A photovoltaic air conditioning energy control method, device, equipment and storage medium

Abstract

This application discloses a photovoltaic air conditioning energy control method, device, equipment, and storage medium, relating to the field of photovoltaic air conditioning power control technology. The method includes: establishing a probability model for the activation of photovoltaic air conditioners at different times based on the activity patterns, dwell time, and number of people in different rooms; calculating a target real-time indoor temperature corresponding to a preset main activity area room based on the power of each photovoltaic air conditioner and indoor / outdoor conditions, combined with the activation probability model, when all photovoltaic air conditioners operate using only the electricity generated by real-time photovoltaic power generation; and controlling the power of the photovoltaic air conditioners based on a preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model. In this way, this application can establish an activation probability model for air conditioning behavior based on information such as the activity patterns of people in different rooms, allowing for flexible control of air conditioning operation, improving the local consumption rate of photovoltaic power generation, increasing energy matching efficiency, and reducing investment costs.

Description

Technical Field

[0001] This invention relates to, and in particular to, a method, apparatus, equipment, and storage medium for controlling energy consumption in photovoltaic air conditioning. Background Technology

[0002] Photovoltaic air conditioning refers to an air conditioning system directly driven by photovoltaic (PV) power generation, which can effectively utilize PV power to reduce building air conditioning energy consumption and grid load. However, PV power generation is unstable due to variations in solar irradiance. Most existing building air conditioning systems are based on fixed temperatures and employ a "full-time, full-space" global control mode, resulting in low real-time energy matching between PV power generation and building air conditioning power consumption. In reality, people's air conditioning usage behavior varies in time and space across different functional rooms within a building, and their thermal comfort needs also differ. The fixed-temperature, "full-time, full-space" global control mode ignores these temporal and spatial differences in air conditioning usage behavior, leading to low real-time energy matching between PV power generation and building air conditioning power consumption. To address real-time power fluctuations, direct-drive PV air conditioning systems typically require batteries or grid connection. However, battery investment is high, and frequent power extraction from or supplying to the grid puts excessive strain on the grid. Compared with the "all-time, all-space" mode, the "partial-time, partial-space" mode is adopted based on the spatiotemporal patterns of people using air conditioning indoors, and the thermal comfort temperature range is considered for building air conditioning power control. This fully utilizes the differences in the time people stay in different functional rooms, the differences in personnel density, and the differences in the level of thermal comfort needs of personnel, so as to achieve time-sharing and zone-based fine control of the air conditioning system. The air conditioning energy consumption will have greater flexibility and adjustment potential to respond to the fluctuations in photovoltaic power generation.

[0003] Therefore, how to comprehensively consider the spatiotemporal characteristics of people in the room and the hierarchical classification of indoor thermal comfort needs to improve the self-generation and self-use of photovoltaic air conditioning energy, thereby achieving real-time energy matching of the system, is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a photovoltaic air conditioning energy control method, device, equipment, and storage medium. This method can establish a photovoltaic air conditioning activation probability model based on information such as the activity patterns and dwell time of people in different rooms at different times. This can improve the local consumption rate of photovoltaic power generation and the energy saving rate of air conditioning, with low investment cost and good results. The specific solution is as follows:

[0005] In a first aspect, this application provides a photovoltaic air conditioning energy consumption control method, including:

[0006] Based on the activity patterns, duration of stay, and number of people in different rooms, establish a probability model for the activation of photovoltaic air conditioners at different times;

[0007] When each of the photovoltaic air conditioners operates using only the electrical energy generated by real-time photovoltaic power generation, the target real-time indoor temperature corresponding to the preset main activity area room is calculated based on the power of each photovoltaic air conditioner and indoor and outdoor conditions, combined with the activation probability model.

[0008] The power of the photovoltaic air conditioner is controlled based on the preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model.

[0009] Optionally, the step of establishing a probability model for the activation of photovoltaic air conditioners at different times based on the activity patterns, duration of stay, and number of people in different rooms includes:

[0010] Based on the Markov chain model, preset thermal comfort requirements are generated for different rooms according to the activity patterns, duration of stay and number of people in different rooms; the preset thermal comfort requirements include thermal comfort temperature range and thermal comfort duration.

[0011] Based on the preset thermal comfort requirements, a probability model for the activation of photovoltaic air conditioners at different times is established.

