Household green power and combined heat and power supply integrated system and intelligent energy control method thereof

Abstract

The invention discloses a household green electricity and combined heat and power supply integrated system and an intelligent energy control method thereof. A controller obtains electricity user information, a historical electricity data set and electricity equipment power supply priority information; determining user household power consumption prediction data, green power to-be-generated prediction data and thermoelectric power to-be-generated prediction data through a power consumption prediction model, and further determining photovoltaic power generation working parameters and thermoelectric power generation working parameters of the day; the photovoltaic power generation module generates power according to the photovoltaic power generation working parameters of the day to supply power to the user electrical equipment and / or the water electrolysis hydrogen production module; and the combined heat and power supply module generates power according to the current day thermoelectric power generation working parameters to supply power to the user electrical equipment and / or the heat storage water tank. By means of the method, photovoltaic power generation, hydrogen production, hydrogen storage and combined heat and power supply are integrated into the integrated distributed energy system, the daily electricity utilization requirement of a family can be met, the standby power supply and heating service can be provided, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a household green electricity and cogeneration integrated system and an energy intelligent control method thereof. Background Art

[0002] With the transformation of the global energy structure, the use of green energy is becoming the mainstream trend of household energy supply. On the one hand, photovoltaic power generation, as an important form of renewable energy, has been widely used in household electricity supply. However, the traditional household photovoltaic power generation system is subject to the conditions of grid access and weather conditions, and its power supply stability is insufficient, especially in the case of power outages or insufficient sunlight, users may face power outages.

[0003] On the other hand, hydrogen energy, as a green and efficient secondary energy source, has good storage and transportation characteristics and can be used for a variety of energy needs. The development of hydrogen fuel cell technology has made it possible to use hydrogen energy at the household level.

[0004] The existing household energy system has the following main defects: (1) Poor stability of energy production. For home energy systems that rely on renewable energy such as solar or wind power, their energy production is greatly affected by weather conditions. For example, solar panels may not be able to generate sufficient electricity on cloudy or rainy days; (2) Currently, they are mainly industrial products with poor adaptability to home scenarios. If the hydrogen production and storage equipment used in the industrial field is used in the home, there will be problems such as large land occupation, low safety and high cost, making it difficult to achieve large-scale application; (3) Poor independence of the energy system. The household photovoltaic system is closely coupled with the power grid and lacks an independent backup power supply. It cannot continue to supply power during a power outage, affecting the daily life of the family; (4) Low energy storage capacity. The battery capacity of the home energy storage system is limited and it is difficult to meet the high power demand of the home during peak hours or for a long time. In addition, over time, the battery performance will gradually decline and need to be replaced, which increases the long-term maintenance cost; (5) Safety issues. Energy storage systems represented by lithium batteries have the risk of thermal runaway, which may cause fires. Gas alarm devices, smoke alarm devices, temperature alarm devices, and automatic fire extinguishing devices need to be installed to ensure the safe operation of the system; (6) Poor environmental protection. Although home energy systems are designed to reduce dependence on fossil fuels, the production and disposal of batteries may have an impact on the environment. Discarded batteries need to be properly handled to reduce potential harm to the environment. Summary of the invention

[0005] The embodiments of the present invention provide a household green electricity and combined heat and power integrated system and an energy intelligent control method thereof, aiming to solve the problems in the prior art methods that the existing household energy system is closely coupled with the power grid, lacks an independent backup power supply, has a low power generation utilization rate, is dependent on the power grid to a certain extent, and photovoltaic power generation cannot be fully stored and utilized.

[0006] In the first aspect, an embodiment of the present invention provides an energy intelligent control method for a household green electricity and cogeneration integrated system, which is applied to the household green electricity and cogeneration integrated system, and includes a controller, a photovoltaic power generation module, a converter, a water electrolysis hydrogen production module, a hydrogen storage module, a cogeneration module and a hot water storage tank; the photovoltaic power generation module is connected to the water electrolysis hydrogen production module through the converter, and can also be connected to the user's electrical equipment, the water electrolysis hydrogen production module is connected to the hydrogen storage module, the cogeneration module is connected to the hot water storage tank and can also be connected to the user's electrical equipment, the photovoltaic power generation module, the converter, the water electrolysis hydrogen production module, the hydrogen storage module, the cogeneration module and the hot water storage tank are all communicatively connected to the controller; the energy intelligent control method for the household green electricity and cogeneration integrated system includes: The controller responds to the energy intelligent control instruction, obtains the power user information corresponding to the energy intelligent control instruction, and determines the historical power consumption data set and power supply priority information of the power consumption equipment corresponding to the user power consumption information; The controller obtains user household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and a pre-trained electricity consumption prediction model; The controller determines the green power generation forecast data and the thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment; The controller determines the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and determines the thermal power generation operating parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data; The photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter; The cogeneration module generates electricity according to the thermoelectric power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the hot water storage tank.

[0007] In a second aspect, an embodiment of the present invention provides a household green electricity and heat and power integrated system, which includes A controller, a photovoltaic power generation module, a converter, a water electrolysis hydrogen production module, a hydrogen storage module, a combined heat and power module and a hot water storage tank; the photovoltaic power generation module is connected to the water electrolysis hydrogen production module through the converter, and can also be connected to a user's electrical equipment, the water electrolysis hydrogen production module is connected to the hydrogen storage module, the combined heat and power module is connected to the hot water storage tank and can also be connected to a user's electrical equipment, and the photovoltaic power generation module, the converter, the water electrolysis hydrogen production module, the hydrogen storage module, the combined heat and power module and the hot water storage tank are all communicatively connected to the controller; The controller is used to respond to the energy intelligent control instruction, obtain the power user information corresponding to the energy intelligent control instruction, and determine the historical power consumption data set and power supply priority information of the power consumption equipment corresponding to the user power consumption information; The controller is further configured to obtain user household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and a pre-trained electricity consumption prediction model; The controller is further used to determine the green power generation forecast data and the thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment; The controller is further used to determine the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and to determine the thermal power generation operating parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data; The photovoltaic power generation module is used to generate electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provide the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter; The cogeneration module is used to generate electricity according to the thermoelectric power generation working parameters of the day determined by the controller, and provide the corresponding generated electric energy to the user's electrical equipment and / or the hot water storage tank.

[0008] The embodiment of the present invention provides a household green electricity and cogeneration integrated system and an energy intelligent control method thereof. The system includes a controller, a photovoltaic power generation module, a converter, a water electrolysis hydrogen production module, a hydrogen storage module, a cogeneration module and a hot water storage tank; the energy intelligent control method includes: the controller responds to the energy intelligent control instruction, obtains the electricity user information corresponding to the energy intelligent control instruction, and determines the historical electricity consumption data set corresponding to the user electricity consumption information and the power supply priority information of the power consumption equipment; the controller obtains the user's household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and the pre-trained electricity consumption prediction model; the controller obtains the user's household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the user's household electricity consumption prediction data and the user's household electricity consumption prediction model; the controller obtains the user's household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and the pre-trained ... The controller determines the photovoltaic power generation working parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and determines the thermal power generation working parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data; the photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provides the corresponding electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter; the cogeneration module generates electricity according to the thermal power generation working parameters of the day determined by the controller, and provides the corresponding electric energy to the user's electrical equipment and / or the water storage tank. Through the above method, photovoltaic power generation, hydrogen production, hydrogen storage and cogeneration are integrated into an integrated distributed energy system, which can not only meet the daily electricity needs of households, but also provide backup power and heating services, and improve energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0010] Figure 1 A schematic diagram of an application scenario of an energy intelligent control method for a household green electricity and combined heat and power generation integrated system provided by an embodiment of the present invention; Figure 2 A schematic flow chart of an energy intelligent control method for a household green electricity and combined heat and power generation integrated system provided by an embodiment of the present invention; Figure 3 A schematic diagram of a sub-process of an energy intelligent control method for a household green electricity and combined heat and power generation integrated system provided by an embodiment of the present invention; Figure 4 A schematic diagram of a sub-process of an energy intelligent control method for a household green electricity and combined heat and power generation integrated system provided by an embodiment of the present invention; Figure 5A schematic diagram of a sub-process of an energy intelligent control method for a household green electricity and combined heat and power generation integrated system provided by an embodiment of the present invention; Figure 6 A schematic diagram of a sub-process of an energy intelligent control method for a household green electricity and combined heat and power generation integrated system provided by an embodiment of the present invention; Figure 7 A schematic diagram of a sub-process of an energy intelligent control method for a household green electricity and cogeneration integrated system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0012] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0013] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0014] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0015] See also Figure 1 , which is a schematic diagram of an application scenario of the energy intelligent control method for the household green electricity and cogeneration integrated system provided by an embodiment of the present invention. Figure 1As shown, the household green electricity and combined heat and power integrated system includes a controller 10, a photovoltaic power generation module 20, a converter 21, a water electrolysis hydrogen production module 30, a hydrogen storage module 40, a combined heat and power module 50 and a hot water storage tank 60; the photovoltaic power generation module 20 is connected to the water electrolysis hydrogen production module 30 through the converter 21, and can also be connected to the user's electrical equipment 70, the water electrolysis hydrogen production module 30 is connected to the hydrogen storage module 40, the combined heat and power module 50 is connected to the hot water storage tank 60 and can also be connected to the user's electrical equipment 70, the photovoltaic power generation module 20, the converter 21, the water electrolysis hydrogen production module 30, the hydrogen storage module 40, the combined heat and power module 50 and the hot water storage tank 60 are communicatively connected or electrically connected to the controller 10.

