Evaluation method of solar coupling medium-deep ground source heat pump hot water supply system

Abstract

The invention discloses an evaluation method of a solar coupling medium-deep ground source heat pump hot water supply system, which relates to the technical field of heat supply systems and comprises the following steps: acquiring various performance indexes based on historical environment parameters, historical system operation parameters and historical energy consumption parameters; the comprehensive energy efficiency ratio, the heat utilization efficiency and the comprehensive performance score of the system are obtained through the multiple performance parameters; and taking the historical environment parameters, the historical system operation parameters and the historical energy consumption parameters as inputs, taking the corresponding system comprehensive energy efficiency ratio, the heat utilization efficiency and the system comprehensive performance score as outputs, and training the neural network model to obtain an evaluation model. According to the method, comprehensive performance evaluation under cooperative work is emphasized, the concept of the comprehensive energy efficiency ratio of the system is put forward, the relation between effective heat output of the system and various input energy consumption of solar energy, the ground source heat pump, auxiliary energy and the like is comprehensively considered, the system performance is comprehensively evaluated, and compared with a single ground source heat pump system, the performance evaluation index is more comprehensive.

Description

Technical Field

[0001] The present invention relates to the technical field of heating systems, and particularly to an evaluation method for a solar-coupled medium-deep geothermal heat pump hot water supply system. Background Art

[0002] With the transformation of the energy structure and the increasing demand for clean energy, multi-energy complementary heating systems have become a research hotspot. Such systems can integrate multiple energy sources such as solar energy and geothermal energy, improve energy utilization efficiency, and reduce environmental pollution. Solar energy, as a renewable energy source, has the characteristics of seasonality and instability. To solve this problem, the rock and soil mass can be used as an energy storage carrier to store solar energy in the form of heat in the non-heating season for cross-seasonal heat storage, maximizing the annual utilization rate of the solar thermal system and minimizing the attenuation of the ground temperature field, and establishing a system capable of storing and regulating energy to ensure the continuity and stability of heating. The multi-energy complementary heating system switches different working modes according to the supply situation of different energy sources and the heat demand by integrating solar collectors and geothermal units, etc., to achieve the complementarity and coupling of energy sources and improve energy utilization efficiency.

[0003] The solar-coupled medium-deep geothermal heat pump hot water supply system is a common multi-energy complementary heating system. It involves the coupling and conversion of multiple energy sources, including multiple links such as solar heat collection, heat exchange of the geothermal heat pump, and hot water supply. In order to measure the pros and cons of the system operation performance under various links, it is necessary to establish a set of index systems that can scientifically and comprehensively evaluate the system performance, and comprehensively evaluate the real-time operation of the solar-coupled medium-deep geothermal heat pump hot water supply system through this index system.

[0004] The existing evaluation methods for multi-energy complementary heating systems mainly establish a coupled heat transfer model database of the ground heat exchanger - heat pump - building by using design parameter data group simulation calculation, establish a neural network model by forming a mapping between the design parameters and the operation results, and input the design parameters to predict the energy efficiency ratio, energy conservation and emission reduction, and the ground temperature in the buried pipe area to evaluate the long-term operation performance of the geothermal heat pump system. It mainly focuses on the evaluation of the parameters related to the operation performance of the geothermal heat pump system itself. However, the solar-coupled medium-deep geothermal heat pump hot water supply system involves the coupling and conversion of multiple energy sources, and this complexity increases the factors that need to be considered in performance evaluation. Therefore, the existing evaluation methods for multi-energy complementary heating systems are difficult to comprehensively reflect the actual operation of the solar-coupled medium-deep geothermal heat pump hot water supply system, resulting in inaccurate evaluation results. Summary of the Invention

[0005] Based on the defects existing in the above-mentioned prior art, the present invention provides an evaluation method for a solar-coupled medium-deep geothermal heat pump hot water supply system, which solves the problem that the existing evaluation methods for multi-energy complementary heating systems are difficult to comprehensively reflect the actual operation of the solar-coupled medium-deep geothermal heat pump hot water supply system, resulting in inaccurate evaluation results.