[0012] Optionally, when each of the photovoltaic air conditioners operates solely using electricity generated by real-time photovoltaic power generation, calculating the target real-time indoor temperature corresponding to the preset main activity area room based on the power of each photovoltaic air conditioner and indoor and outdoor conditions, combined with the activation probability model, includes:

[0013] When each of the photovoltaic air conditioners operates using only the electrical energy generated by real-time photovoltaic power generation, the first real-time indoor temperature of each room is predicted based on the power of the photovoltaic air conditioner and indoor and outdoor conditions.

[0014] Establish a correlation model between the first real-time indoor temperature and the indoor and outdoor conditions;

[0015] The second real-time indoor temperature corresponding to each room is calculated based on the association model and the opening probability model, and the target real-time indoor temperature corresponding to the room in the preset main activity area is selected from the second real-time indoor temperature corresponding to each room.

[0016] Optionally, controlling the power of the photovoltaic air conditioner based on a preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model includes:

[0017] Determine whether the target real-time indoor temperature is within the preset thermal comfort temperature range;

[0018] If the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, then the photovoltaic air conditioner with a probability of zero corresponding to the activation probability model will be turned on.

[0019] If the target real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, then the photovoltaic air conditioner with a probability lower than the preset activation probability corresponding to the activation probability model will be turned off.

[0020] Optionally, the method further includes:

[0021] Recalculate the third real-time indoor temperature corresponding to the preset main activity area room;

[0022] If the third real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, the power consumption of the photovoltaic air conditioner corresponding to the preset main activity area room is reduced to form a corresponding real-time power generation surplus, and the real-time power generation surplus is stored according to the preset energy storage method.

[0023] Optionally, the method further includes:

[0024] Recalculate the fourth real-time indoor temperature corresponding to the preset main activity area room;

[0025] If the fourth real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, it is determined that the current power generated by all photovoltaic air conditioners through real-time photovoltaic power generation is insufficient, and the corresponding power gap is calculated.

[0026] Based on the power gap, the relevant photovoltaic air conditioning energy is supplemented by a preset power replenishment method so that the real-time indoor temperature of the room corresponding to the preset main activity area can be controlled within the preset thermal comfort temperature range within a preset time.

[0027] Optionally, the method further includes:

[0028] When the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, if there is a target photovoltaic air conditioner with a zero probability of being turned on, the target real-time power generation corresponding to the target photovoltaic air conditioner is used to maintain the temperature of the target room where the target photovoltaic air conditioner is located within the corresponding preset thermal comfort temperature range, and then the real-time power generation margin of all photovoltaic air conditioners is calculated.

[0029] The real-time power generation capacity of all photovoltaic air conditioners is stored according to the preset energy storage method.

[0030] Secondly, this application provides a photovoltaic air conditioning energy control device, comprising:

[0031] The activation probability model building module is used to establish activation probability models for photovoltaic air conditioners at different times based on the activity patterns, duration of stay, and number of people in different rooms.

[0032] The temperature calculation module is used to calculate the target real-time indoor temperature of the room in the preset main activity area based on the power of each photovoltaic air conditioner and indoor and outdoor conditions, combined with the activation probability model, when each of the photovoltaic air conditioners is operating using only the electrical energy generated by real-time photovoltaic power generation.

[0033] The power control module is used to control the power of the photovoltaic air conditioner based on a preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model.

[0034] Thirdly, this application provides an electronic device, comprising:

[0035] Memory, used to store computer programs;

[0036] A processor is used to execute the computer program to implement the photovoltaic air conditioning energy control method described above.

[0037] Fourthly, this application provides a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the photovoltaic air conditioning energy control method described above.

[0038] Therefore, this application can establish a probability model for the activation of photovoltaic air conditioners at different times based on the activity patterns, duration of stay, and number of people in different rooms. Then, when each photovoltaic air conditioner operates solely using electricity generated by real-time photovoltaic power generation, the target real-time indoor temperature corresponding to the main activity area room is calculated based on the power of each photovoltaic air conditioner and indoor and outdoor conditions, combined with the activation probability model. Finally, the power of the photovoltaic air conditioners is controlled based on the preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model. In this way, this application can establish an activation probability model for air conditioners based on information such as the activity patterns of people, and then control the photovoltaic air conditioners according to the thermal comfort temperature range of the main activity area room and the corresponding real-time indoor temperature. This improves the real-time energy matching of photovoltaic air conditioners, reduces dependence on supplementary power, and increases the local consumption rate of photovoltaic power generation and the energy saving rate of air conditioning. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0040] Figure 1 This is a flowchart of a photovoltaic air conditioning energy consumption control method disclosed in this application;

[0041] Figure 2This application discloses a specific flowchart of a photovoltaic air conditioning energy consumption control method.

