Fusion Control Method for Operation Simulation Prediction and Measured Data Feedback of Ground Source Heat Pump System

Abstract

The present invention relates to the technical field of operation control of a ground source heat pump system, and provides a fusion control method for operation simulation prediction and measured data feedback of a ground source heat pump system, including: S1. Constructing a ground source heat pump system model and inputting model parameters and initial boundary conditions; S2. Selecting the boundary conditions for long-term operation scheduling in the initial boundary conditions and calculating the current long-term operation scheduling plan; S3. Selecting the boundary conditions for short-term control in the initial boundary conditions, calculating and issuing a short-term control strategy plan; S4. After a short-term control ends, obtaining on-site measured data, and looping through steps S2-S4 until the current long-term operation ends. The present invention can improve the operation energy efficiency of a composite ground source heat pump system, optimize the load prediction and scheduling strategy of the system, achieve seamless connection between long-term and short-term periods, improve the system's intelligence and automation level, and ensure the stability and safety of the ground source heat pump system.

Description

Technical Field

[0001] The present invention relates to the technical field of operation control of ground source heat pump systems, and particularly relates to a method for fusing operation simulation prediction and measured data feedback control of a ground source heat pump system. Background Art

[0002] As a typical environmental protection and energy-saving technology, the ground source heat pump system has been widely used in the field of building heating and cooling in recent years. This system uses groundwater or soil as a heat source or a cold source, and realizes the exchange of thermal energy through a heat pump device, thereby providing refrigeration or heating functions. Compared with traditional air conditioning and heating systems, the energy efficiency of the ground source heat pump system is significantly improved, especially suitable for regional environments with small temperature differences, because the temperature difference required during its operation is relatively small, and it can provide a stable heat exchange effect under the condition of low energy consumption.

[0003] The combined ground source heat pump system combines the advantages of traditional ground source heat pump technology and peak shaving systems, and can maintain the efficient operation of the system in a more complex load fluctuation environment. However, there is no effective solution in traditional solutions on how to improve the operation energy efficiency of the combined ground source heat pump system and how to optimize the load prediction and scheduling strategies of the system. Therefore, there are still problems of high energy consumption, poor stability and safety during the operation of the combined ground source heat pump system. Summary of the Invention

[0004] The purpose of the present invention is to solve at least one technical problem in the background art, and provide a method for fusing operation simulation prediction and measured data feedback control of a ground source heat pump system.

[0005] To achieve the above purpose, the present invention provides a method for fusing operation simulation prediction and measured data feedback control of a ground source heat pump system, including:

[0006] S1. Construct a ground source heat pump system model, input model parameters and initial boundary conditions, and perform long-period operation scheduling of the ground source heat pump system and operation simulation of multiple short-period controls in the long period based on the ground source heat pump system model;

[0007] S2. Select the boundary conditions for the long-period operation scheduling of the ground source heat pump system model in the initial boundary conditions, and calculate the current long-period operation scheduling plan of the ground source heat pump system model;

[0008] S3. Based on the current long-period operation scheduling plan, select the boundary conditions for the short-period control of the ground source heat pump system model in the initial boundary conditions, and calculate and issue the short-period control strategy plan under the current long-period operation scheduling plan of the ground source heat pump system model;

[0009] S4. After a short-cycle control of the ground source heat pump system model ends, obtain on-site measured data, update the boundary conditions for long-cycle operation scheduling and the boundary conditions for short-cycle control based on the on-site measured data, and loop through steps S2 - S4 on the basis of the updated boundary conditions until the current long-cycle operation of the ground source heat pump system model ends;

[0010] Among them, the on-site measured data is used to update the corresponding data in the boundary conditions of step S2.

[0011] According to one aspect of the present invention, the ground source heat pump system model includes: a ground source side hydraulic model, a ground source heat pump system model, a peak shaving cooling system model, a peak shaving heating system model, and a compound ground source heat pump system model;

[0012] The initial boundary conditions include: operation mode, long-cycle control interval hours, control hours of the current short cycle, long-cycle predicted load vector, short-cycle predicted load vector, cumulative heat extraction from the shallow soil source, operation scheduling plan for the last hour of the previous short cycle, and optimal operation scheduling plan for the corresponding short cycle.

[0013] According to one aspect of the present invention, the boundary conditions for the long-cycle operation scheduling of the ground source heat pump system model selected from the initial boundary conditions are calculated to obtain the current long-cycle operation scheduling plan of the ground source heat pump system model, including:

[0014] (1) Construct and solve the long-cycle operation scheduling optimization objective function of the compound ground source heat pump system, including:

[0015] 1) Determine the long-cycle operation scheduling optimization solution objective:

[0016] Set the long-cycle operation scheduling optimization solution objective as the ground heat exchanger zoning operation variable and the peak shaving system operation variable, denoted as:

[0017] ;

[0018] ;

[0019] In the formula: is the long-cycle operation scheduling plan; is the operation scheduling plan for the kth control interval, ; is the ground source side operation scheduling plan for the kth control interval, ; is the peak shaving side operation scheduling plan for the kth control interval, ; is the operation mode for the kth control interval, -1 for the cooling season and 1 for the heating season, ; is the start / stop of the i-th ground source side partition in the k-th control interval, with 1 for start and 0 for stop. ; is the start / stop of the i-th chiller in the k-th control interval. ; is the start / stop of the i-th hot water boiler in the k-th control interval. ; is the number of long-term control intervals; is the number of ground source heat pump units; is the number of peak shaving chiller units; is the number of peak shaving heating units;

[0020] Express the operating energy consumption of the ground source heat pump system and the peak shaving system as a function that only depends on the operating scheduling scheme of the ground source side and the operating scheduling scheme of the peak shaving side:

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] In the formula: is the daily average operating power of the ground source heat pump system in the k-th control interval. is the daily average operating power of the peak shaving system in the k-th control interval. ; is the average cooling tower water consumption of the peak shaving system in the k-th control interval. ; is the average gas operating volume of the peak shaving system in the k-th control interval. ;

[0026] 2) Construct and solve the long-term operating scheduling optimization objective function:

[0027] The objective of the long-term scheduling optimization is to minimize the operating energy consumption of the hybrid ground source heat pump system as much as possible under the condition of ensuring the balance of heat extraction and rejection on the ground source side of the ground source heat pump system. The optimization objective function is:

[0028] ;

[0029] In the formula: is the optimization function; is the number of operating hours in the k-th control interval; is the unit electricity price; is the unit water price; is the unit gas price; To consider the penalty factor for the heat and cold imbalance on the ground source side; is the average heat extraction on the ground source side during the k-th control interval, ; is the cumulative heat extraction from the shallow soil source during the period from the start of the current operation season to the current long-term operation scheduling optimization solution calculation;

[0030] Use the particle swarm optimization algorithm to solve the long-term operation scheduling optimization objective function: The optimization period is from the start of the current cooling season to the start of the next cooling season or from the start of the current heating season to the end of the next heating season, including a total of 365 / 366 days in the cooling season, transition season, heating season, and transition season; The decision variables are the ground source side partition operation variables , the peak shaving system operation variables ; Obtain the long-term optimal operation scheduling plan ;

[0031] (2) Solve the long-term operation scheduling plan:

[0032] Decompose the long-term optimal operation scheduling plan calculated by the long-term operation scheduling optimization objective function into the ground heat exchanger partition operation variables and the peak shaving system operation variables:

[0033] ;

[0034] From the interlock control of the ground heat exchanger partitions on the ground source side, the ground source side circulation pumps, and the ground source heat pump units, and the interlock control of the peak shaving cooling towers, cooling tower pumps, and peak shaving chillers, obtain the start-stop information of the key equipment of the compound ground source heat pump system: is the start-stop situation of the i-th ground heat exchanger partition on the ground source side during the k-th control interval, ; is the start-stop situation of the i-th peak shaving chiller during the k-th control interval, ; is the start-stop situation of the i-th hot water boiler during the k-th control interval, ; is the number of operating units of the ground source heat pump unit during the k-th control interval; is the number of operating units of the ground source side circulation pump group during the k-th control interval; is the number of operating units of the peak shaving chiller during the k-th control interval; is the number of operating units of the cooling tower during the k-th control interval; is the number of operating units of the cooling tower circulation pump group during the k-th control interval; is the number of operating units of the peak shaving heating hot water boiler during the k-th control interval; is the control hour number during the k-th control interval.

[0035] According to one aspect of the present invention, the boundary conditions of the short - cycle control strategy optimization method for updating the ground - source heat pump system model based on the current long - cycle operation scheduling scheme are calculated, and the short - cycle control strategy scheme under the current long - cycle operation scheduling scheme of the ground - source heat pump system model is issued, including:

[0036] (1) Short - cycle load distribution:

[0037] The number of operable units of the ground - source heat pump unit and the peak - shaving unit within a short cycle is determined by the long - cycle optimal operation scheduling scheme:

[0038] ;

[0039] Where: is the number of operable units of the ground - source heat pump unit within the current short cycle; is the number of operable units of the peak - shaving chiller or peak - shaving boiler within the current short cycle; is the operation variable of the peak - shaving cooling unit within the current short cycle; is the operation variable of the peak - shaving boiler within the current short cycle;

[0040] The operation load of the ground - source heat pump system and the operation load of the peak - shaving system are determined by the short - cycle predicted load vector :

[0041] ;

[0042] Where: is the operation load of the ground - source heat pump system at the h - th hour, ; is the operation load of the peak - shaving system at the h - th hour, ; is the short - cycle predicted load vector;

[0043] (2) Calculate the optimization method of the short - cycle control strategy for the compound ground - source heat pump unit, including:

[0044] 1) Determine the relationship between the load factor of the ground - source heat pump unit and the peak - shaving system:

[0045] The load factor of any unit or hot - water boiler is calculated as follows:

[0046] ;

[0047] Where: is the actually allocated load; is the rated load;

[0048] For the ground - source heat pump unit, the load factor satisfies the relationship:

[0049] ;

[0050] In the formula: is the operating load of the ground source heat pump system; is the operating load rate of the i-th ground source heat pump unit, ; is the rated operating load of the i-th ground source heat pump unit, ;

[0051] For the peak-shaving chiller or peak-shaving boiler, the load rate satisfies the relationship:

[0052] ;

[0053] In the formula: is the operating load of the peak-shaving chiller or peak-shaving boiler; is the operating load rate of the i-th peak-shaving chiller or peak-shaving boiler, ; is the rated operating load of the i-th peak-shaving chiller or peak-shaving boiler, ;

[0054] 2) Optimization of the load rate of the ground source heat pump unit:

[0055] Construct the optimization objective function of the load rate of the ground source heat pump unit in the cooling season as follows:

[0056] ;

[0057] Among them:

[0058] ;

[0059] In the formula: is the load rate of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the minimum unit load rate of the i-th operable ground source heat pump unit; is the maximum unit load rate of the i-th operable ground source heat pump unit; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the chilled water outlet temperature of the ground source heat pump unit; is the chilled water supply temperature of the ground source heat pump unit;

[0060] By analogy with the optimization objective function of the load rate of the ground source heat pump unit in the cooling season, the optimization objective function of the load rate of the ground source heat pump unit in the heating season is as follows:

[0061] ;

[0062] Among them:

[0063] ;

[0064] In the formula: is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the hot water outlet temperature of the ground source heat pump unit; is the hot water inlet temperature of the ground source heat pump unit;

[0065] Solve the load rate of the ground source heat pump unit in the cooling season and heating season through the interior point penalty function method to determine the operating load rate of each ground source heat pump unit ; According to the unit operating load rate , the calculation formulas for the outlet water temperature of each ground source heat pump unit in the cooling season and heating season are as follows:

[0066] ;

[0067] In the formula: is the chilled water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the cooling season; is the hot water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the heating season;

[0068] 3) Optimization of the load rate of the peak shaving system:

[0069] In the peak shaving cooling system, the operating frequency of the cooling tower fan adopts open-loop approximate optimal control, and the cooling water circulating pump adopts variable frequency control with quantity regulation to ensure the minimum pressure requirement of the cooling tower water mist nozzle, and the following optimization objective function for the load rate of the peak shaving chiller is constructed:

[0070] ;

[0071] Among them:

[0072] ;

[0073] In the formula: is the unit load rate of the i-th operable peak shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak shaving chiller at the h-th hour; is the chilled water outlet temperature of the peak shaving chiller; is the chilled water supply temperature of the peak - shaving chiller

[0074] By establishing a mathematical model of the hot - water boiler, the optimization objective function of the peak - shaving chiller load rate is constructed as follows:

[0075] ;

[0076] Where:

[0077] ;

[0078] In the formula: is the load rate of the i - th operable hot - water boiler at the h - th hour; is the coefficient of the i - th operable hot - water boiler at the h - th hour; is the coefficient of the i - th operable hot - water boiler at the h - th hour; is the coefficient of the i - th operable hot - water boiler at the h - th hour; is the outlet water temperature of the hot - water boiler; is the return water temperature of the hot - water boiler;

[0079] Solve the load rates of the peak - shaving chiller and the hot - water boiler by the interior - point penalty function method to determine the operating load rates of the chiller and the boiler ; According to the operating load rate of the chiller The calculation formulas for the outlet water temperatures of each chiller and boiler in the cooling season and the heating season are as follows:

[0080] ;

[0081] In the formula: is the outlet water temperature of the i - th peak - shaving chiller at the h - th hour in the cooling season; is the outlet water temperature of the i - th hot - water boiler at the h - th hour in the heating season;

[0082] (3)Obtain the short - cycle control strategy, including:

[0083] The daily control strategy sequence in the cooling season:

[0084] is the load rate of the i - th ground - source heat pump unit at the h - th hour, ;

[0085] is the outlet chilled water temperature on the user side of the hybrid ground - source heat pump system at the h - th hour, ;

[0086] is the outlet chilled water temperature of the i - th ground - source heat pump unit at the h - th hour in the cooling season, ;

[0087] The chilled water circulation flow rate for the h-th small time interval of the cooling season ;

[0088] The return water temperature of the chilled water of the hybrid ground source heat pump system for the h-th small time interval ;

[0089] The number of operating units of the user-side circulating water pump group for the h-th hour ;

[0090] The operating frequency of the user-side circulating water pump group for the h-th hour ;

[0091] The chilled water outlet temperature of the chiller in the peak shaving system for the h-th hour of the cooling season ;

[0092] The load ratio of the chiller in the peak shaving system for the h-th hour of the cooling season ;

[0093] Daily control strategy sequence for the heating season:

[0094] The load ratio of the i-th ground source heat pump unit for the h-th hour ;

[0095] The hot water outlet temperature on the user side of the hybrid ground source heat pump system for the h-th hour ;

[0096] The hot water outlet temperature of the i-th ground source heat pump unit for the h-th hour of the heating season ;

[0097] The hot water circulation flow rate for the h-th hour of the heating season ;

[0098] The return water temperature of the chilled water of the hybrid ground source heat pump system for the h-th hour ;

[0099] The number of operating units of the user-side circulating water pump group for the h-th hour ;

[0100] The operating frequency of the user-side circulating water pump group for the h-th hour ;

[0101] For the heating season, the hot water outlet temperature of the hot water boiler in the peak shaving system at the h-th hour, ;

[0102] For the load rate of the hot water boiler in the peak shaving system at the h-th hour, .