[0006] The present invention adopts the following technical solutions:

[0007] In the first aspect, the present invention provides an evaluation method for a solar-coupled medium-deep geothermal heat pump hot water supply system, including the following steps:

[0008] Collect the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters of the solar-coupled medium-deep geothermal heat pump hot water supply system; obtain various performance indicators based on the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters;

[0009] Obtain the system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score through various performance parameters;

[0010] Taking the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters as inputs, and the corresponding system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score as outputs, train the neural network model to obtain an evaluation model;

[0011] Real-time collect the environmental parameters, system operation parameters, and energy consumption parameters of the solar-coupled medium-deep geothermal heat pump hot water supply system, and input them into the evaluation model to obtain the corresponding system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score, and evaluate the solar-coupled medium-deep geothermal heat pump hot water supply system through the system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score.

[0012] Preferably, the environmental parameters include solar radiation intensity, ambient temperature, and surface temperature, the system operation parameters include collector plate temperature, ground source side temperature, water tank temperature, inlet and outlet water temperature difference, and water flow rate, and the energy consumption parameters include solar system power consumption, heat pump compressor power consumption, and circulation pump power consumption.

[0013] Preferably, the various performance indicators include system effective heat output, solar input energy consumption, ground source heat pump system input energy consumption, and auxiliary energy input energy consumption.

[0014] Preferably, the system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score are obtained through various performance parameters, where the system comprehensive energy efficiency ratio is specifically as follows:

[0015] C COP =(Q useful ) / (Einput-solar +E input-ground +E input-auxiliary );

[0016] Among them,

[0017] Q useful = ∫(Q * dt);

[0018] Q = m * C p * ΔT;

[0019] In the formula, C COP is the system comprehensive energy efficiency ratio, Q useful is the system effective heat output, E input-solar is the solar energy input energy consumption, E input-ground is the ground source heat pump system input energy consumption, E input-auxiliary is the auxiliary energy input energy consumption, Q is the instantaneous heat, m is the real-time flow rate, C p is the specific heat capacity, and ΔT is the temperature difference between the inlet and outlet of the heat pump.

[0020] Preferably, the heat utilization efficiency is specifically as follows:

[0021] η = Q useful / (E input-solar * η solar + E input-ground );

[0022] In the formula, η is the heat utilization efficiency, and η solar is the solar energy collection efficiency.

[0023] Preferably, the system comprehensive performance score includes:

[0024] When C COP > 3.5, the grade is excellent;

[0025] When 2.5 < C COP ≤ 3.5, the grade is good;

[0026] When 1.5 < C COP ≤ 2.5, the grade is medium;

[0027] When C COP ≤ 1.5, the grade is poor.

[0028] Preferably, the solar-coupled medium and deep ground source heat pump hot water supply system includes a solar energy collection system, a medium and deep ground source heat pump system, a heat storage system, and an intelligent control system.

[0029] Compared with the prior art, the above at least one technical solution adopted by the present invention can achieve the following beneficial effects:

[0030] The present invention first collects the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters of a solar-coupled medium-deep geothermal heat pump hot water supply system, and obtains various performance indicators based on these parameters. Through various performance parameters, the comprehensive energy efficiency ratio, heat utilization efficiency, and comprehensive system performance score of the system are obtained. The present invention collects the relevant operation parameters of multiple different subsystems included during system operation, emphasizing the comprehensive performance evaluation under the collaborative work of multiple subsystems. And the concept of the comprehensive energy efficiency ratio of the system is proposed, comprehensively considering the relationship between the effective heat output of the system and various input energy consumptions such as solar energy, geothermal heat pump, and auxiliary energy, comprehensively evaluating the system performance, which is more comprehensive, accurate, and scientific than the performance evaluation index of a single geothermal heat pump system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0032] Figure 1 It is a schematic structural diagram of a solar-coupled medium-deep geothermal heat pump hot water supply system of the present invention;

[0033] Figure 2 It is a schematic diagram of the training process of the neural network of the present invention;

[0034] Figure 3 It is a control logic diagram of the present invention;

[0035] Figure 4 It is a flowchart of the evaluation method for the solar-coupled medium-deep geothermal heat pump hot water supply system of the present invention.