[0016] The integrated household green electricity and combined heat and power system is specifically deployed outside the house, especially outside the houses of independent houses in cities and houses in remote areas with inconvenient power supply (such as mountainous areas, islands, and remote rural and pastoral areas). Moreover, in the integrated household green electricity and combined heat and power system, photovoltaic power generation, water electrolysis hydrogen production, small hydrogen storage tanks and hydrogen combined heat and power are integrated into the system.

[0017] The photovoltaic power generation module 20 is implemented by using photovoltaic panels installed on the roof or wall of a house to generate electricity using solar energy to provide initial power for the system. The photovoltaic power generation module converts direct current into alternating current through an inverter to provide daily electricity for the household.

[0018] The water electrolysis hydrogen production module 30 uses the electricity generated by the photovoltaic power generation module 20 to drive the water electrolysis equipment to decompose water into hydrogen and oxygen. The hydrogen enters the small hydrogen storage tank (i.e., the hydrogen storage module 40) through the pressure regulator for storage.

[0019] Hydrogen storage module 40 uses a small hydrogen storage tank with a safety design to ensure the safety of hydrogen storage. In addition, the capacity of the small hydrogen storage tank is designed based on the daily household usage to maintain a safe hydrogen storage scale.

[0020] The combined heat and power module 50 is a module that generates electricity and waste heat when the household needs additional electricity or heating. The hydrogen in the small hydrogen storage tank will be transported to the hydrogen fuel cell unit in the combined heat and power module 50 to generate electricity and waste heat. The electricity can supplement household electricity or serve as a backup power source, and the waste heat can be used for household heating or hot water supply.

[0021] The hot water storage tank 60 is a hot water storage tank with a heat preservation function, which absorbs the heat energy generated during the hydrogen power generation process of the cogeneration module 50 and stores the heat.

[0022] The controller 10 can be used to deploy a control and safety monitoring system. The controller adjusts the output of the cogeneration module 50 to optimize the distribution and utilization of energy according to the household electricity and heating needs. In addition, the safety monitoring function of the controller 10 can detect the pressure, temperature and hydrogen leakage of the system, and take safety measures such as alarm and chain emergency release in case of sudden dangerous situations. More specifically, the controller 10 can also adjust the power generation power of the photovoltaic panels in the photovoltaic power generation module 20, the output power of the cogeneration module 50 and the amount of hydrogen stored in the hydrogen storage tank in the hydrogen storage module 40 in real time according to the household's electricity demand and thermal energy demand, so as to avoid safety problems caused by excess or insufficient energy supply. Moreover, the controller 10 can also monitor and control the operating status of the entire household green electricity and cogeneration integrated system in real time. It can collect and obtain data such as the power generation of the photovoltaic panels in the photovoltaic power generation module 20, the hydrogen storage pressure of the hydrogen storage tank in the hydrogen storage module 40, and the output power of the cogeneration module 50, and compare and analyze them with the preset power generation threshold, storage tank pressure threshold and cogeneration module output power threshold respectively; if any of the power generation of the photovoltaic panels in the photovoltaic power generation module 20, the hydrogen storage pressure of the hydrogen storage tank in the hydrogen storage module 40, and the output power of the cogeneration module 50 exceeds or falls below the corresponding threshold, an alarm can be issued in time and corresponding control measures can be taken, such as adjusting the operating parameters of the equipment, automatically cutting off the power supply, exhausting ventilation, fire fighting, etc.

[0023] When the household green electricity and combined heat and power integrated system is deployed in a household for use as an example, the specific energy intelligent control method of the household green electricity and combined heat and power integrated system is as follows: Figure 2 As shown, the energy intelligent control method of the household green electricity and cogeneration integrated system includes steps S110 to S160.

[0024] S110, the controller responds to the energy intelligent control instruction, obtains the electricity user information corresponding to the energy intelligent control instruction, and determines the historical electricity consumption data set and power supply priority information of the power-consuming equipment corresponding to the user electricity consumption information.

[0025] In this embodiment, the controller (which can also be understood as a control console, control host, etc.) as the control core of the entire system can intelligently control the daily photovoltaic power generation, water electrolysis hydrogen production, hydrogen cogeneration, etc. processes of the household green electricity and cogeneration system. For example, taking the entire working process of the household green electricity and cogeneration system in a natural day as an example, when the controller detects an energy intelligent control instruction, it means that the specific power generation working mode of the household green electricity and cogeneration system on that day needs to be intelligently controlled.

[0026] Generally, in order to improve the effectiveness of the energy intelligent control method of the household green electricity and cogeneration integrated system, the energy intelligent control instruction can be automatically generated at the time corresponding to the 30 minutes before the time point when photovoltaic power generation can be effectively utilized (for example, 6:30). After that, the controller needs to first obtain the electricity user information corresponding to the household where the household green electricity and cogeneration integrated system is deployed, and at the same time obtain the historical electricity consumption data set corresponding to the user's electricity consumption information and the power supply priority information of the electricity-consuming equipment, and use the above-mentioned information and data as the initial basic data for subsequent intelligent control.

[0027] In one embodiment, if Figure 3 As shown, step S110 includes: S111, based on the instruction generation time of the energy intelligent control instruction, determining the target time interval by the instruction generation time and the preset data acquisition cycle; S112, obtaining the unique number of the user ID in the electricity user information, and obtaining the corresponding historical electricity consumption data set from the storage space corresponding to the controller based on the unique number of the user ID and the target time interval; wherein the historical electricity consumption data set includes multiple historical electricity consumption data, each of which corresponds to a unique electricity consumption date within the target time interval, and each of which includes the electricity consumption, electricity consumption time distribution information and power of multiple user electrical appliances respectively; S113. Acquire corresponding power supply priority information of the electric device from a storage space corresponding to the controller based on the user ID unique number and the target time interval.

[0028] In this embodiment, when the controller determines the target time interval corresponding to the energy intelligent control instruction, it first needs to determine the instruction generation time. At this time, a current date such as XX3, XX2, XX1 can be determined for the instruction generation time. Because a preset data acquisition cycle is also preset in the controller (such as a week, 10 days, 15 days, one month, three months, half a year, etc., of course, it is not limited to the above duration during specific implementation, and can be flexibly set according to the actual needs of the user), after the current date and preset data acquisition cycle corresponding to the instruction generation time are known, [current date-preset data acquisition cycle, current date-1] can be used as the target time interval.

[0029] After that, the unique number of the user ID in the electricity user information is obtained, and the unique number of the user ID and the target time interval are used as search conditions to obtain the corresponding historical electricity consumption data set from the storage space corresponding to the controller. In the total historical electricity consumption data set stored in the storage space corresponding to the controller (which can be either a local storage space or a storage space of a cloud server, and the controller can be connected to the cloud server for communication), historical electricity consumption data corresponding to the unique number of the user ID and corresponding to multiple electricity consumption dates are stored, and each piece of historical electricity consumption data includes the electricity consumption corresponding to multiple user electrical appliances, electricity consumption time distribution information (i.e., several time periods when the electrical appliances mainly consume electricity), and the power of the electrical appliances.