[0103] According to one aspect of the present invention, after the end of a short-cycle control of the ground source heat pump system model, field measured data is obtained, and the boundary conditions for the long-cycle operation scheduling and the boundary conditions for the short-cycle control are updated based on the field measured data. And on the basis of updating the boundary conditions, steps S2 - S4 are cyclically executed until the current long-cycle operation of the ground source heat pump system model ends as follows:

[0104] After the end of the short-cycle control, the measured operation data of the ground source heat pump system is uploaded, and the operation scheduling plan for the last hour of the previous short cycle is extracted And the cumulative heat extraction from the shallow soil source is calculated , delete the first lines of data in the long-cycle load prediction long-cycle prediction load vector, update the short-cycle prediction load vector, and update the control hours of the current short cycle; roll and run the long-cycle operation scheduling plan and the short-cycle control strategy plan to obtain the equipment start-stop operation scheduling plan and the specific operation control strategy for each subsequent short cycle in the current long-cycle operation scheduling plan until the current long-cycle operation of the ground source heat pump system model ends.

[0105] Furthermore, to achieve the above object, the present invention also provides a ground source heat pump system operation simulation prediction and measured data feedback fusion control system, including:

[0106] A model construction module that constructs a ground source heat pump system model, inputs model parameters and initial boundary conditions, and performs long-cycle operation scheduling of the ground source heat pump system and operation simulation of multiple short-cycle controls under the long cycle based on the ground source heat pump system model;

[0107] A long-cycle operation scheduling plan calculation module that selects the boundary conditions for the long-cycle operation scheduling of the ground source heat pump system model in the initial boundary conditions and calculates the current long-cycle operation scheduling plan of the ground source heat pump system model;

[0108] A short-cycle control strategy plan calculation module that, based on the current long-cycle operation scheduling plan, selects the boundary conditions for the short-cycle control of the ground source heat pump system model in the initial boundary conditions, calculates and issues the short-cycle control strategy plan under the current long-cycle operation scheduling plan of the ground source heat pump system model;

[0109] The rolling operation module obtains on-site measured data after the end of a short-cycle control of the ground source heat pump system model, updates the boundary conditions of the long-cycle operation scheduling and the boundary conditions of the short-cycle control based on the on-site measured data, and cyclically executes the long-cycle operation scheduling scheme calculation module - rolling operation module on the basis of the updated boundary conditions until the current long-cycle operation of the ground source heat pump system model ends;

[0110] Among them, the on-site measured data is used to update the corresponding data in the boundary conditions of the long-cycle operation scheduling scheme calculation module.

[0111] Furthermore, to achieve the above object, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the ground source heat pump system operation simulation prediction and measured data feedback fusion control method as described above.

[0112] Furthermore, to achieve the above object, the present invention also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, it implements the ground source heat pump system operation simulation prediction and measured data feedback fusion control method as described above.

[0113] According to the solution of the present invention, the present invention realizes the high-efficiency operation of the ground source heat pump system and its peak shaving equipment through the combination of long-cycle and short-cycle optimal scheduling. The long-cycle optimization method can accurately predict the load demand and reasonably arrange the operation and rest time of the equipment, while the short-cycle optimization method dynamically adjusts the load rate of the unit according to the real-time load to ensure that the equipment is always in the best working state, thus significantly improving the energy efficiency of the system.

[0114] The present invention realizes the efficient utilization of energy by optimizing the consumption of various resources such as electricity, water, and gas. The optimized objective function not only considers the energy efficiency of the system operation but also considers the operation cost, including factors such as unit electricity price, unit water price, and gas price, so as to minimize the overall operation cost while ensuring the efficient operation of the system.

[0115] The present invention effectively guarantees the balance of the cooling and heating loads of the ground source heat pump system through accurate load prediction and scheduling strategies. Whether in the cooling season or the heating season, the system can dynamically adjust the operation state of the equipment to avoid the situation of cooling and heating imbalance, thus improving the stability and reliability of the system.

[0116] The present invention introduces an intelligent scheduling system that can collect on-site data in real time and combine it with optimization algorithms to automatically adjust the start / stop and operation modes of equipment. Through an adaptive control strategy, the system can quickly respond and optimize operation under various complex conditions such as load changes and season transitions. The intelligent scheduling control not only reduces manual intervention but also improves the flexibility and response speed of the system.

[0117] Through the rolling horizon optimization method, the present invention has successfully achieved seamless connection between long-term scheduling and short-term control strategies. The matching of long-term predicted load and short-term actual load ensures the stability of the system during long-term operation, while making the short-term load distribution more refined and accurate, thus improving the continuity and efficiency of system operation.

[0118] Based on the optimized scheduling, the present invention fully considers the load distribution and resource scheduling of equipment. Through intelligent algorithms and interlock control, the system can ensure the start / stop of each key equipment at the appropriate time, avoiding waste caused by over-operation or idle operation, thereby further optimizing resource allocation and reducing unnecessary energy waste.

[0119] The optimized control method of the present invention not only improves the efficiency of the ground source heat pump system but also enhances the overall effectiveness of building energy management. The combination of intelligent scheduling and optimization algorithms makes the internal energy use of the building more reasonable, thus providing technical support for building energy conservation, environmental protection, and sustainable development.

[0120] By improving the operation efficiency of the ground source heat pump system, the present invention reduces energy consumption and greenhouse gas emissions, contributing to the construction of green buildings. This technology can be widely applied in various building fields to promote the improvement of building energy efficiency and achieve the goals of environmental protection and sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0121] Figure 1 Schematically showing the flowchart of a method for fusing operation simulation prediction and measured data feedback control of a ground source heat pump system according to an embodiment of the present invention;

[0122] Figure 2 Schematically showing the operation principle diagram of a method for fusing operation simulation prediction and measured data feedback control of a ground source heat pump system according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0123] Now, the content of the present invention will be described with reference to exemplary embodiments. It should be understood that the described embodiments are only for enabling those of ordinary skill in the art to better understand and thus implement the content of the present invention, rather than implying any limitation on the scope of the present invention.

[0124] As used herein, the term "comprising" and its variants are to be construed as open-ended terms meaning "including but not limited to". The term "based on" is to be construed as "at least partially based on". The terms "an embodiment" and "one embodiment" are to be construed as "at least one embodiment".