[0042] Figure 3 This is a flowchart of another specific photovoltaic air conditioning energy consumption control method disclosed in this application;

[0043] Figure 4 This is a schematic diagram of the structure of a file access control device disclosed in this application;

[0044] Figure 5 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a photovoltaic air conditioning energy consumption control method, including:

[0047] Step S11: Based on the activity patterns, duration of stay, and number of people in different rooms, establish a probability model for the activation of photovoltaic air conditioners at different times.

[0048] In this application, it is understood that because people spend varying amounts of time in different functional areas of a building, their thermal comfort needs also differ in different rooms. In a specific embodiment, this may include: generating preset thermal comfort requirement targets for different rooms based on a Markov chain model, considering the activity patterns, duration of stay, and number of people in each room; the preset thermal comfort requirement targets include a thermal comfort temperature range and a thermal comfort duration; and establishing a probability model for the activation of photovoltaic air conditioning at different times based on the preset thermal comfort requirement targets. Specifically, based on the Markov chain model, the activity purpose and duration of people in different functional areas of a building, as well as information such as the number of people, can be used to predict the activity patterns of people and generate corresponding preset thermal comfort demand targets for rooms at different time periods. It is understood that the temperature at which people feel comfortable indoors is not a fixed value, but rather exists within a temperature range. Therefore, the preset thermal comfort temperature range and duration in the preset thermal comfort demand targets can be determined based on the activity time of people. In specific embodiments, thermal comfort levels (levels distinguished by different temperature ranges) can also be included. Furthermore, the Markov chain model can be introduced to characterize the activity patterns of people in different functional areas, considering the differences in the time people stay and the differences in personnel density, and combining this with the preset thermal comfort demand targets to establish a model of the activation probability of the air conditioning system in different rooms at different times. In a specific embodiment, the cooling conditions of the air conditioning in areas where people stay for short periods should be 1-2°C higher than those in areas where people stay for long periods. In another specific embodiment, when there are many people in the office area, the probability of people staying in the meeting room is lower. At this time, the thermal comfort needs of people in the office area should be met as much as possible, while the air conditioning energy consumption in other areas can be used to adjust the overall air conditioning power consumption to match the real-time photovoltaic power generation.

[0049] Step S12: When each of the photovoltaic air conditioners operates using only the electrical energy generated by real-time photovoltaic power generation, calculate the target real-time indoor temperature corresponding to the preset main activity area room based on the power of each photovoltaic air conditioner and indoor and outdoor conditions, combined with the activation probability model.

[0050] Furthermore, it can be determined whether the electricity generated solely by the photovoltaic power generation of the photovoltaic air conditioner is sufficient to meet the preset thermal comfort requirements for different rooms. In this application, when the photovoltaic air conditioner operates solely on the electricity generated by real-time photovoltaic power generation, the target real-time indoor temperature for the preset main activity area room can be calculated based on the power of each photovoltaic air conditioner, considering indoor and outdoor conditions and the corresponding air conditioner activation probability model. It is understood that indoor and outdoor conditions affect the real-time photovoltaic power generation. Due to the instability of solar irradiance, it is necessary to comprehensively consider indoor and outdoor conditions and the usage of each photovoltaic air conditioner according to the activation probability model. This allows for a more reasonable calculation of the target real-time indoor temperature for the preset main activity area room.

[0051] Step S13: Control the power of the photovoltaic air conditioner based on the preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model.

[0052] In this application, the usage of different air conditioners can be adjusted in a timely manner based on the preset thermal comfort temperature range, the target real-time indoor temperature corresponding to the preset main activity area room, and the corresponding air conditioner activation probability model, so as to ensure that the preset main activity area room always meets the preset thermal comfort requirements.

