CN116094032A - High-permeability photovoltaic access power distribution network Yun Bianduan cooperative energy self-balancing method - Google Patents
High-permeability photovoltaic access power distribution network Yun Bianduan cooperative energy self-balancing method Download PDFInfo
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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
- H02J3/381—Dispersed generators
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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
- H02J13/00022—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 using wireless data transmission
- H02J13/00026—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 using wireless data transmission involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
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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
- H02J3/26—Arrangements for eliminating or reducing asymmetry in polyphase networks
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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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- 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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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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
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
- H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
- H02J2310/58—The condition being electrical
- H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
Abstract
The invention discloses a high-permeability photovoltaic accessed power distribution network Yun Bianduan collaborative energy self-balancing method in the technical field of power electronic control, which comprises the following steps: collecting a platform load historical operation curve, photovoltaic data and meteorological information of the platform; carrying out power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information; uploading the power prediction result to a power distribution cloud master station; receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling, and issuing the operation scheduling instruction to comprehensive adjusting equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction. According to the invention, through the energy optimization management of the power distribution network under the high-permeability photovoltaic access, the photovoltaic is absorbed in situ, the advantages of coordinated scheduling of the cloud edge end are fully exerted, the multi-level scheduling capability is realized, the global optimization and the local autonomy are considered, and the problems of power balance and voltage quality caused by the high-permeability photovoltaic access are solved.
Description
Technical Field
The invention relates to a high-permeability photovoltaic accessed power distribution network Yun Bianduan cooperative energy self-balancing method, and belongs to the technical field of power electronic control.
Background
With the high-permeability photovoltaic access to the power distribution network, the problems of insufficient absorption capacity, voltage lifting and the like of the photovoltaic absorption in the power distribution network area are caused, and the popularization and application of the distributed photovoltaic are severely restricted. Distributed photovoltaics present a significant challenge to the coordinated control of distributed photovoltaics due to the small monomer capacity and the large number of access points. In addition, there are differences in communication and control of different types of photovoltaic inverters, making it objectively impractical for a single photovoltaic inverter.
There are two general cases of energy optimization management of existing distributed photovoltaic access distribution networks. One is an unsupervised mode, where only marketing data is collected for electricity bill settlement. In the mode, when the distributed photovoltaic capacity is small enough to cause the problems of digestion and voltage, operation scheduling can not be performed. One is centralized control, and communication with each photovoltaic inverter is sought to be established in a cloud mode, so that accurate control of each photovoltaic inverter is achieved. The data volume required by the mode is huge, and the mode is in communication with each photovoltaic inverter, so that the operability is particularly insufficient in practice, and the mode is difficult to popularize and apply.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a power distribution network Yun Bianduan collaborative energy self-balancing method with high-permeability photovoltaic access, which can effectively consider the superiority of a cloud end architecture, fully exert the regulating capability of comprehensive regulating equipment, and maximize the photovoltaic on-site digestion capability on the premise of reducing equipment investment under the condition of limited communication requirements.
In order to achieve the above purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the present invention provides a method for self-balancing energy in cooperation with a power distribution network Yun Bianduan accessed by high-permeability photovoltaic, which is executed by a platform area fusion terminal, and includes:
collecting a platform load historical operation curve, photovoltaic data and meteorological information of the platform;
carrying out power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
uploading the power prediction result to a power distribution cloud master station;
receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling, and issuing the operation scheduling instruction to comprehensive adjusting equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
Further, the optimal scheduling information is obtained by the power distribution cloud master station performing optimal power flow optimization according to the operation information and the line topology information of each station area and then solving an optimal power flow model according to an optimization target and operation constraint, wherein: optimization objectives include economy, photovoltaic in-situ consumption and line losses; the operation constraint comprises node voltage constraint, line power constraint, platform region load factor constraint, line radial constraint, energy storage charge and discharge power constraint and platform region interaction power operation interval.
Further, the power distribution cloud master station performs energy optimization management of different time scales by adopting a mode of combining day-ahead optimization scheduling and day-in rolling optimization scheduling, wherein: the scheduling instruction used for determining slow-acting equipment of the power distribution network in day-ahead optimal scheduling comprises a gear for on-load voltage regulation and a power distribution network switch state; the daily rolling optimization is used for determining the charging and discharging power of the energy storage and the interaction power of the platform area.