[0030] Finally, the corresponding power supply priority information of the electrical equipment can also be obtained from the storage space corresponding to the controller based on the unique number of the user ID and the target time interval as the retrieval conditions. The power supply priority information of the electrical equipment includes power supply priority data set for multiple electrical appliances. For example, taking an electrical appliance A1 as an example, the electrical appliance A1 sets the first power supply priority (regarded as the highest power supply priority) and the power supply requirement remark information is uninterrupted power supply, which means that when the electrical appliance A1 is powered by the household green electricity and cogeneration integrated system, the corresponding power supply can be used when both the power grid and the photovoltaic power generation module can supply power. However, as long as both the power grid and the photovoltaic power generation module cannot supply power, it is necessary to immediately switch to the cogeneration module to provide uninterrupted power supply to the electrical appliance A1. Among them, the power supply priority information of the electrical equipment with the unique number of the user ID can be flexibly adjusted by the user according to the update of the electrical appliances in the user's home, and it is not a fixed information.

[0031] S120. The controller obtains user household electricity consumption prediction data corresponding to the historical electricity consumption dataset based on the historical electricity consumption dataset and a pre-trained electricity consumption prediction model.

[0032] In this embodiment, after a historical electricity consumption data set corresponding to the user's electricity consumption information is obtained in the controller, the historical electricity consumption data set can be input as input data into an electricity consumption prediction model. The electricity consumption prediction model can be used to predict the user's household electricity consumption on the natural day corresponding to the time when the energy intelligent control instruction is generated. This can then be used to intelligently control the specific power generation working mode of the household green electricity and cogeneration integrated system on that day based on the user's household electricity consumption prediction data.

[0033] In one embodiment, if Figure 4 As shown, step S120 includes: S121, obtaining the i-th historical electricity consumption data subset corresponding to the i-th electrical appliance in the historical electricity consumption data set; wherein the initial value of i is 1; S122, concatenating the electricity consumption data in the i-th historical electricity consumption data subset in ascending order of date to form the i-th electrical appliance input vector; S123, inputting the input vector of the i-th electrical appliance into the power consumption prediction model to obtain power consumption prediction data of the i-th electrical appliance; S124, increment i by 1 to update the value of i; S125, if it is determined that i does not exceed N, then return to the step of obtaining the i-th historical electricity consumption data subset corresponding to the i-th electrical appliance in the historical electricity consumption data set; wherein N is the total number of electrical appliances included in the historical electricity consumption data set; S126: If it is determined that i exceeds N, the electricity consumption forecast data of the first electrical appliance to the Nth electrical appliance are obtained and constitute the user's household electricity consumption forecast data.

[0034] In this embodiment, in the scenario where the household green electricity and cogeneration integrated system is deployed in a household, since there are multiple electrical appliances in the household, such as the 1st electrical appliance to the Nth electrical appliance, the electrical consumption forecast data of each electrical appliance on the natural day corresponding to the time when the energy intelligent control instruction is generated can be intelligently predicted.

[0035] Specifically, taking the process of predicting the first electrical appliance power consumption forecast data of the first electrical appliance as an example, first obtain the first historical power consumption data subset corresponding to the first electrical appliance from the historical power consumption data set; then, concatenate the power consumption data in the first historical power consumption data subset in ascending order of date to form the first electrical appliance input vector; finally, input the first electrical appliance input vector into the power consumption forecast model (such as a BP neural network model, a time series model or other forecasting model used in the specific implementation) to obtain the first electrical appliance power consumption forecast data. Among them, the power consumption forecast data of other electrical appliances in the historical power consumption data set is also obtained by referring to the above process of obtaining the first electrical appliance power consumption forecast data, which will not be repeated here. After the power consumption forecast data of multiple electrical appliances in the family on the day are obtained, the user's family power consumption forecast data can be formed.

[0036] S130. The controller determines green power generation forecast data and thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment.

[0037] In this embodiment, when the user's household electricity consumption forecast data and the power supply priority information of the electrical equipment are obtained in the controller, it can be specifically determined whether each electrical appliance needs green electricity or thermal power supply. After determining the green electricity / thermal power supply type of each electrical appliance in the household, the household's green electricity to be generated forecast data and thermal power to be generated forecast data can be accurately determined.

[0038] In one embodiment, if Figure 5 As shown, step S130 includes: S131, obtaining the electricity consumption forecast data of the jth electrical appliance in the household electricity consumption forecast data of the user; wherein the initial value of j is 1; S132, obtaining the jth electrical appliance corresponding to the power consumption forecast data of the jth electrical appliance, and determining the jth electrical appliance power supply priority information and the jth electrical appliance power supply requirement information corresponding to the jth electrical appliance in the power supply priority information of the electrical equipment; S133. If it is determined that the power supply priority information of the j-th electrical appliance and the power supply requirement information of the j-th electrical appliance meet the first preset condition, obtain the current green electricity to be generated prediction data, and add the power consumption prediction data of the j-th electrical appliance to the current green electricity to be generated prediction data, so as to update the current green electricity to be generated prediction data; S134, if it is determined that the power supply priority information of the j-th electrical appliance and the power supply requirement information of the j-th electrical appliance meet the second preset condition, then obtaining the current thermal power generation prediction data, and adding the power consumption prediction data of the j-th electrical appliance to the current thermal power generation prediction data, so as to update the current thermal power generation prediction data; S135, increment j by 1 to update the value of j; S136: If it is determined that j does not exceed N, return to the step of obtaining the jth electrical appliance power consumption forecast data in the user's household power consumption forecast data; S137: If it is determined that j exceeds N, the current green power generation prediction data is obtained and used as the green power generation prediction data, and the current thermal power generation prediction data is obtained and used as the thermal power generation prediction data.

[0039] In this embodiment, a first preset condition is preset that the power supply priority corresponding to the power supply priority information of the electrical appliance is lower than the first power supply priority (such as the second power supply priority, the third power supply priority, etc., which are power supply priorities exceeding the first power supply priority); and a second preset condition is preset that the power supply priority corresponding to the power supply priority information of the electrical appliance is equal to the first power supply priority and the power supply requirement information of the electrical appliance is uninterrupted power supply; of course, the above-mentioned first preset condition and the second preset condition are only a specific example, and the specific implementation is not limited to the above-mentioned example, but can be flexibly set according to user needs. Still referring to the above example, taking the green electricity / thermal power supply type determination process of the first electrical appliance power consumption forecast data of the first electrical appliance of the household as an example, the first electrical appliance corresponding to the first electrical appliance power consumption forecast data is first obtained, and the first electrical appliance power supply priority information and the first electrical appliance power supply requirement information (which can be understood as power supply requirement remark information) corresponding to the first electrical appliance are determined in the power supply priority information of the electrical equipment. Afterwards, if it is determined that the power supply priority information of the first power consumer and the power supply requirement information of the first power consumer meet the first preset condition, it is necessary to obtain the current green electricity to be generated forecast data (generally, the initial value of the current green electricity to be generated forecast data of the day is 0, and it is continuously updated and adjusted with each round of updates), and add the power consumption forecast data of the first power consumer to the current green electricity to be generated forecast data to update the current green electricity to be generated forecast data; if it is determined that the power supply priority information of the first power consumer and the power supply requirement information of the first power consumer meet the second preset condition, it is necessary to obtain the current thermal power to be generated forecast data (generally, the initial value of the current thermal power to be generated forecast data of the day is 0, and it is continuously updated and adjusted with each round of updates), and add the power consumption forecast data of the first power consumer to the current thermal power to be generated forecast data to update the current thermal power to be generated forecast data.

[0040] Among them, the electricity consumption forecast data of other electrical appliances in the historical electricity consumption data set is obtained and added to the current green electricity to be generated forecast data or the current thermal power to be generated forecast data. It also refers to the above process and will not be repeated here. When the electricity consumption forecast data of multiple electrical appliances in the household on the day are added to the current green electricity to be generated forecast data or the current thermal power to be generated forecast data, the final updated current green electricity to be generated forecast data can be obtained and used as the green electricity to be generated forecast data, and the final updated current thermal power to be generated forecast data can be obtained and used as the thermal power to be generated forecast data. It can be seen that after determining the green electricity / thermal power supply type of each electrical appliance in the household through the above method, the green electricity to be generated forecast data and the thermal power to be generated forecast data of the household can be accurately determined.

[0041] S140, the controller determines the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and determines the thermal power generation operating parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data.