[0036] In the figure: 1 - solar hot water storage tank, 2 - solar panel, 3 - makeup water tank, 4 - medium-deep buried tube heat exchanger, 5, 6, 8, 12, 25, 43 - temperature sensors, 7, 9, 11, 13, 24 - flow sensors, 10, 22, 23, 32, 34, 44 - solenoid valves, 14, 16, 17, 19, 26, 28, 29, 31, 35, 37, 38, 40 - pressure gauges, 15, 18 - heat storage geothermal pumps, 27, 30 - heat extraction geothermal pumps, 36, 39 - hot water pumps, 33, 45 - geothermal heat pumps, 41 - user-side water use, 42 - domestic hot water tank. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] The present invention provides an evaluation method for a solar-coupled medium-deep geothermal heat pump hot water supply system, specifically an accurate and dynamic performance evaluation method for a heat storage type solar-coupled medium-deep geothermal heat pump domestic hot water supply system. It mainly collects multiple parameters in real time, including solar radiation intensity, collector plate temperature, ground source side temperature, hot water storage tank temperature, system inlet and outlet water temperature difference, and instantaneous energy consumption, calculates performance indicators, calculates the system comprehensive energy efficiency ratio, and uses a BP neural network for system evaluation to further achieve system optimization control. Refer to Figure 4 , and specifically includes the following steps:

[0039] S1: Collect historical environmental parameters, historical system operation parameters, and historical energy consumption parameters of the solar-coupled medium-deep geothermal heat pump hot water supply system.

[0040] In this embodiment, the environmental parameters cover solar radiation intensity, environmental temperature, and ground surface temperature, etc. The system operation parameters include collector plate temperature, ground source side temperature, water tank temperature, inlet and outlet water temperature difference, and water flow rate, etc. The energy consumption parameters include the electricity consumption of the solar system, the electricity consumption of the heat pump compressor, and the electricity consumption of the circulation pump, etc.

[0041] Refer to Figure 1 , the system of the present invention mainly consists of the following parts: a solar collector system, a medium-deep geothermal heat pump system, a heat storage system, an intelligent control system, and a performance monitoring module.

[0042] The solar system includes a solar panel 2, a solar hot water storage tank 1, and a makeup water tank 3. The geothermal heat pump system includes a medium-deep buried tube heat exchanger 4, a geothermal heat pump (33, 45), a heat storage geothermal pump (15, 18), a heat extraction geothermal pump (27, 30), and a hot water pump (36, 39). The heat storage system includes a solar hot water storage tank 1 and a domestic hot water tank 42. The intelligent control system includes temperature sensors (5, 6, 8, 12, 25, 43), flow sensors (7, 9, 11, 13, 24), solenoid valves (10, 22, 23, 32, 34, 44), and the pump group connected to the system. The performance monitoring module reuses the sensors of the intelligent control system and further includes pressure gauges (14, 16, 17, 19, 26, 28, 29, 31, 35, 37, 38, and 40) for real-time monitoring of system operation parameters and optimization of control strategies.

[0043] On this basis, a performance evaluation method for a heat storage type solar energy coupled medium and deep geothermal heat pump domestic hot water supply system is constructed. Mainly through multi-parameter real-time acquisition, real-time acquisition of solar radiation intensity, collector plate temperature 2, geothermal side temperature 4, real-time flow rates (7, 9, 11, 13, 24), heat storage water tank temperature 43, system inlet and outlet water temperature difference (4, 42, 33, 45), instantaneous energy consumption (33, 45).