[0053] In a specific embodiment, controlling the power of the photovoltaic air conditioner based on the preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model may include: determining whether the target real-time indoor temperature is within the preset thermal comfort temperature range; if the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, then activating the photovoltaic air conditioner with a probability of zero corresponding to the activation probability model; if the target real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, then deactivating the photovoltaic air conditioner with a probability lower than the preset activation probability corresponding to the activation probability model. Specifically, determining whether the target real-time indoor temperature corresponding to the room in the preset main activity area is within the preset thermal comfort temperature range; if the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, it indicates that the power of the photovoltaic air conditioner in the corresponding main activity area is too high, and the real-time power generation of all photovoltaic air conditioners is surplus; therefore, those photovoltaic air conditioners with an activation probability of zero can be activated, thus utilizing the surplus real-time power generation of more air conditioners, relatively reducing the power consumption of the photovoltaic air conditioners corresponding to the room in the preset main activity area, to ensure that the target real-time indoor temperature of the room in the preset main activity area rises to within the preset thermal comfort temperature range. Correspondingly, if the target real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, it means that the real-time power generation of all photovoltaic air conditioners is insufficient, resulting in a power shortage. At this time, photovoltaic air conditioners with an activation probability lower than the preset activation probability can be turned off, such as those with an activation probability of less than 30%. This can avoid the power consumption of those unimportant photovoltaic air conditioners and relatively increase the power consumption of photovoltaic air conditioners in the main activity area to ensure that the target real-time indoor temperature of the rooms in the main activity area is within the preset thermal comfort temperature range.

[0054] In another specific embodiment, after turning on the photovoltaic air conditioners with a probability of zero corresponding to the activation probability model, the process may further include: recalculating the third real-time indoor temperature corresponding to the preset main activity area room; if the third real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, reducing the power consumption of the photovoltaic air conditioners corresponding to the preset main activity area room to form a corresponding real-time power generation surplus, and storing the real-time power generation surplus according to a preset energy storage method. Specifically, after turning on those photovoltaic air conditioners with a probability of zero activation when the temperature of the preset main activity area room is lower than the lower limit of the preset thermal comfort temperature range, the third real-time indoor temperature of the preset main activity area room can be recalculated after a period of waiting. If the temperature at this time is still less than the lower limit of the preset thermal comfort temperature range, it indicates that the real-time power generation of all photovoltaic air conditioners fully supports the use of all photovoltaic air conditioners, and there is still a real-time power generation surplus. Therefore, under the premise of ensuring that the temperature of the preset main activity area room is within the preset thermal comfort range, the real-time power generation surplus can be stored through a preset energy storage method; for example, the excess power can be stored through a battery, or the power generation surplus can be input into the power grid.

[0055] Accordingly, in specific embodiments, the method may further include: when the target real-time indoor temperature is lower than the lower limit of the preset thermal comfort temperature range, if there is a target photovoltaic air conditioner with a zero probability of activation, the target real-time power generation corresponding to the target photovoltaic air conditioner is used to maintain the temperature of the target room where the target photovoltaic air conditioner is located within the corresponding preset thermal comfort temperature range, and then the real-time power generation surplus of all photovoltaic air conditioners is calculated; the real-time power generation surplus of all photovoltaic air conditioners is saved according to a preset energy storage method. Specifically, after the target photovoltaic air conditioner is activated, if the temperature of the room corresponding to the target photovoltaic air conditioner is also lower than the lower limit of the corresponding preset thermal comfort temperature range, it indicates that the real-time photovoltaic power generation of the photovoltaic air conditioner is much greater than the real-time power consumption of all photovoltaic air conditioners, and the power generation of the photovoltaic air conditioner can completely cover the power consumption, or even have a surplus. Therefore, under the premise of ensuring that the temperature of all rooms is within the preset thermal comfort temperature range, the real-time power generation surplus of all photovoltaic air conditioners can be calculated, and then these power generation surpluses can be saved through a preset energy storage method. Furthermore, if the temperature of all rooms can be within the preset thermal comfort temperature range, a dynamic balance between the real-time power generation and power consumption of the photovoltaic air conditioner can be achieved. At this time, the corresponding air conditioner temperature control command can be executed to achieve dynamic adjustment of the energy consumption of the photovoltaic air conditioner.

[0056] In another specific embodiment, after shutting down the photovoltaic air conditioners whose activation probability is lower than the second activation probability according to the activation probability model, the process may further include: recalculating the fourth real-time indoor temperature corresponding to the preset main activity area room; if the fourth real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, it is determined that the current power generated by all photovoltaic air conditioners through real-time photovoltaic power generation is insufficient, and the corresponding power gap is calculated; based on the power gap, the energy consumption of the relevant photovoltaic air conditioners is supplemented through a preset power supplementation method, so as to control the real-time indoor temperature corresponding to the preset main activity area room within the preset thermal comfort temperature range within a preset time. Specifically, when the temperature of the preset main activity area room is greater than the upper limit of the preset thermal comfort temperature range, after shutting down those photovoltaic air conditioners whose activation probability is lower than the preset activation probability, a period of time can be waited for the fourth real-time indoor temperature of the preset main activity area room to be recalculated. If the fourth real-time indoor temperature is still greater than the upper limit of the preset thermal comfort temperature range, it indicates that the real-time power generation of all photovoltaic air conditioners cannot meet the use of the photovoltaic air conditioners corresponding to each main activity area room, that is, the current power generated solely through real-time photovoltaic power generation is insufficient; therefore, the corresponding power gap can be calculated to supplement the air conditioning energy consumption through a preset power supplementation method. For example, supplementing the air conditioner's power supply with a battery or with mains power.

[0057] Therefore, this application can consider the differences in thermal comfort needs, dwell time, and density of people in different functional rooms at different times and in different zones, and classify the thermal comfort needs of different functional rooms in different indoor buildings. At the same time, a Markov chain model is introduced to characterize the spatiotemporal characteristics of people, and the photovoltaic air conditioning is controlled by time and zone according to the real-time photovoltaic power generation. This can improve the dynamic balance between photovoltaic air conditioning power generation and electricity consumption, and reduce the dependence on batteries and the power grid.

[0058] See Figure 2 As shown in the figure, an embodiment of the present invention discloses a photovoltaic air conditioning energy consumption control method, including:

[0059] Step S21: Based on the activity patterns, duration of stay, and number of people in different rooms, establish a probability model for the activation of photovoltaic air conditioners at different times.

[0060] Step S22: When each of the photovoltaic air conditioners operates using only the electrical energy generated by real-time photovoltaic power generation, predict the first real-time indoor temperature of each room based on the power of the photovoltaic air conditioner and indoor and outdoor conditions.

[0061] In this embodiment, when each photovoltaic air conditioner operates solely using the computer generated by real-time photovoltaic power generation, the first real-time indoor temperature of each room can be predicted based on the power output of the photovoltaic air conditioner and indoor and outdoor conditions. It is understood that this allows for the statistical analysis of the relationship between indoor and outdoor conditions and the temperature of each room based solely on the internal circulation of the photovoltaic air conditioner's power output, without the aid of batteries or the power grid.

[0062] Step S23: Establish a correlation model between the first real-time indoor temperature and the indoor and outdoor conditions.

[0063] Accordingly, based on the relationship between the first real-time indoor temperature of each room and the corresponding indoor and outdoor conditions obtained in step S22 above, a corresponding correlation model can be established. It can be understood that, based on this correlation model, the relationship between the electricity consumption of a photovoltaic air conditioner in a certain room and the real-time photovoltaic power generation of all photovoltaic air conditioners can be obtained under certain specific indoor and outdoor conditions.

[0064] Step S24: Calculate the second real-time indoor temperature corresponding to each room based on the association model and the opening probability model, and select the target real-time indoor temperature corresponding to the room in the preset main activity area from the second real-time indoor temperature corresponding to each room.

[0065] Furthermore, the second real-time indoor temperature of each room can be calculated based on the correlation model between indoor and outdoor conditions and indoor temperature, and the activation probability model of each photovoltaic air conditioner. It can be understood that the second real-time indoor temperature is also the temperature of each room under the premise that the photovoltaic air conditioners only use the corresponding real-time photovoltaic power generation. Then, the target real-time indoor temperature of the preset main activity area rooms can be selected. It can be understood that, in most cases, it is possible to ensure that only the temperature of the preset main activity area rooms is within the preset thermal comfort temperature range, and appropriately reduce the energy consumption of photovoltaic air conditioners in other rooms.

[0066] Step S25: Control the power of the photovoltaic air conditioner based on the preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model.