[0042] In this embodiment, after the green power generation forecast data and thermal power generation forecast data of the household are determined in the controller, the photovoltaic power generation working parameters corresponding to the photovoltaic power generation module on the day can be determined based on the green power generation forecast data, and the thermal power generation working parameters corresponding to the cogeneration module on the day can be determined based on the thermal power generation forecast data. The photovoltaic power generation working parameters obtained on the day can be used to determine the specific working state of the photovoltaic power generation module on the day, and the thermal power generation working parameters obtained on the day can be used to determine the specific working state of the cogeneration module on the day.

[0043] In one embodiment, if Figure 6 As shown, step S140 includes: S141, obtaining the maximum photovoltaic power generation power of the photovoltaic power generation module, and obtaining the sunshine weather forecast data of the day from the background server; S142. Determine the photovoltaic power generation operating parameters for the day based on the sunshine duration on the day in the sunshine weather forecast data for the day and the green electricity to be generated forecast data; wherein the photovoltaic average power generation in the photovoltaic power generation operating parameters for the day is less than or equal to the photovoltaic maximum power generation.

[0044] In this embodiment, the controller can obtain the maximum photovoltaic power generation power of the photovoltaic power generation module (such as denoted as P1), and can also obtain the sunshine weather forecast data of the day from the background server with which a communication connection has been established (which specifically includes the duration of sunshine on the day, and the sunshine intensity at different time points on the day, and based on the sunshine weather forecast data of the day, the maximum power generation of the photovoltaic power generation module on the day and other information can be effectively estimated).

[0045] Then, a photovoltaic power generation working parameter suitable for the sunshine conditions of the day is determined based on the sunshine duration of the day in the sunshine weather forecast data of the day (more specifically, it can also be combined with the sunshine intensity at different time points of the day) and the photovoltaic maximum power generation power P1 of the photovoltaic power generation module. Among them, it should be noted that the photovoltaic average power generation power in the photovoltaic power generation working parameter of the day is less than or equal to the photovoltaic maximum power generation power. After determining the photovoltaic power generation working parameter of the photovoltaic power generation module for the specific green electricity generation on the day, the photovoltaic power generation working parameter of the day is specifically referred to for operation to effectively utilize solar power generation.

[0046] In one embodiment, if Figure 6As shown, after step S142 in step S140, the following steps are further included: S143, obtaining the maximum thermal power generation power of the cogeneration module, and obtaining the remaining hydrogen storage capacity of the hydrogen storage module on that day; S144, if it is determined that the thermal power generation amount corresponding to the remaining hydrogen storage amount on the day is less than the thermal power generation prediction data, then the difference in the amount of electricity on the day between the thermal power generation prediction data and the thermal power generation amount on the day is obtained, and the actual thermal power generation amount on the day is determined based on the preset thermal power storage amount and the difference in the amount of electricity on the day; S145. Determine the thermal power generation operating parameters for the day based on the actual thermal power generation for the day and the maximum thermal power generation power for the day.

[0047] In this embodiment, the controller can obtain the maximum thermoelectric power generation power of the cogeneration module (such as denoted as P2), and can also obtain the remaining hydrogen storage capacity for the day from the hydrogen storage module (which is the remaining hydrogen storage capacity for the day obtained from the hydrogen storage module at the time point corresponding to the instruction generation time of the energy intelligent control instruction), and according to the remaining hydrogen storage capacity for the day and the preset thermoelectric power generation efficiency value (corresponding to a percentage parameter value, which is used to represent the ratio between the actual power generation determined in the thermoelectric power generation process when the hydrogen storage capacity is known and the theoretical power generation), the thermoelectric power generation capacity for the day can be determined (the theoretical power generation corresponding to the remaining hydrogen storage capacity for the day * the thermoelectric power generation efficiency value).

[0048] After determining the amount of thermal power that can be generated on the day, if it is further determined that it is less than the predicted data for the amount of thermal power to be generated, it means that the electricity generated by the remaining hydrogen storage on the day being specifically delivered to the cogeneration module for thermal power generation is not enough to meet the thermal power demand on the day. It is necessary to first obtain the difference in the amount of electricity on the day between the predicted data for thermal power to be generated and the amount of thermal power that can be generated on the day, and then determine the actual amount of thermal power generated on the day based on the preset thermal power storage amount (this preset amount of thermal power storage is to determine that a certain amount of hydrogen needs to be stored in the hydrogen storage module at the end of the day to be used as a source of thermal power generation tomorrow) and the difference in the amount of electricity on the day. Finally, based on the actual amount of thermal power generated on the day and the maximum thermal power generation power P2, a thermal power generation operating parameter for the day that is suitable for the actual situation on the day can be determined. It should also be noted that the average thermal power generation power in the thermal power generation operating parameters on the day is less than or equal to the maximum thermal power generation power. After determining the thermal power generation operating parameters of the cogeneration module for performing thermal power generation on that day, the module is operated with reference to the thermal power generation operating parameters for that day to effectively utilize hydrogen for power generation, and at the same time, the heat energy generated during the hydrogen power generation process can be transferred to the hot water storage tank for heat storage.

[0049] S150, the photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter.

[0050] In this embodiment, after the controller determines the photovoltaic power generation working parameters of the day, the photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day, and provides the corresponding electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter. The specific situation of whether the electric energy generated by the photovoltaic power generation module is provided to the user's electrical equipment and / or the water electrolysis hydrogen production module needs to be determined by the user. In one embodiment, if Figure 7 As shown, step S150 includes: S151, the photovoltaic power generation module obtains a first power distribution ratio for distributing power to user electrical equipment, and a second power distribution ratio for distributing power to the water electrolysis hydrogen production module; S152. Generate electricity according to the photovoltaic power generation parameters of the day, provide the generated electric energy to the user's electrical equipment based on the first power distribution ratio, and provide the generated electric energy to the water electrolysis hydrogen production module based on the second power distribution ratio.

[0051] In this embodiment, a first electricity distribution ratio for distributing electricity to user electrical equipment and a second electricity distribution ratio for distributing electricity to a water electrolysis hydrogen production module can be pre-set for the photovoltaic power generation module. The above-mentioned first electricity distribution ratio and second electricity distribution ratio can be fixed values ​​for each day, or can be flexibly set according to the weather conditions of the day.

[0052] After knowing that the photovoltaic power generation module obtains the first power distribution ratio for distributing power to the user's electrical equipment and the second power distribution ratio for distributing power to the water electrolysis hydrogen production module, when the photovoltaic power generation module generates power based on the photovoltaic power generation parameters of the day, the generated electric energy is provided to the user's electrical equipment based on the first power distribution ratio to directly power the equipment, and the generated electric energy is provided to the water electrolysis hydrogen production module based on the second power distribution ratio. The water electrolysis hydrogen production module produces hydrogen through electrolysis, and stores renewable energy through the hydrogen storage module. When the user's electrical equipment on the user side needs energy, the prepared hydrogen can be supplied to the cogeneration module. The cogeneration module uses the electric energy generated by hydrogen to provide it to the user's electrical equipment on the user side, and the generated heat energy is stored in the water storage tank, which improves the utilization rate of green electricity.

[0053] S160, the cogeneration module generates electricity according to the thermoelectric power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the hot water storage tank.

[0054] In this embodiment, when the cogeneration module generates electricity according to the thermoelectric power generation working parameters of the day, since the cogeneration module is connected to the hydrogen storage module through a gas supply pipeline, the cogeneration module can obtain hydrogen from the hydrogen storage module and generate electricity, thereby supplying power to the user's electrical equipment connected to the cogeneration module, and transferring the generated heat energy to the hot water storage tank for heat storage. The above process makes full use of the electrical energy and heat energy generated in the hydrogen power generation process. The hot water storage tank is used to store the heat energy generated by the cogeneration module to provide heating to users or hot water for domestic use.

[0055] It can be seen that through the above method, photovoltaic power generation, hydrogen production, hydrogen storage and cogeneration can be integrated into an integrated distributed energy system, which can not only meet the daily electricity needs of households, but also provide backup power and heating services, thereby improving energy utilization efficiency.

[0056] The embodiment of the present invention also provides a household green electricity and heat and power integrated system, which is used to implement the energy intelligent control method of the household green electricity and heat and power integrated system as described above. Figure 1 As shown, the household green electricity and cogeneration integrated system includes a controller 10, a photovoltaic power generation module 20, a converter 21, a water electrolysis hydrogen production module 30, a hydrogen storage module 40, a cogeneration module 50 and a hot water storage tank 60; the photovoltaic power generation module 20 is connected to the water electrolysis hydrogen production module 30 through the converter 21, and can also be connected to the user's electrical equipment 70, the water electrolysis hydrogen production module 30 is connected to the hydrogen storage module 40, the cogeneration module 50 is connected to the hot water storage tank 60 and can also be connected to the user's electrical equipment 70, the photovoltaic power generation module 20, the converter 21, the water electrolysis hydrogen production module 30, the hydrogen storage module 40, the cogeneration module 50 and the hot water storage tank 60 are communicatively connected or electrically connected to the controller 10.

[0057] The integrated household green electricity and combined heat and power system is specifically deployed outside the house, especially outside the houses of independent houses in cities and houses in remote areas with inconvenient power supply (such as mountainous areas, islands, and remote rural and pastoral areas). Moreover, in the integrated household green electricity and combined heat and power system, photovoltaic power generation, water electrolysis hydrogen production, small hydrogen storage tanks and hydrogen combined heat and power are integrated into the system.

[0058] The photovoltaic power generation module 20 is implemented by using photovoltaic panels installed on the roof or wall of a house to generate electricity using solar energy to provide initial power for the system. The photovoltaic power generation module converts direct current into alternating current through an inverter to provide daily electricity for the household.

[0059] The water electrolysis hydrogen production module 30 uses the electricity generated by the photovoltaic power generation module 20 to drive the water electrolysis equipment to decompose water into hydrogen and oxygen. The hydrogen enters the small hydrogen storage tank (i.e., the hydrogen storage module 40) through the pressure regulator for storage.

[0060] Hydrogen storage module 40 uses a small hydrogen storage tank with a safety design to ensure the safety of hydrogen storage. In addition, the capacity of the small hydrogen storage tank is designed based on the daily household usage to maintain a safe hydrogen storage scale.

[0061] The combined heat and power module 50 is a module that generates electricity and waste heat when the household needs additional electricity or heating. The hydrogen in the small hydrogen storage tank will be transported to the hydrogen fuel cell unit in the combined heat and power module 50 to generate electricity and waste heat. The electricity can supplement household electricity or serve as a backup power source, and the waste heat can be used for household heating or hot water supply.

[0062] The controller 10 can be used to deploy a control and safety monitoring system. The controller adjusts the output of the cogeneration module 50 to optimize the distribution and utilization of energy according to the household electricity and heating needs. In addition, the safety monitoring function of the controller 10 can be used to detect the pressure, temperature and hydrogen leakage of the system, and to take safety measures such as alarm and chain emergency release in case of sudden dangerous situations.

[0063] Compared with the existing household energy system, the household green electricity and combined heat and power system used in this application achieves the following beneficial effects: 1) Small-scale hydrogen production and safe storage, that is, by designing small-scale hydrogen production and storage equipment suitable for household use, the safe production and storage of hydrogen energy is achieved, ensuring the continuity and safety of household energy supply; 2) Integrated energy system, which combines photovoltaic power generation with hydrogen energy utilization to form an independent energy supply system, greatly improving energy utilization efficiency and enhancing the independence and stability of the system; 3) Multifunctional integration, that is, the system not only provides electricity, but also has heating function, which can flexibly respond to the diverse energy needs of households and reduce dependence on external power grids; 4) Enhance the utilization rate of photovoltaic power generation, that is, convert the excess photovoltaic power during the day into chemical energy storage through the method of electrolyzing water to produce hydrogen, thereby reducing energy waste; 5) Energy conservation and emission reduction, that is, by using green energy to replace traditional fossil fuels, significantly reducing household carbon emissions and achieving energy conservation and environmental protection.

[0064] More specifically, in the integrated system of household green electricity and combined heat and power: The controller 10 is used to respond to the energy intelligent control instruction, obtain the power user information corresponding to the energy intelligent control instruction, and determine the historical power consumption data set and power supply priority information of the power consumption equipment corresponding to the user power consumption information.

[0065] In this embodiment, the controller (which can also be understood as a control console, control host, etc.) as the control core of the entire system can intelligently control the daily photovoltaic power generation, water electrolysis hydrogen production, hydrogen cogeneration, etc. processes of the household green electricity and cogeneration system. For example, taking the entire working process of the household green electricity and cogeneration system in a natural day as an example, when the controller detects an energy intelligent control instruction, it means that the specific power generation working mode of the household green electricity and cogeneration system on that day needs to be intelligently controlled.

[0066] Generally, in order to improve the effectiveness of the energy intelligent control method of the household green electricity and cogeneration integrated system, the energy intelligent control instruction can be automatically generated at the time corresponding to the 30 minutes before the time point when photovoltaic power generation can be effectively utilized (for example, 6:30). After that, the controller needs to first obtain the electricity user information corresponding to the household where the household green electricity and cogeneration integrated system is deployed, and at the same time obtain the historical electricity consumption data set corresponding to the user's electricity consumption information and the power supply priority information of the electricity-consuming equipment, and use the above-mentioned information and data as the initial basic data for subsequent intelligent control.

[0067] In one embodiment, the controller 10 is specifically used for: Based on the instruction generation time of the energy intelligent control instruction, the target time interval is determined by the instruction generation time and the preset data acquisition cycle; Obtain the unique number of the user ID in the electricity user information, and obtain the corresponding historical electricity consumption data set from the storage space corresponding to the controller based on the unique number of the user ID and the target time interval; wherein the historical electricity consumption data set includes multiple historical electricity consumption data, each of which corresponds to a unique electricity consumption date within the target time interval, and each of which includes the electricity consumption, electricity consumption time distribution information and power of multiple user electrical appliances respectively; Based on the user ID unique number and the target time interval, corresponding power supply priority information of the power-consuming device is obtained from the storage space corresponding to the controller.

[0068] In this embodiment, when the controller determines the target time interval corresponding to the energy intelligent control instruction, it first needs to determine the instruction generation time. At this time, a current date such as XX3, XX2, XX1 can be determined for the instruction generation time. Because a preset data acquisition cycle is also preset in the controller (such as a week, 10 days, 15 days, one month, three months, half a year, etc., of course, it is not limited to the above duration during specific implementation, and can be flexibly set according to the actual needs of the user), after the current date and preset data acquisition cycle corresponding to the instruction generation time are known, [current date-preset data acquisition cycle, current date-1] can be used as the target time interval.

[0069] After that, the unique number of the user ID in the electricity user information is obtained, and the unique number of the user ID and the target time interval are used as search conditions to obtain the corresponding historical electricity consumption data set from the storage space corresponding to the controller. In the total historical electricity consumption data set stored in the storage space corresponding to the controller (which can be either a local storage space or a storage space of a cloud server, and the controller can be connected to the cloud server for communication), historical electricity consumption data corresponding to the unique number of the user ID and corresponding to multiple electricity consumption dates are stored, and each piece of historical electricity consumption data includes the electricity consumption corresponding to multiple user electrical appliances, electricity consumption time distribution information (i.e., several time periods when the electrical appliances mainly consume electricity), and the power of the electrical appliances.

[0070] Finally, the corresponding power supply priority information of the electrical equipment can also be obtained from the storage space corresponding to the controller based on the unique number of the user ID and the target time interval as the retrieval conditions. The power supply priority information of the electrical equipment includes power supply priority data set for multiple electrical appliances. For example, taking an electrical appliance A1 as an example, the electrical appliance A1 sets the first power supply priority (regarded as the highest power supply priority) and the power supply requirement remark information is uninterrupted power supply, which means that when the electrical appliance A1 is powered by the household green electricity and cogeneration integrated system, the corresponding power supply can be used when both the power grid and the photovoltaic power generation module can supply power. However, as long as both the power grid and the photovoltaic power generation module cannot supply power, it is necessary to immediately switch to the cogeneration module to provide uninterrupted power supply to the electrical appliance A1. Among them, the power supply priority information of the electrical equipment with the unique number of the user ID can be flexibly adjusted by the user according to the update of the electrical appliances in the user's home, and it is not a fixed information.

[0071] The controller 10 is further configured to obtain user household electricity consumption prediction data corresponding to the historical electricity consumption dataset based on the historical electricity consumption dataset and a pre-trained electricity consumption prediction model.

[0072] In this embodiment, after a historical electricity consumption data set corresponding to the user's electricity consumption information is obtained in the controller, the historical electricity consumption data set can be input as input data into an electricity consumption prediction model. The electricity consumption prediction model can be used to predict the user's household electricity consumption on the natural day corresponding to the time when the energy intelligent control instruction is generated. This can then be used to intelligently control the specific power generation working mode of the household green electricity and cogeneration integrated system on that day based on the user's household electricity consumption prediction data.

