A solar water heater energy-saving optimization control method based on internet of things technology

Abstract

The application discloses a solar water heater energy-saving optimization control method based on Internet of Things technology, and relates to the field of photovoltaic solar water heater energy-saving control. The method comprises the following steps: predicting a first water temperature change amount of photovoltaic power generation heating based on the Internet of Things technology; when the sum of the current water temperature and the first water temperature change amount is greater than or equal to a preset water temperature, performing photovoltaic power generation heating; otherwise, predicting a second water temperature change amount of photovoltaic medium circulation heating; when the sum of the current water temperature, the first water temperature change amount and the second water temperature change amount is greater than or equal to the preset water temperature, performing photovoltaic power generation heating and photovoltaic medium circulation heating; otherwise, the solar water heater first performs photovoltaic power generation heating and photovoltaic medium circulation heating, and then starts city power heating from a city power heating start time. The application predicts water temperature changes caused by different heating modes through the Internet of Things technology, optimizes the heating mode in combination with the preset temperature and time, and improves the energy utilization efficiency of the solar water heater.

Description

Technical Field

[0001] This invention relates to the field of energy-saving control of photovoltaic solar water heaters, and in particular to an energy-saving optimization control method for solar water heaters based on Internet of Things (IoT) technology. Background Technology

[0002] Energy, as a vital material foundation and driving force for national economic development, holds significant strategic importance. Photovoltaic solar water heaters, as indispensable devices in daily life, perfectly align with the needs of the current era due to their near-pollution-free characteristics.

[0003] Intelligent control is an automation control method designed to achieve the intelligent operation of systems or equipment. Intelligent control enables photovoltaic solar energy systems to intelligently select the most suitable heating method based on factors such as real-time sunlight conditions, weather forecasts, water tank temperature, and user needs. This reduces the frequency of mains electricity usage, achieves efficient energy utilization, and saves energy costs. Through intelligent control, the system can maximize the use of solar energy resources and reduce dependence on traditional fossil fuels. Intelligent control also improves user experience and meets users' personalized hot water needs.

[0004] Traditional photovoltaic (PV) water heater systems are typically mechanized, operating in a fixed mode, resulting in significant shortcomings in energy efficiency. While current solar water heaters offer numerous functions, such as remote control and timed automatic operation, they lack intelligent control and adaptability, as they only automatically select two or more heating methods based on user-set water temperature and time requirements. They cannot automatically adjust to weather conditions and user needs, leading to energy waste due to their relatively fixed operating mode. Furthermore, traditional water heaters are usually controlled manually, preventing users from remotely monitoring or adjusting their status. Therefore, existing PV solar water heater systems, to a certain extent, fail to meet the demand for clean, efficient, and intelligent energy systems. Summary of the Invention

[0005] The purpose of this invention is to provide an energy-saving optimization control method for solar water heaters based on Internet of Things (IoT) technology. This method can predict water temperature changes caused by different heating methods through IoT technology, and optimize the heating method by combining preset temperature and time, thereby improving the energy utilization efficiency of solar water heaters.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for energy-saving optimization control of solar water heaters based on Internet of Things (IoT) technology, the method comprising:

[0008] The first water temperature change ΔT1 is predicted based on Internet of Things (IoT) technology; the first water temperature change ΔT1 is the change in water temperature from the current time t0 to the preset time t of the solar water heater.预设 The water temperature change is generated by photovoltaic power generation heating the water in the tank of the solar water heater;

[0009] Determine if the current water temperature T0 is greater than or equal to the preset water temperature T. 预设 The first judgment result is obtained;

[0010] If the first judgment result is yes, then the solar water heater will generate electricity from photovoltaic power for heating;

[0011] If the first judgment result is negative, then determine whether the sum of the current water temperature T0 and the first water temperature change ΔT1 is greater than or equal to the preset water temperature T. 预设 The second judgment result is obtained;

[0012] If the second judgment result is yes, then the solar water heater will generate electricity through photovoltaic power generation for heating;

[0013] If the second judgment result is negative, then the second water temperature change ΔT2 is predicted based on IoT technology; the second water temperature change ΔT2 is the change in water temperature from the current time t0 to the preset time t of the solar water heater. 预设 The water temperature changes are generated by circulating heat from the photovoltaic medium to the water tank of the solar water heater.

[0014] Determine whether the sum of the current water temperature T0, the first water temperature change ΔT1, and the second water temperature change ΔT2 is greater than or equal to the preset water temperature T. 预设 The third judgment result is obtained;

[0015] If the third judgment result is yes, then the solar water heater uses photovoltaic power generation for heating and photovoltaic medium circulation for heating;

[0016] If the third judgment result is negative, the solar water heater first performs photovoltaic power generation heating and photovoltaic medium circulation heating, and then starts from the mains power heating start time t. 市电 We started adding mains power heating.

[0017] Optionally, the prediction of the first water temperature change ΔT1 based on IoT technology includes:

[0018] The predicted heat output E1 of photovoltaic power generation heating is calculated based on Internet of Things (IoT) technology.

[0019] The first water temperature change ΔT1 is calculated based on the predicted heat output E1 from photovoltaic power generation heating.

[0020] Optionally, the formula for calculating the predicted heat output E1 of photovoltaic power generation heating is as follows:

[0021]

[0022] In the formula, t0 is the current time, t预设 P1 represents the preset time and the predicted heating power of the solar water heater's photovoltaic power generation.

[0023] Optionally, the formula for calculating the first water temperature change ΔT1 is:

[0024]

[0025] In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E1 represents the volume of the water tank in the solar water heater, and E1 represents the predicted heat output from photovoltaic power generation.

[0026] Optionally, the second water temperature change ΔT2 can be predicted based on Internet of Things (IoT) technology, specifically including:

[0027] Based on IoT technology, the predicted thermal energy output E2 of photovoltaic dielectric circulating heating is obtained;

[0028] The first water temperature change ΔT2 is calculated based on the predicted heat output E2 of the photovoltaic medium circulating heating.

[0029] Optionally, the formula for calculating the predicted thermal output E2 of the photovoltaic dielectric circulating heating is as follows:

[0030]

[0031] In the formula, t0 is the current time, t 预设 P2 is the preset time, and P2 is the predicted heating power of the photovoltaic medium circulation heating of the solar water heater.

[0032] Optionally, the formula for calculating the first water temperature change ΔT2 is:

[0033]

[0034] In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E1 represents the volume of the water tank in the solar water heater, and E2 represents the predicted heat output of the photovoltaic medium circulation heating system.

[0035] Optionally, the mains heating start-up time t 市电 The calculation formula is as follows:

[0036]

[0037] In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水E3 is the volume of the water tank of the solar water heater, E3 is the predicted heat output of the solar water heater from mains heating, and t 市电 t is the mains heating start-up time of the solar water heater. 预设 P3 is the preset time, t is the duration of the solar water heater's mains heating, and P3 is the heating power of the solar water heater's mains heating.

[0038] A computer system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described energy-saving optimization control method for solar water heaters based on Internet of Things technology.

[0039] A computer-readable storage medium storing a computer program thereon, characterized in that, when executed by a processor, the computer program implements the steps of the above-described energy-saving optimization control method for solar water heaters based on Internet of Things technology.

[0040] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0041] This invention uses Internet of Things (IoT) technology to predict the first water temperature change caused by photovoltaic (PV) power generation for heating. When the sum of the current water temperature and the first water temperature change is greater than or equal to a preset water temperature, PV power generation heating is initiated; otherwise, the invention predicts the second water temperature change caused by PV medium circulation heating. When the sum of the current water temperature, the first water temperature change, and the second water temperature change is greater than or equal to the preset water temperature, both PV power generation heating and PV medium circulation heating are initiated; otherwise, the solar water heater first initiates PV power generation heating and PV medium circulation heating, and then gradually increases PV power heating starting from the mains power heating start time. This invention uses IoT technology to predict water temperature changes caused by different heating methods and optimizes the heating method by combining preset temperature and time, thereby improving the energy utilization efficiency of the solar water heater. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A first flowchart of an energy-saving optimization control method for solar water heaters based on Internet of Things technology is provided in an embodiment of the present invention;

[0044] Figure 2 A second flowchart of an energy-saving optimization control method for solar water heaters based on Internet of Things technology, provided in an embodiment of the present invention;

[0045] Figure 3 This is a flowchart of the PCA algorithm data dimensionality reduction processing provided in an embodiment of the present invention;

[0046] Figure 4 A flowchart illustrating the modeling process of the ADARNN-StemGNN fusion model provided in this embodiment of the invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] The purpose of this invention is to provide an energy-saving optimization control method for solar water heaters based on Internet of Things (IoT) technology. This method uses IoT technology to predict water temperature changes caused by different heating methods, and optimizes the heating method by combining preset temperature and time, thereby improving the energy utilization efficiency of solar water heaters.

[0049] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] Example 1

[0051] like Figures 1-2 As shown, this invention provides an energy-saving optimization control method for solar water heaters based on Internet of Things (IoT) technology, the method comprising:

[0052] S1. Predict the first water temperature change ΔT1 based on Internet of Things (IoT) technology; the first water temperature change ΔT1 is the change in water temperature from the current time t0 to the preset time t of the solar water heater. 预设 The water temperature changes are generated by photovoltaic power generation heating the water in the tank of the solar water heater.

[0053] Step S1 specifically includes:

[0054] S11. Calculate the predicted heat output E1 of photovoltaic power generation heating based on Internet of Things technology.

[0055] S12. The first water temperature change ΔT1 is calculated based on the predicted heat output E1 from photovoltaic power generation heating.

[0056] The formula for calculating the predicted heat output E1 of photovoltaic power generation heating is as follows:

[0057] .

[0058] In the formula, t0 is the current time, t 预设 P1 represents the preset time and the predicted heating power of the solar water heater generated by photovoltaic power generation.

[0059] The formula for calculating the first water temperature change ΔT1 is:

[0060] .

[0061] In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E1 represents the volume of the water tank in the solar water heater, and E1 represents the predicted heat output from photovoltaic power generation.

[0062] The energy sources of the solar water heater in this embodiment 1 are mainly three aspects: first, using solar photovoltaic power generation to heat the water in the water heater; second, when the temperature of the medium in the solar photovoltaic panel is higher than the temperature of the water in the water heater by a certain temperature, the water in the water heater is heated by heat transfer through the flow of the medium in the solar photovoltaic panel; and third, using mains electricity to heat the water in the solar water heater.

[0063] In practical applications, such as Figures 3-4 As shown, photovoltaic power generation is typically predicted based on the ADARNN-Stem GNN model, and the specific process is as follows:

[0064] 1) Data preprocessing.

[0065] A time-series dataset was created by collecting photovoltaic module data and weather forecast data. The dataset mainly includes information such as weather, temperature, wind speed, wind direction, air humidity, irradiance, power, and light intensity. Wind direction and weather features are semantic features, requiring text feature extraction and conversion into low-dimensional numerical feature vectors. All other features are numerical features. The sample data can be viewed as multivariate time-series data.

[0066] 1.1 Using the BERT model to extract text features. A BERT-Base model pre-trained with the Chinese library was used. Each character was processed by the BERT model into a 768-dimensional vector. Dimensionality reduction was performed using the PCA algorithm, and matrix transformations were used to convert the multivariate time-series data into feature-independent vectors, thereby obtaining the important features of the data.

[0067] 1.2 The torch framework in PyCharm is used to import the pre-trained BERT model, encode the weather and wind direction features and output the text tensor, and then import it into the PCA model for dimensionality reduction.

[0068] 1.3 Perform standard normalization on the dataset:

[0069] .

[0070] in, The characteristic mean, The characteristic variance is denoted as .

[0071] 1.4 Divide the dataset into training, validation and test sets. Randomly select 70% of the data as the training set, 20% as the validation set, and the remaining 10% as the test set.

[0072] 2) ADARNN-StemGNN ensemble predictive modeling:

[0073] 2.1 Write the ADARNN model and adjust its parameters. Train the GRU model and verify whether there is overfitting or underfitting. If so, readjust the model parameters so that the model can fit the data well.

[0074] 2.2 Write the StemGNN model and adjust its parameters. Train the StemGNN model and verify whether there is overfitting or underfitting. If so, readjust the model parameters so that the model can fit the data well.

[0075] 2.3 Use the prediction accuracy of the validation set to obtain the predicted values ​​of the prediction set.

[0076] 2.4 The ADARNN and StemGNN models are fused for modeling. Mean squared error is chosen as the loss function to measure the effectiveness of power prediction; the formula is as follows:

[0077] .

[0078] in, For the true value of the i-th sample, Let be the predicted value for the i-th sample. To improve training efficiency and accelerate the gradient descent of the model, this invention uses the Adam (Adaptive Momentum Unstiation) optimization algorithm. Furthermore, by selecting the prediction accuracy of the model on the validation set as the weight of each model's prediction result on the test set, and then weighting and summing the prediction values ​​of the two models to obtain the final result, the prediction accuracy of the model is further improved.

[0079] S2. Determine if the current water temperature T0 is greater than or equal to the preset water temperature T. 预设 Thus, the first judgment result was obtained.

[0080] S3. If the first judgment result is yes, then the solar water heater performs photovoltaic power generation heating.

[0081] S4. If the first judgment result is negative, then determine whether the sum of the current water temperature T0 and the first water temperature change ΔT1 is greater than or equal to the preset water temperature T. 预设 Thus, the second judgment result is obtained.

[0082] S5. If the second judgment result is yes, then the solar water heater performs photovoltaic power generation heating.

[0083] S6. If the second judgment result is negative, then predict the second water temperature change ΔT2 based on IoT technology; the second water temperature change ΔT2 is the change in water temperature from the current time t0 to the preset time t of the solar water heater. 预设 The water temperature changes are generated by circulating heat in the water tank of the solar water heater through a photovoltaic medium.

[0084] S7. Determine whether the sum of the current water temperature T0, the first water temperature change ΔT1, and the second water temperature change ΔT2 is greater than or equal to the preset water temperature T. 预设 The third judgment result is obtained.

[0085] Step S7 specifically includes:

[0086] S71. Based on Internet of Things (IoT) technology, the predicted thermal output E2 of photovoltaic dielectric circulating heating is obtained.

[0087] S72. The first water temperature change ΔT2 is calculated based on the predicted heat output E2 of photovoltaic medium circulating heating.

[0088] The formula for calculating the predicted thermal output E2 of the photovoltaic dielectric circulating heating is as follows:

[0089] .

[0090] In the formula, t0 is the current time, t 预设 P2 is the preset time, and P2 is the predicted heating power of the photovoltaic medium circulation heating of the solar water heater.

[0091] The formula for calculating the first water temperature change ΔT2 is:

[0092] .

[0093] In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E1 represents the volume of the water tank in the solar water heater, and E2 represents the predicted heat output of the photovoltaic medium circulation heating system.

[0094] S8. If the third judgment result is yes, then the solar water heater uses photovoltaic power generation for heating and photovoltaic medium circulation for heating.

[0095] S9. If the third judgment result is negative, the solar water heater first performs photovoltaic power generation heating and photovoltaic medium circulation heating, and then starts from the mains power heating start time t. 市电 We started adding mains power heating.

[0096] The mains heating start time t 市电 The calculation formula is as follows:

[0097] .

[0098] In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E3 is the volume of the water tank of the solar water heater, E3 is the predicted heat output of the solar water heater from mains heating, and t 市电 t is the mains heating start-up time of the solar water heater. 预设 P3 is the preset time, t is the duration of the solar water heater's mains heating, and P3 is the heating power of the solar water heater's mains heating.

[0099] This invention relates to the field of energy-saving control of photovoltaic solar water heaters. Based on Internet of Things (IoT) technology, it is an energy-saving optimization control algorithm that addresses the personalized needs of different users regarding the time and temperature of hot water usage. By using IoT technology to predict water temperature changes caused by different heating methods, and combining preset temperature and time, the heating method is optimized, thereby improving the energy utilization efficiency of solar water heaters.

[0100] This invention utilizes IoT technology, intelligent algorithms, photovoltaic power generation technology, and medium circulation heating technology. By monitoring solar irradiance, water tank temperature, and energy supply in real time, the system automatically selects the appropriate energy source for heating. The system offers three heating methods: photovoltaic panel heating, medium circulation heating, and mains power heating. Through IoT technology, real-time weather information is obtained to predict the daily power generation of the solar photovoltaic panels. A relevant function model is established to analyze users' personalized needs, providing the heating solution that meets user requirements while minimizing costs, and enabling automatic control of the solar system. The system can intelligently select the most suitable heating method. This invention introduces IoT technology, using WiFi or Bluetooth to obtain real-time weather conditions for the current city, and performs cluster analysis on the current season and weather type to establish a mathematical model and predict photovoltaic power generation. By predicting and analyzing whether the energy generated by solar power can meet user needs, if not, mains power is activated to heat the water tank. The intelligent control system determines when to activate mains power to ensure user needs are met while minimizing electricity costs. Photovoltaic solar water heater systems are an important component of clean energy technology, helping to reduce dependence on traditional fossil fuels, lower greenhouse gas emissions, and promote the clean energy transition.

[0101] The solar water heater system proposed in this invention can maximize the use of solar energy for heating, reduce dependence on traditional energy sources, and promote the use of green energy. It can intelligently select the heating method based on real-time weather conditions, user needs, and cost factors, thereby improving energy efficiency, reducing energy costs, and achieving energy-saving goals. Through Internet of Things technology and intelligent algorithms, the system can monitor in real time and automatically select the most suitable heating method, improving the system's intelligence.

[0102] Example 2

[0103] A computer system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described energy-saving optimization control method for solar water heaters based on Internet of Things technology.

[0104] Example 3

[0105] A computer-readable storage medium storing a computer program thereon, characterized in that, when executed by a processor, the computer program implements the steps of the above-described energy-saving optimization control method for solar water heaters based on Internet of Things technology.

[0106] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0107] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for energy-saving optimization control of solar water heaters based on Internet of Things (IoT) technology, characterized in that, The method includes: The first water temperature change ΔT1 is predicted based on Internet of Things (IoT) technology; the first water temperature change ΔT1 is the change in water temperature from the current time t0 to the preset time t of the solar water heater. 预设 The water temperature change is generated by photovoltaic power generation heating the water in the tank of the solar water heater; Determine if the current water temperature T0 is greater than or equal to the preset water temperature T. 预设 The first judgment result is obtained; If the first judgment result is yes, then the solar water heater will generate electricity from photovoltaic power for heating; If the first judgment result is negative, then determine whether the sum of the current water temperature T0 and the first water temperature change ΔT1 is greater than or equal to the preset water temperature T. 预设 The second judgment result is obtained; If the second judgment result is yes, then the solar water heater will generate electricity through photovoltaic power generation for heating; If the second judgment result is negative, then the second water temperature change ΔT2 is predicted based on IoT technology; the second water temperature change ΔT2 is the change in water temperature from the current time t0 to the preset time t of the solar water heater. 预设 The water temperature changes are generated by circulating heat from the photovoltaic medium to the water tank of the solar water heater. Determine whether the sum of the current water temperature T0, the first water temperature change ΔT1, and the second water temperature change ΔT2 is greater than or equal to the preset water temperature T. 预设 The third judgment result is obtained; If the third judgment result is yes, then the solar water heater uses photovoltaic power generation for heating and photovoltaic medium circulation for heating; If the third judgment result is negative, the solar water heater first performs photovoltaic power generation heating and photovoltaic medium circulation heating, and then starts from the mains power heating start time t. 市电 We started adding mains power heating.

2. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 1, characterized in that, The prediction of the first water temperature change ΔT1 based on Internet of Things (IoT) technology specifically includes: The predicted heat output E1 of photovoltaic power generation heating is calculated based on Internet of Things (IoT) technology. The first water temperature change ΔT1 is calculated based on the predicted heat output E1 from photovoltaic power generation heating.

3. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 2, characterized in that, The formula for calculating the predicted heat output E1 of photovoltaic power generation heating is as follows: In the formula, t0 is the current time, t 预设 P1 represents the preset time and the predicted heating power of the solar water heater's photovoltaic power generation.

4. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 2, characterized in that, The formula for calculating the first water temperature change ΔT1 is: In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E1 represents the volume of the water tank in the solar water heater, and E1 represents the predicted heat output from photovoltaic power generation.

5. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 1, characterized in that, The prediction of the second water temperature change ΔT2 based on Internet of Things (IoT) technology specifically includes: Based on IoT technology, the predicted thermal energy output E2 of photovoltaic dielectric circulating heating is obtained; The second water temperature change ΔT2 is calculated based on the predicted heat output E2 of the photovoltaic medium circulating heating.

6. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 5, characterized in that, The formula for calculating the predicted thermal output E2 of the photovoltaic dielectric circulating heating is as follows: In the formula, t0 is the current time, t 预设 P2 is the preset time, and P2 is the predicted heating power of the photovoltaic medium circulation heating of the solar water heater.

7. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 5, characterized in that, The formula for calculating the second water temperature change ΔT2 is: In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E1 represents the volume of the water tank in the solar water heater, and E2 represents the predicted heat output of the photovoltaic medium circulation heating system.

8. The energy-saving optimization control method for solar water heaters based on Internet of Things technology according to claim 1, characterized in that, The mains heating start time t 市电 The calculation formula is as follows: In the formula, C 水 ρ is the specific heat capacity of water. 水 V is the density of water. 水 E3 is the volume of the water tank of the solar water heater, E3 is the predicted heat output of the solar water heater from mains heating, and t 市电 t is the mains heating start-up time of the solar water heater. 预设 P3 is the preset time, t is the duration of the solar water heater's mains heating, and P3 is the heating power of the solar water heater's mains heating.

9. A computer system, comprising: The memory and processor contain a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the energy-saving optimization control method for a solar water heater based on Internet of Things technology as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the energy-saving optimization control method for solar water heaters based on Internet of Things technology as described in any one of claims 1-8.

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