CN115224743A - Distribution network scheduling management method based on energy interconnection - Google Patents
Distribution network scheduling management method based on energy interconnection Download PDFInfo
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- CN115224743A CN115224743A CN202210541170.5A CN202210541170A CN115224743A CN 115224743 A CN115224743 A CN 115224743A CN 202210541170 A CN202210541170 A CN 202210541170A CN 115224743 A CN115224743 A CN 115224743A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00028—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment involving the use of Internet protocols
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention relates to a distribution network scheduling management method based on energy interconnection, which comprises a fusion terminal and a scheduling master station, wherein the fusion terminal is connected with the scheduling master station, and the method comprises the following steps: s1, acquiring real-time data, S2, analyzing the real-time data, S3, mining photovoltaic prediction data, S4, formulating an energy storage charging and discharging strategy and S5, uploading the energy storage charging and discharging strategy; the invention has the advantages that: by combining photovoltaic prediction data and user load data, an energy storage charging and discharging strategy is automatically formulated, so that charging time and peak discharging time in the low ebb of equipment are reasonably arranged, the load peak-valley difference of a transformer can be reduced by 35%, the electric energy quality is improved, when multiple energy storages are jointly regulated and controlled, point-line-surface multi-level self-balancing from a transformer area to a line to a transformer substation is achieved, the elasticity and stable operation capacity of a power distribution network are effectively improved, the operation working condition of active equipment is effectively judged, a source end operation mode and strategy are finally formulated by a regulation and control master station, and the utilization rate of renewable energy is improved.
Description
Technical Field
The invention relates to a distribution network scheduling management method based on energy interconnection.
Background
Currently, there are two modes of transition in the development of the power industry: the first is the combination of concentrated power generation and distributed power generation; secondly, participate in jointly by supplier owner direction supplier and user and combine together, because the electric energy has real-time balance characteristic, supply side and demand side should be balanced in real time promptly, and large-scale new forms of energy and distributed power supply are incorporated into the power networks and can influence the trend of electric wire netting, voltage, system stability and electric energy quality, consequently, along with electric wire netting dynamic characteristic complexity constantly increases, to joining in marriage net regulation and control reliability requirement higher and higher, compare major network spatial grid structure, the distribution network development lags behind relatively weak, the state perception and the risk assessment of current regulation and control management mode are difficult to satisfy the demand, the problem exists: data are difficult to be interconnected and communicated, information is difficult to be subjected to panoramic detection, a distribution network is difficult to be subjected to collaborative management and control, and the operation and maintenance efficiency is low.
Disclosure of Invention
The invention aims to provide a distribution network scheduling management method based on energy interconnection, which can realize point-line-plane multilevel self-balance from a transformer area to a line to a transformer substation and effectively improve the elasticity and stable operation capability of a distribution network.
In order to solve the technical problems, the invention is realized by the following technical scheme: a distribution network scheduling management method based on energy interconnection is suitable for an energy scheduling platform, the energy scheduling platform comprises a fusion terminal and a scheduling master station, the fusion terminal comprises a spatial database engine and a relational database management system, and the fusion terminal is connected with the scheduling master station and comprises the following steps:
s1: the method comprises the steps of obtaining environment data, energy storage equipment state data and real-time data of the running state of electric equipment, and gathering the environment data, the energy storage equipment state data and the real-time data in a relational database management system through a spatial database engine;
s2: the fusion terminal analyzes the energy storage equipment state data and the real-time data of the electric equipment operation state acquired by the S1, and evaluates the output prediction of the power generation equipment and the operation state of the electric equipment;
s3: taking the output prediction of the power generation equipment evaluated in the step S2 and the environmental data obtained in the step S1 as training samples, constructing a short-time photovoltaic output prediction model based on a random forest algorithm, and finishing mining of photovoltaic prediction data;
s4: according to photovoltaic prediction data mined in the S3, combining with a user load monitoring value and taking a platform area as a basic unit, formulating an energy storage charging and discharging strategy, when the load change reaches an energy storage set threshold, automatically switching a charging and discharging mode, and when self-balancing cannot be realized in the platform area, performing cluster regulation and control on multiple energy storage devices in the area by taking an upper-level line and even a transformer substation as units;
s5: and transmitting the energy storage charging and discharging strategy formulated by the S4 to the scheduling master station.