[0125] Figure 1 Schematically shows a flowchart of a method for fusing operation simulation prediction and measured data feedback control of a ground-source heat pump system according to an embodiment of the present invention. As Figure 1 shown, in this embodiment, the method for fusing operation simulation prediction and measured data feedback control of a ground-source heat pump system includes:

[0126] S1. Construct a ground-source heat pump system model, input model parameters and initial boundary conditions, and perform long-term operation scheduling and operation simulation of multiple short-term controls in the long term based on the ground-source heat pump system model;

[0127] S2. Select the boundary conditions for the long-term operation scheduling of the ground-source heat pump system model among the initial boundary conditions, and calculate the current long-term operation scheduling scheme of the ground-source heat pump system model;

[0128] S3. Based on the current long-term operation scheduling scheme, select the boundary conditions for the short-term control of the ground-source heat pump system model among the initial boundary conditions, calculate and issue the short-term control strategy scheme under the current long-term operation scheduling scheme of the ground-source heat pump system model;

[0129] S4. After a short-term control of the ground-source heat pump system model ends, obtain on-site measured data, update the boundary conditions for long-term operation scheduling and the boundary conditions for short-term control based on the on-site measured data, and loop through steps S2 - S4 on the basis of the updated boundary conditions until the current long-term operation of the ground-source heat pump system model ends;

[0130] Among them, the on-site measured data is used to update the corresponding data in the boundary conditions of step S2.

[0131] Furthermore, according to an embodiment of the present invention, the ground-source heat pump system model includes: a ground-source side hydraulic model, a ground-source heat pump system model, a peak-shaving cooling system model, a peak-shaving heating system model, and a composite ground-source heat pump system model;

[0132] The initial boundary conditions include: an operation mode vector 、the number of hours of long-term control interval, the number of control hours of the current short term, a long-term predicted load vector 、a short-term predicted load vector 、the cumulative heat extraction from the shallow soil source 、the operation scheduling scheme of the last hour of the previous short term , the optimal operation scheduling plan for the corresponding short period.

[0133] Furthermore, according to an embodiment of the present invention, select the boundary conditions for the long-period operation scheduling of the ground source heat pump system model in the initial boundary conditions, and calculate the current long-period operation scheduling plan of the ground source heat pump system model, including:

[0134] (1) Select the following boundary conditions:

[0135] Operation mode vector ;

[0136] Outdoor wet bulb temperature vector ;

[0137] Long-period predicted load vector ;

[0138] Long-period control interval in hours ;

[0139] Accumulated heat extraction from the shallow soil source ;

[0140] Operation scheduling plan for the last hour of the previous short period ;

[0141] (2) Construct and solve the optimization objective function for the long-period operation scheduling of the compound ground source heat pump system, including:

[0142] 1) Determine the optimization solution objective for the long-period operation scheduling:

[0143] Set the optimization solution objective for the long-period operation scheduling as the operation variables of the buried pipe partition and the operation variables of the peak shaving system, denoted as:

[0144] ;

[0145] ;

[0146] Where: X is the long-period operation scheduling plan; is the operation scheduling plan for the kth control interval, ; is the operation scheduling plan for the ground source side at the kth control interval, ; is the operation scheduling plan for the peak shaving side at the kth control interval, ; is the operation mode at the kth control interval, -1 for the cooling season and 1 for the heating season, ; is the start / stop of the ith ground source side partition at the kth control interval, 1 for on and 0 for off, ; is the start / stop of the i-th chiller in the k-th control interval, ; is the start / stop of the i-th hot water boiler in the k-th control interval, ; is the number of long-term control intervals; is the number of ground source heat pump units; is the number of peak shaving chiller units; is the number of peak shaving heating units;

[0147] Express the operating energy consumption of the ground source heat pump system and the peak shaving system as a function that only depends on the operation scheduling scheme on the ground source side and the operation scheduling scheme on the peak shaving side:

[0148] ;

[0149] ;

[0150] ;

[0151] ;

[0152] In the formula: is the daily average operating power of the ground source heat pump system in the k-th control interval, is the daily average operating power of the peak shaving system in the k-th control interval, ; is the average cooling tower water consumption of the peak shaving system in the k-th control interval, ; is the average gas operating volume of the peak shaving system in the k-th control interval, ;

[0153] 2) Construct and solve the long-term operation scheduling optimization objective function:

[0154] The objective of the long-term scheduling optimization solution is to minimize the operating energy consumption of the composite ground source heat pump system as much as possible under the condition of ensuring the balance of cold and heat extraction on the ground source side of the ground source heat pump system. The optimization objective function is:

[0155] ;

[0156] In the formula: F is the optimization function; is the number of operating hours in the k-th control interval; is the unit electricity price; is the unit water price; is the unit gas price; is the penalty factor for considering the cold and heat imbalance on the ground source side; is the average heat extraction on the ground source side in the k-th control interval, ; is the cumulative heat extraction from the shallow soil source from the start of the current operation season to the calculation of the optimal solution for the long-cycle operation scheduling this time;

[0157] Use the particle swarm optimization algorithm to solve the long-cycle operation scheduling objective function: The optimization period is from the start of the current cooling season to the start of the next cooling season or from the start of the current heating season to the end of the next heating season, including a total of 365 / 366 days for the cooling season, transition season, heating season, and transition season; the decision variables are the operation variables of the ground source side partitions , and the operation variables of the peak shaving system ; Obtain the optimal long-cycle operation scheduling plan ;

[0158] (3) Solve the long-cycle operation scheduling plan:

[0159] Decompose the optimal long-cycle operation scheduling plan calculated by the long-cycle operation scheduling objective function into the operation variables representing the ground heat exchanger partitions and the peak shaving system:

[0160] ;

[0161] From the interlocking control of the ground source side ground heat exchanger partitions, the ground source side circulating water pumps, and the ground source heat pump units, and the interlocking control of the peak shaving cooling towers, cooling tower pumps, and peak shaving chillers, obtain the start-stop information of the key equipment of the compound ground source heat pump system: is the start-stop situation of the i-th ground source side ground heat exchanger partition in the k-th control interval, ; is the start-stop situation of the i-th peak shaving chiller in the k-th control interval, ; is the start-stop situation of the i-th hot water boiler in the k-th control interval, ; is the number of operating units of the ground source heat pump unit in the k-th control interval; is the number of operating units of the ground source side circulating water pump group in the k-th control interval; is the number of operating units of the peak shaving chiller in the k-th control interval; is the number of operating units of the cooling tower in the k-th control interval; is the number of operating units of the cooling tower circulating water pump group in the k-th control interval; is the number of operating units of the peak shaving heating hot water boiler in the k-th control interval; is the control hour number of the k-th control interval.

[0162] In this embodiment, extract the long-cycle operation scheduling plan calculated by the long-cycle optimization scheduling algorithm The first vector in is, that is , as the optimal operation scheduling plan for the short cycle.

