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2653606A1 (en) * | 2006-06-29 | 2008-01-03 | Edsa Micro Corporation | Automatic real-time optimization and intelligent control of electrical power distribution and transmission systems |
| CN103379608B (en) * | 2013-04-07 | 2017-06-09 | 东南大学 | Wireless sensor network multi-stage launch power distribution method |
| CN105743126A (en) * | 2016-04-14 | 2016-07-06 | 华南理工大学 | Microgrid energy management system capable of realizing load management |
| GB2577853B (en) * | 2018-06-22 | 2021-03-24 | Moixa Energy Holdings Ltd | Systems for machine learning, optimising and managing local multi-asset flexibility of distributed energy storage resources |
| CN109462231B (en) * | 2018-11-15 | 2020-09-01 | 合肥工业大学 | Load optimization scheduling method, system and storage medium for residential micro-grid |
| CN113592134B (en) * | 2021-06-15 | 2023-09-26 | 国网浙江省电力有限公司 | Electric power carbon emission evaluation system and method based on energy data |
| CN114707776B (en) * | 2022-06-08 | 2022-09-02 | 山东暖谷新能源环保科技有限公司 | Carbon emission double control-based low-carbon energy consumption optimization system and method |
-
2022
- 2022-07-28 CN CN202210899692.2A patent/CN115269652B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114092027A (en) * | 2021-10-13 | 2022-02-25 | 中国电力科学研究院有限公司 | Carbon flow master station management system, management method and demand side carbon management system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115269652A (en) | 2022-11-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106655522B (en) | A kind of main station system suitable for electric grid secondary equipment operation management | |
| CN108562854B (en) | A kind of motor abnormal condition on-line early warning method | |
| CN105069695B (en) | A kind of real-time risk analysis system of intelligent substation and analysis method | |
| CN103475059B (en) | Multiple-channel output cooperation control electric automobile integrated charger supervisory control system and method | |
| CN111934332A (en) | Energy storage power station system based on cloud edge cooperation | |
| CN110866616A (en) | Fault early warning method and device for secondary equipment of transformer substation | |
| CN117477794B (en) | Power distribution station power consumption management optimization system and method based on gateway machine data exchange | |
| CN115685050B (en) | Electric energy meter fault detection method and system | |
| CN103199628A (en) | Real-time power equipment monitoring system based on OSGA (Open Grid Service Architecture) grid technology | |
| CN117318614A (en) | Photovoltaic inverter fault prediction method | |
| CN116846085A (en) | Self-sensing monitoring intelligent distribution box control system | |
| CN117394346A (en) | Operation control method of virtual power plant | |
| CN115269652B (en) | Dual-carbon electric power balance optimization system and method | |
| CN115800552A (en) | Intelligent regulation and control system and method for super capacitor operation power frequency modulation | |
| CN106325258B (en) | Relay protection device state evaluation method based on online monitoring information | |
| CN110855001A (en) | Distribution automation and power grid optimization management operation system | |
| CN117336137B (en) | Internet of things data processing method and system based on intelligent edge gateway | |
| CN117335570B (en) | Visual monitoring system and method for panoramic information of elastic power distribution network | |
| CN117544872A (en) | Efficient electric power data acquisition and transmission system | |
| CN116317138B (en) | Circuit breaker control system | |
| CN118199257A (en) | Parallel power supply operation monitoring control management system | |
| CN117955171A (en) | Real-time optimal scheduling system for micro-grid | |
| CN116032011A (en) | Distributed photovoltaic monitoring control system | |
| CN211880401U (en) | Centralized monitoring and early warning equipment based on optical fiber network maintenance | |
| CN112415343A (en) | Intelligent assembly of multi-state-quantity configurable totally-enclosed gas combined electrical appliance |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |