A non-pressurized electric boiler system and a control method thereof

Abstract

The application discloses an electric boiler system without capacity expansion and a control method thereof. The electric boiler system without capacity expansion comprises a power monitor, a temperature sensor and an electric boiler. The power monitor is used for detecting real-time power of a user and sending the real-time power to the electric boiler; the temperature sensor is used for collecting real-time temperature of a room and sending the real-time temperature to the electric boiler; and the electric boiler is used for calculating maximum starting power allowed for starting of the electric boiler according to the real-time power of the power monitor and the real-time temperature of the temperature sensor and dynamically adjusting starting power of the electric boiler. The application can intelligently adjust the starting power of the electric boiler, dynamically adjusts the starting power of the electric boiler in combination with indoor temperature and set temperature, achieves the purpose of intelligent energy saving, solves the industry bottleneck, enables original projects that cannot use the electric boiler for heating to use the electric boiler for heating, improves user power safety, and adds a powerful guarantee for highly electrified life.

Description

Technical Field

[0001] This invention relates to the field of heating control technology, and in particular to a capacity-saving electric boiler system and its control method. Background Technology

[0002] An electric boiler, also known as an electric heating boiler or electric thermal boiler, is, as the name suggests, a boiler device that uses electricity as its energy source and converts it into heat energy. This heat energy is then converted by the boiler and output as steam, high-temperature water, or organic heat carriers. The main components of an electric boiler include a steel shell, a computer control system, a low-voltage electrical system, electric heating elements, inlet and outlet water pipes, and monitoring instruments.

[0003] In existing electric boiler heating systems, the boiler's power is fixed. If a user's electricity consumption suddenly increases, the total power may exceed the user's rated power, causing a circuit breaker to trip. There is also a risk of fire due to a rapid current surge. Therefore, this invention proposes an electric boiler system and its control method that do not require capacity expansion, adding a strong layer of protection to our highly electrified lives. Summary of the Invention

[0004] This invention provides a capacity-saving electric boiler system, comprising: a power detector, a temperature sensor, and an adjustable power heating electric boiler; the power detector is installed in the household electrical box to detect the user's real-time power and send the real-time power to the adjustable power heating electric boiler; the temperature sensor is used to collect the real-time room temperature and send the real-time temperature to the adjustable power heating electric boiler; the adjustable power electric boiler calculates the maximum starting power allowed for the electric boiler to start based on the real-time power of the power detector and the real-time temperature of the temperature sensor, and dynamically adjusts the starting power of the electric boiler.

[0005] As described above, the electric boiler system without capacity expansion includes an electric boiler main control board, a heating module control board, and a remote intelligent control module. The electric boiler main control board is connected to both the heating module control board and the remote intelligent control module.

[0006] As described above, in a capacity-increase-free electric boiler system, a heating module control board connects to multiple heating modules, each heating module is connected to a corresponding electric boiler heating element, and controls the start / stop and temperature of the electric boiler heating element; each heating module is connected to a temperature sensor to monitor the indoor temperature.

[0007] In the aforementioned capacity-saving electric boiler system, a remote intelligent control module sets and reads parameters of the temperature sensor and the electric boiler via a network.

[0008] As described above, in a capacity-free electric boiler system, the electric boiler can be installed indoors or in a stairwell, connected to an indoor electrical box and a heat exchange circulation system, converting electrical energy into heat energy, and then delivering the heat generated by the electrical energy to the user's room for heating through the heat exchange circulation system.

[0009] This invention also provides a control method for an electric boiler system that does not require capacity expansion, comprising:

[0010] The power monitoring module monitors the actual power used by the user in real time and transmits it to the electric boiler control mainboard.

[0011] The electric boiler control board calculates the maximum startable power of the electric boiler based on the actual power used and the indoor temperature monitored by the temperature sensor, dynamically adjusts the start-up power of the electric boiler, and determines the start and stop of each heating module according to the parameters of each heating module.

[0012] Send heating instructions to heating modules that need to be started, and send stop instructions to heating modules that need to be stopped.

[0013] In the above-described control method for an electric boiler system that does not require capacity expansion, the total power S is fixed, the actual power used by the user as monitored by the power monitor is W, and the maximum startable power of the electric boiler is SW-α, where α is the deviation.

[0014] The above-described control method for a capacity-saving electric boiler system includes, after calculating the power consumption of each heating module, calculating... Find the value of n, p i The value of n represents the rated power of the heating module, which is the number of heating modules that can be started. In other words, it is the number of heating modules that can be started when the starting power is as close as possible to the electric boiler.

[0015] The present invention also provides a computer-readable storage medium, characterized in that the computer-readable storage medium contains one or more program instructions, the one or more program instructions being executed by a processor as described in any of the preceding claims, a control method for an electric boiler system without capacity expansion.

[0016] The beneficial effects achieved by this invention are as follows: By adopting the technical solution of this invention, the starting power of the electric boiler can be intelligently allocated, and the starting power of the electric boiler can be dynamically adjusted in combination with the indoor temperature and the set temperature to achieve the purpose of intelligent energy saving; it solves the industry bottleneck, enabling projects that could not use electric boilers for heating in the past to also use electric boilers for heating; at the same time, it improves the electrical safety of users and adds a strong guarantee for today's highly electrified life. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a schematic diagram of an electric boiler system that does not require capacity expansion, provided in Embodiment 1 of the present invention;

[0019] Figure 2 This is a flowchart of a control method for an electric boiler that does not require capacity expansion, provided in Embodiment 1 of the present invention. Detailed Implementation

[0020] 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, not all, of the embodiments of the present invention. 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.

[0021] Example 1

[0022] See Figure 1 Embodiment 1 of the present invention provides a capacity-increase-free electric boiler system, comprising: a power detector, a temperature sensor, and an adjustable-power heating electric boiler. The power detector is installed in the household electrical box to detect the user's real-time power consumption and transmits this real-time power to the adjustable-power heating electric boiler. The temperature sensor collects the real-time room temperature and transmits this real-time temperature to the adjustable-power heating electric boiler. The adjustable-power electric boiler calculates the maximum allowable starting power based on the real-time power from the power detector and the real-time temperature from the temperature sensor, and dynamically adjusts the starting power of the electric boiler.

[0023] Specifically, the electric boiler includes a main control board, a heating module control board, and a remote intelligent control module. The main control board is connected to the heating module control board, a power detector, a temperature sensor, and the remote intelligent control module. The heating module control board connects to multiple heating modules, each connected to a corresponding heating element of the electric boiler, controlling the start / stop and temperature of the heating element. Each heating module is connected to a temperature sensor to monitor its corresponding temperature, i.e., the corresponding indoor temperature. The remote intelligent control module sets and reads parameters from the temperature sensor and the electric boiler via a network. The electric boiler can be installed indoors or in a hallway, connected to an indoor electrical box and a heat exchange circulation system to convert electrical energy into heat energy, which is then delivered to the user's room for heating via the heat exchange circulation system.

[0024] Example 2

[0025] See Figure 2 Embodiment 2 of the present invention provides a control method for an electric boiler that does not require capacity expansion, comprising:

[0026] Step 210: The power monitoring module monitors the actual power used by the user in real time and transmits it to the electric boiler control mainboard;

[0027] Step 220: The electric boiler control mainboard calculates the maximum startable power of the electric boiler based on the actual power used and the indoor temperature monitored by the temperature sensor, dynamically adjusts the start-up power of the electric boiler, and determines the start and stop of each heating module according to the parameters of each heating module.

[0028] Step S1: The power monitor monitors the actual power used by the user in real time, transmits the actual power used by the user to the main control board of the electric boiler, and calculates the maximum power that the electric boiler can start.

[0029] This application aims to achieve control of an electric boiler without increasing its capacity, so the total power S is fixed. The actual power used by the user is monitored by the power monitor as W. Then the maximum startable power of the electric boiler is SW-α, where α is the deviation. This value is set to prevent potential safety issues when the power is exactly equal.

[0030] Step S2: Input the rated power, priority, heating time period and the temperature required for each heating time period of each heating module into the pre-trained power consumption prediction model, and output the power consumption of each heating module.

[0031] In this embodiment of the application, the training of the electricity consumption prediction module specifically includes the following sub-steps:

[0032] Step 1: Collect electricity consumption data of the electric boiler over a historical period, including the rated power of each heating module, the temperature of the corresponding time period, the priority set for each heating module, and the electricity consumption in multiple historical time periods. Construct an electricity consumption dataset from the above data.

[0033] Specifically, historical data of the electric boiler is sent to a cloud platform or mobile device for storage via a remote intelligent control module. This collects historical electricity consumption data for the electric boiler, including the rated power of each heating module across multiple historical time periods, the priority set for each heating module, and the temperature for the corresponding time period. This data is then used to construct an electricity consumption dataset S = {(p1,T1,v1,c1)...(p i ,T i ,v i ,c i )…(p t ,T t ,v t ,c t)}, where p1, T1, v1, and c1 represent the rated power of the heating module collected in the first time period, the temperature of the corresponding time period, the corresponding set priority, and the power consumption, respectively. i ,T i ,v i ,c i Let p represent the rated power of the heating module, the temperature of the corresponding time period, the set priority, and the power consumption collected in the i-th time period, respectively. t ,T t ,v t ,c t These represent the rated power of the heating module, the temperature for the corresponding time period, the set priority, and the power consumption collected during time period t, respectively. In the above data, the rated power may change due to the replacement of the heating module, the temperature may change due to the control of the electric boiler, the priority may change due to the adjustment of external equipment, and the power consumption may change as the above data changes.

[0034] Step 2: Input the electricity consumption dataset into different sub-prediction models, classify the electricity consumption dataset using each sub-prediction model, and estimate the set of weights of each sub-prediction model based on the classification results.

[0035] Specifically, the electricity consumption dataset is input into the sub-prediction model. Reusing the subclassification model The feature vector set is classified, and the classification result is used to apply a formula. The set of weights for estimating the subclassification model, where β1, β2, and Λβ M Let λ1, λ2, and λ3 be the weight set, where λ1, λ2, and λ3 are the influence weights of the rated power of the heating module in the electricity consumption data, the temperature of the corresponding time period, and the corresponding set priority, respectively.

[0036] Step 3: Find the optimal value corresponding to each weight in the set of weights, and determine the electricity consumption prediction model by combining the optimal values ​​of each sub-preset model and its corresponding weight, and obtain the electricity consumption prediction value.

[0037] Through each sub-classification model And the optimal values ​​of their corresponding weights β1,β2Λβ M Combine and determine the electricity consumption prediction model to obtain the electricity consumption prediction value.

[0038] Step 4: Based on the electricity consumption forecast and the historical actual electricity consumption c, obtain the correction deviation, and determine the final electricity consumption forecast model based on the correction deviation.

[0039] Step S3: Based on the calculated maximum power that the electric boiler can start and the power consumption of each heating module, determine which heating modules can be started;

[0040] After calculating the power consumption of each heating module, the calculation... The value of n is obtained, which is the number of heating modules that can be started. That is, the number of heating modules that can be started when the boiler is as close as possible to the startable power of the electric boiler.

[0041] Step 230: Send a heating instruction to the heating module that needs to be started, and send a stop instruction to the heating module that needs to be stopped.

[0042] Corresponding to the above embodiments, the present invention provides a control system for an electric boiler that does not require capacity expansion. The system includes at least one memory and at least one processor.

[0043] The memory is used to store one or more program instructions;

[0044] A processor is used to run one or more program instructions to execute a control method for an electric boiler that does not require capacity expansion.

[0045] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide a control method for an electric boiler that does not require capacity expansion.

[0046] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are executed on a computer, the computer performs the above-described control method for an electric boiler that does not require capacity expansion.

[0047] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0048] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0049] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0050] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0051] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0052] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0053] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0054] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A non-attenuation electric boiler system control method, characterized by, The power monitoring module monitors the actual power used by the user in real time and transmits the actual power to the electric boiler control mainboard. The electric boiler control mainboard calculates the maximum start-up power of the electric boiler according to the actual power used and the indoor temperature monitored by the temperature sensor, dynamically adjusts the start-up power of the electric boiler, and determines the start-stop of each heating module according to the parameters of each heating module; this step specifically includes: Step S2, inputting the rated power, priority, heating time period, and temperature required for each heating time period of each heating module into the pre-trained power consumption prediction model, and outputting the power consumption of each heating module; Step S1, the power monitor monitors the actual power used by the user in real time, transmits the actual power used by the user to the electric boiler master control board, and calculates the maximum power that the electric boiler can start; the total power S is fixed, the actual power used by the user monitored by the power monitor is W, and the maximum power that the electric boiler can start is , is the deviation amount; Training the power consumption prediction module includes the following sub-steps: Step 1, collect the power consumption data of the electric boiler in the historical time, including the rated power of each heating module, the temperature of the corresponding time period, the priority set for each heating module, and the power consumption in the historical multiple time periods, and construct the power consumption dataset from the above data; Step 2, input the power consumption dataset into different sub-prediction models, respectively use each sub-prediction model to classify the power consumption dataset, and estimate the weight set of each sub-prediction model through the classification result; Specifically, the historical data of the electric boiler is sent to the cloud platform or the mobile device for storage by the remote intelligent control module, the power consumption data in the historical time of the electric boiler is collected, including the rated power of each heating module, the priority set for each heating module, and the temperature of the corresponding time period, and an electricity consumption data set is constructed wherein, respectively represent the heating module rated power, the temperature of the corresponding time period, the corresponding set priority and the power consumption collected in the first time period, respectively represent the heating module rated power, the temperature of the corresponding time period, the corresponding set priority and the power consumption collected in the i-th time period, respectively represent the heating module rated power, the temperature of the corresponding time period, the corresponding set priority and the power consumption collected in the t-th time period; Step 4, according to the power consumption prediction value and the actually measured power consumption c, the correction deviation is obtained, and the final power consumption prediction model is determined according to the correction deviation; Specifically, the power consumption dataset is input into a sub-prediction model ; a recycling sub-classification model Classify the feature vector set, and estimate the weight set of the sub-classification model by the classification result using the formula Classify the feature vector set, and estimate the weight set of the sub-classification model by the classification result using the formula The weight set is The heating module rated power in the power consumption dataset, the temperature corresponding to the time period, and the influence weight corresponding to the priority setting, respectively Step 3, finding the optimal value corresponding to each weight in the set of weights, determining the electricity consumption prediction model through the combination of each sub-preset model and the optimal value of the corresponding weight to obtain the electricity prediction value; specifically through each sub-classification model and the optimal value of the corresponding weight combination to determine the electricity consumption prediction model and obtain the electricity prediction value; sending a heating instruction to the heating module that needs to be started and a stop instruction to the heating module that needs to be stopped. Step S3, determining the heating modules that can be started according to the calculated maximum startable power of the electric boiler and the power consumption of each heating module; specifically, after the power consumption of each heating module is calculated, the following is calculated to obtain the value of n, which is the number of heating modules that can be started, i.e. the number of heating modules that need to be started when the startable power of the electric boiler is as close as possible; The power detector, the temperature sensor, and the adjustable power heating electric boiler; the power monitor is installed in the household electric box for detecting the real-time power of the user and transmitting the real-time power to the adjustable power heating electric boiler; the temperature sensor is used to collect the real-time temperature of the room and transmit the real-time temperature to the adjustable power heating electric boiler; the adjustable power electromagnetic furnace calculates the maximum start-up power allowed for the electric boiler according to the real-time power of the power monitor and the real-time temperature of the temperature sensor, and dynamically adjusts the start-up power of the electric boiler; 2. A non-condensing electric boiler system, characterized by The capacity-free electric boiler system executes the capacity-free electric boiler system control method of claim 1. The electric boiler includes an electric boiler main control board, a heating module control board, and a remote intelligent control module. The heating module control board is connected to multiple heating modules, each heating module is connected to a corresponding electric boiler heating body, and controls the start-stop and temperature of the electric boiler heating body; each heating module is connected to a temperature sensor for monitoring the indoor temperature.

3. The non-expansion electric boiler system of claim 2, wherein, The remote intelligent control module sets and reads parameters of the temperature sensor and the electric boiler through the network.

4. The non-expansion electric boiler system of claim 3, wherein, The electric boiler can be set indoors or in the corridor, connected to the indoor electric box and the heat exchange circulation system, and converts electrical energy into heat energy, and delivers the heat generated by the electrical energy to the user's room for heating.

5. The non-expansion electric boiler system as claimed in claim 3, wherein, The computer readable storage medium contains one or more program instructions for being executed by the processor to perform the capacity-free electric boiler system control method of claim 1.

6. The non-expansion electric boiler system of claim 2, wherein, ​ 7. A computer readable storage medium characterized by ​

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