[0163] Furthermore, according to an embodiment of the present invention, based on the current long-cycle operation scheduling plan, select the boundary conditions for the short-cycle control in the initial boundary conditions for the ground source heat pump system model, calculate and issue the short-cycle control strategy plan under the current long-cycle operation scheduling plan of the ground source heat pump system model, including:

[0164] (1) Select the following boundary conditions:

[0165] Operation mode vector ;

[0166] Optimal operation scheduling plan corresponding to the short cycle ;

[0167] Control hours of the current short cycle ;

[0168] Outdoor wet bulb temperature vector ;

[0169] Short cycle predicted load vector ;

[0170] (2) Short cycle load distribution:

[0171] The number of operable units of the ground source heat pump unit and the peak shaving unit within the short cycle is determined by the long-cycle optimal operation scheduling plan:

[0172] ;

[0173] Where: is the number of operable units of the ground source heat pump unit within the current short cycle; is the number of operable units of the peak shaving chiller or peak shaving boiler within the current short cycle; is the operation variable of the peak shaving cooling unit within the current short cycle; is the operation variable of the peak shaving boiler within the current short cycle;

[0174] Determine the operation load of the ground source heat pump system and the operation load of the peak shaving system from the short cycle predicted load vector :

[0175] ;

[0176] Where: is the operation load of the ground source heat pump system at the hth hour, ; is the operation load of the peak shaving system at the hth hour, ; is the short cycle predicted load vector;

[0177] (3)Calculate the optimization method for the short - cycle control strategy of the compound ground - source heat pump unit, including:

[0178] 1) Determine the relationship between the load rate of the ground - source heat pump unit and the peak - shaving system:

[0179] The load rate of any unit or hot - water boiler is calculated as follows:

[0180] ;

[0181] In the formula: is the actual allocated load; is the rated load;

[0182] For the ground - source heat pump unit, the load rate satisfies the relationship:

[0183] ;

[0184] In the formula: is the operating load of the ground - source heat pump system; is the operating load rate of the i - th ground - source heat pump unit, ; is the rated operating load of the i - th ground - source heat pump unit, ;

[0185] For the peak - shaving chiller or peak - shaving boiler, the load rate satisfies the relationship:

[0186] ;

[0187] In the formula: is the operating load of the peak - shaving chiller or peak - shaving boiler; is the operating load rate of the i - th peak - shaving chiller or peak - shaving boiler, ; is the rated operating load of the i - th peak - shaving chiller or peak - shaving boiler, ;

[0188] 2) Optimization of the load rate of the ground - source heat pump unit:

[0189] Construct the optimization objective function for the load rate of the ground - source heat pump unit in the cooling season as follows:

[0190] ;

[0191] Among them:

[0192] ;

[0193] In the formula: is the load rate of the i - th operable ground - source heat pump unit at the h - th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the minimum unit load rate of the i-th operable ground source heat pump unit; is the maximum unit load rate of the i-th operable ground source heat pump unit; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the chilled water outlet temperature of the ground source heat pump unit;

[0194] is the chilled water supply temperature of the ground source heat pump unit;

[0195] Analogous to the optimization objective function of the ground source heat pump unit load rate in the cooling season, the optimization objective function of the ground source heat pump unit load rate in the heating season is as follows:

[0196] ;

[0197] Where:

[0198] ;

[0199] In the formula: is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the hot water outlet temperature of the ground source heat pump unit; is the hot water inlet temperature of the ground source heat pump unit;

[0200] Solve the load rate of the ground source heat pump unit in the cooling season and heating season through the interior point penalty function method to determine the operating load rate of each ground source heat pump unit ; According to the unit operating load rate , the calculation formulas for the outlet temperature of each ground source heat pump unit in the cooling season and heating season are as follows:

[0201] ;

[0202] In the formula: is the chilled water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the cooling season; is the hot water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the heating season;

[0203] 3) Optimization of the load rate of the peak shaving system:

[0204] In the peak shaving cooling system, the operating frequency of the cooling tower fan adopts open-loop approximate optimal control, and the cooling water circulating pump adopts variable frequency control with quantity adjustment to ensure the minimum pressure requirement of the cooling tower water mist nozzle. The optimization objective function of the peak shaving chiller load rate is constructed as follows:

[0205] ;

[0206] Where:

[0207] ;

[0208] In the formula: is the unit load rate of the i-th operable peak shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak shaving chiller at the h-th hour; is the chilled water outlet temperature of the peak shaving chiller; is the chilled water supply temperature of the peak shaving chiller;

[0209] By establishing a mathematical model of the hot water boiler, the optimization objective function of the peak shaving chiller load rate is constructed as follows:

[0210] ;

[0211] Where:

[0212] ;

[0213] In the formula: is the load rate of the i-th operable hot water boiler at the h-th hour; is the coefficient of the i-th operable hot water boiler at the h-th hour; is the coefficient of the i-th operable hot water boiler at the h-th hour; is the coefficient of the i-th operable hot water boiler at the h-th hour; is the hot water boiler outlet temperature; is the hot water boiler return water temperature;

[0214] Solve the load rates of the peak shaving chiller and the hot water boiler by the interior point penalty function method to determine the operating load rates of the chiller and the boiler ; According to the operating load rate of the chiller , the calculation formulas for the outlet temperatures of each chiller and boiler in the cooling season and heating season are as follows:

[0215] ;

[0216] In the formula: During the cooling season, at the h-th hour, the outlet water temperature of the i-th peak-shaving chiller; During the heating season, at the h-th hour, the outlet water temperature of the i-th hot water boiler;

[0217] In this embodiment, the load rate calculation formula for any unit or hot water boiler is:

[0218] ;

[0219] Where: is the actual allocated load, kW; is the rated load, kW;

[0220] For a ground source heat pump unit, the load rate satisfies the relationship:

[0221] ;

[0222] Where: is the operating load of the ground source heat pump system, kW; is the operating load rate of the i-th ground source heat pump unit, ; is the rated operating load of the i-th ground source heat pump unit, , kW;

[0223] For a peak-shaving chiller or a peak-shaving boiler, the load rate satisfies the relationship:

[0224] ;

[0225] Where: is the operating load of the peak-shaving chiller or the peak-shaving boiler, kW; is the operating load rate of the i-th peak-shaving chiller or the i-th peak-shaving boiler, ; is the rated operating load of the i-th peak-shaving chiller or the i-th peak-shaving boiler, , kW;

[0226] (4) Obtain the short-term control strategy, including:

[0227] Daily control strategy sequence for the cooling season:

[0228] is the load rate of the i-th ground source heat pump unit at the h-th hour, ;

[0229] is the chilled water outlet temperature on the user side of the compound ground source heat pump system at the h-th hour, ;

[0230] During the cooling season, the chilled water outlet temperature of the i-th ground source heat pump unit at the h-th hour, ;

[0231] is the chilled water circulation flow rate during the intermittent cooling season at the h-th hour, ;

[0232] is the chilled water return temperature of the hybrid ground source heat pump system at the h-th hour, ;

[0233] is the number of operating units of the user-side circulating water pump group at the h-th hour, ;

[0234] is the operating frequency of the user-side circulating water pump group at the h-th hour, ;

[0235] During the cooling season, the chilled water outlet temperature of the chiller in the peak shaving system at the h-th hour, ;

[0236] is the load rate of the chiller in the peak shaving system during the cooling season at the h-th hour, ;

[0237] Daily control strategy sequence for the heating season:

[0238] is the load rate of the i-th ground source heat pump unit at the h-th hour, ;

[0239] is the hot water outlet temperature on the user side of the hybrid ground source heat pump system at the h-th hour, ;

[0240] During the heating season, the hot water outlet temperature of the i-th ground source heat pump unit at the h-th hour, ;

[0241] is the hot water circulation flow rate during the heating season at the h-th hour, ;

[0242] is the chilled water return temperature of the hybrid ground source heat pump system at the h-th hour, ;

[0243] is the number of operating units of the user-side circulating water pump group at the h-th hour, ;

[0244] is the operating frequency of the user-side circulating water pump group in the h-th hour, ;

[0245] is the hot water outlet temperature of the peak-shaving system's hot water boiler in the h-th hour of the heating season, ;

[0246] is the load rate of the peak-shaving system's hot water boiler in the h-th hour, .