[0073] In one embodiment, the controller 10 is further specifically configured to: Obtaining an i-th historical electricity consumption data subset corresponding to an i-th electrical appliance in the historical electricity consumption data set; wherein an initial value of i is 1; Concatenate each power consumption data in the i-th historical power consumption data subset in ascending order of date to form the i-th power consumption appliance input vector; Inputting the input vector of the i-th electrical appliance into the power consumption prediction model to obtain the power consumption prediction data of the i-th electrical appliance; Increment i by 1 to update the value of i; If it is determined that i does not exceed N, then return to the step of obtaining the i-th historical electricity consumption data subset corresponding to the i-th electrical appliance in the historical electricity consumption data set; wherein N is the total number of electrical appliances included in the historical electricity consumption data set; If it is determined that i exceeds N, the electricity consumption forecast data of the first electrical appliance to the Nth electrical appliance are obtained and constitute the user's household electricity consumption forecast data.

[0074] In this embodiment, in the scenario where the household green electricity and cogeneration integrated system is deployed in a household, since there are multiple electrical appliances in the household, such as the 1st electrical appliance to the Nth electrical appliance, the electrical consumption forecast data of each electrical appliance on the natural day corresponding to the time when the energy intelligent control instruction is generated can be intelligently predicted.

[0075] Specifically, taking the process of predicting the first electrical appliance power consumption forecast data of the first electrical appliance as an example, first obtain the first historical power consumption data subset corresponding to the first electrical appliance from the historical power consumption data set; then, concatenate the power consumption data in the first historical power consumption data subset in ascending order of date to form the first electrical appliance input vector; finally, input the first electrical appliance input vector into the power consumption forecast model (such as a BP neural network model, a time series model or other forecasting model used in the specific implementation) to obtain the first electrical appliance power consumption forecast data. Among them, the power consumption forecast data of other electrical appliances in the historical power consumption data set is also obtained by referring to the above process of obtaining the first electrical appliance power consumption forecast data, which will not be repeated here. After the power consumption forecast data of multiple electrical appliances in the family on the day are obtained, the user's family power consumption forecast data can be formed.

[0076] The controller 10 is further configured to determine green power generation forecast data and thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment.

[0077] In this embodiment, when the user's household electricity consumption forecast data and the power supply priority information of the electrical equipment are obtained in the controller, it can be specifically determined whether each electrical appliance needs green electricity or thermal power supply. After determining the green electricity / thermal power supply type of each electrical appliance in the household, the household's green electricity to be generated forecast data and thermal power to be generated forecast data can be accurately determined.

[0078] In one embodiment, the controller 10 is further specifically configured to: Obtaining the electricity consumption forecast data of the jth electrical appliance in the household electricity consumption forecast data of the user; wherein the initial value of j is 1; Obtaining the jth electrical appliance corresponding to the power consumption forecast data of the jth electrical appliance, and determining the jth electrical appliance power supply priority information and the jth electrical appliance power supply requirement information corresponding to the jth electrical appliance in the power supply priority information of the electrical equipment; If it is determined that the power supply priority information of the j-th electrical appliance and the power supply requirement information of the j-th electrical appliance meet the first preset condition, the current green electricity to be generated prediction data is obtained, and the power consumption prediction data of the j-th electrical appliance is added to the current green electricity to be generated prediction data, so as to update the current green electricity to be generated prediction data; If it is determined that the power supply priority information of the j-th electrical appliance and the power supply requirement information of the j-th electrical appliance meet the second preset condition, then obtaining the current thermal power generation prediction data, and adding the power consumption prediction data of the j-th electrical appliance to the current thermal power generation prediction data, so as to update the current thermal power generation prediction data; Increment j by 1 to update the value of j; If it is determined that j does not exceed N, returning to the step of obtaining the jth electrical appliance power consumption forecast data in the user's household power consumption forecast data; If it is determined that j exceeds N, the current green power generation prediction data is obtained and used as the green power generation prediction data, and the current thermal power generation prediction data is obtained and used as the thermal power generation prediction data.

[0079] In this embodiment, a first preset condition is preset that the power supply priority corresponding to the power supply priority information of the electrical appliance is lower than the first power supply priority (such as the second power supply priority, the third power supply priority, etc., which are power supply priorities exceeding the first power supply priority); and a second preset condition is preset that the power supply priority corresponding to the power supply priority information of the electrical appliance is equal to the first power supply priority and the power supply requirement information of the electrical appliance is uninterrupted power supply; of course, the above-mentioned first preset condition and the second preset condition are only a specific example, and the specific implementation is not limited to the above-mentioned example, but can be flexibly set according to user needs. Still referring to the above example, taking the green electricity / thermal power supply type determination process of the first electrical appliance power consumption forecast data of the first electrical appliance of the household as an example, the first electrical appliance corresponding to the first electrical appliance power consumption forecast data is first obtained, and the first electrical appliance power supply priority information and the first electrical appliance power supply requirement information (which can be understood as power supply requirement remark information) corresponding to the first electrical appliance are determined in the power supply priority information of the electrical equipment. Afterwards, if it is determined that the power supply priority information of the first power consumer and the power supply requirement information of the first power consumer meet the first preset condition, it is necessary to obtain the current green electricity to be generated forecast data (generally, the initial value of the current green electricity to be generated forecast data of the day is 0, and it is continuously updated and adjusted with each round of updates), and add the power consumption forecast data of the first power consumer to the current green electricity to be generated forecast data to update the current green electricity to be generated forecast data; if it is determined that the power supply priority information of the first power consumer and the power supply requirement information of the first power consumer meet the second preset condition, it is necessary to obtain the current thermal power to be generated forecast data (generally, the initial value of the current thermal power to be generated forecast data of the day is 0, and it is continuously updated and adjusted with each round of updates), and add the power consumption forecast data of the first power consumer to the current thermal power to be generated forecast data to update the current thermal power to be generated forecast data.

[0080] Among them, the electricity consumption forecast data of other electrical appliances in the historical electricity consumption data set is obtained and added to the current green electricity to be generated forecast data or the current thermal power to be generated forecast data. It also refers to the above process and will not be repeated here. When the electricity consumption forecast data of multiple electrical appliances in the household on the day are added to the current green electricity to be generated forecast data or the current thermal power to be generated forecast data, the final updated current green electricity to be generated forecast data can be obtained and used as the green electricity to be generated forecast data, and the final updated current thermal power to be generated forecast data can be obtained and used as the thermal power to be generated forecast data. It can be seen that after determining the green electricity / thermal power supply type of each electrical appliance in the household through the above method, the green electricity to be generated forecast data and the thermal power to be generated forecast data of the household can be accurately determined.

[0081] The controller 10 is further used to determine the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and to determine the thermal power generation operating parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data.

[0082] In this embodiment, after the green power generation forecast data and thermal power generation forecast data of the household are determined in the controller, the photovoltaic power generation working parameters corresponding to the photovoltaic power generation module on the day can be determined based on the green power generation forecast data, and the thermal power generation working parameters corresponding to the cogeneration module on the day can be determined based on the thermal power generation forecast data. The photovoltaic power generation working parameters obtained on the day can be used to determine the specific working state of the photovoltaic power generation module on the day, and the thermal power generation working parameters obtained on the day can be used to determine the specific working state of the cogeneration module on the day.

[0083] In one embodiment, the controller 10 is further specifically configured to: Obtain the maximum photovoltaic power generation power of the photovoltaic power generation module, and obtain the sunshine weather forecast data of the day from the background server; Based on the sunshine duration on that day in the sunshine weather forecast data on that day and the green electricity generation forecast data, the photovoltaic power generation working parameters on that day are determined; wherein the photovoltaic average power generation power in the photovoltaic power generation working parameters on that day is less than or equal to the photovoltaic maximum power generation power.

[0084] In this embodiment, the controller can obtain the maximum photovoltaic power generation power of the photovoltaic power generation module (such as denoted as P1), and can also obtain the sunshine weather forecast data of the day from the background server with which a communication connection has been established (which specifically includes the duration of sunshine on the day, and the sunshine intensity at different time points on the day, and based on the sunshine weather forecast data of the day, the maximum power generation of the photovoltaic power generation module on the day and other information can be effectively estimated).

[0085] Then, a photovoltaic power generation working parameter suitable for the sunshine conditions of the day is determined based on the sunshine duration of the day in the sunshine weather forecast data of the day (more specifically, it can also be combined with the sunshine intensity at different time points of the day) and the photovoltaic maximum power generation power P1 of the photovoltaic power generation module. Among them, it should be noted that the photovoltaic average power generation power in the photovoltaic power generation working parameter of the day is less than or equal to the photovoltaic maximum power generation power. After determining the photovoltaic power generation working parameter of the photovoltaic power generation module for the specific green electricity generation on the day, the photovoltaic power generation working parameter of the day is specifically referred to for operation to effectively utilize solar power generation.

[0086] In one embodiment, the controller 10 is further specifically configured to: Obtaining the maximum thermal power generation power of the cogeneration module, and obtaining the remaining hydrogen storage capacity of the hydrogen storage module on that day; If it is determined that the thermal power generation amount corresponding to the remaining hydrogen storage amount on that day is less than the thermal power generation prediction data, the difference in power on that day between the thermal power generation prediction data and the thermal power generation amount on that day is obtained, and the actual thermal power generation amount on that day is determined based on the preset thermal power storage amount and the difference in power on that day; Based on the actual thermal power generation on that day and the maximum thermal power generation power, the thermal power generation operating parameters on that day are determined.

[0087] In this embodiment, the controller can obtain the maximum thermoelectric power generation power of the cogeneration module (such as denoted as P2), and can also obtain the remaining hydrogen storage capacity for the day from the hydrogen storage module (which is the remaining hydrogen storage capacity for the day obtained from the hydrogen storage module at the time point corresponding to the instruction generation time of the energy intelligent control instruction), and according to the remaining hydrogen storage capacity for the day and the preset thermoelectric power generation efficiency value (corresponding to a percentage parameter value, which is used to represent the ratio between the actual power generation determined in the thermoelectric power generation process when the hydrogen storage capacity is known and the theoretical power generation), the thermoelectric power generation capacity for the day can be determined (the theoretical power generation corresponding to the remaining hydrogen storage capacity for the day * the thermoelectric power generation efficiency value).

[0088] After determining the amount of thermal power that can be generated on the day, if it is further determined that it is less than the predicted data for the amount of thermal power to be generated, it means that the electricity generated by the remaining hydrogen storage on the day being specifically delivered to the cogeneration module for thermal power generation is not enough to meet the thermal power demand on the day. It is necessary to first obtain the difference in the amount of electricity on the day between the predicted data for thermal power to be generated and the amount of thermal power that can be generated on the day, and then determine the actual amount of thermal power generated on the day based on the preset thermal power storage amount (this preset amount of thermal power storage is to determine that a certain amount of hydrogen needs to be stored in the hydrogen storage module at the end of the day to be used as a source of thermal power generation tomorrow) and the difference in the amount of electricity on the day. Finally, based on the actual amount of thermal power generated on the day and the maximum thermal power generation power P2, a thermal power generation operating parameter for the day that is suitable for the actual situation on the day can be determined. It should also be noted that the average thermal power generation power in the thermal power generation operating parameters on the day is less than or equal to the maximum thermal power generation power. After determining the thermal power generation operating parameters of the cogeneration module for performing thermal power generation on that day, the module is operated with reference to the thermal power generation operating parameters for that day to effectively utilize hydrogen for power generation, and at the same time, the heat energy generated during the hydrogen power generation process can be transferred to the hot water storage tank for heat storage.

[0089] The photovoltaic power generation module 20 is used to generate electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provide the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter.

[0090] In this embodiment, after the controller determines the photovoltaic power generation working parameters of the day, the photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day, and provides the corresponding electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter. The specific situation of whether the electric energy generated by the photovoltaic power generation module is provided to the user's electrical equipment and / or the water electrolysis hydrogen production module needs to be determined by the user. In one embodiment, the photovoltaic power generation module 20 is specifically used for: Obtaining a first power distribution ratio for distributing power to user electrical equipment and a second power distribution ratio for distributing power to a water electrolysis hydrogen production module; Power generation is performed according to the photovoltaic power generation parameters of the day, the generated electric energy is provided to the user's electrical equipment based on the first power distribution ratio, and the generated electric energy is provided to the water electrolysis hydrogen production module based on the second power distribution ratio.

[0091] In this embodiment, a first electricity distribution ratio for distributing electricity to user electrical equipment and a second electricity distribution ratio for distributing electricity to a water electrolysis hydrogen production module can be pre-set for the photovoltaic power generation module. The above-mentioned first electricity distribution ratio and second electricity distribution ratio can be fixed values ​​for each day, or can be flexibly set according to the weather conditions of the day.

[0092] After knowing that the photovoltaic power generation module obtains the first power distribution ratio for distributing power to the user's electrical equipment and the second power distribution ratio for distributing power to the water electrolysis hydrogen production module, when the photovoltaic power generation module generates power based on the photovoltaic power generation parameters of the day, the generated electric energy is provided to the user's electrical equipment based on the first power distribution ratio to directly power the equipment, and the generated electric energy is provided to the water electrolysis hydrogen production module based on the second power distribution ratio. The water electrolysis hydrogen production module produces hydrogen through electrolysis, and stores renewable energy through the hydrogen storage module. When the user's electrical equipment on the user side needs energy, the prepared hydrogen can be supplied to the cogeneration module. The cogeneration module uses the electric energy generated by hydrogen to provide it to the user's electrical equipment on the user side, and the generated heat energy is stored in the water storage tank, which improves the utilization rate of green electricity.

[0093] The cogeneration module 50 is used to generate electricity according to the thermoelectric power generation working parameters of the day determined by the controller, and provide the corresponding generated electric energy to the user's electrical equipment and / or the hot water storage tank.

[0094] In this embodiment, when the cogeneration module generates electricity according to the thermoelectric power generation working parameters of the day, since the cogeneration module is connected to the hydrogen storage module through a gas supply pipeline, the cogeneration module can obtain hydrogen from the hydrogen storage module and generate electricity, thereby supplying power to the user's electrical equipment connected to the cogeneration module, and transferring the generated heat energy to the hot water storage tank for heat storage. The above process makes full use of the electrical energy and heat energy generated in the hydrogen power generation process. The hot water storage tank is used to store the heat energy generated by the cogeneration module to provide heating to users or hot water for domestic use.

[0095] Through the above system, photovoltaic power generation, hydrogen production, hydrogen storage and cogeneration are integrated into an integrated distributed energy system, which can not only meet the daily electricity needs of households, but also provide backup power and heating services, thereby improving energy utilization efficiency.

[0096] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An energy intelligent control method for a household green electricity and combined heat and power integrated system, applied to the household green electricity and combined heat and power integrated system, characterized in that: The household green electricity and combined heat and power integrated system comprises a controller, a photovoltaic power generation module, a converter, a water electrolysis hydrogen production module, a hydrogen storage module, a combined heat and power module and a hot water storage tank; the photovoltaic power generation module is connected to the water electrolysis hydrogen production module through the converter, and can also be connected to the user's electrical equipment, the water electrolysis hydrogen production module is connected to the hydrogen storage module, the combined heat and power module is connected to the hot water storage tank and can also be connected to the user's electrical equipment, the photovoltaic power generation module, the converter, the water electrolysis hydrogen production module, the hydrogen storage module, the combined heat and power module and the hot water storage tank are all connected to the controller in communication; the energy intelligent control method of the household green electricity and combined heat and power integrated system comprises: The controller responds to the energy intelligent control instruction, obtains the power user information corresponding to the energy intelligent control instruction, and determines the historical power consumption data set and power supply priority information of the power consumption equipment corresponding to the user power consumption information; The controller obtains user household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and a pre-trained electricity consumption prediction model; The controller determines the green power generation forecast data and the thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment; The controller determines the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and determines the thermal power generation operating parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data; The photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter; The cogeneration module generates electricity according to the thermoelectric power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the hot water storage tank.

2. The method according to claim 1, characterized in that: The acquiring of the electricity user information corresponding to the energy intelligent control instruction, and determining the historical electricity consumption data set and the power supply priority information of the electric equipment corresponding to the user electricity consumption information, includes: Based on the instruction generation time of the energy intelligent control instruction, the target time interval is determined by the instruction generation time and the preset data acquisition cycle; Obtain the unique number of the user ID in the electricity user information, and obtain the corresponding historical electricity consumption data set from the storage space corresponding to the controller based on the unique number of the user ID and the target time interval; wherein the historical electricity consumption data set includes multiple historical electricity consumption data, each of which corresponds to a unique electricity consumption date within the target time interval, and each of which includes the electricity consumption, electricity consumption time distribution information and power of multiple user electrical appliances respectively; Based on the user ID unique number and the target time interval, corresponding power supply priority information of the power-consuming device is obtained from the storage space corresponding to the controller.