Preferably, the environmental data, the energy storage device state data and the electric device running state real-time data in the step S1 are acquired through an acquisition device, the acquisition device comprises a first acquisition component for acquiring the electric device running state real-time data, a first sensor group for acquiring the environmental data, a second sensor group for acquiring the energy storage device state data, and a gateway for receiving the environmental data, the energy storage device state data and the electric device running state real-time data, the first acquisition component, the first sensor group and the second sensor group are all connected with the gateway, and the gateway is connected with the fusion terminal.
Preferably, first collection subassembly includes voltage transformer, current transformer and frequency monitor, first sensor group includes temperature sensor, humidity transducer and sunshine intensity sensor, second sensor group includes hydrogen sensor and carbon monoxide sensor.
Preferably, the gateway is connected with the convergence terminal through a 4G network or/and a 5G network.
Preferably, the output prediction of the power generation equipment in the step S2 is evaluated through a random forest algorithm, and the running state of the power utilization equipment is evaluated through an error back propagation artificial neural network and a principal component analysis method.
Preferably, a network security access area is arranged between the convergence terminal and the scheduling master station.
Preferably, the network security access area comprises a longitudinal encryption device, a front gateway machine, a forward isolation device and a boundary gateway machine which are connected in sequence, the longitudinal encryption device is connected with the dispatching master station, and the boundary gateway machine is connected with the convergence terminal.
Preferably, the data in the fusion terminal is read by the boundary gateway machine through a DISA protocol or an IEC101 protocol, and the data read by the boundary gateway machine is transmitted to the scheduling master station through E text format data.
In conclusion, the invention has the advantages that: by the distribution network scheduling management method comprising the steps of S1, S2, S3, mining of real-time data, S4, formulating an energy storage charging and discharging strategy and S5, uploading the energy storage charging and discharging strategy, because the step S1 is to assemble the environment data, the energy storage device state data and the real-time data of the running state of the electric equipment in a relational database management system through a spatial database engine, the spatial database engine can assemble the real-time data in the relational database management system and send the real-time data to a scheduling master station through the relational database management system, the collection and storage of diversified data are realized, the unified management and data safety check can be realized, the safe transmission of the data is ensured, the statistical data, the meteorological data, the energy-saving and emission-reducing data, the equipment communication state and the station running state are collected, a power real-time trend graph is drawn, and the equipment running parameters are analyzed, drawing a daily load curve and detecting the running health state of equipment, then completing mining of photovoltaic prediction data through a short-time photovoltaic output prediction model based on a random forest algorithm, effectively improving the power generation plan in the jurisdiction and the reasonability of electric equipment maintenance, so that the photovoltaic power data in multiple time, space and regions can be inquired, the photovoltaic power data can be used as a powerful basic support for energy aggregation regulation and control, and regulation and control management of field energy storage equipment are realized. Therefore, charging time and peak discharging time of the equipment during the low ebb are reasonably arranged, the load peak valley difference of the transformer can be reduced by 35%, the electric energy quality is improved, when multiple energy storage units are jointly regulated and controlled, the 10kV line peak valley difference rate can be reduced by 30%, meanwhile, the load rate of the line is reduced by 10%, red early warning of the line is relieved, the capacity-load ratio of a 110kV transformer substation in the area can be increased to 1.37 from 1.21, the red early warning state of the transformer substation is relieved, point-line-plane multi-level self balance from the transformer area to the line to the transformer substation is achieved, the elasticity and stable operation capacity of the power distribution network are effectively improved, the operation working condition of the active equipment is effectively judged, the source end operation mode and strategy are finally formulated by the regulation and control master station, the utilization rate of renewable energy resources is improved, finally, the dispatching master station can realize multi-element data of the energy storage equipment, and historical charging and discharging data and peak-clipping and valley-filling electric quantity of each energy storage equipment can be checked.