Furthermore, the platform fusion terminal communicates with the intelligent ammeter and the comprehensive line terminal regulating equipment in a wireless 4G, 5G or HPLC mode.
Further, the operation scheduling instruction includes an operation optimization target and an operation optimization constraint, wherein: the operation optimization targets include: the electricity purchasing cost from the main network is minimum, the photovoltaic in-situ absorption rate is maximum and the three-phase unbalance degree is minimum; the operation optimization constraint comprises line voltage constraint, line bearing capacity constraint, transformer capacity constraint, comprehensive regulation equipment regulation capacity constraint, energy storage charge and discharge constraint, line power flow constraint and power balance constraint.
Furthermore, the comprehensive regulating equipment is provided with a standardized interface comprising a direct current quick-plug interface, and the flexible interconnection of the two low-voltage lines is achieved through the interconnection and intercommunication of the direct current interface and the comprehensive regulating equipment on the adjacent lines, so that the power and the voltage are regulated; the comprehensive regulating equipment is communicated with the photovoltaic inverter in the area in a LoRa wireless mode, and distributed photovoltaic is subjected to cluster control.
Furthermore, the comprehensive regulating equipment integrates three regulating equipment including an AC/DC energy storage conversion module, an intelligent reactor and an intelligent capacitor, and can flexibly select and match according to the voltage regulation requirement of a low-voltage distribution line, so that four regulating means including three-phase unbalance management, active control, reactive control and photovoltaic power limiting/photovoltaic cutting are realized.
In a second aspect, the present invention provides a high-permeability photovoltaic-accessed power distribution network Yun Bianduan collaborative energy self-balancing system, comprising:
and a data receiving module: the platform load historical operation curve, photovoltaic data and meteorological information are collected;
and a power prediction module: the power prediction method comprises the steps of performing power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
and a data uploading module: the power prediction method comprises the steps of uploading a power prediction result to a power distribution cloud master station;
an operation scheduling instruction receiving module: the power distribution cloud management system is used for receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling and issuing the operation scheduling instruction to comprehensive adjustment equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
In a third aspect, the invention provides a high-permeability photovoltaic-accessed power distribution network Yun Bianduan collaborative energy self-balancing device, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is operative according to the instructions to perform the steps of the method according to any one of the preceding claims.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of any of the methods described above.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a cloud edge end cooperative energy self-balancing method for a power distribution network station area with high-permeability photovoltaic access, which can effectively exert the advantages of cloud edge end cooperative, not only can give consideration to overall dispatching optimization of a power distribution network, but also can fully exert the autonomous dispatching capability of each station area, and well meet the optimized dispatching control requirement of the high-permeability photovoltaic access. The method has the following two obvious advantages compared with the existing scheduling method:
1) Compared with the existing cloud-edge end architecture, the existing cloud-edge end architecture has the advantages that end-side equipment is a photovoltaic inverter, and in practice, the photovoltaic inverter is different in model number and control mode, and is difficult to implement. The cloud edge end framework provided by the invention aims at distribution network areas, can well solve the photovoltaic digestion problem of each area, is a primary part of comprehensive adjusting equipment and a controllable photovoltaic inverter, and has good controllability and flexible operation.
2) The invention fully plays the regulating capability and flexible operation mode of the comprehensive regulating equipment, does not need to communicate with each photovoltaic inverter, has strong actual operability, and can well meet the optimal scheduling requirement of high-permeability photovoltaic access only through the comprehensive regulating equipment at the tail end.
Drawings
Fig. 1 is a schematic diagram of a cloud edge end cooperative energy self-balancing method in a power distribution network station area of high-permeability photovoltaic access according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
Embodiment one:
the embodiment provides a high-permeability photovoltaic access power distribution network Yun Bianduan collaborative energy self-balancing method, which is realized by adopting the following technical scheme:
the photovoltaic problem that causes of reply hypertonic light transmission photovoltaic access distribution network platform district is absorbed, and cloud limit end specifically includes as follows:
1) The distribution cloud master station serves as a 'cloud': the power distribution cloud master station is responsible for operation optimization scheduling of the whole power distribution network, performs overall energy optimization scheduling of the power distribution network according to historical operation information, measurement information of each station area, load and photovoltaic prediction information, line topology information and other data, and issues optimization scheduling instructions to station area fusion terminals of each side.