[0247] Furthermore, in this embodiment, as shown in Figure 2 , the present invention can construct a long-short cycle coupled rolling time domain operation optimization method for the ground source heat pump system based on the above current long-cycle operation scheduling scheme and short-cycle control strategy scheme, combined with on-site measured data. The operation steps are as follows:

[0248] In the current long-cycle operation scheduling scheme, the long-cycle predicted load vector is used as the main input control boundary condition of this method. Through the above method, the operation scheduling scheme X for each control interval in the current long cycle is calculated. Take the operation scheduling scheme of the first control interval as the start-stop operation scheduling scheme of each key device in the next control short cycle.

[0249] In the short-cycle control strategy scheme, the short-cycle operation scheduling scheme and the short-cycle predicted load vector are used as the main input control boundary conditions. Through the above method, the specific operation control strategies of each unit in the current short cycle are calculated.

[0250] The start-stop operation scheduling scheme of the short-cycle key devices and the specific operation control strategies are sent to each device at the actual site through the automatic control system to control the operation of each device in the ground source heat pump system in the current short cycle.

[0251] Furthermore, according to an embodiment of the present invention, after a short-cycle control of the ground source heat pump system model is completed, on-site measured data is obtained, and the boundary conditions of the long-cycle operation scheduling and the boundary conditions of the short-cycle control are updated based on the on-site measured data. And on the basis of updating the boundary conditions, steps S2-S4 are cyclically executed until the current long-cycle operation of the ground source heat pump system model ends:

[0252] After the short-cycle control is completed, the measured operation data of the ground source heat pump system is uploaded, and the operation scheduling scheme of the last hour of the previous short cycle is extracted and the cumulative heat extraction from the shallow soil source is calculated , and the front part of the long-cycle load prediction long-cycle predicted load vector is deleted Line data, call the relevant load forecasting algorithm to update the short-term forecasting load vector , update the control hours of the current short cycle , run the long-term operation scheduling plan and the short-term control strategy plan in a rolling manner to obtain the equipment start-stop operation scheduling plan and specific operation control strategies for each subsequent short cycle in the current long-term operation scheduling plan until the current long-term operation of the ground source heat pump system model ends.

[0253] According to the above solution of the present invention, the present invention can improve the operation energy efficiency of the composite ground source heat pump system: by adopting an optimized scheduling method combining long cycles and short cycles, accurately predicting the system load and dynamically adjusting the operation state of the equipment, realizing the coordinated and efficient operation of the ground source heat pump system and the peak shaving system. On the premise of ensuring the thermal balance of the ground source side of the system, the energy consumption is reduced as much as possible, and the energy configuration of the system is optimized.

[0254] The present invention can optimize the load forecasting and scheduling strategies of the system: by using the improved genetic algorithm to optimize the long-term and short-term operation scheduling objective functions, solving the scheduling problem of the ground source heat pump system under variable load conditions, ensuring the accurate distribution of the load in each cycle, and improving the load forecasting accuracy and scheduling response speed of the system.

[0255] The present invention can achieve seamless connection between long cycles and short cycles: through the rolling horizon optimization method, the present invention establishes an effective feedback mechanism between long cycles and short cycles, ensuring the continuity and consistency of the two scheduling plans. Using real-time data feedback, dynamically adjust the long-term boundary conditions and short-term control strategies, thereby improving the adaptability and intelligent level of the system at different time scales.

[0256] The present invention can improve the intelligent and automatic level of the system: the intelligent scheduling system designed by the present invention can monitor the operation states of the ground source heat pump system and the peak shaving equipment in real time, and automatically adjust the start-stop and operation modes of the equipment through the adaptive optimization algorithm. This intelligent scheduling method greatly improves the operation efficiency and stability of the system, and reduces the manual intervention and management costs.

[0257] The present invention can ensure the stability and safety of the ground source heat pump system: through multi-level interlock control and optimized scheduling strategies, the present invention ensures the coordinated operation of the key equipment of the composite ground source heat pump system in each operation cycle, thereby ensuring the stability and safety of the system under load fluctuations, seasonal changes and complex environments.

[0258] Furthermore, to achieve the above object, the present invention also provides a fusion control system for the operation simulation prediction and measured data feedback of a ground source heat pump system, including:

[0259] A model construction module that constructs a ground source heat pump system model, inputs model parameters and initial boundary conditions, and performs long-term operation scheduling of the ground source heat pump system and operation simulation of multiple short-term controls in the long term based on the ground source heat pump system model;

[0260] A long-term operation scheduling plan calculation module that selects the boundary conditions for the long-term operation scheduling of the ground source heat pump system model from the initial boundary conditions and calculates the current long-term operation scheduling plan for the ground source heat pump system model;

[0261] A short-term control strategy plan calculation module that, based on the current long-term operation scheduling plan, selects the boundary conditions for the short-term control of the ground source heat pump system model from the initial boundary conditions, calculates and issues the short-term control strategy plan under the current long-term operation scheduling plan of the ground source heat pump system model;

[0262] A rolling operation module that, after the end of a short-term control of the ground source heat pump system model, obtains on-site measured data, updates the boundary conditions for the long-term operation scheduling and the boundary conditions for the short-term control based on the on-site measured data, and cyclically executes the long-term operation scheduling plan calculation module - rolling operation module on the basis of the updated boundary conditions until the current long-term operation of the ground source heat pump system model ends;

[0263] Among them, the on-site measured data is used to update the corresponding data in the boundary conditions of the long-term operation scheduling plan calculation module.

[0264] The ground source heat pump system operation simulation prediction and measured data feedback fusion control system according to the present invention can implement the above-mentioned ground source heat pump system operation simulation prediction and measured data feedback fusion control method. The specific method steps are as described above and will not be elaborated here.

[0265] Furthermore, to achieve the above object, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the above-mentioned ground source heat pump system operation simulation prediction and measured data feedback fusion control method.

[0266] Furthermore, to achieve the above object, the present invention also provides a computer-readable storage medium with a computer program stored thereon. When the computer program is executed by the processor, it implements the above-mentioned ground source heat pump system operation simulation prediction and measured data feedback fusion control method.

[0267] Those of ordinary skill in the art will recognize that the modules and algorithm steps described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled professionals can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the present invention.

[0268] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0269] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there can be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or modules can be in electrical, mechanical or other forms.

[0270] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they can be located in one place, or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the embodiments of the present invention.

[0271] In addition, the various functional modules in the embodiments of the present invention can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0272] When the above-mentioned functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method for sending / receiving energy-saving signals in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0273] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the technical solution formed by mutually replacing the above features with the (but not limited to) technical features with similar functions disclosed in the present application.

