CN117439128A - Multi-element energy storage and new energy collaborative planning configuration method - Google Patents
Multi-element energy storage and new energy collaborative planning configuration method Download PDFInfo
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Abstract
The invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps: step 1: acquiring real-time output data of a new energy system, and simultaneously acquiring configuration information of diversified energy storage equipment; step 2: acquiring equipment information of a new energy system, and matching the real-time output data of the new energy system with configuration information of the diversified energy storage equipment to generate an output-energy storage equipment matching result; step 3: inputting the output-energy storage equipment matching result into a preset resource matching model to generate a resource allocation method of a new energy system and target equipment; step 4: and based on the resource allocation method, the parameters of the new energy system and the target equipment are cooperatively planned, so that the resource allocation between the new energy system and the target equipment is realized. Unnecessary energy loss of the new energy source in the process of storing energy is reduced, and the utilization rate of the new energy source is further improved.
Description
Technical Field
The invention relates to the technical field of new energy storage, in particular to a multi-element energy storage and new energy collaborative planning configuration method.
Background
Developing green economy and reducing the dependence on traditional energy is an important measure for realizing carbon neutralization in China. Therefore, the hanging rack encourages the development of new energy industry, changes the traditional economic structure, and changes the current energy mechanism by developing wind energy, light energy and water energy. To date, the accumulated loading of energy storage in China reaches 35.6GW and accounts for 18.6% of the total scale of the global market, the accumulated loading of electrochemical energy storage reaches 3.27GW from the aspect of an energy storage structure, and the lithium ion battery takes the absolute dominant position with the loading ratio of 88.8%, so that China has become the most important market of the global energy storage market.
The mainstream energy storage modes in the market at present comprise physical energy storage and electrochemical energy storage. The physical energy storage is taken as the most mature and commercialized energy storage mode, and mainly comprises pumped storage, compressed air storage and the like. Electrochemical energy storage is taken as an energy storage mode which is the most rapid in recent years, benefits from the rapid progress of energy storage technology, gradually reduces unit cost, has good commercial application conditions, and mainly comprises the following modes: lithium ion battery energy storage, lead storage battery energy storage and flow battery energy storage. However, the new energy storage system which is widely applied in the market at present is used for carrying out overall planning and planning on single energy, and the traditional operation mode causes the problems of complex management, low energy utilization rate and the like of the energy supply system.
Therefore, the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy.
Disclosure of Invention
The invention provides a multi-element energy storage and new energy collaborative planning configuration method, which is used for accurately selecting energy storage configuration matched with a new energy system, so that the efficiency of resource allocation between the new energy system and energy storage equipment is improved, unnecessary energy loss of the new energy in the energy storage process is reduced, and the utilization rate of the new energy is further improved.
The invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
step 1: acquiring real-time output data of a new energy system, and simultaneously acquiring configuration information of diversified energy storage equipment;
step 2: acquiring equipment information of a new energy system, and matching the real-time output data of the new energy system with configuration information of the diversified energy storage equipment to generate an output-energy storage equipment matching result;
step 3: inputting the output-energy storage equipment matching result into a preset resource matching model to generate a resource allocation method of a new energy system and target equipment;
step 4: and based on the resource allocation method, the parameters of the new energy system and the target equipment are cooperatively planned, so that the resource allocation between the new energy system and the target equipment is realized.
Preferably, in step 1, the method includes:
acquiring instantaneous output power and average output power of a new energy system, inputting the instantaneous output power and the average output power into a preset power curve generating function, and generating a real-time output power curve of the new energy system;
meanwhile, energy storage equipment information and energy storage configuration information of the diversified energy storage equipment are obtained, and networking is carried out on all the energy storage equipment based on the energy storage equipment information and the energy storage configuration information to form a diversified energy storage network.
Preferably, in step 2, it includes:
acquiring equipment information of a new energy system, distinguishing the power output type of the new energy system, and determining a first screening factor by combining a real-time output power curve graph of the new energy system;
meanwhile, acquiring equipment information and corresponding load conditions of all equipment in the diversified energy storage network, and determining a second screening factor;
and screening out equipment information matched with a new energy system in the diversified energy storage network according to a preset factor-equipment matching table based on the first screening factor and the second screening factor, and synchronously generating an output-energy storage equipment matching result.
Preferably, in step 3, it includes:
Performing content analysis on the output-energy storage device matching result to generate data analysis packages, extracting features of all the data analysis packages, and marking the extracted feature information in the corresponding data analysis packages respectively;
acquiring a data format of the preset resource matching model, and simultaneously, converting the format of all data analysis packets under the same output-energy storage equipment matching result;
inputting all the data analysis packages after format conversion into the pre-trained preset resource matching model, and matching a resource allocation method between a new energy system and target equipment in the preset resource matching model based on the characteristic information attached to each data analysis package.
Preferably, the resource allocation method between the new energy system and the target equipment comprises the following steps:
acquiring an upper limit value and a fluctuation range of output power of a new energy system, performing power matching with input power of target equipment, and generating a first matching factor based on a power matching result;
acquiring energy storage cost information and energy conversion rate of target equipment, and generating a second matching factor based on the energy storage cost information and the energy conversion rate;
And screening the target type of energy conversion in the preset resource matching model based on the first matching factor and the second matching factor, and acquiring a resource allocation method matched with the target type of energy conversion by combining the characteristic information in each data analysis packet.
Preferably, in step 4, the method includes:
analyzing the resource allocation method, acquiring equipment information of all related equipment involved in the resource allocation process under the resource allocation method, and simultaneously acquiring real-time operation parameter information of corresponding equipment and connection states among the equipment;
constructing a temporary equipment connection network based on the equipment information, the real-time operation parameter information of the corresponding equipment and the connection state among the equipment;
based on the temporary connection network of the equipment, carrying out parameter matching on the parameters of the input port and the output port among the equipment, and screening out corresponding parameter matching strategies in a parameter-strategy mapping table;
acquiring historical peak data and historical average data of input and output ports of each device, and calculating redundancy parameters of each device according to a preset redundancy formula based on the historical peak data and the historical average data;
Based on the parameter matching strategy and the redundant parameter of each device, simultaneously combining a preset strategy-redundant-instruction mapping table, acquiring a corresponding parameter adjustment instruction from an instruction database, and carrying out corresponding parameter adjustment on each device;
acquiring and analyzing and verifying the real-time operation parameters of the output and input ports of each device after adjustment, generating a parameter adjustment verification result, and judging the verification result meeting the preset first threshold condition as qualified;
inputting a qualified verification result into a preset resource scheduling model, and screening out a corresponding resource scheduling test operation instruction;
based on the resource scheduling test operation instruction, executing corresponding resource scheduling operation on each device, simultaneously acquiring scheduling parameter information and operation state of each device in a resource scheduling process, uploading the scheduling parameter information and operation state of each device to the temporary connection network, and generating a resource scheduling state table according to a preset parameter evaluation model;
comparing each parameter corresponding to each device in the resource scheduling test operation process with a preset ideal parameter based on the resource scheduling state table to generate a test operation evaluation table;
Comparing and analyzing the test run evaluation table with a preset run evaluation table, and judging a resource scheduling instruction corresponding to the test run evaluation table with a qualified analysis result as an instruction to be executed;
and based on the instruction to be executed, performing corresponding resource allocation operation on the new energy system and the target equipment.
Preferably, in step 4, further includes:
acquiring energy storage purposes and energy storage requirements of a new energy system, and screening out a first result meeting the energy storage purposes and the energy storage requirements based on a preset purpose-requirement-equipment adaptation table;
acquiring the running state information of the energy storage equipment corresponding to the first result, and inputting the running state information corresponding to the first result into a preset state information processing model to generate a first applicable equipment state table;
meanwhile, obtaining loss coefficients of the energy storage devices corresponding to the first result, and based on the loss coefficients corresponding to each result, arranging the corresponding energy storage devices in the first applicable device state table in a descending order to generate an applicable device loss ordering table;
establishing a mapping relation between the data of each energy storage device in the first applicable device state table and the applicable device loss sequencing table, inputting the first applicable device state table and the applicable device loss sequencing table into a preset resource allocation strategy matching model for strategy matching, generating a first resource allocation strategy, and outputting the first resource allocation strategy to the artificial terminal, wherein the number of the first resource allocation strategies is more than 2;
Optimally judging all the first resource allocation strategies to generate a system strategy selection instruction;
synchronously acquiring an artificial strategy selection instruction input by an artificial terminal and a system strategy selection instruction matched with the system, setting the priority of the artificial strategy selection instruction as a first priority and the system strategy selection instruction as a second priority, wherein the first priority is higher than the second priority;
performing priority comparison on the manual strategy selection instruction and the system strategy selection instruction, and generating an allocation strategy to be executed based on comparison results;
performing first analysis on the distribution strategy to be executed to obtain an energy storage distribution mode in the distribution strategy to be executed;
performing second analysis on the allocation strategy to be executed based on the energy storage allocation mode to acquire the allocation of the corresponding energy storage equipment;
and simultaneously, the electric energy of the new energy system is transmitted to the corresponding energy storage equipment for storage by combining the resource allocation method, the energy storage allocation mode and the allocation of the corresponding energy storage equipment.
Preferably, generating the second matching factor based on the energy storage cost information and the energy conversion rate includes:
constructing a first function G0 (C1, N1) based on the energy storage cost information C1 and the energy conversion rate N1;
And comparing the first function G0 (C1, N1) with a preset constraint condition to obtain a second matching factor.
The technical scheme of the invention has the beneficial effects that: according to the method, the corresponding resource allocation strategy and the resource allocation method can be obtained according to the parameter information of the new energy system and the energy storage equipment, and meanwhile, the new energy system and the corresponding energy storage equipment are subjected to parameter adjustment according to the resource allocation strategy and the resource allocation method, so that the resources between the new energy system and the energy storage equipment are allocated. The energy storage configuration adaptive to the new energy system can be accurately selected, so that the efficiency of resource allocation between the new energy system and the energy storage equipment is improved, unnecessary energy loss of the new energy in the process of energy storage is reduced, and the utilization rate of the new energy is further improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for collaborative planning and configuration of multiple energy storage and new energy in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Referring to the figure, an embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
step 1: acquiring real-time output data of a new energy system, and simultaneously acquiring configuration information of diversified energy storage equipment;
step 2: acquiring equipment information of a new energy system, and combining real-time output data of the new energy system to match configuration information of the diversified energy storage equipment so as to generate an output-energy storage equipment matching result;
step 3: inputting the output-energy storage equipment matching result into a preset resource matching model to generate a resource allocation method of the new energy system and the target equipment;
Step 4: and based on the resource allocation method, the parameters of the new energy system and the target equipment are cooperatively planned, so that the resource allocation between the new energy system and the target equipment is realized.
In this embodiment, the data is output in real time: the system comprises parameter data of output ends such as real-time output power, real-time output voltage and the like of a new energy system;
in this embodiment, configuration information: the device type, the energy storage mode and the energy storage parameter information of each energy storage device are included;
in this embodiment, the device information: information of output equipment corresponding to the output end of the new energy system;
in this embodiment, the output-energy storage device match results: matching the equipment information, the real-time output data and the configuration information of the energy storage equipment of the new energy system to obtain information of the corresponding energy storage equipment;
in this embodiment, a resource matching model is preset: the data processing model which is processed by big data in advance and is used for processing the matching result of the output-energy storage equipment is preset;
in this embodiment, the target device: outputting all energy storage devices matched with the new energy system in the matching result of the energy storage devices;
in this embodiment, the resource allocation method includes: processing and analyzing the output-energy storage equipment matching result according to a preset resource matching model to obtain a method for allocating resources of the new energy system and corresponding target equipment;
In this embodiment, collaborative planning: and carrying out parameter adjustment on the new energy system and the target equipment according to the resource allocation method so as to meet the energy transmission and storage conditions, thereby achieving the purpose of storing the energy of the new energy into the corresponding energy storage equipment.
In this embodiment, resource allocation: including energy storage, recovery, etc. resource call operations.
The working principle and the beneficial effects of the technical scheme are as follows: according to the method, the equipment information of the new energy system, the real-time output data and the configuration information of the diversified energy storage equipment are matched to obtain the information of the corresponding energy storage equipment suitable for storing the new energy, and further, a corresponding resource allocation method is obtained through analysis of a preset resource matching model, and resource allocation is carried out on the new energy system and the target energy storage equipment. The energy storage configuration adaptive to the new energy system can be accurately selected, so that the efficiency of resource allocation between the new energy system and the energy storage equipment is improved, unnecessary energy loss of the new energy in the process of energy storage is reduced, and the utilization rate of the new energy is further improved.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
Acquiring instantaneous output power and average output power of a new energy system, inputting the instantaneous output power and the average output power into a preset power curve generating function, and generating a real-time output power curve of the new energy system;
meanwhile, energy storage equipment information and energy storage configuration information of the diversified energy storage equipment are obtained, and networking is carried out on all the energy storage equipment based on the energy storage equipment information and the energy storage configuration information to form a diversified energy storage network.
In this embodiment, the instantaneous output power: the output power value of the output equipment corresponding to the output end of the new energy system at each moment;
in this embodiment, the average output power: the new energy system output device outputs an average value of power in a certain time period;
in this embodiment, the power curve generation function is preset: the function for generating the output power curve graph of the output equipment according to the instantaneous output power and the average output power of the output equipment of the new energy system is preset;
in this embodiment, the real-time output power profile: calculating the instantaneous output power of the output equipment at each moment and the average output power in a certain period according to a preset power curve generating function, and obtaining a curve graph for observing the real-time power change of the output equipment;
In this embodiment, the energy storage device information: equipment information such as equipment numbers, positions and the like of all sub-equipment in the diversified energy storage equipment;
in this embodiment, the stored energy configuration information: configuration information such as equipment types and equipment duty ratios of all sub-equipment in the diversified energy storage equipment;
in this embodiment, networking: establishing network connection among all the energy storage devices according to the energy storage device information and the energy storage configuration information, and realizing the information intercommunication among the energy storage devices;
in this embodiment, the multi-element energy storage network: and networking all the energy storage devices in the diversified energy storage devices to obtain the network structure of the diversified energy storage devices.
The working principle and the beneficial effects of the technical scheme are as follows: according to the invention, the instantaneous output power and the average output power of the output equipment at the output end of the new energy system are calculated through the preset power curve function, so that the real-time output power curve of the output equipment is obtained, the transparency and the visibility of the output of the new energy power are improved, the purpose of monitoring the output power of the new energy in real time is realized, meanwhile, all the energy storage equipment in the diversified equipment is networked to construct a diversified energy storage network, the information intercommunication among the energy storage equipment can be realized, and the perception level and the monitoring level of the running state of the multi-element energy storage equipment are improved.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
acquiring equipment information of a new energy system, distinguishing the power output type of the new energy system, and determining a first screening factor by combining a real-time output power curve graph of the new energy system;
meanwhile, acquiring equipment information and corresponding load conditions of all equipment in the diversified energy storage network, and determining a second screening factor;
and screening out equipment information matched with the new energy system in the diversified energy storage network according to a preset factor-equipment matching table based on the first screening factor and the second screening factor, and synchronously generating an output-energy storage equipment matching result.
In this embodiment, the power output type: the type of the new energy output power obtained based on the equipment information of the output equipment of the output end of the new energy;
in this embodiment, the first screening factor: according to the equipment information of the new energy system, the corresponding power output type and the real-time output power curve graph, the generated parameters for screening the corresponding energy storage equipment are generated;
in this embodiment, the load conditions: information such as energy storage conditions of energy storage devices in the diversified energy storage network and current load states;
In this embodiment, the second screening factor: according to the equipment information of all the energy storage equipment in the diversified energy storage network and the corresponding load conditions, parameters for screening out the energy storage equipment matched with the new energy system are obtained;
in this embodiment, a factor-device matching table is preset: the energy storage system comprises a table containing a first screening factor, a second screening factor and a mapping relation among the energy storage devices, and is used for selecting the energy storage devices matched with the new energy output devices from the diversified energy storage network according to the first screening factor and the second screening factor.
The working principle and the beneficial effects of the technical scheme are as follows: according to the method, the power output type is judged according to the equipment information of the output equipment of the energy system, the first screening factor is generated by combining the real-time output power curve graph, the second screening factor is generated according to the equipment information and the load condition of the energy storage equipment, and the adaptive energy storage equipment is screened out from the preset factor-equipment matching table through the first screening factor and the second screening factor, so that the corresponding target energy storage equipment can be accurately obtained in the diversified energy storage network, the occurrence of the condition that the energy storage equipment is not matched with the output equipment of the new energy system is reduced, and the accuracy of the matching energy storage equipment is greatly improved.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
performing content analysis on the output-energy storage device matching result to generate data analysis packages, extracting features of all the data analysis packages, and marking the extracted feature information in the corresponding data analysis packages respectively;
acquiring a data format of a preset resource matching model, and simultaneously, converting the format of all data analysis packets under the same output-energy storage device matching result;
inputting all the data analysis packages after format conversion into a pre-trained preset resource matching model, and matching a resource allocation method between the new energy system and the target equipment in the preset resource matching model based on the characteristic information attached to each data analysis package.
In this embodiment, the data parse packet: an analysis packet obtained through analysis of the output-energy storage device matching result;
in this embodiment, feature extraction: extracting characteristic information in the data analysis packet;
in this embodiment, the feature information: information having distinguishing significances regarding the type, model, etc. of the energy storage device;
in this embodiment, the data format: presetting a format required by a resource matching model when data processing is performed;
In this embodiment, format conversion: and converting the formats of all the data analysis packets into operations consistent with the required formats of the preset resource matching model.
The working principle and the beneficial effects of the technical scheme are as follows: according to the method, firstly, the content analysis is carried out on the output-energy storage equipment matching result, then the format of the data analysis package obtained through analysis is converted into the data format matched with the preset resource matching model, the content in the data analysis package is conveniently analyzed and processed by the preset resource matching model, meanwhile, the corresponding resource allocation method is generated by carrying out the preset resource matching model trained by big data in advance in combination with the characteristic information attached to the data analysis package, the speed of data processing and the matching precision of the resource allocation method are greatly improved, and the matching effect of the resource allocation method, a new energy system and the energy storage equipment is ensured.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, wherein the method for allocating resources between a matched new energy system and target equipment comprises the following steps:
acquiring an upper limit value and a fluctuation range of output power of a new energy system, performing power matching with input power of target equipment, and generating a first matching factor based on a power matching result;
Acquiring energy storage cost information and energy conversion rate of target equipment, and generating a second matching factor based on the energy storage cost information and the energy conversion rate;
and screening the target type of energy conversion in a preset resource matching model based on the first matching factor and the second matching factor, and combining the characteristic information in each data analysis packet to acquire a resource allocation method matched with the target type of energy conversion.
In this embodiment, the upper limit value: maximum and minimum values of output power of the output device in normal operation;
in this embodiment, the fluctuation range: acceptable fluctuation range of output power under normal conditions caused by factors such as interference;
in this embodiment, the power is matched: a process of performing power adaptation on the output power of the output device of the new energy system and the input power of the target device;
in this embodiment, the power match results: the output power of the new energy system is matched with the input power of the target equipment in power;
in this embodiment, the first matching factor: the method comprises the steps of generating parameters for screening energy conversion target types in a preset resource matching model according to a power matching result;
In this embodiment, the energy storage cost: the cost spent in the process of storing energy by the target equipment;
in this embodiment, the energy conversion rate: the target equipment has higher energy conversion efficiency in the energy conversion process, and the higher the conversion efficiency is, the smaller the energy loss is, and the higher the energy conversion rate is;
in this embodiment, the second matching factor: according to the energy storage cost and the energy conversion rate, generating parameters for screening energy conversion target types in a preset resource matching model;
in this embodiment, the target type: and converting the energy types output by the new energy sources into various forms of energy types corresponding to the energy storage devices.
The working principle and the beneficial effects of the technical scheme are as follows: according to the method, the target type of energy conversion is determined through comprehensive analysis by the first matching factor generated according to the power matching result, the energy storage cost information of the target equipment and the second matching factor generated by the energy conversion rate, so that the accuracy and the effectiveness of equipment matching between the new energy system and the diversified energy storage equipment are improved, meanwhile, the characteristic information in the data packet is combined to match a corresponding resource allocation method in a preset resource matching model, the ordering of each execution process in the energy storage process is improved, and the energy storage efficiency and the energy storage effect in the energy storage process are further improved.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
analyzing the resource allocation method, acquiring equipment information of all related equipment involved in the resource allocation process under the resource allocation method, and simultaneously acquiring real-time operation parameter information of the corresponding equipment and connection states among the equipment;
constructing a temporary equipment connection network based on the equipment information, the real-time operation parameter information of the corresponding equipment and the connection state among the equipment;
based on the temporary connection network of the equipment, carrying out parameter matching on the parameters of the input port and the output port between the equipment, and screening out corresponding parameter matching strategies in a parameter-strategy mapping table;
acquiring historical peak data and historical average data of input and output ports of each device, and calculating redundancy parameters of each device according to a preset redundancy formula based on the historical peak data and the historical average data;
based on the parameter matching strategy and the redundant parameter of each device, simultaneously combining a preset strategy-redundant-instruction mapping table, acquiring a corresponding parameter adjustment instruction from an instruction database, and carrying out corresponding parameter adjustment on each device;
Acquiring and analyzing and verifying the real-time operation parameters of the output and input ports of each device after adjustment, generating a parameter adjustment verification result, and judging the verification result meeting the preset first threshold condition as qualified;
inputting a qualified verification result into a preset resource scheduling model, and screening out a corresponding resource scheduling test operation instruction;
based on the resource scheduling test running instruction, executing corresponding resource scheduling operation on each device, simultaneously acquiring scheduling parameter information and running state of each device in a resource scheduling process, uploading the scheduling parameter information and the running state of each device to a temporary connection network, and generating a resource scheduling state table according to a preset parameter evaluation model;
comparing each parameter corresponding to each device in the process of resource scheduling test operation with preset ideal parameters based on a resource scheduling state table to generate a test operation evaluation table;
comparing and analyzing the test run evaluation table with a preset run evaluation table, and judging a resource scheduling instruction corresponding to the test run evaluation table with a qualified analysis result as an instruction to be executed;
and based on the instruction to be executed, performing corresponding resource allocation operation on the new energy system and the target equipment.
In this embodiment, the relevant device: all devices involved in the implementation of the resource allocation method;
in this embodiment, the real-time operating parameter information: real-time parameter information of all equipment involved in the resource allocation process in the operation process, such as parameters of working voltage, working current, input-output power ratio and the like;
in this embodiment, the connection state: the method comprises the steps of physical connection relation, electrical connection mode and network connection mode among all the devices;
in this embodiment, the device temporarily connects to the network: the network structure for temporary use is constructed by the equipment information of all relevant equipment related to the resource allocation method, the corresponding real-time operation parameter information and the connection state among the equipment;
in this embodiment, input and output port parameters: operating parameters of the input and output ends of each device;
in this embodiment, the parameters match: matching parameters of each device in the temporary connection network of the device at the connection position;
in this embodiment, the parameter-policy mapping table: a table containing mapping relations between input and output port parameters and parameter matching strategies of each device;
In this embodiment, the parameter matching policy: a policy for matching parameters of the respective devices at the connection;
in this embodiment, historical peak data: data composed of historical maximum value and minimum value of each parameter of each equipment input and output port;
in this embodiment, historical mean data: data composed of historical average values of various parameters of input ports and output ports of various devices;
in this embodiment, a redundancy formula is preset: the formula for calculating the historical peak value data and the historical average value data of the input port and the output port of each device respectively so as to obtain the redundancy parameter of each device is preset;
in this embodiment, redundancy parameters: analyzing and calculating historical peak data and historical average data of each device through a preset redundancy formula to obtain redundancy quantity of each device;
in this embodiment, the policy-redundancy-instruction mapping table is preset: a table containing mapping relationships among the parameter matching policies, the redundancy parameters, and the parameter adjustment instructions;
in this embodiment, the instruction database: a database containing a plurality of operating instructions for controlling the operation of each device;
in this embodiment, the parameter adjustment instruction: obtaining an adjustment instruction for parameter matching of input and output ports of each device according to a preset strategy-redundancy-instruction mapping table;
In this embodiment, the parameter adjustment verifies the result: verifying real-time operation parameters of the input port and the output port after the parameter adjustment of the corresponding equipment according to the parameter adjustment instruction, and judging whether the parameter adjustment instruction is effective or not;
in this embodiment, the first threshold condition: the parameter adjustment verification method is used for judging whether the parameter adjustment verification result meets a threshold value of a preset condition, for example, the parameter error range in the parameter verification result at the joint of 1 equipment and 2 equipment after parameter adjustment is 2%, the parameter error range is less than or equal to 2.1% under the first threshold value condition, and the parameter verification result is qualified because 2% < 2.1%.
In this embodiment, a resource scheduling model is preset: the method is used for receiving the qualified parameter verification result and processing, analyzing and screening the qualified parameter verification result to obtain a corresponding resource scheduling test operation instruction;
in this embodiment, the resource scheduling tries the instruction: an operation instruction which is generated through a pre-trained preset resource scheduling model and is used for carrying out experimental scheduling on resources between a new energy system and multi-element energy storage equipment;
in this embodiment, the scheduling parameter information and the running state: operating parameter information of each device in the resource scheduling process and operating states of the corresponding devices;
In this embodiment, a parameter evaluation model is preset: the method is used for analyzing and processing the scheduling parameter information and the running state of each device so as to generate a state table of the resource scheduling condition among the devices in the resource scheduling process, and the state table is a model which is generated by training big data in advance;
in this embodiment, ideal parameters are preset: ideal scheduling parameter information of each device caused by executing the resource scheduling test run instruction under the theoretical condition;
in this embodiment, the test run evaluation table: comparing each parameter of each device in the resource scheduling state table with a corresponding preset ideal parameter to generate a table for evaluating the resource scheduling trial operation effect under the resource scheduling trial operation instruction;
in this embodiment, the running evaluation table is preset: the comparison table is used for comparing and analyzing with the test run evaluation table, judging whether the resource scheduling test run effect meets the preset requirement or not according to the analysis result, and is preset;
in this embodiment, the instructions to be executed: and comparing and analyzing the test run evaluation table with a preset run evaluation table, and analyzing the resource scheduling instruction corresponding to the test run evaluation table with qualified result.