2) The platform area fusion terminal is used as an edge: the platform area fusion terminal is arranged at the distribution transformer, can collect various loads and photovoltaic data of the platform area, and communicates with comprehensive regulating equipment at the tail end of a line. And the platform region fusion terminal performs energy optimization scheduling of the platform region according to scheduling information issued by the cloud master station, by combining load and photovoltaic prediction information of the platform region fusion terminal and control capability of the comprehensive adjustment equipment, and issues the generated scheduling instruction to the comprehensive adjustment equipment.
3) The integrated regulating device acts as an "edge": the device integrates an AC/DC energy storage conversion module, an intelligent reactor and an intelligent capacitor, so that three-phase imbalance management, active control, reactive control and photovoltaic power limiting/photovoltaic cutting control are performed through comprehensive regulating equipment. And can communicate with photovoltaic inverter in a certain range, thus can control photovoltaic inverter and controllable energy storage of "end" apparatus, track the instruction issued.
The power distribution cloud master station energy optimization scheduling method has the following characteristics:
the power distribution cloud master station is responsible for energy optimization management of the whole power distribution network, and a fusion terminal of each power distribution station needs to upload a load and photovoltaic real-time running curve and a prediction curve of the station and an interval of interaction power of the station and a power grid. And the cloud master station optimizes the optimal power flow according to the operation information and the line topology information of each station area, and determines the operation scheduling information of each station area. Goals for power flow optimization may include goals of economy, photovoltaic in-situ rates, line losses, etc. The constraint of the tide optimization comprises node voltage constraint, line power constraint, platform region load factor constraint, line radial constraint, energy storage charge and discharge power constraint and platform region interactive power operation interval. And solving the optimal power flow model according to the optimization target and the operation constraint to obtain an operation optimization result of the whole power distribution network. According to the requirements, the cloud master station can perform energy optimization management of different time scales in a mode of combining daily optimization scheduling and daily rolling optimization scheduling. In day-ahead optimal scheduling, mainly determining scheduling instructions of slow-acting equipment of a power distribution network, wherein the scheduling instructions comprise on-load voltage-regulating gears and power distribution network switch states. The daily rolling optimization mainly determines the charging and discharging power of energy storage and the platform area interaction power.
The method for optimizing and scheduling the platform zone fusion terminal is characterized in that:
the power distribution network area fusion terminal is arranged at the position of the power distribution transformer and can communicate with the intelligent ammeter and the line terminal comprehensive regulation equipment in a wireless 4G, 5G or HPLC mode. The platform region fusion terminal is responsible for collecting platform region power supply and utilization information and optimizing and managing energy, sending the power supply and utilization information to the cloud, and deciding a region for exchanging power with the power grid.
The platform region fusion terminal can predict the power of the load and the photovoltaic according to the platform region load historical operation curve and the photovoltaic historical power generation curve and by combining with meteorological information, and send the prediction result to the cloud, so that the cloud operation calculation burden is reduced.
On the basis of load and photovoltaic prediction, the platform area fusion terminal performs local energy optimization scheduling by combining with an operation scheduling instruction issued by a cloud. The operational optimization objectives may include: the method has the advantages of minimum electricity purchasing cost from a main network, maximum photovoltaic in-situ absorption rate, minimum three-phase unbalance degree and the like. Constraints for the run optimization include: line voltage constraint, line bearing capacity constraint, transformer capacity constraint, comprehensive regulation equipment regulation capacity constraint, energy storage charge and discharge constraint, line power flow constraint, power balance constraint and the like.
The comprehensive adjusting device has the following characteristics:
the comprehensive regulating device can integrate three kinds of devices with regulation, namely an AC/DC energy storage conversion module, an intelligent reactor and an intelligent capacitor, can flexibly select and match according to the voltage regulation requirement of a low-voltage distribution line, and the capacity of each device can be optimally configured according to the requirement. The AC/DC energy storage conversion module needs to be configured, and the intelligent reactor suggests configuration in terminal voltage lifting treatment, so that investment cost and voltage management capability can be considered. The intelligent capacitor can be used for solving the problem of low voltage caused by overload.
The comprehensive regulating equipment is provided with standardized interfaces such as a direct current fast plug interface and the like, so that plug and play of distributed energy storage can be realized. Meanwhile, through the direct current interface, the interconnection and the intercommunication of the comprehensive regulating equipment on the adjacent lines can be realized, the flexible interconnection of the two low-voltage lines is achieved, and the power and the voltage are regulated.