[0067] For more detailed processing of steps S21 and S25, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0068] Therefore, this embodiment of the application can establish a correlation model between temperature and indoor and outdoor conditions based on indoor and outdoor conditions and the temperatures of different rooms under the corresponding conditions. Then, the temperature of each room can be calculated based on this correlation model and the activation probability model of the photovoltaic air conditioner. Furthermore, the energy consumption of the relevant photovoltaic air conditioner can be dynamically adjusted based on whether the temperature of the room in the preset main activity area is within the preset thermal comfort temperature range. This adopts a "partial time, partial space" air conditioning control mode and considers the thermal comfort temperature range of the human body in different functional areas, which greatly improves the real-time energy matching of the photovoltaic air conditioner, reduces the dependence on batteries and the power grid, improves economic efficiency, and reduces the burden on the power grid.

[0069] like Figure 3 As shown in the figure, this application discloses a photovoltaic air conditioning energy consumption control method, including:

[0070] In this embodiment, the following data can be obtained first: thermal inertia parameters of the target building, air conditioning operating frequency of different functional rooms within the building, thermal comfort temperature range of different functional areas, air conditioning energy consumption behavior data, room heat gain at time t, and indoor temperature at time t-1. Then, the real-time photovoltaic power generation of the photovoltaic air conditioning system at time t and the theoretical air conditioning output data of each photovoltaic air conditioning system are statistically analyzed. Next, based on the previously obtained data, the expected indoor temperature Tn of each functional room (preset main activity area room) under 100% photovoltaic power generation consumption conditions is calculated. Furthermore, it can be determined whether Tn is within the thermal comfort temperature range, and then the energy consumption of the relevant photovoltaic air conditioning systems can be controlled and adjusted.

[0071] Specifically, if Tn is within the thermal comfort temperature range, then the current state is considered an energy matching moment, indicating that the real-time photovoltaic power generation can meet the needs of the photovoltaic air conditioner, thus maintaining the existing air conditioning behavior mode. Conversely, if Tn is less than the lower limit of the thermal comfort temperature range, other photovoltaic air conditioners can be further controlled to ensure that the temperature in the main activity area is within the thermal comfort temperature range. Specifically, photovoltaic air conditioners with a zero probability of activation in certain rooms can be turned on, and the minimum indoor temperature Tn that the current real-time photovoltaic power generation can provide in these rooms can be calculated. Then, it is determined whether this new Tn is within the thermal comfort temperature range. If so, it indicates that the photovoltaic air conditioners are currently in an energy matching phase, and relevant air conditioning temperature control commands can be executed, maintaining the current air conditioning behavior mode. Conversely, if there are no photovoltaic air conditioners with a zero probability of activation, the power generation margin of all photovoltaic air conditioners can be directly calculated and stored through batteries or the power grid. Furthermore, if the new Tn is not within the thermal comfort temperature range, either too low or too high, the power generation margin of all photovoltaic air conditioners can be calculated and stored, provided that the temperature in the main activity area is within the thermal comfort temperature range.

[0072] Correspondingly, if the predicted indoor temperature Tn of each functional room under 100% photovoltaic power generation conditions is not within the thermal comfort temperature range, but is not lower than the lower limit of the thermal comfort temperature range (i.e., higher than the upper limit), then it can be determined whether there are photovoltaic air conditioners (on-demand) with an activation probability of less than 0.3 (30%). If so, the relevant photovoltaic air conditioners can be turned off, and then the new temperature Tn of the main activity area room can be recalculated. If the new Tn is less than the upper limit of the thermal comfort temperature range, it indicates that there is an energy match between real-time photovoltaic power generation and the power consumption of photovoltaic air conditioners, and the relevant air conditioning temperature control command can be executed. Furthermore, if there are no air conditioners with an on / off probability of less than 0.3 (in the on / off state), the power deficit of the photovoltaic air conditioners can be directly calculated to ensure that the temperature of the main activity area room is within the thermal comfort temperature range. This deficit can be supplemented by mains power or batteries. Conversely, if the temperature of the main activity area room is still higher than the upper limit of the thermal comfort temperature range after a period of time after turning off those air conditioners with an on / off probability of less than 0.3, the power deficit that needs to be supplemented to ensure that the temperature of the main activity area room is within the thermal comfort temperature range can be calculated and supplemented by mains power or batteries.