[0274] It should be understood that the magnitudes of the sequence numbers of the steps in the content and embodiments of the present invention do not absolutely mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

Claims

1. A ground source heat pump system operation simulation prediction and measured data feedback fusion control method, characterized in that: include: S1. Construct a geothermal heat pump system model, input model parameters and initial boundary conditions, and perform long-term operation scheduling of the geothermal heat pump system and operation simulation of multiple short-term controls under long-term operation based on the geothermal heat pump system model; S2. Selecting the boundary conditions for the long-term operation scheduling of the ground source heat pump system model in the initial boundary conditions, and calculating the current long-term operation scheduling scheme of the ground source heat pump system model; S3. Based on the current long-cycle operation scheduling scheme, select the boundary conditions for short-cycle control of the ground source heat pump system model in the initial boundary conditions, calculate and issue the short-cycle control strategy scheme under the current long-cycle operation scheduling scheme of the ground source heat pump system model; S4. After a short-cycle control of the geothermal heat pump system model is completed, the field measured data is obtained, and the boundary conditions of the long-cycle operation scheduling and the boundary conditions of the short-cycle control are updated based on the field measured data, and the steps S2 to S4 are executed cyclically based on the updated boundary conditions until the current long-cycle operation of the geothermal heat pump system model is completed; Among them, the field measured data is used to update the corresponding data in the boundary conditions of step S2; The ground source heat pump system model includes: a ground source side hydraulic model, a peak-shaving cooling system model, a peak-shaving heating system model and a ground source heat pump model; The initial boundary conditions include: operation mode, long-cycle control interval hours, current short-cycle control hours, long-cycle predicted load vector, short-cycle predicted load vector, shallow soil source cumulative heat extraction, operation scheduling plan for the last hour of the previous short cycle, and the optimal operation scheduling plan under the corresponding short cycle.

2. The method for fusion control of ground source heat pump system operation simulation prediction and measured data feedback according to claim 1 is characterized in that: The step of selecting the boundary conditions for the long-term operation scheduling of the ground source heat pump system model in the initial boundary conditions and calculating the current long-term operation scheduling scheme of the ground source heat pump system model includes: (1) Construct and solve the long-term operation scheduling optimization objective function of the ground source heat pump system, including: 1) Determine the long-term operation scheduling optimization solution target: The long-term operation scheduling optimization solution target is set as the ground source side partition operation variable and the peak load system operation variable, which is recorded as: ； Where: Provide scheduling solutions for long-term operations; Run the schedule for the kth control interval, ; is the scheduling scheme for the source side operation of the kth control interval, ; is the peak load side operation scheduling plan for the kth control interval, ; Control the number of intervals for long periods; The operating energy consumption of the ground source heat pump system and the peak load regulation system is expressed as a function that is only related to the ground source side operation scheduling scheme and the peak load regulation side operation scheduling scheme: ； ； ； ； Where: is the daily average operating power of the ground source heat pump system in the kth control interval, ; is the daily average operating power of the peak load regulation system in the kth control interval, ; is the average cooling tower water consumption of the k-th control interval peak load system, ; is the average gas operation volume of the peak-shaving system in the kth control interval, ; 2) Construct and solve the long-term operation scheduling optimization objective function: The goal of long-term scheduling optimization is to reduce the operating energy consumption of the ground source heat pump system as much as possible while ensuring the balance of cooling and heating on the ground source side of the ground source heat pump system. The optimization objective function is: ； Where: Provide scheduling solutions for long-term operations; is the number of operating hours in the kth control interval; is the unit electricity price; is the unit water price; is the unit gas price; To consider the penalty factor of heat and cold imbalance on the ground source side; is the average heat taken from the source side of the kth control interval, ; The cumulative heat taken by the shallow soil source from the beginning of this year's operating season to the optimization solution calculation of this long-term operation scheduling; The particle swarm algorithm is used to solve the long-term operation scheduling optimization objective function: the optimization period is from the beginning of the cooling season of the current year to the beginning of the cooling season of the next year or from the beginning of the heating season of the current year to the end of the heating season of the next year, including the cooling season, transition season, heating season, and transition season, a total of 365 / 366 days; the decision variables are the ground source side partition operation variables and the peak load system operation variables; the optimal long-term operation scheduling scheme is obtained by solving ; (2) Solving the long-term operation scheduling plan: The optimal long-term operation scheduling solution calculated by the long-term operation scheduling optimization objective function Decomposed into the operating variables of the ground source side partition and the peak load system operating variables: ； The start and stop information of key equipment of the ground source heat pump system is obtained through the interlocking control of the buried pipe on the ground source side, the circulating water pump on the ground source side and the ground source heat pump unit, the interlocking control of the peak-shaving cooling tower, the cooling tower water pump and the peak-shaving chiller unit: The start and stop of the i-th ground source side partition of the k-th control interval, which is 1 for start and 0 for shutdown. , ; is the start and stop of the i-th peak-shaving chiller in the k-th control interval, , ; is the start and stop of the i-th hot water boiler in the k-th control interval, , ; Control the number of intervals for long periods; is the number of ground source heat pump units; The number of peak-shaving refrigeration units; The number of heating units for peak load regulation; is the kth control interval operation mode, -1 for cooling season and 1 for heating season. .