The comprehensive regulating equipment is communicated with the photovoltaic inverter in the area in a LoRa wireless mode, so that distributed photovoltaic is subjected to cluster control, and under the necessary condition, the problem of overvoltage can be reduced through photovoltaic limiting power or photovoltaic cutting, and the safe operation of a low-voltage circuit is ensured.
The comprehensive regulation equipment control of the control 'end' side has the following characteristics:
the voltage comprehensive regulation equipment arranged at the tail end of the line can be communicated with the platform area fusion terminal, and the measurement information and the regulation capability of the tail end of the line provide data support for the decision-making of the platform area fusion terminal. The voltage comprehensive regulation equipment receives an operation control instruction of the platform area fusion terminal and combines local load and photovoltaic information to regulate voltage and power. The comprehensive adjusting device has four adjusting means:
1) Three-phase unbalance management: the AC/DC energy storage conversion module is utilized to carry out three-phase unbalance management on the low-voltage line, single-phase overvoltage caused by overlarge single-phase photovoltaic reverse power is reduced, and mutual balance and consumption of the photovoltaic phases are promoted;
2) Active control: based on the direct current port of the comprehensive regulating equipment, flexible interconnection with a similar low-voltage circuit can be realized, and mutual economy and consumption of the interconnection circuit are realized through flow control of the interconnection circuit; in addition, the comprehensive regulating equipment can be connected with the distributed energy storage device, so that peak clipping and valley filling are realized by utilizing the charge and discharge of energy storage, photovoltaic absorption is promoted, the photovoltaic reverse power is reduced, and voltage control is realized;
3) Reactive power control: the comprehensive regulating equipment is provided with the AC/DC energy storage conversion module, the intelligent reactor and the intelligent capacitor, so that the rapid reactive power control can be performed, including the absorption and the reactive power generation, thereby flexibly controlling the terminal voltage;
4) Photovoltaic limited power/cut photovoltaic: the comprehensive regulating equipment is communicated with the photovoltaic inverter in the area in a LoRa wireless mode, so that distributed photovoltaic is subjected to cluster control, and under the necessary condition, the problem of overvoltage can be reduced through photovoltaic limiting power or photovoltaic cutting, and the safe operation of a low-voltage circuit is ensured.
Embodiment two:
the utility model provides a high permeability photovoltaic access's distribution network Yun Bianduan cooperatees energy self-balancing system, can realize the high permeability photovoltaic access's distribution network Yun Bianduan cooperatees energy self-balancing method, include:
and a data receiving module: the platform load historical operation curve, photovoltaic data and meteorological information are collected;
and a power prediction module: the power prediction method comprises the steps of performing power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
and a data uploading module: the power prediction method comprises the steps of uploading a power prediction result to a power distribution cloud master station;
an operation scheduling instruction receiving module: the power distribution cloud management system is used for receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling and issuing the operation scheduling instruction to comprehensive adjustment equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
Embodiment III:
the embodiment of the invention also provides a high-permeability photovoltaic accessed power distribution network Yun Bianduan cooperative energy self-balancing device, which can realize the high-permeability photovoltaic accessed power distribution network Yun Bianduan cooperative energy self-balancing method described in the embodiment I, and comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the method of:
collecting a platform load historical operation curve, photovoltaic data and meteorological information of the platform;
carrying out power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
uploading the power prediction result to a power distribution cloud master station;
receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling, and issuing the operation scheduling instruction to comprehensive adjusting equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
Embodiment four:
the embodiment of the present invention also provides a computer readable storage medium, which can implement the method for self-balancing energy of the power distribution network Yun Bianduan with high-permeability photovoltaic access according to the embodiment, wherein a computer program is stored on the computer readable storage medium, and the program when executed by a processor implements the steps of the method as follows:
collecting a platform load historical operation curve, photovoltaic data and meteorological information of the platform;
carrying out power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
uploading the power prediction result to a power distribution cloud master station;
receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling, and issuing the operation scheduling instruction to comprehensive adjusting equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. The power distribution network Yun Bianduan collaborative energy self-balancing method for high-permeability photovoltaic access is characterized by comprising the following steps of:
collecting a platform load historical operation curve, photovoltaic data and meteorological information of the platform;
carrying out power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
uploading the power prediction result to a power distribution cloud master station;
receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling, and issuing the operation scheduling instruction to comprehensive adjusting equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
2. The method for self-balancing the cooperative energy of the power distribution network Yun Bianduan with the high-permeability photovoltaic access according to claim 1, wherein the optimal scheduling information is obtained by a power distribution cloud master station performing optimal power flow optimization according to operation information of each station area and line topology information and then solving an optimal power flow model according to an optimization target and operation constraint, wherein: optimization objectives include economy, photovoltaic in-situ consumption and line losses; the operation constraint comprises node voltage constraint, line power constraint, platform region load factor constraint, line radial constraint, energy storage charge and discharge power constraint and platform region interaction power operation interval.
