CN118242782B - Flexible operation control method for medium-deep ground source heat pump system - Google Patents
Flexible operation control method for medium-deep ground source heat pump system Download PDFInfo
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Abstract
The invention discloses a flexible operation control method of a medium-deep ground source heat pump system, which comprises the steps of establishing a medium-deep ground source heat pump buried pipe heat transfer calculation model based on a deep hole coaxial buried pipe heat exchanger heat transfer mechanism, establishing a building load calculation model based on a simulation method, predicting energy consumption side super supply requirements of a building based on indoor temperature dynamic simulation calculation and thermal load dynamic simulation calculation according to the adjustment target value, comparing and analyzing the maximum heat-taking performance with heat-taking performance under a medium-deep ground pipe reference working condition to obtain heat source supply side super capacity, carrying out matching analysis on the heat source supply side super capacity and the building energy consumption side super supply requirements to obtain matching data, and establishing a regulation and control decision of the medium-deep ground source heat pump system according to the matching data. The method not only can improve the accuracy of the operation control of the middle-deep ground source heat pump system, but also has better interpretability, and can be directly applied to the operation control system of the middle-deep ground source heat pump system.
Description
Technical Field
The invention relates to the field of control, in particular to a flexible operation control method of a medium-deep ground source heat pump system.
Background
With the increasing severity of global energy crisis and environmental pollution problems, energy conservation and environmental protection have become the focus of attention in today's society. In the building field, how to effectively utilize the heat storage capacity of a building body, improve the energy utilization efficiency and reduce the energy consumption becomes a problem to be solved urgently. The medium-deep ground source heat pump system is widely applied in recent years as an efficient and environment-friendly energy utilization mode. How to better operate and control the middle-deep ground source heat pump system so as to combine the heat storage capacity of the building body, and further improve the energy utilization efficiency and the system operation stability is a technical problem in the current field.
The invention provides a method for controlling the operation of a middle-deep ground source heat pump system by utilizing the heat storage capacity of a building body, and aims to solve the problems. The method realizes intelligent operation control of the system by reasonably utilizing the heat storage capacity of the building body and combining with the medium-deep ground source heat pump system, improves the energy utilization efficiency, reduces the energy consumption and ensures the stable operation of the system.
Disclosure of Invention
The invention aims to provide a flexible operation control method of a medium-deep ground source heat pump system.
In order to achieve the above purpose, the invention is implemented according to the following technical scheme:
the invention comprises the following steps:
Establishing a medium-deep ground source heat pump buried pipe heat transfer calculation model based on a deep hole coaxial buried pipe heat exchanger heat transfer mechanism, establishing a building load calculation model based on a simulation method, and determining an initial operation strategy, a cold-hot electric load and operation parameters of a medium-deep ground source heat pump system in an operation regulation period;
Acquiring power grid data of a service user of a middle-deep ground source heat pump system through actual investigation, determining power grid interaction requirements according to the power grid data, and acquiring an adjustment target value according to the power grid interaction requirements; the power grid data comprise a power grid dynamic electricity price policy, power grid renewable energy consumption requirements and a power grid power load regulation and control target value;
Predicting the building energy side super-supply demand based on indoor temperature dynamic simulation calculation and thermal load dynamic simulation calculation according to the regulation target value, analyzing the medium-deep buried pipe dynamic maximum heat-taking performance based on the medium-deep buried pipe time-by-time heat-taking performance in dynamic simulation calculation, and comparing and analyzing the maximum heat-taking performance with the heat-taking performance under the medium-deep buried pipe reference working condition to obtain the heat source supply side super-supply capacity;
carrying out matching analysis on the super capacity of the heat source supply side and the super supply and demand of the building energy side to obtain matching data, and establishing a regulation and control decision of a middle-deep ground source heat pump system according to the matching data;
and optimizing the middle-deep ground source heat pump system according to the regulation and control decision.
Further, the method for establishing the medium-deep ground source heat pump buried pipe heat transfer calculation model based on the deep hole coaxial buried pipe heat exchanger heat transfer mechanism comprises the following steps:
the medium-deep ground source heat pump buried pipe heat transfer calculation model is constructed by adopting a random forest algorithm, a numerical simulation method and a machine learning algorithm;
The random forest algorithm outputs factors with contribution degree larger than 0.732 as the heat transfer influence factors of the buried pipes of the medium-deep ground source heat pump; the numerical simulation method utilizes computer software to establish a physical model of the buried pipe, and predicts the heat conduction performance of the buried pipe after adjusting the influence factors by performing numerical calculation simulation on the model; the machine learning algorithm calculates the heat transfer of the buried pipe by learning the heat transfer performance rule of the buried pipe;
Calculating adjustment parameters:
Wherein the buried pipe transfers heat The individual influencing factors areFirst, theThe importance of the individual influencing factors isThe number of influencing factors isGenetic coefficient ofThe random number is r, and the adjustment constant isThe first weight coefficient isThe second weight coefficient isThe underground temperature distribution is D, and the adjustment parameters are；
Constructing an objective function according to the adjustment parameters:
wherein the objective function of the i-th section of the buried pipe is The i-th section of the buried pipe transfers heat toThe temperature difference between the fluid of the i-th section of the buried pipe and the surrounding soil isGiven a loss function of a buried pipe heat transfer calculation model of the middle-deep layer ground source heat pump, the expression is as follows:
wherein the ith section of buried pipe predicts heat transfer as The actual heat transfer of the i-th section of buried pipe isThe number of the underground pipe sections isThe control coefficient of heat transfer of the i-th section of buried pipe isError coefficient is。
Further, the method for building the building load calculation model based on the simulation method comprises the following steps:
Building a building load calculation model by adopting a simulation method, a Monte Carlo method and an artificial neural network algorithm;
The simulation method simulates a building load process according to actual data; the Monte Carlo method estimates relevant factors through random sampling under simulation; the artificial neural network algorithm establishes a complex relation model of building load and related factors, and approximates the change rule of the actual building load through a training network;
building a building load function, wherein the expression is as follows:
wherein the a-th building load function is The value of the kth related factor of the a building isThe standard value of the kth related factor of the a building isThe number of related factors isThe first contribution degree of the kth related factor isThe second contribution degree of the kth related factor isThe third contribution degree of the kth related factor isThe influence constant isThe indoor and outdoor temperature difference of the a building isThe heat transfer coefficient of the a building is。
Further, a method of determining an initial operating strategy, a thermal-electrical-thermal load, and an operating parameter of a medium depth ground source heat pump system, comprising:
The indoor and outdoor boundary conditions of a service user of the medium-deep ground source heat pump system directly influence the cold and hot electric load demands and the operation parameters of the system, and the outdoor meteorological parameters in the operation regulation period are predicted and determined based on the actual historical meteorological data of the region where the heat pump system is located;
acquiring user indoor boundary condition parameters of heat pump system service based on a medium-deep ground source heat pump system monitoring and information acquisition system;
Establishing a heat pump system cold-heat power multielement load demand and running state prediction mathematical model by adopting a simulation method, importing indoor and outdoor boundary condition prediction parameter values, and calculating the cold-heat demand of a user;
On the premise of meeting the requirements of cold and hot demands and comfort of users, an initial operation strategy of the heat pump system is established, and the power load, the unit load rate and the water supply and return temperature operation state parameters of the heat pump system are calculated in a simulation mode;
Meteorological parameters include temperature, humidity, wind speed and solar radiation intensity; the user indoor boundary condition parameters include indoor temperature, indoor humidity, equipment work and rest, lighting work and rest, and people behavior parameters.
Further, the method for predicting the energy-consumption-side super-supply demand of the building based on the indoor temperature dynamic simulation calculation and the thermal load dynamic simulation calculation according to the adjustment target value comprises the following steps:
building a dynamic simulation model of the heat load and the indoor and outdoor temperatures of the building according to the energy utilization data inside and outside the building, and setting an indoor temperature regulation target value according to the use requirement and the energy saving requirement of the building;
and carrying out dynamic simulation calculation on the indoor and outdoor temperatures and the thermal load by utilizing a dynamic simulation model according to the indoor temperature regulation target value.
Further, the method for comparing and analyzing the maximum heat-extracting performance with the heat-extracting performance under the medium-deep buried pipe reference working condition to obtain the super-capacity of the heat source supply side comprises the following steps:
Setting a reference working condition of normal operation of a conventional strategy and an oversupply working condition of an excessive heating strategy before participating in demand response by adopting dynamic simulation calculation of time-by-time heat extraction of the deep buried pipe, analyzing dynamic maximum heat extraction performance under different operation working conditions of the deep buried pipe, comparing the dynamic maximum heat extraction performance with heat extraction under the reference working condition of the deep buried pipe, and analyzing super-capacity and dynamic response characteristics of the deep buried pipe;
Analyzing the super capacity, accumulated heat gain of super supply period, peak heat gain of super supply mode and accumulated heat gain of whole day of the middle-deep buried pipe system under different super supply strategies;
the peak heat gain mode is outputted as the heat source supply side super capacity.
Further, the method for obtaining matching data by matching analysis of the heat source supply side super capacity and the building energy side super supply and demand comprises the following steps:
Extracting an oversupply index of the oversupply capacity of the heat source supply side according to the oversupply requirement of the building energy side by adopting a self-encoder;
Matching the super capacity of the heat source supply side according to the capacity standard of the super capacity demand of the building energy side, and calculating the matching degree of the capacity standard and the super capacity of the heat source supply side:
wherein the degree of matching of the super capacity of the heat source supply side is The deviation value of the s-th super-supply index isThe maximum standard value of the s-th super-supply index isThe minimum standard value of the s-th super-supply index isThe s-th super supply index value isThe natural constant is e, the cosine function isThe number of super-supply indexes isThe importance is thatThe control factor is；
When the matching degree is smaller than 0.82, the super-capacity of the heat source supply side cannot meet the super-supply requirement of the energy side for the tail end of the building, and the energy system is put into operation according to the maximum heat supply capacity until the response starting time;
If the matching degree is greater than 0.82, the super-capacity of the heat source supply side can meet the energy-side super-supply requirement of the tail end of the building, the reserved time length required by the super-supply operation of the heat source system is calculated according to the super-capacity of the heat source system, the super-supply load capacity of the user side and the super-supply time, and the heat source system operates normally until the heat source system operates according to the super-supply working condition at other times.
Further, the method for optimizing the deep-layer ground source heat pump system according to the regulation and control decision comprises the following steps:
and according to the operation and maintenance data and the baseline load, analyzing the power load reduction amount and peak load reduction amount response benefit of the current power demand side response period, and adjusting parameters of the middle-deep ground source heat pump system according to the regulation and control decision until the error range is lower than 0.19.
In a second aspect, an embodiment of the present application further provides an electronic device, including:
a processor; and a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method steps of the first aspect.
In a third aspect, embodiments of the present application also provide a computer-readable storage medium storing one or more programs, which when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method steps of the first aspect.
The beneficial effects of the invention are as follows:
The invention relates to a flexible operation control method of a medium-deep ground source heat pump system, which has the following technical effects compared with the prior art:
The method can improve the accuracy of the operation control of the middle-deep ground source heat pump system through the steps of model construction, matching analysis, dynamic simulation calculation, acquisition adjustment decision and optimization model, so that the accuracy of the operation control of the middle-deep ground source heat pump system is improved, the operation control of the middle-deep ground source heat pump system is optimized, resources can be greatly saved, the working efficiency is improved, intelligent control of the operation of the middle-deep ground source heat pump system can be realized, decision adjustment is carried out on the operation control of the middle-deep ground source heat pump system in real time, the important significance is provided for the operation control of the middle-deep ground source heat pump system, and the method can adapt to the operation control requirements of the middle-deep ground source heat pump system with different standards and has certain universality.
Drawings
FIG. 1 is a flow chart of the steps of a flexible operation control method of a medium-deep ground source heat pump system;
Fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
The invention is further described by the following specific examples, which are presented to illustrate, but not to limit, the invention.
The invention discloses a flexible operation control method of a medium-deep ground source heat pump system, which comprises the following steps:
as shown in fig. 1, in this embodiment, the steps include:
Establishing a medium-deep ground source heat pump buried pipe heat transfer calculation model based on a deep hole coaxial buried pipe heat exchanger heat transfer mechanism, establishing a building load calculation model based on a simulation method, and determining an initial operation strategy, a cold-hot electric load and operation parameters of a medium-deep ground source heat pump system in an operation regulation period;
Acquiring power grid data of a service user of a middle-deep ground source heat pump system through actual investigation, determining power grid interaction requirements according to the power grid data, and acquiring an adjustment target value according to the power grid interaction requirements; the power grid data comprise a power grid dynamic electricity price policy, power grid renewable energy consumption requirements and a power grid power load regulation and control target value;
Predicting the building energy side super-supply demand based on indoor temperature dynamic simulation calculation and thermal load dynamic simulation calculation according to the regulation target value, analyzing the medium-deep buried pipe dynamic maximum heat-taking performance based on the medium-deep buried pipe time-by-time heat-taking performance in dynamic simulation calculation, and comparing and analyzing the maximum heat-taking performance with the heat-taking performance under the medium-deep buried pipe reference working condition to obtain the heat source supply side super-supply capacity;
carrying out matching analysis on the super capacity of the heat source supply side and the super supply and demand of the building energy side to obtain matching data, and establishing a regulation and control decision of a middle-deep ground source heat pump system according to the matching data;
and optimizing the middle-deep ground source heat pump system according to the regulation and control decision.
In this embodiment, the method for establishing the buried pipe heat transfer calculation model of the deep-in-the-middle ground source heat pump based on the deep-hole coaxial buried pipe heat exchanger heat transfer mechanism includes:
the medium-deep ground source heat pump buried pipe heat transfer calculation model is constructed by adopting a random forest algorithm, a numerical simulation method and a machine learning algorithm;
The random forest algorithm outputs factors with contribution degree larger than 0.732 as the heat transfer influence factors of the buried pipes of the medium-deep ground source heat pump; the numerical simulation method utilizes computer software to establish a physical model of the buried pipe, and predicts the heat conduction performance of the buried pipe after adjusting the influence factors by performing numerical calculation simulation on the model; the machine learning algorithm calculates the heat transfer of the buried pipe by learning the heat transfer performance rule of the buried pipe;
Calculating adjustment parameters:
Wherein the buried pipe transfers heat The individual influencing factors areFirst, theThe importance of the individual influencing factors isThe number of influencing factors isGenetic coefficient ofThe random number is r, and the adjustment constant isThe first weight coefficient isThe second weight coefficient isThe underground temperature distribution is D, and the adjustment parameters are；
Constructing an objective function according to the adjustment parameters:
wherein the objective function of the i-th section of the buried pipe is The i-th section of the buried pipe transfers heat toThe temperature difference between the fluid of the i-th section of the buried pipe and the surrounding soil isGiven a loss function of a buried pipe heat transfer calculation model of the middle-deep layer ground source heat pump, the expression is as follows:
wherein the ith section of buried pipe predicts heat transfer as The actual heat transfer of the i-th section of buried pipe isThe number of the underground pipe sections isThe control coefficient of heat transfer of the i-th section of buried pipe isError coefficient is。
In this embodiment, the method for building a building load calculation model based on a simulation method includes:
Building a building load calculation model by adopting a simulation method, a Monte Carlo method and an artificial neural network algorithm;
The simulation method simulates a building load process according to actual data; the Monte Carlo method estimates relevant factors through random sampling under simulation; the artificial neural network algorithm establishes a complex relation model of building load and related factors, and approximates the change rule of the actual building load through a training network;
building a building load function, wherein the expression is as follows:
wherein the a-th building load function is The value of the kth related factor of the a building isThe standard value of the kth related factor of the a building isThe number of related factors isThe first contribution degree of the kth related factor isThe second contribution degree of the kth related factor isThe third contribution degree of the kth related factor isThe influence constant isThe indoor and outdoor temperature difference of the a building isThe heat transfer coefficient of the a building is。
In this embodiment, a method for determining an initial operation strategy, a cold-hot electrical load, and an operation parameter of a medium-depth ground source heat pump system includes:
The indoor and outdoor boundary conditions of a service user of the medium-deep ground source heat pump system directly influence the cold and hot electric load demands and the operation parameters of the system, and the outdoor meteorological parameters in the operation regulation period are predicted and determined based on the actual historical meteorological data of the region where the heat pump system is located;
acquiring user indoor boundary condition parameters of heat pump system service based on a medium-deep ground source heat pump system monitoring and information acquisition system;
Establishing a heat pump system cold-heat power multielement load demand and running state prediction mathematical model by adopting a simulation method, importing indoor and outdoor boundary condition prediction parameter values, and calculating the cold-heat demand of a user;
On the premise of meeting the requirements of cold and hot demands and comfort of users, an initial operation strategy of the heat pump system is established, and the power load, the unit load rate and the water supply and return temperature operation state parameters of the heat pump system are calculated in a simulation mode;
Meteorological parameters include temperature, humidity, wind speed and solar radiation intensity; the user indoor boundary condition parameters include indoor temperature, indoor humidity, equipment work and rest, lighting work and rest, and people behavior parameters.
In this embodiment, the method for predicting the energy consumption side super supply requirement of the building based on the indoor temperature dynamic simulation calculation and the thermal load dynamic simulation calculation according to the adjustment target value includes:
building a dynamic simulation model of the heat load and the indoor and outdoor temperatures of the building according to the energy utilization data inside and outside the building, and setting an indoor temperature regulation target value according to the use requirement and the energy saving requirement of the building;
and carrying out dynamic simulation calculation on the indoor and outdoor temperatures and the thermal load by utilizing a dynamic simulation model according to the indoor temperature regulation target value.
In this embodiment, the method for comparing and analyzing the maximum heat-extracting performance with the heat-extracting performance under the reference working condition of the buried pipe at the middle-deep layer to obtain the super-capacity of the heat source supply side includes:
Setting a reference working condition of normal operation of a conventional strategy and an oversupply working condition of an excessive heating strategy before participating in demand response by adopting dynamic simulation calculation of time-by-time heat extraction of the deep buried pipe, analyzing dynamic maximum heat extraction performance under different operation working conditions of the deep buried pipe, comparing the dynamic maximum heat extraction performance with heat extraction under the reference working condition of the deep buried pipe, and analyzing super-capacity and dynamic response characteristics of the deep buried pipe;
Analyzing the super capacity, accumulated heat gain of super supply period, peak heat gain of super supply mode and accumulated heat gain of whole day of the middle-deep buried pipe system under different super supply strategies;
the peak heat gain mode is outputted as the heat source supply side super capacity.
In this embodiment, the method for obtaining matching data by matching analysis of the heat source supply side super capacity and the building energy side super supply and demand includes:
Extracting an oversupply index of the oversupply capacity of the heat source supply side according to the oversupply requirement of the building energy side by adopting a self-encoder;
Matching the super capacity of the heat source supply side according to the capacity standard of the super capacity demand of the building energy side, and calculating the matching degree of the capacity standard and the super capacity of the heat source supply side:
wherein the degree of matching of the super capacity of the heat source supply side is The deviation value of the s-th super-supply index isThe maximum standard value of the s-th super-supply index isThe minimum standard value of the s-th super-supply index isThe s-th super supply index value isThe natural constant is e, the cosine function isThe number of super-supply indexes isThe importance is thatThe control factor is；
When the matching degree is smaller than 0.82, the super-capacity of the heat source supply side cannot meet the super-supply requirement of the energy side for the tail end of the building, and the energy system is put into operation according to the maximum heat supply capacity until the response starting time;
If the matching degree is greater than 0.82, the super-capacity of the heat source supply side can meet the energy-side super-supply requirement of the tail end of the building, the reserved time length required by the super-supply operation of the heat source system is calculated according to the super-capacity of the heat source system, the super-supply load capacity of the user side and the super-supply time, and the heat source system operates normally until the heat source system operates according to the super-supply working condition at other times.
In this embodiment, the method for optimizing the deep-medium ground source heat pump system according to the regulation decision includes:
and according to the operation and maintenance data and the baseline load, analyzing the power load reduction amount and peak load reduction amount response benefit of the current power demand side response period, and adjusting parameters of the middle-deep ground source heat pump system according to the regulation and control decision until the error range is lower than 0.19.
Fig. 2 is a schematic structural view of an electronic device according to an embodiment of the present application. Referring to fig. 2, at the hardware level, the electronic device includes a processor, and optionally an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, network interface, and memory may be interconnected by an internal bus, which may be an ISA (Industry Standard Architecture ) bus, a PCI (PERIPHERAL COMPONENT INTERCONNECT, peripheral component interconnect standard) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 2, but not only one bus or type of bus.
And the memory is used for storing programs. In particular, the program may include program code including computer-operating instructions. The memory may include memory and non-volatile storage and provide instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory to the memory and then operates, and a medium-deep ground source heat pump system operation control device is formed on a logic level. The processor executes the program stored in the memory and is specifically used for executing the flexible operation control method of any one of the deep-layer ground source heat pump systems.
The flexible operation control method of the medium-deep ground source heat pump system disclosed in the embodiment shown in fig. 1 of the present application can be applied to a processor or implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but may also be a digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
The electronic device may also execute a flexible operation control method of the deep-medium ground source heat pump system in fig. 1, and implement the functions of the embodiment shown in fig. 1, which is not described herein.
The embodiment of the application also provides a computer readable storage medium storing one or more programs, the one or more programs including instructions, which when executed by an electronic device including a plurality of application programs, perform a method for controlling flexible operation of a deep-medium ground source heat pump system as described above.
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.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
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 foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (8)
1. The flexible operation control method of the medium-deep ground source heat pump system is characterized by comprising the following steps of:
Establishing a medium-deep ground source heat pump buried pipe heat transfer calculation model based on a deep hole coaxial buried pipe heat exchanger heat transfer mechanism, establishing a building load calculation model based on a simulation method, and determining an initial operation strategy, a cold-hot electric load and operation parameters of a medium-deep ground source heat pump system in an operation regulation period;
Acquiring power grid data of a service user of a middle-deep ground source heat pump system through actual investigation, determining power grid interaction requirements according to the power grid data, and acquiring an adjustment target value according to the power grid interaction requirements; the power grid data comprise a power grid dynamic electricity price policy, a power grid renewable energy consumption demand and a power grid power load regulation and control target value;
Predicting the building energy side super-supply demand based on indoor temperature dynamic simulation calculation and thermal load dynamic simulation calculation according to the regulation target value, analyzing the medium-deep buried pipe dynamic maximum heat-taking performance based on the medium-deep buried pipe time-by-time heat-taking performance in dynamic simulation calculation, and comparing and analyzing the maximum heat-taking performance with the heat-taking performance under the medium-deep buried pipe reference working condition to obtain the heat source supply side super-supply capacity;
And carrying out matching analysis on the super capacity of the heat source supply side and the super supply and demand of the building energy side to obtain matching data, establishing a regulation and control decision of the middle-deep ground source heat pump system according to the matching data, and optimizing the middle-deep ground source heat pump system according to the regulation and control decision.
2. The method for flexibly operating and controlling the medium-deep ground source heat pump system according to claim 1, wherein the method for establishing the medium-deep ground source heat pump buried pipe heat transfer calculation model based on the deep hole coaxial buried pipe heat exchanger heat transfer mechanism comprises the following steps:
The medium-deep ground source heat pump buried pipe heat transfer calculation model is constructed by adopting a random forest algorithm, a numerical simulation method and a machine learning algorithm;
The random forest algorithm outputs factors with contribution degree larger than 0.732 as the heat transfer influence factors of the buried pipes of the medium-deep ground source heat pump; the numerical simulation method utilizes computer software to establish a physical model of the buried pipe, and predicts the heat conduction performance of the buried pipe after adjusting the influence factors by performing numerical calculation simulation on the model; the machine learning algorithm calculates the heat transfer loss of the buried pipe by learning the heat transfer performance rule of the buried pipe;
Calculating adjustment parameters:
Wherein the buried pipe transfers heat The individual influencing factors areFirst, theThe importance of the individual influencing factors isThe number of influencing factors isGenetic coefficient ofThe random number is r, and the adjustment constant isThe first weight coefficient isThe second weight coefficient isThe underground temperature distribution is D, and the adjustment parameters are；
Constructing an objective function of the buried pipe according to the adjustment parameters:
wherein the objective function of the i-th section of the buried pipe is The i-th section of the buried pipe transfers heat toThe temperature difference between the fluid of the i-th section of the buried pipe and the surrounding soil isGiven a loss function of a buried pipe heat transfer calculation model of the middle-deep layer ground source heat pump, the expression is as follows:
wherein the objective function of the i-th section of the buried pipe is The actual heat transfer of the i-th section of buried pipe isThe number of the underground pipe sections isThe control coefficient of heat transfer of the i-th section of buried pipe isError coefficient is。
3. The method for controlling flexible operation of a deep-medium ground source heat pump system according to claim 1, wherein the method for building a building load calculation model based on a simulation method comprises the following steps:
Building a building load calculation model by adopting a simulation method, a Monte Carlo method and an artificial neural network algorithm;
The simulation method simulates a building load process according to actual data; the Monte Carlo method estimates relevant factors through random sampling under simulation; the artificial neural network algorithm establishes a complex relation model of building load and related factors, and approximates the change rule of the actual building load through a training network;
building a building load function, wherein the expression is as follows:
wherein the a-th building load function is The value of the kth related factor of the a building isThe standard value of the kth related factor of the a building isThe number of related factors isThe first contribution degree of the kth related factor isThe second contribution degree of the kth related factor isThe third contribution degree of the kth related factor isThe influence constant isThe indoor and outdoor temperature difference of the a building isThe heat transfer coefficient of the a building is。
4. The method for controlling flexible operation of a deep-medium ground source heat pump system according to claim 1, wherein the method for predicting building energy-consumption-side super-supply demand based on indoor temperature dynamic simulation calculation and thermal load dynamic simulation calculation according to the adjustment target value comprises the steps of:
building a dynamic simulation model of the heat load and the indoor and outdoor temperatures of the building according to the energy utilization data inside and outside the building, and setting an indoor temperature regulation target value according to the use requirement and the energy saving requirement of the building;
and carrying out dynamic simulation calculation on the indoor and outdoor temperatures and the thermal load by utilizing a dynamic simulation model according to the indoor temperature regulation target value.
5. The method for controlling flexible operation of a deep-medium ground source heat pump system according to claim 1, wherein the method for comparing and analyzing the maximum heat-extracting performance with the heat-extracting performance under the reference working condition of the deep-medium ground buried pipe to obtain the super capacity of the heat source supply side comprises the following steps:
Setting a reference working condition of normal operation of a conventional strategy and an oversupply working condition of an excessive heating strategy before participating in demand response by adopting dynamic simulation calculation of time-by-time heat extraction of the deep buried pipe, analyzing dynamic maximum heat extraction performance under different operation working conditions of the deep buried pipe, comparing the dynamic maximum heat extraction performance with heat extraction under the reference working condition of the deep buried pipe, and analyzing super-capacity and dynamic response characteristics of the deep buried pipe;
Analyzing the super capacity, accumulated heat gain of super supply period, peak heat gain of super supply mode and accumulated heat gain of whole day of the middle-deep buried pipe system under different super supply strategies;
the peak heat gain mode is outputted as the heat source supply side super capacity.
6. The method for controlling flexible operation of a deep-medium ground source heat pump system according to claim 1, wherein the method for matching the super capacity of the heat source supply side with the super supply and demand of the building energy side to obtain matching data comprises the steps of:
Extracting an oversupply index of the oversupply capacity of the heat source supply side according to the oversupply requirement of the building energy side by adopting a self-encoder;
Matching the super capacity of the heat source supply side according to the capacity standard of the super capacity demand of the building energy side, and calculating the matching degree of the capacity standard and the super capacity of the heat source supply side:
wherein the degree of matching of the super capacity of the heat source supply side is The deviation value of the s-th super-supply index isThe maximum standard value of the s-th super-supply index isThe minimum standard value of the s-th super-supply index isThe s-th super supply index value isThe natural constant is e, the cosine function isThe number of super-supply indexes isThe importance is thatThe control factor is；
When the matching degree is smaller than 0.82, the super capacity of the heat source supply side cannot meet the energy-consumption side super supply requirement of the building end, and the middle-deep ground source heat pump system is put into operation according to the maximum heat supply capacity until the response starting time;
if the matching degree is greater than 0.82, the super-capacity of the heat source supply side can meet the energy-side super-supply requirement of the tail end of the building, and the super-supply operation of the middle-deep layer ground source heat pump system is calculated according to the super-capacity of the middle-deep layer ground source heat pump system, the super-supply load capacity of the user side and the super-supply time, so that the middle-deep layer ground source heat pump system operates normally until the middle-deep layer ground source heat pump system operates according to the super-supply working condition.
7. An electronic device, comprising: a processor; and
A memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any of claims 1 to 6.
8. A computer readable storage medium storing one or more programs, which when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of any of claims 1-6.
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