[0044] Use an electric energy meter to measure and record the energy consumption of each component, including the real-time and cumulative electricity consumption of solar energy, geothermal heat pump, and auxiliary system.

[0045] Environmental parameters affect the solar energy collection efficiency and the performance of the geothermal heat pump, and need to be monitored in real time to judge whether the system is in the optimal operating condition. System operating parameters are used to diagnose potential problems (such as pipeline blockage, heat exchange efficiency decline), and avoid energy loss. Through multi-parameter linkage (such as adjusting the working mode of the collector plate according to the solar radiation intensity), improve energy utilization efficiency.

[0046] S2: Obtain various performance indicators based on historical environmental parameters, historical system operating parameters, and historical energy consumption parameters.

[0047] The performance indicators include the effective heat output Q of the system useful , the input energy consumption E of solar energy input-solar , the input energy consumption E of the geothermal heat pump system input-ground , and the input energy consumption E of auxiliary energy input-auxiliary .

[0048] The effective heat output Q of the system useful is calculated by the following formula:

[0049] Q useful = ∫(Q*dt);

[0050] where

[0051] Q = m * C p * ΔT;

[0052] In the formula, Q is the calculated instantaneous heat, m is the water mass flow rate, C p is the specific heat capacity, and ΔT is the temperature difference between the inlet and outlet of the heat pump. The parameters corresponding to Q useful include: real-time flow rate (m), measured by flow sensors 7, 9, 11, 13, 24; inlet and outlet temperature difference (ΔT) measured by 4, 42, 33, 45.

[0053] The input energy consumption E of solar energy input-solar includes the electricity consumption of the collector plate circulation pump and the conversion loss of radiation intensity. The electricity consumption of the circulation pump is directly measured by an electric energy meter, and the conversion loss is estimated by combining the radiation intensity and the collection efficiency.

[0054] Input energy consumption E of the ground source heat pump system input-ground It includes the electricity consumption of the ground source side circulation pump and the electricity consumption of the heat pump compressor. The energy consumption of these two parts is directly measured by an electric energy meter and summed up.

[0055] Input energy consumption E of the auxiliary energy input-auxiliary It is the direct measurement of the real-time or cumulative electricity consumption of the auxiliary equipment through an electric energy meter.

[0056] S3: Obtain the system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score through various performance parameters.

[0057] Among them, the system comprehensive energy efficiency ratio is as follows:

[0058] C COP =(Q useful ) / (E input-solar +E input-ground +E input-auxiliary );

[0059] In the formula, C COP is the system comprehensive energy efficiency ratio.

[0060] The heat utilization efficiency represents the ratio of the effective heat (Q useful ) actually output by the system to the theoretical maximum heat (total solar radiation energy and geothermal extractable energy). Specifically, it is as follows:

[0061] η=Q useful / (E input-solar *η solar +E input-ground );

[0062] In the formula, η is the heat utilization efficiency, and η solar is the solar energy collection efficiency.

[0063] The system comprehensive performance score is specifically as follows:

[0064] Excellent: CCOP>3.5

[0065] Good: 2.5<CCOP≤3.5

[0066] Medium: 1.5<CCOP≤2.5

[0067] Poor: CCOP≤1.5.

[0068] Referring to the energy efficiency evaluation standards of multi - energy complementary heating systems at home and abroad, the European Heat Pump Association (EHPA) defines a ground - source heat pump with a COP ≥ 4.0 as "excellent"; in the "Renewable Energy Building Application Energy Efficiency Evaluation Standard" of China, a heat pump with a comprehensive energy efficiency ratio ≥ 3.0 is considered to meet the standard. In actual operating conditions, through long - term operation tests (such as more than one year), collect C values under different climate conditions (summer, winter) and operating conditions (high / low load), analyze their distribution laws and then select. COP Value, analyze its distribution law and then select.

[0069] S4: Using historical environmental parameters, historical system operation parameters, and historical energy consumption parameters as inputs, and the corresponding system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score as outputs, train the neural network model to obtain an evaluation model.

[0070] Long - term collection of multi - parameter data can verify the rationality of system design (such as whether the heat storage system effectively reduces energy loss), correct the energy efficiency calculation model, and improve the evaluation accuracy. Provide input features for the machine learning model to achieve real - time performance prediction and optimization.

[0071] After calculating the performance indicators, use the BP neural network for system evaluation. On the basis of completing the parameter calculation, use the BP neural network to comprehensively evaluate the heat - storage type solar - coupled medium - deep ground - source heat pump domestic hot water supply system. The specific steps are as Figure 2 shown.

[0072] The input key parameters are environmental parameters, system operation parameters, and energy consumption parameters. Parameters such as solar radiation intensity, environmental temperature, and ground - source side temperature change in real time, affecting the linear relationship of system energy efficiency.

[0073] Multi - parameter coupling effect: For example, the relationship between the collector plate temperature and solar radiation intensity may be disturbed by factors such as sudden weather changes and equipment aging, and it is difficult to accurately model with a simple formula.

[0074] The output variable is the system performance evaluation index, specifically the system comprehensive energy efficiency ratio (C COP ), heat utilization efficiency, and system comprehensive performance score.

[0075] Historical data and trend analysis: The neural network can capture the performance laws of the system in different seasons and climates by learning long - term operation data (such as more than one year), providing dynamic prediction capabilities.

[0076] Improve evaluation accuracy and adaptability: Formula calculations may ignore some losses (such as pipeline heat loss, sensor error), and the neural network optimizes the model through data - driven methods, reducing the deviation of human assumptions.

[0077] Support multi - objective optimization: The neural network can simultaneously output C COP, indicators such as heat utilization efficiency and system comprehensive score to assist in formulating a more comprehensive optimization strategy.

[0078] The neural network can predict future energy efficiency trends based on real-time input parameters (such as solar radiation intensity and water tank temperature), adjust the operation mode in advance (such as switching between ground-source heat pumps and auxiliary energy sources), and reduce energy consumption.

[0079] (1) Data collection: Collect long-term operation data (at least one year or more) and data under different working conditions (covering different climate conditions); (2) Data preprocessing: including data standardization (handling missing values, checking data consistency), normalization (eliminating the influence of dimensions, unifying the scales of different indicators), outlier handling, and interpolation filling, etc.; (3) Data division: Follow the principle of random allocation to ensure the consistency of data distribution and avoid data leakage. Specifically, it is divided into a training set (70%), a validation set (15%), and a test set (15%).

[0080] According to the characteristics of the solar energy system, select the long short-term memory network (LSTM) with time series learning ability as the evaluation model. The network hierarchical structure is designed as follows:

[0081] Input layer: Used to receive system operation parameters.

[0082] Hidden layer: Design a multi-layer neuron structure to capture complex non-linear relationships.

[0083] Output layer: Used to predict the energy efficiency performance of the system.

[0084] According to the constructed network structure, carry out the training process of the model.

[0085] Establish evaluation indicators: including R 2 score, root mean square error (RMSE), and mean absolute percentage error (MAPE), etc. Cross-validation: Further verify the stability and reliability of the model through the cross-validation method.

[0086] Performance score calculation: Use the trained model to score the system performance;

[0087] Result visualization: Realize the intuitive display of evaluation results.

[0088] Through the neural network algorithm, a data-driven system performance evaluation model can be established to achieve accurate and dynamic evaluation of the hot water supply system of the heat storage type solar energy coupled with medium and deep ground source heat pumps, and then complete the system optimization control. The control logic is shown in the figure.

[0089] Figure 3This is the control logic diagram of the present invention. It specifically includes the following key parts: Temperature signal A / D converter: responsible for converting the analog temperature signal collected by the temperature sensor into a digital signal for subsequent digital signal processing and control; BP neural network: used to predict and evaluate the performance of the system. The BP neural network receives the digital signal from the temperature signal A / D converter and other relevant operation data, and calculates and predicts the comprehensive energy efficiency ratio (C COP ) and other performance indicators of the system in real time through the trained model; PID controller: According to the performance evaluation result output by the BP neural network, the PID controller adjusts the control strategy to optimize the operation state of the system. The PID controller ensures the efficient operation of the system under different working conditions by adjusting the output signal; Digital signal D / A converter: Converts the digital control signal output by the PID controller into an analog signal to control the subsequent actuator; Variable frequency water pump: Receives the analog signal from the D / A converter and adjusts the operation frequency of the water pump according to the signal, thereby controlling the water flow rate to meet the system requirements. Supply and return pipe flow control: Through the adjustment of the variable frequency water pump, precise control of the water flow rate in the supply and return pipes is achieved, ensuring the stable operation of the system under different load conditions and optimizing the energy utilization efficiency. Through this closed-loop control system, dynamic and real-time optimal control of the solar-coupled medium and deep geothermal heat pump hot water supply system is realized, improving the overall performance and energy efficiency of the system.

[0090] The existing methods mainly focus on the ground source heat pump system and involve components related to the coupled heat transfer model of the ground heat exchanger - heat pump - building, without mentioning the solar collector system, heat storage system, intelligent control system, and performance monitoring module, etc. The present invention includes a solar collector system, a medium and deep geothermal heat pump system, a heat storage system, an intelligent control system, a performance monitoring module, etc., and is a multi-system coupled domestic hot water supply system.

[0091] The existing methods establish a database of the coupled heat transfer model of the ground heat exchanger - heat pump - building through simulation calculation using a group of design parameter data, establish a neural network model by forming a mapping between the design parameters and the operation results, and input the design parameters to predict the energy efficiency ratio, energy conservation and emission reduction, and the ground temperature in the buried pipe area to evaluate the long-term operation performance of the ground source heat pump system. It mainly focuses on the evaluation of the parameters related to the operation performance of the ground source heat pump system itself and does not involve the calculation of the comprehensive energy efficiency ratio of multi-system coupling and the system evaluation through real-time data acquisition.

[0092] The present invention calculates the comprehensive energy efficiency ratio of the system by collecting multiple parameters in real time (such as solar radiation intensity, temperatures of various parts, temperature difference between the inlet and outlet water of the system, instantaneous energy consumption, etc.), and uses an intelligent algorithm (BP neural network) for system evaluation. It emphasizes more on the comprehensive performance evaluation under the collaborative operation of multiple systems, and the evaluation index focuses on the relationship between the effective heat output of the system and various input energy consumptions, as well as the calculation of instantaneous heat and cumulative effective heat. At the same time, it pays attention to the impact of real-time data collection on the evaluation.

[0093] The present invention integrates multiple energy systems such as a solar heat collection system, a medium-deep ground source heat pump system, and a heat storage system to achieve the collaborative utilization of multiple energies, improve the energy utilization efficiency, and proposes the concept of the comprehensive energy efficiency ratio (C COP ). It comprehensively considers the relationship between the effective heat output of the system and various input energy consumptions such as solar energy, ground source heat pump, and auxiliary energy, and comprehensively evaluates the system performance. Compared with the performance evaluation index of a single ground source heat pump system, it is more comprehensive and scientific.

[0094] The present invention emphasizes real-time collection of multiple parameters, and calculates performance indicators and conducts system evaluation based on real-time data, which can timely reflect the current operating state of the system, realize dynamic monitoring and evaluation, and provide a more timely and accurate basis for system operation optimization.