Drawings
The invention is further described below with reference to the accompanying drawings:
fig. 1 is a block diagram of a scheduling platform according to the present invention.
Detailed Description
A distribution network scheduling management method based on energy interconnection is suitable for an energy scheduling platform, as shown in figure 1, the energy scheduling platform comprises a fusion terminal 1 and a scheduling master station 2, the fusion terminal comprises a spatial database engine and a relational database management system, and the fusion terminal is connected with the scheduling master station and comprises the following steps:
s1: the method comprises the steps of obtaining environmental data, energy storage equipment state data and real-time data of the running state of electric equipment, and gathering the environmental data, the energy storage equipment state data and the real-time data in a relational database management system through a spatial database engine;
s2: the fusion terminal analyzes the energy storage equipment state data and the real-time data of the electric equipment operation state acquired by the S1, and evaluates the output prediction of the power generation equipment and the operation state of the electric equipment;
s3: taking the output prediction of the power generation equipment evaluated in the step S2 and the environmental data obtained in the step S1 as training samples, constructing a short-time photovoltaic output prediction model based on a random forest algorithm, and finishing mining of photovoltaic prediction data;
s4: according to the photovoltaic prediction data mined in the S3, combining with a user load monitoring value, and taking a platform area as a basic unit, formulating an energy storage charging and discharging strategy, when the load change reaches an energy storage set threshold, automatically switching a charging and discharging mode, and when self-balancing cannot be realized in the platform area, performing cluster regulation and control on a plurality of energy storage devices in the area by taking the upper-level line and even the transformer substation as units;
s5: and transmitting the energy storage charging and discharging strategy formulated by the S4 to the scheduling master station.
By the distribution network scheduling management method comprising the steps of S1 obtaining real-time data, S2 analyzing the real-time data, S3 mining the photovoltaic prediction data, S4 formulating the energy storage charging and discharging strategy and S5 uploading the energy storage charging and discharging strategy, because the step S1 converges the environmental data, the energy storage device state data and the real-time data of the operating state of the electric equipment in the relational database management system through the spatial database engine, the spatial database engine can converge the real-time data in the relational database management system and send the real-time data to the scheduling master station through the relational database management system, the collection and storage of diversified data are realized, the unified management and the data safety check can be realized, the safe transmission of the data is ensured, the statistical data, the meteorological data, the energy conservation and emission reduction data, the device communication state and the station operating state are collected, the power real-time trend graph is drawn, and the device operating parameters are analyzed, drawing a daily load curve and detecting the running health state of equipment, then completing mining of photovoltaic prediction data through a short-time photovoltaic output prediction model based on a random forest algorithm, effectively improving the power generation plan in the jurisdiction and the reasonability of electric equipment maintenance, so that the photovoltaic power data in multiple time, space and regions can be inquired, the photovoltaic power data can be used as a powerful basic support for energy aggregation regulation and control, and regulation and control management of field energy storage equipment are realized. Therefore, charging time and peak discharging time of the equipment during the low ebb are reasonably arranged, the load peak valley difference of the transformer can be reduced by 35%, the electric energy quality is improved, when multiple energy storage units are jointly regulated and controlled, the 10kV line peak valley difference rate can be reduced by 30%, meanwhile, the load rate of the line is reduced by 10%, red early warning of the line is relieved, the capacity-load ratio of a 110kV transformer substation in the area can be increased to 1.37 from 1.21, the red early warning state of the transformer substation is relieved, point-line-plane multi-level self balance from the transformer area to the line to the transformer substation is achieved, the elasticity and stable operation capacity of the power distribution network are effectively improved, the operation working condition of the active equipment is effectively judged, the source end operation mode and strategy are finally formulated by the regulation and control master station, the utilization rate of renewable energy resources is improved, finally, the dispatching master station can realize multi-element data of the energy storage equipment, and historical charging and discharging data and peak-clipping and valley-filling electric quantity of each energy storage equipment can be checked.