3. The method according to claim 1, characterized in that The acquiring user household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and the pre-trained electricity consumption prediction model includes: Obtaining an i-th historical electricity consumption data subset corresponding to an i-th electrical appliance in the historical electricity consumption data set; wherein an initial value of i is 1; Concatenate each power consumption data in the i-th historical power consumption data subset in ascending order of date to form the i-th power consumption appliance input vector; Inputting the input vector of the i-th electrical appliance into the power consumption prediction model to obtain the power consumption prediction data of the i-th electrical appliance; Increment i by 1 to update the value of i; If it is determined that i does not exceed N, then return to the step of obtaining the i-th historical electricity consumption data subset corresponding to the i-th electrical appliance in the historical electricity consumption data set; wherein N is the total number of electrical appliances included in the historical electricity consumption data set; If it is determined that i exceeds N, the electricity consumption forecast data of the first electrical appliance to the Nth electrical appliance are obtained and constitute the user's household electricity consumption forecast data.

4. The method according to claim 3, characterized in that The step of determining the green power generation forecast data and the thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment includes: Obtaining the electricity consumption forecast data of the jth electrical appliance in the household electricity consumption forecast data of the user; wherein the initial value of j is 1; Obtaining the jth electrical appliance corresponding to the power consumption forecast data of the jth electrical appliance, and determining the jth electrical appliance power supply priority information and the jth electrical appliance power supply requirement information corresponding to the jth electrical appliance in the power supply priority information of the electrical equipment; If it is determined that the power supply priority information of the j-th electrical appliance and the power supply requirement information of the j-th electrical appliance meet the first preset condition, the current green electricity to be generated prediction data is obtained, and the power consumption prediction data of the j-th electrical appliance is added to the current green electricity to be generated prediction data, so as to update the current green electricity to be generated prediction data; If it is determined that the power supply priority information of the j-th electrical appliance and the power supply requirement information of the j-th electrical appliance meet the second preset condition, then obtaining the current thermal power generation prediction data, and adding the power consumption prediction data of the j-th electrical appliance to the current thermal power generation prediction data, so as to update the current thermal power generation prediction data; Increment j by 1 to update the value of j; If it is determined that j does not exceed N, returning to the step of obtaining the jth electrical appliance power consumption forecast data in the user's household power consumption forecast data; If it is determined that j exceeds N, the current green power generation prediction data is obtained and used as the green power generation prediction data, and the current thermal power generation prediction data is obtained and used as the thermal power generation prediction data.

5. The method according to claim 1, characterized in that The determining of the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green electricity to be generated prediction data includes: Obtain the maximum photovoltaic power generation power of the photovoltaic power generation module, and obtain the sunshine weather forecast data of the day from the background server; Based on the sunshine duration on that day in the sunshine weather forecast data on that day and the green electricity generation forecast data, the photovoltaic power generation working parameters on that day are determined; wherein the photovoltaic average power generation power in the photovoltaic power generation working parameters on that day is less than or equal to the photovoltaic maximum power generation power.

6. The method according to claim 1, characterized in that The determining of the thermoelectric power generation operating parameters of the day corresponding to the cogeneration module based on the thermoelectric power generation prediction data includes: Obtaining the maximum thermal power generation power of the cogeneration module, and obtaining the remaining hydrogen storage capacity of the hydrogen storage module on that day; If it is determined that the thermal power generation amount corresponding to the remaining hydrogen storage amount on that day is less than the thermal power generation prediction data, the difference in power on that day between the thermal power generation prediction data and the thermal power generation amount on that day is obtained, and the actual thermal power generation amount on that day is determined based on the preset thermal power storage amount and the difference in power on that day; Based on the actual thermal power generation on that day and the maximum thermal power generation power, the thermal power generation operating parameters on that day are determined.

7. The method according to claim 1, characterized in that The photovoltaic power generation module generates electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provides the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter, including: The photovoltaic power generation module obtains a first power distribution ratio for distributing power to user electrical equipment and a second power distribution ratio for distributing power to the water electrolysis hydrogen production module; Power generation is performed according to the photovoltaic power generation parameters of the day, the generated electric energy is provided to the user's electrical equipment based on the first power distribution ratio, and the generated electric energy is provided to the water electrolysis hydrogen production module based on the second power distribution ratio.

8. A household green electricity and combined heat and power system, characterized in that: It includes a controller, a photovoltaic power generation module, a converter, a water electrolysis hydrogen production module, a hydrogen storage module, a combined heat and power module and a hot water storage tank; the photovoltaic power generation module is connected to the water electrolysis hydrogen production module through the converter, and can also be connected to the user's electrical equipment, the water electrolysis hydrogen production module is connected to the hydrogen storage module, the combined heat and power module is connected to the hot water storage tank and can also be connected to the user's electrical equipment, and the photovoltaic power generation module, the converter, the water electrolysis hydrogen production module, the hydrogen storage module, the combined heat and power module and the hot water storage tank are all connected to the controller in communication; The controller is used to respond to the energy intelligent control instruction, obtain the power user information corresponding to the energy intelligent control instruction, and determine the historical power consumption data set and power supply priority information of the power consumption equipment corresponding to the user power consumption information; The controller is further configured to obtain user household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and a pre-trained electricity consumption prediction model; The controller is further used to determine the green power generation forecast data and the thermal power generation forecast data based on the user's household power consumption forecast data and the power supply priority information of the power-consuming equipment; The controller is further used to determine the photovoltaic power generation operating parameters of the day corresponding to the photovoltaic power generation module based on the green power generation prediction data, and to determine the thermal power generation operating parameters of the day corresponding to the cogeneration module based on the thermal power generation prediction data; The photovoltaic power generation module is used to generate electricity according to the photovoltaic power generation working parameters of the day determined by the controller, and provide the corresponding generated electric energy to the user's electrical equipment and / or the water electrolysis hydrogen production module through the converter; The cogeneration module is used to generate electricity according to the thermoelectric power generation working parameters of the day determined by the controller, and provide the corresponding generated electric energy to the user's electrical equipment and / or the hot water storage tank.

9. The household green electricity and combined heat and power integrated system according to claim 8, characterized in that: The acquiring of the electricity user information corresponding to the energy intelligent control instruction, and determining the historical electricity consumption data set and the power supply priority information of the electric equipment corresponding to the user electricity consumption information, includes: Based on the instruction generation time of the energy intelligent control instruction, the target time interval is determined by the instruction generation time and the preset data acquisition cycle; Obtain the unique number of the user ID in the electricity user information, and obtain the corresponding historical electricity consumption data set from the storage space corresponding to the controller based on the unique number of the user ID and the target time interval; wherein the historical electricity consumption data set includes multiple historical electricity consumption data, each of which corresponds to a unique electricity consumption date within the target time interval, and each of which includes the electricity consumption, electricity consumption time distribution information and power of multiple user electrical appliances respectively; Based on the user ID unique number and the target time interval, corresponding power supply priority information of the power-consuming device is obtained from the storage space corresponding to the controller.

10. The household green electricity and combined heat and power integrated system according to claim 8, characterized in that: The acquiring user household electricity consumption prediction data corresponding to the historical electricity consumption data set based on the historical electricity consumption data set and the pre-trained electricity consumption prediction model includes: Obtaining an i-th historical electricity consumption data subset corresponding to an i-th electrical appliance in the historical electricity consumption data set; wherein an initial value of i is 1; Concatenate each power consumption data in the i-th historical power consumption data subset in ascending order of date to form the i-th power consumption appliance input vector; Inputting the input vector of the i-th electrical appliance into the power consumption prediction model to obtain the power consumption prediction data of the i-th electrical appliance; Increment i by 1 to update the value of i; If it is determined that i does not exceed N, then return to the step of obtaining the i-th historical electricity consumption data subset corresponding to the i-th electrical appliance in the historical electricity consumption data set; wherein N is the total number of electrical appliances included in the historical electricity consumption data set; If it is determined that i exceeds N, the electricity consumption forecast data of the first electrical appliance to the Nth electrical appliance are obtained and constitute the user's household electricity consumption forecast data.

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