3. The method for self-balancing energy of the power distribution network Yun Bianduan with high-permeability photovoltaic access according to claim 1, wherein the power distribution cloud master station performs energy optimization management of different time scales by adopting a mode of combining daily optimization scheduling and daily rolling optimization scheduling, wherein: the scheduling instruction used for determining slow-acting equipment of the power distribution network in day-ahead optimal scheduling comprises a gear for on-load voltage regulation and a power distribution network switch state; the daily rolling optimization is used for determining the charging and discharging power of the energy storage and the interaction power of the platform area.
4. The method for self-balancing the energy of the power distribution network Yun Bianduan with the high-permeability photovoltaic access according to claim 1, wherein the platform area fusion terminal communicates with the intelligent ammeter and the line terminal comprehensive regulation equipment in a wireless 4G, 5G or HPLC mode.
5. The high-permeability photovoltaic-accessed power distribution network Yun Bianduan collaborative energy self-balancing method of claim 1, wherein the operational scheduling instructions include operational optimization objectives and operational optimization constraints, wherein: the operation optimization targets include: the electricity purchasing cost from the main network is minimum, the photovoltaic in-situ absorption rate is maximum and the three-phase unbalance degree is minimum; the operation optimization constraint comprises line voltage constraint, line bearing capacity constraint, transformer capacity constraint, comprehensive regulation equipment regulation capacity constraint, energy storage charge and discharge constraint, line power flow constraint and power balance constraint.
6. The method for self-balancing the cooperative energy of the power distribution network Yun Bianduan accessed by high-permeability photovoltaic according to claim 1, wherein the comprehensive regulating equipment is provided with a standardized interface comprising a direct-current quick-plug interface, and the flexible interconnection of two low-voltage lines is achieved through the interconnection and the intercommunication of the direct-current interface and the comprehensive regulating equipment on adjacent lines, so that the regulation of power and voltage is performed; the comprehensive regulating equipment is communicated with the photovoltaic inverter in the area in a LoRa wireless mode, and distributed photovoltaic is subjected to cluster control.
7. The method for self-balancing the energy of the power distribution network Yun Bianduan with the high-permeability photovoltaic access, which is disclosed in claim 1, is characterized in that the comprehensive regulating equipment integrates three regulating devices including an AC/DC energy storage conversion module, an intelligent reactor and an intelligent capacitor, and can flexibly select and match according to the voltage regulating requirement of a low-voltage distribution line, thereby realizing four regulating means of three-phase imbalance management, active control, reactive control and photovoltaic power limiting/photovoltaic cutting.
8. A high permeability photovoltaic accessed power distribution network Yun Bianduan synergistic energy self-balancing system, comprising:
and a data receiving module: the platform load historical operation curve, photovoltaic data and meteorological information are collected;
and a power prediction module: the power prediction method comprises the steps of performing power prediction based on a platform load historical operation curve of the platform, photovoltaic data and weather information;
and a data uploading module: the power prediction method comprises the steps of uploading a power prediction result to a power distribution cloud master station;
an operation scheduling instruction receiving module: the power distribution cloud management system is used for receiving an operation scheduling instruction issued by a power distribution cloud master station to perform local energy optimization scheduling and issuing the operation scheduling instruction to comprehensive adjustment equipment; the comprehensive regulating equipment controls and tracks the photovoltaic inverter and the controllable energy storage based on the scheduling instruction.
9. The utility model provides a high permeability photovoltaic access's distribution network Yun Bianduan cooperation energy self-balancing device which characterized in that includes treater and storage medium;
the storage medium is used for storing instructions;
the processor being operative according to the instructions to perform the steps of the method according to any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the program when executed by a processor realizes the steps of the method according to any of claims 1 to 7.
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