The environmental data, the energy storage device state data and the real-time data of the electric equipment operation state in the step S1 are acquired through an acquisition device 3, the acquisition device 3 comprises a first acquisition component 31 for acquiring the real-time data of the electric equipment operation state, a first sensor group 32 for acquiring the environmental data, a second sensor group 33 for acquiring the energy storage device state data, and a gateway 34 for receiving the environmental data, the energy storage device state data and the real-time data of the electric equipment operation state, the first acquisition component 31, the first sensor group 32 and the second sensor group 33 are all connected with the gateway 34, the gateway 34 is connected with the fusion terminal 1, the independent acquisition of the environmental data, the energy storage device state data and the real-time data of the electric equipment operation state can be realized, the three groups of data do not interfere with each other, and the data acquisition quality is improved, secondly, the gateway can receive the acquired data, the data can be safely transmitted to the fusion terminal, the first acquisition component comprises a voltage transformer, a current transformer and a frequency monitor, the first sensor group comprises a temperature sensor, a humidity sensor and a sunshine intensity sensor, the second sensor group comprises a hydrogen sensor and a carbon monoxide sensor, the voltage, the current and the frequency of the electric equipment can be effectively acquired, the temperature, the humidity and the sunshine intensity can be acquired in real time through the temperature sensor, the humidity sensor and the sunshine intensity sensor, the environmental data can be accurately acquired, the hydrogen sensor and the carbon monoxide sensor can effectively monitor the combustible gas of the energy storage equipment, so that the state of the energy storage equipment can be prepared, the gateway is connected with the fusion terminal through a 4G network or/and a 5G network, the method can ensure that the data in the gateway is accurately transmitted to the convergence terminal, and meets different application occasions.
The output prediction of the power generation equipment in the step S2 is evaluated through a random forest algorithm, the running state of the power utilization equipment is evaluated through an error back propagation artificial neural network and a principal component analysis method, the random forest algorithm does not need to extract features, the capability of processing the problem of sample loss is realized, and the model training speed is high; the artificial neural network carries out mode classification on the samples by mapping the samples to a high-dimensional space and correcting the weight threshold of the model through an error back propagation algorithm, so that the accuracy is high and the generalization capability of the model is strong; the principal component analysis reserves sample characteristics to the maximum extent, eliminates correlation (eliminates redundant information), reserves principal components and effectively reduces model training time.
The network security access area 4 is arranged between the fusion terminal and the scheduling master station, so that the secure transmission of data is realized, the network security access area 4 comprises a longitudinal encryption device, a front-end gateway machine, a forward isolation device and a boundary gateway machine which are sequentially connected, the longitudinal encryption device is connected with the scheduling master station, the boundary gateway machine is connected with the fusion terminal, the data in the fusion terminal can be transmitted to the boundary gateway machine firstly, then the read data is uploaded to the scheduling master station through the boundary gateway machine, the unified management and the data security check can be realized, so that the secure transmission of the data is ensured, the data in the fusion terminal is read through a DISA protocol or an IEC101 protocol by the boundary gateway machine, the data read by the boundary gateway machine is transmitted to the scheduling master station through E text format data, the unified management and the data security check can be realized, and the secure transmission of the data is ensured.
The above description is only an embodiment of the present invention, but the technical features of the present invention are not limited thereto, and any changes or modifications within the technical field of the present invention by those skilled in the art are covered by the claims of the present invention.