3. The ground source heat pump system operation simulation prediction and measured data feedback fusion control method according to claim 2 is characterized in that: The method comprises: selecting a boundary condition for short-cycle control of the ground source heat pump system model in the initial boundary condition based on the current long-cycle operation scheduling scheme, and calculating and issuing a short-cycle control strategy scheme under the current long-cycle operation scheduling scheme of the ground source heat pump system model. (1) Short-cycle load distribution: The number of local heat pump units and peak load units that can be operated in the short period is determined by the long-term optimal operation scheduling plan: ； Where: The number of local source heat pump units that can be operated in the current short period; The number of peak-shaving chillers or peak-shaving boilers that can be operated in the current short period; It is the operating variable of the peak-shaving cooling unit in the current short cycle; It is the operating variable of the peak load boiler in the current short period; The load vector is predicted by the short-term Determine the operating load of the ground source heat pump system and the peak load regulation system: ； Where: is the operating load of the ground source heat pump system in the hth hour, ; is the peak load of the system in the hth hour, ; Forecast load vectors for short periods; (2) The optimization method of the short-cycle control strategy of the ground source heat pump unit is calculated, including: 1) Determine the relationship between the load rate ground source heat pump unit and the peak load regulation system: The load rate of any unit or hot water boiler is calculated as follows: ； Where: To distribute the load in reality; is the rated load; For ground source heat pump units, the load rate satisfies the relationship: ； Where: Operating load for the ground source heat pump system; is the operating load rate of the i-th ground source heat pump unit, ; is the rated operating load of the i-th ground source heat pump unit, ; For peak-shaving chillers or peak-shaving boilers, the load factor satisfies the relationship: ； Where: To peak the chiller or boiler operating load; is the operating load rate of the i-th peak-shaving chiller or peak-shaving boiler, ; is the rated operating load of the i-th peak-shaving chiller or peak-shaving boiler, ; 2) Optimization of load rate of ground source heat pump units: The objective function for optimizing the load rate of ground source heat pump units in the cooling season is constructed as follows: ； in: ； Where: is the unit load rate of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the minimum unit load rate of the i-th operable ground source heat pump unit; is the maximum unit load rate of the i-th operable ground source heat pump unit; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; The outlet temperature of chilled water of the ground source heat pump unit; The chilled water supply temperature of the ground source heat pump unit; Analogous to the load rate optimization objective function of the ground source heat pump unit in the cooling season, the load rate optimization objective function of the ground source heat pump unit in the heating season is as follows: ； in: ； Where: is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; is the unit coefficient of the i-th operable ground source heat pump unit at the h-th hour; The hot water outlet temperature of the ground source heat pump unit; is the hot water inlet temperature of the ground source heat pump unit; The load rate of ground source heat pump units in the cooling and heating seasons is solved by the interior point penalty function method, and the operating load rate of ground source heat pump units in each region is determined ; According to the unit operating load rate The calculation formula for the outlet water temperature of each local heat pump unit in the cooling season and heating season is as follows: ； Where: is the chilled water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the cooling season; is the hot water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the heating season; 3) Peak load rate optimization of the peak load regulation system: In the peak-shaving cooling system, the fan operating frequency of the cooling tower is controlled by open-loop approximate optimal control, and the cooling water circulation pump is controlled by variable frequency control to ensure the minimum pressure requirement of the cooling tower water mist nozzle. The load rate optimization objective function of the peak-shaving chiller is constructed as follows: ； in: ； Where: is the unit load rate of the i-th operable peak-shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak-shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak-shaving chiller at the h-th hour; is the unit coefficient of the i-th operable peak-shaving chiller at the h-th hour; The outlet temperature of chilled water for peak-shaving chillers; To adjust the chilled water supply temperature of the peak-shaving chiller; By establishing a mathematical model of the hot water boiler, the load rate optimization objective function of the peak-shaving chiller is constructed as follows: ； in: ； Where: is the load rate of the i-th operable hot water boiler at the h-th hour; is the coefficient of the i-th operable hot water boiler at the h-th hour; is the coefficient of the i-th operable hot water boiler at the h-th hour; is the coefficient of the i-th operable hot water boiler at the h-th hour; is the outlet water temperature of the hot water boiler; is the return water temperature of the hot water boiler; The load rate of the peak-shaving chiller and hot water boiler is solved by the interior point penalty function method to determine the operating load rate of the unit and boiler ; According to the unit operating load rate , the calculation formula for the outlet water temperature of each unit and boiler in the cooling season and heating season is as follows: ； Where: is the outlet water temperature of the i-th peak-shaving chiller at the h-th hour in the cooling season; is the outlet water temperature of the i-th hot water boiler at the h-th hour in the heating season; (3) Obtain short-cycle control strategies, including: Cooling season daily control strategy sequence: is the load rate of the i-th ground source heat pump unit in the h-th hour, ; is the chilled water outlet temperature of the user side of the ground source heat pump system at hour h, ; In the cooling season, the chilled water outlet temperature of the i-th ground source heat pump unit at the h-th hour is ; is the chilled water circulation flow rate in the h-hour interval cooling season, ; is the chilled water return temperature of the ground source heat pump system at the h-hour interval, ; is the number of operating circulating water pumps on the user side at hour h, ; is the operating frequency of the circulating water pump group on the user side at the hth hour, ; In the cooling season, the chilled water outlet temperature of the peak load system chiller in the h hour is ; is the load rate of the chiller in the peak load regulation system in the hth hour during the cooling season. ; Heating season daily control strategy sequence: is the load rate of the i-th ground source heat pump unit in the h-th hour, ; is the hot water outlet temperature of the ground source heat pump system at the user side at the hth hour, ; is the hot water outlet temperature of the i-th ground source heat pump unit at the h-th hour in the heating season, ; is the hot water circulation flow rate in the hth hour of the heating season, ; is the chilled water return temperature of the ground source heat pump system at hour h, ; is the number of operating circulating water pumps on the user side at hour h, ; is the operating frequency of the circulating water pump group on the user side at the hth hour, ; is the outlet water temperature of the hot water boiler in the peak load regulation system at hour h during the heating season. ; is the load rate of the hot water boiler in the peak load regulation system at hour h, .

4. The method for fusion control of ground source heat pump system operation simulation prediction and measured data feedback according to claim 3 is characterized in that: After a short-cycle control of the geothermal heat pump system model is completed, the field measured data is obtained, the boundary conditions of the long-cycle operation scheduling and the boundary conditions of the short-cycle control are updated based on the field measured data, and the steps S2 to S4 are cyclically executed on the basis of the updated boundary conditions until the current long-cycle operation of the geothermal heat pump system model is completed: After the short-cycle control is completed, the measured ground source heat pump system operation data is uploaded to extract the operation scheduling plan for the last hour of the previous short cycle. And calculate the cumulative heat taken by the shallow soil source , delete the long-term load forecast long-term forecast load vector The data is updated, the short-cycle forecast load vector is updated, and the control hours of the current short cycle are updated; the long-cycle operation scheduling plan and the short-cycle control strategy plan are rolled out to obtain the equipment start-stop operation scheduling plan and specific operation control strategy for subsequent short cycles in the current long-cycle operation scheduling plan until the current long-cycle operation of the ground source heat pump system model ends.

5. The ground source heat pump system operation simulation prediction and measured data feedback fusion control system is characterized by: include: Model building module, builds the ground source heat pump system model, inputs model parameters and initial boundary conditions, and performs long-term operation scheduling of the ground source heat pump system and operation simulation of multiple short-term controls under long-term based on the ground source heat pump system model; The long-term operation scheduling scheme calculation module selects the boundary conditions for the long-term operation scheduling of the ground source heat pump system model in the initial boundary conditions, and calculates the current long-term operation scheduling scheme of the ground source heat pump system model; The short-cycle control strategy calculation module selects the boundary conditions for the short-cycle control of the ground source heat pump system model in the initial boundary conditions based on the current long-cycle operation scheduling plan, calculates and issues the short-cycle control strategy under the current long-cycle operation scheduling plan of the ground source heat pump system model; The rolling operation module obtains the field measured data after a short-cycle control of the ground source heat pump system model ends, updates the boundary conditions of the long-cycle operation scheduling and the boundary conditions of the short-cycle control based on the field measured data, and cyclically executes the long-cycle operation scheduling scheme calculation module-rolling operation module on the basis of the updated boundary conditions until the current long-cycle operation of the ground source heat pump system model ends; Among them, the field measured data is used to update the corresponding data in the boundary conditions of the long-term operation scheduling scheme calculation module; The ground source heat pump system model includes: a ground source side hydraulic model, a peak-shaving cooling system model, a peak-shaving heating system model and a ground source heat pump model; The initial boundary conditions include: operation mode, long-cycle control interval hours, current short-cycle control hours, long-cycle predicted load vector, short-cycle predicted load vector, shallow soil source cumulative heat extraction, operation scheduling plan for the last hour of the previous short cycle, and the optimal operation scheduling plan under the corresponding short cycle.

6. An electronic device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the ground source heat pump system operation simulation prediction and measured data feedback fusion control method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method for fusion control of ground source heat pump system operation simulation prediction and measured data feedback is implemented as described in any one of claims 1 to 4.

Images