[0095] The present invention conducts system evaluation based on real-time monitoring data, and can timely adjust the operating parameters or control strategies of each component according to the real-time operating state of the system to achieve the optimized operation of the system, improve the reliability and stability of the system, and reduce energy waste. For example, according to the real-time solar radiation intensity and the system energy consumption situation, the intelligent control system can decide the working mode switching of the solar heat collection system and the ground source heat pump system to achieve the best operating effect.

[0096] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be interpreted to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0097] Obviously, those skilled in the art can make various changes and deformations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and deformations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and deformations.

Claims

1. An evaluation method for a solar-coupled medium and deep geothermal heat pump hot water supply system, characterized in that It includes the following steps: Collect the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters of the solar energy-coupled medium-deep geothermal heat pump hot water supply system; obtain various performance indicators based on the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters; Obtain the system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score through various performance parameters; Use the historical environmental parameters, historical system operation parameters, and historical energy consumption parameters as inputs, and the corresponding system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score as outputs to train the neural network model to obtain an evaluation model; Collect the environmental parameters, system operation parameters, and energy consumption parameters of the solar energy-coupled medium-deep geothermal heat pump hot water supply system in real time, and input them into the evaluation model to obtain the corresponding system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score, and evaluate the solar energy-coupled medium-deep geothermal heat pump hot water supply system through the system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score.

2. The evaluation method of a solar-coupled medium-deep geothermal heat pump hot water supply system according to claim 1, characterized in that, The environmental parameters include solar radiation intensity, ambient temperature, and surface temperature. The system operation parameters include collector plate temperature, ground source side temperature, water tank temperature, inlet and outlet water temperature difference, and water flow rate. The energy consumption parameters include the power consumption of the solar energy system, the power consumption of the heat pump compressor, and the power consumption of the circulation pump.

3. The evaluation method of a solar-coupled medium-deep geothermal heat pump hot water supply system according to claim 1, characterized in that The various performance indicators include the effective heat output of the system, the input energy consumption of solar energy, the input energy consumption of the ground source heat pump system, and the input energy consumption of auxiliary energy.

4. The evaluation method of a solar-coupled medium-deep geothermal heat pump hot water supply system according to claim 1, characterized in that The system comprehensive energy efficiency ratio, heat utilization efficiency, and system comprehensive performance score are obtained through various performance parameters. Among them, the system comprehensive energy efficiency ratio is specifically as follows: C COP = (Q useful ) / (E input-solar + E input-ground + E input-auxiliary ); Among them, Q useful = ∫(Q * dt); Q = m * C p * ΔT; Where, C COP is the system comprehensive energy efficiency ratio, Q useful is the effective heat output of the system, E input-solar is the input energy consumption of solar energy, E input-ground is the input energy consumption of the ground source heat pump system, E input-auxiliary is the input energy consumption of auxiliary energy, Q is the instantaneous heat, m is the real-time flow rate, C p is the specific heat capacity, and ΔT is the temperature difference between the inlet and outlet of the heat pump.

5. The evaluation method of a solar energy-coupled medium-deep geothermal heat pump hot water supply system according to claim 4, wherein the heat utilization efficiency is specifically as follows: η = Q useful / (E input-solar * η solar + E input-ground ); In the formula, η is the heat utilization efficiency, and η solar is the solar heat collection efficiency.

6. The evaluation method of a solar-coupled medium-deep geothermal heat pump hot water supply system according to claim 4, characterized in that The system comprehensive performance score includes: When C COP > 3.5, the grade is excellent; When 2.5 < C COP ≤ 3.5, the grade is good; When 1.5 < C COP ≤ 2.5, the grade is medium; When C COP ≤ 1.5, the grade is poor.

7. The evaluation method of a solar-coupled medium-deep geothermal heat pump hot water supply system according to claim 1, characterized in that The solar energy-coupled medium-deep geothermal heat pump hot water supply system includes a solar energy collection system, a medium-deep geothermal heat pump system, a heat storage system, and an intelligent control system.

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