Claims (8)
1. A distribution network scheduling management method based on energy interconnection is suitable for an energy scheduling platform and is characterized in that: the energy scheduling platform comprises a fusion terminal and a scheduling master station, wherein the fusion terminal comprises a spatial database engine and a relational database management system, the fusion terminal is connected with the scheduling master station, and the energy scheduling platform comprises the following steps:
s1: the method comprises the steps of obtaining environment data, energy storage equipment state data and real-time data of the running state of electric equipment, and gathering the environment data, the energy storage equipment state data and the real-time data in a relational database management system through a spatial database engine;
s2: the fusion terminal analyzes the energy storage equipment state data acquired in the S1 and the real-time data of the operating state of the electric equipment, and evaluates the output prediction of the power generation equipment and the operating state of the electric equipment;
s3: taking the output prediction of the power generation equipment evaluated in the S2 and the environmental data obtained in the S1 as training samples, constructing a short-time photovoltaic output prediction model based on a random forest algorithm, and completing mining of photovoltaic prediction data;
s4: according to the photovoltaic prediction data mined in the S3, combining with a user load monitoring value, and taking a platform area as a basic unit, formulating an energy storage charging and discharging strategy, when the load change reaches an energy storage set threshold, automatically switching a charging and discharging mode, and when self-balancing cannot be realized in the platform area, performing cluster regulation and control on a plurality of energy storage devices in the area by taking the upper-level line and even the transformer substation as units;
s5: and transmitting the energy storage charging and discharging strategy formulated in the S4 to a scheduling master station.
2. The distribution network scheduling management method based on energy interconnection according to claim 1, wherein: the method comprises the following steps that environmental data, energy storage equipment state data and electric equipment running state real-time data in the S1 step are acquired through an acquisition device, the acquisition device comprises a first acquisition assembly used for acquiring the real-time data of the running state of the electric equipment, a first sensor group used for acquiring the environmental data, a second sensor group used for acquiring the state data of the energy storage equipment and a gateway used for receiving the real-time data of the environmental data, the state data of the energy storage equipment and the running state of the electric equipment, the first acquisition assembly, the first sensor group and the second sensor group are all connected with the gateway, and the gateway is connected with a fusion terminal.
3. The distribution network scheduling management method based on energy interconnection as claimed in claim 2, wherein: first collection subassembly includes voltage transformer, current transformer and frequency monitor, first sensor group includes temperature sensor, humidity transducer and sunshine intensity sensor, second sensor group includes hydrogen sensor and carbon monoxide sensor.
4. The distribution network scheduling management method based on energy interconnection according to claim 2, wherein: the gateway is connected with the convergence terminal through a 4G network or/and a 5G network.
5. The distribution network scheduling management method based on energy interconnection of claim 1, wherein: and S2, estimating the output prediction of the power generation equipment by a random forest algorithm, and estimating the running state of the electric equipment by an error back propagation artificial neural network and a principal component analysis method.
6. The distribution network scheduling management method based on energy interconnection of claim 1, wherein: and a network security access area is arranged between the convergence terminal and the scheduling master station.
7. The distribution network scheduling management method based on energy interconnection as claimed in claim 6, wherein: the network security access area comprises a longitudinal encryption device, a front-end gateway machine, a forward isolation device and a boundary gateway machine which are sequentially connected, wherein the longitudinal encryption device is connected with the dispatching master station, and the boundary gateway machine is connected with the fusion terminal.
8. The distribution network scheduling management method based on energy interconnection of claim 7, wherein: and the boundary gateway machine reads the data in the fusion terminal through a DISA protocol or an IEC101 protocol, and the data read by the boundary gateway machine is transmitted to the scheduling master station through E text format data.
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| CN116307287A (en) * | 2023-05-19 | 2023-06-23 | 国网信息通信产业集团有限公司 | Prediction method, system and prediction terminal for effective period of photovoltaic power generation |
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| CN116307287A (en) * | 2023-05-19 | 2023-06-23 | 国网信息通信产业集团有限公司 | Prediction method, system and prediction terminal for effective period of photovoltaic power generation |
| CN116307287B (en) * | 2023-05-19 | 2023-08-01 | 国网信息通信产业集团有限公司 | Prediction method, system and prediction terminal for effective period of photovoltaic power generation |
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