The working principle and the beneficial effects of the technical scheme are as follows: according to the method, the equipment temporary connection network is constructed through all related equipment involved in the resource allocation process under the resource allocation method, so that the information interference of other irrelevant equipment is reduced, the anti-interference capability in the execution process of the resource allocation method is greatly improved, the information intercommunication effect among the equipment is improved, the situations of incomplete implementation of a resource scheduling instruction, low execution efficiency and the like caused by information blockage among the equipment are reduced, and the information transmission efficiency in the resource scheduling process is greatly improved. Meanwhile, parameters of input and output ports of each device are analyzed, and various data in the temporary connection network of the device are processed and analyzed based on a plurality of preset data processing models trained by big data, so that the efficiency and speed of data processing are greatly improved.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps:
acquiring the energy storage purpose and the energy storage requirement of a new energy system, and screening out a first result meeting the energy storage purpose and the energy storage requirement based on a preset purpose-requirement-equipment adaptation table;
acquiring operation state information of energy storage equipment corresponding to a first result, and inputting the operation state information corresponding to the first result into a preset state information processing model to generate a first applicable equipment state table;
meanwhile, obtaining loss coefficients of the energy storage devices corresponding to the first results, and based on the loss coefficients corresponding to each result, arranging the corresponding energy storage devices in the first applicable device state table in a descending order to generate an applicable device loss ordering table;
establishing a mapping relation between the data of each same energy storage device in the first applicable device state table and the applicable device loss ordered table, inputting the first applicable device state table and the applicable device loss ordered table into a preset resource allocation strategy matching model for strategy matching, generating a first resource allocation strategy, and outputting the first resource allocation strategy to the artificial terminal, wherein the number of the first resource allocation strategies is more than 2;
optimally judging all the first resource allocation strategies to generate a system strategy selection instruction;
Synchronously acquiring an artificial strategy selection instruction input by an artificial terminal and a system strategy selection instruction matched with the system, setting the priority of the artificial strategy selection instruction as a first priority and the system strategy selection instruction as a second priority, wherein the first priority is higher than the second priority;
the manual strategy selection instruction and the system strategy selection instruction are subjected to priority comparison, and an allocation strategy to be executed is generated based on comparison results;
performing first analysis on the allocation strategy to be executed to obtain an energy storage allocation mode in the allocation strategy to be executed;
performing second analysis on the allocation strategy to be executed based on the energy storage allocation mode to acquire the allocation of the corresponding energy storage equipment;
meanwhile, the electric energy of the new energy system is transmitted to the corresponding energy storage equipment for storage by combining a resource allocation method, an energy storage allocation mode and the allocation of each corresponding energy storage equipment.
In this embodiment, energy storage uses: the use purpose and the use purpose of the energy after energy storage are carried out;
in this embodiment, the energy storage requirement: the new energy system needs information of the pure equipment, such as equipment type, equipment capacity and the like, when performing an energy storage process;
in this embodiment, the usage-demand-device adaptation table is preset: the energy storage system comprises an energy storage application, an energy storage requirement and an adaptation table of a mapping relation among the energy storage devices, wherein the adaptation table is used for screening the energy storage devices which meet the energy storage application and the energy storage requirement of the new energy system;
In this embodiment, the first result is: the energy storage equipment meeting the energy storage purpose and the energy storage requirement of the new energy system is obtained through screening, and corresponding equipment information is obtained;
in this embodiment, the operation state information: the state information of the energy storage equipment corresponding to the first result in the running process;
in this embodiment, a state information processing model is preset: the model for analyzing and processing the operation state information of the energy storage equipment corresponding to the first result is preset;
in this embodiment, a first applicable device state table: a table which is obtained after the operation state information of the corresponding energy storage equipment is processed and analyzed through a preset state information processing model and used for representing the state information of the currently applicable energy storage equipment;
in this embodiment, loss factor: the coefficient of energy loss caused by the corresponding energy storage equipment in the energy conversion process is smaller, and the energy conversion rate is higher;
in this embodiment, the descending order is: according to the energy storage equipment in the first applicable equipment state table, arranging all corresponding energy storage equipment from high to low according to the loss coefficient of each equipment;
in this embodiment, a device loss ranking table is applicable: a sorting table generated after the corresponding energy storage devices in the first applicable device state table are arranged in a descending order according to the loss coefficient;
In this embodiment, a resource allocation policy matching model is preset: the method comprises the steps of training big data in advance, and analyzing and processing a first applicable equipment state table and an applicable equipment loss sorting table to obtain a data analysis model of a corresponding resource allocation strategy;
in this embodiment, a first resource allocation policy: inputting a first applicable equipment state table and an applicable equipment loss sorting table into a preset resource allocation strategy matching model, and obtaining a resource allocation strategy through analysis;
in this embodiment, the manual terminal: one of the ports for transmitting the first resource allocation strategy is used for receiving the first resource allocation strategy and transmitting the first resource allocation strategy to related staff, and is also used for acquiring an input instruction of the staff;
in this embodiment, optimal judgment: performing optimal selection operation on all the first resource allocation strategies through preset optimal judgment logic of the system;
in this embodiment, the system policy selects the instruction: the system selects the obtained optimal resource allocation strategy after the optimal judgment of the first resource allocation strategy;
in this embodiment, manual policy selection instruction: a strategy selection instruction after the related staff selects the first resource allocation strategy through the manual terminal;
In this embodiment, the first priority: the manual strategy selects the priority level of the instruction;
in this embodiment, the second priority: the system policy selects the priority level of the instruction, the priority level is lower than the first priority level;
in this embodiment, the allocation policy is to be executed: after comparing the priorities of the manual strategy selection instruction and the system strategy selection instruction, selecting a strategy selection instruction with higher priority;
in this embodiment, the first resolution: resolving the allocation strategy to be executed to obtain an resolving process of an energy storage allocation mode in the allocation strategy to be executed;
in this embodiment, the energy storage distribution mode: a mode for energy storage distribution of energy from a new source, comprising: a single energy storage device stores energy or a plurality of energy storage devices are combined to store energy in two distribution modes;
in this embodiment, the second resolution: resolving the allocation policy to be executed to obtain resolving processes of the allocation of each corresponding energy storage device;
in this embodiment, the allocation is: and allocating the amount of energy storage capacity to each corresponding energy storage device based on the allocation policy to be executed.
The working principle and the beneficial effects of the technical scheme are as follows: according to the invention, the energy storage equipment suitable for energy storage is screened out according to the energy storage purpose and the energy storage requirement of the new energy system, the energy storage equipment is ordered according to the loss coefficient of the corresponding energy storage equipment, and then the strategy matching is carried out according to the preset resource allocation strategy matching model, so that a plurality of resource allocation strategies are obtained through selection, meanwhile, the optimal resource strategy is selected through the optimal judgment logic of the system, the manual selection strategy is selected through the selection instruction input by the manual terminal, and the manually selected resource allocation strategy is used as a high priority, so that not only is the control of the energy storage process by related personnel facilitated, but also the safety and reliability of resource allocation between the new energy system and the multi-element energy storage equipment are improved, and the system can automatically match the optimal resource allocation strategy under the condition that no manual strategy selection instruction is input, so that the automation level and the intelligent level of energy storage are greatly improved.
The embodiment of the invention provides a method for collaborative planning and configuration of multiple energy storage and new energy, which comprises the following steps: preferably, generating the second matching factor based on the energy storage cost information and the energy conversion rate includes:
constructing a first function G0 (C1, N1) based on the energy storage cost information C1 and the energy conversion rate N1;
and comparing the first function G0 (C1, N1) with a preset constraint condition to obtain a second matching factor.
The working principle and the beneficial effects of the technical scheme are as follows: by constructing the function and comparing the function with the condition, the parameter information meeting the constraint is convenient to determine, and the second matching factor is convenient to obtain.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. A method for collaborative planning and configuration of multiple energy storage and new energy is characterized by comprising the following steps:
step 1: acquiring real-time output data of a new energy system, and simultaneously acquiring configuration information of diversified energy storage equipment;
step 2: acquiring equipment information of a new energy system, and matching the real-time output data of the new energy system with configuration information of the diversified energy storage equipment to generate an output-energy storage equipment matching result;
Step 3: inputting the output-energy storage equipment matching result into a preset resource matching model to generate a resource allocation method of a new energy system and target equipment;
step 4: and based on the resource allocation method, the parameters of the new energy system and the target equipment are cooperatively planned, so that the resource allocation between the new energy system and the target equipment is realized.
2. The method for collaborative planning and configuration of multiple energy storage and new energy according to claim 1, wherein in step 1, the method comprises:
acquiring instantaneous output power and average output power of a new energy system, inputting the instantaneous output power and the average output power into a preset power curve generating function, and generating a real-time output power curve of the new energy system;
meanwhile, energy storage equipment information and energy storage configuration information of the diversified energy storage equipment are obtained, and networking is carried out on all the energy storage equipment based on the energy storage equipment information and the energy storage configuration information to form a diversified energy storage network.
3. The method for collaborative planning and configuration of multiple energy storage and new energy according to claim 2, wherein in step 2, the method comprises:
acquiring equipment information of a new energy system, distinguishing the power output type of the new energy system, and determining a first screening factor by combining a real-time output power curve graph of the new energy system;
Meanwhile, acquiring equipment information and corresponding load conditions of all equipment in the diversified energy storage network, and determining a second screening factor;
and screening out equipment information matched with a new energy system in the diversified energy storage network according to a preset factor-equipment matching table based on the first screening factor and the second screening factor, and synchronously generating an output-energy storage equipment matching result.
4. The method for collaborative planning and configuration of multiple energy storage and new energy according to claim 1, wherein in step 3, the method comprises:
performing content analysis on the output-energy storage device matching result to generate data analysis packages, extracting features of all the data analysis packages, and marking the extracted feature information in the corresponding data analysis packages respectively;
acquiring a data format of the preset resource matching model, and simultaneously, converting the format of all data analysis packets under the same output-energy storage equipment matching result;
inputting all the data analysis packages after format conversion into the pre-trained preset resource matching model, and matching a resource allocation method between a new energy system and target equipment in the preset resource matching model based on the characteristic information attached to each data analysis package.
5. The method for collaborative planning and configuration of multiple energy storage and new energy according to claim 4, wherein the method for matching resource allocation between a new energy system and a target device comprises:
acquiring an upper limit value and a fluctuation range of output power of a new energy system, performing power matching with input power of target equipment, and generating a first matching factor based on a power matching result;
acquiring energy storage cost information and energy conversion rate of target equipment, and generating a second matching factor based on the energy storage cost information and the energy conversion rate;
and screening the target type of energy conversion in the preset resource matching model based on the first matching factor and the second matching factor, and acquiring a resource allocation method matched with the target type of energy conversion by combining the characteristic information in each data analysis packet.
6. The method for collaborative planning and configuration of multiple energy storage and new energy according to claim 1, wherein in step 4, the method comprises:
analyzing the resource allocation method, acquiring equipment information of all related equipment involved in the resource allocation process under the resource allocation method, and simultaneously acquiring real-time operation parameter information of corresponding equipment and connection states among the equipment;
Constructing a temporary equipment connection network based on the equipment information, the real-time operation parameter information of the corresponding equipment and the connection state among the equipment;
based on the temporary connection network of the equipment, carrying out parameter matching on the parameters of the input port and the output port among the equipment, and screening out corresponding parameter matching strategies in a parameter-strategy mapping table;
acquiring historical peak data and historical average data of input and output ports of each device, and calculating redundancy parameters of each device according to a preset redundancy formula based on the historical peak data and the historical average data;
based on the parameter matching strategy and the redundant parameter of each device, simultaneously combining a preset strategy-redundant-instruction mapping table, acquiring a corresponding parameter adjustment instruction from an instruction database, and carrying out corresponding parameter adjustment on each device;
acquiring and analyzing and verifying the real-time operation parameters of the output and input ports of each device after adjustment, generating a parameter adjustment verification result, and judging the verification result meeting the preset first threshold condition as qualified;
inputting a qualified verification result into a preset resource scheduling model, and screening out a corresponding resource scheduling test operation instruction;
Based on the resource scheduling test operation instruction, executing corresponding resource scheduling operation on each device, simultaneously acquiring scheduling parameter information and operation state of each device in a resource scheduling process, uploading the scheduling parameter information and operation state of each device to the temporary connection network, and generating a resource scheduling state table according to a preset parameter evaluation model;
comparing each parameter corresponding to each device in the resource scheduling test operation process with a preset ideal parameter based on the resource scheduling state table to generate a test operation evaluation table;
comparing and analyzing the test run evaluation table with a preset run evaluation table, and judging a resource scheduling instruction corresponding to the test run evaluation table with a qualified analysis result as an instruction to be executed;
and based on the instruction to be executed, performing corresponding resource allocation operation on the new energy system and the target equipment.
7. The method for collaborative planning and configuration of multiple energy storage and new energy according to claim 1, wherein in step 4, further comprising:
acquiring energy storage purposes and energy storage requirements of a new energy system, and screening out a first result meeting the energy storage purposes and the energy storage requirements based on a preset purpose-requirement-equipment adaptation table;
Acquiring the running state information of the energy storage equipment corresponding to the first result, and inputting the running state information corresponding to the first result into a preset state information processing model to generate a first applicable equipment state table;
meanwhile, obtaining loss coefficients of the energy storage devices corresponding to the first result, and based on the loss coefficients corresponding to each result, arranging the corresponding energy storage devices in the first applicable device state table in a descending order to generate an applicable device loss ordering table;
establishing a mapping relation between the data of each energy storage device in the first applicable device state table and the applicable device loss sequencing table, inputting the first applicable device state table and the applicable device loss sequencing table into a preset resource allocation strategy matching model for strategy matching, generating a first resource allocation strategy, and outputting the first resource allocation strategy to the artificial terminal, wherein the number of the first resource allocation strategies is more than 2;
optimally judging all the first resource allocation strategies to generate a system strategy selection instruction;
synchronously acquiring an artificial strategy selection instruction input by an artificial terminal and a system strategy selection instruction matched with the system, setting the priority of the artificial strategy selection instruction as a first priority and the system strategy selection instruction as a second priority, wherein the first priority is higher than the second priority;
Performing priority comparison on the manual strategy selection instruction and the system strategy selection instruction, and generating an allocation strategy to be executed based on comparison results;
performing first analysis on the distribution strategy to be executed to obtain an energy storage distribution mode in the distribution strategy to be executed;
performing second analysis on the allocation strategy to be executed based on the energy storage allocation mode to acquire the allocation of the corresponding energy storage equipment;
and simultaneously, the electric energy of the new energy system is transmitted to the corresponding energy storage equipment for storage by combining the resource allocation method, the energy storage allocation mode and the allocation of the corresponding energy storage equipment.
8. The method of collaborative planning configuration of multiple energy storage and new energy according to claim 1, wherein generating a second matching factor based on the energy storage cost information and energy conversion rate comprises:
constructing a first function G0 (C1, N1) based on the energy storage cost information C1 and the energy conversion rate N1;
and comparing the first function G0 (C1, N1) with a preset constraint condition to obtain a second matching factor.
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