[0073] Therefore, this application can take into account indoor and outdoor conditions, temperature requirements of the main activity area rooms, and the probability of each photovoltaic air conditioner being turned on, so as to reasonably control the energy consumption of each photovoltaic air conditioner, fully explore the flexibility potential of building air conditioning to absorb real-time photovoltaic power generation fluctuations, effectively improve the self-consumption rate of photovoltaic air conditioning energy, and reduce the dependence on batteries and the power grid while achieving real-time energy matching of the system.

[0074] like Figure 4 As shown in the figure, this application discloses a photovoltaic air conditioning energy control device, including:

[0075] The activation probability model establishment module 11 is used to establish the activation probability model of photovoltaic air conditioners at different times based on the activity patterns, stay duration and number of people in different rooms.

[0076] Temperature calculation module 12 is used to calculate the target real-time indoor temperature of the room in the preset main activity area based on the power of each photovoltaic air conditioner and indoor and outdoor conditions, combined with the activation probability model, when each of the photovoltaic air conditioners only uses the electrical energy generated by real-time photovoltaic power generation to work.

[0077] The power control module 13 is used to control the power of the photovoltaic air conditioner based on the preset thermal comfort temperature range, the target real-time indoor temperature, and the activation probability model.

[0078] Therefore, this application can establish a probability model for air conditioning activation based on information such as the activity patterns of people in different rooms. Then, it can control the photovoltaic air conditioning based on the thermal comfort temperature range of the main activity area room and the corresponding real-time indoor temperature. This can improve the real-time energy matching of photovoltaic air conditioning, reduce dependence on supplementary power, and increase the local consumption rate of photovoltaic power generation and the energy saving rate of air conditioning.

[0079] In one specific embodiment, the activation probability model establishment module 11 may include:

[0080] The demand generation unit is used to generate the preset thermal comfort demand targets for different rooms based on the activity patterns, stay duration and number of people in different rooms according to the Markov chain model; the preset thermal comfort demand targets include thermal comfort temperature range and thermal comfort duration.

[0081] The activation probability model establishment unit is used to establish activation probability models of photovoltaic air conditioners at different times based on the preset thermal comfort demand target.

[0082] In one specific embodiment, the temperature calculation module 12 may include:

[0083] A temperature prediction unit is used to predict the first real-time indoor temperature of each room based on the power of the photovoltaic air conditioner and indoor and outdoor conditions when each of the photovoltaic air conditioners is operating using only the electrical energy generated by real-time photovoltaic power generation.

[0084] The correlation model establishment unit is used to establish a correlation model between the first real-time indoor temperature and the indoor and outdoor conditions.

[0085] The first temperature calculation unit is used to calculate the second real-time indoor temperature corresponding to each room based on the association model and the opening probability model.

[0086] The temperature filtering unit is used to filter out the target real-time indoor temperature corresponding to the main activity area room from the second real-time indoor temperature corresponding to each room.

[0087] In one specific embodiment, the power control module 13 may include:

[0088] A temperature judgment unit is used to determine whether the target real-time indoor temperature is within the preset thermal comfort temperature range;

[0089] An air conditioning activation unit is used to activate a photovoltaic air conditioner with a probability of zero corresponding to the activation probability model when the target real-time indoor temperature is lower than the lower limit of the preset thermal comfort temperature range.

[0090] An air conditioning shutdown unit is used to shut down a photovoltaic air conditioner whose probability of activation is lower than the preset activation probability when the target real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range.

[0091] In one specific embodiment, the device may further include:

[0092] The second temperature calculation unit is used to recalculate the third real-time indoor temperature corresponding to the preset main activity area room;

[0093] The first air conditioning adjustment unit is used to reduce the power consumption of the photovoltaic air conditioner corresponding to the preset main activity area room when the third real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, so as to form a corresponding real-time power generation surplus, and to save the real-time power generation surplus according to the preset energy storage method.

[0094] In another specific embodiment, the device may further include:

[0095] The third temperature calculation unit is used to recalculate the fourth real-time indoor temperature corresponding to the preset main activity area room;

[0096] The power gap calculation unit is used to determine that the electrical energy generated by all photovoltaic air conditioners through real-time photovoltaic power generation is insufficient when the fourth real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, and to calculate the corresponding power gap.

[0097] The energy replenishment unit is used to replenish the energy consumption of the photovoltaic air conditioner based on the power gap through a preset power replenishment method, so as to control the real-time indoor temperature of the room corresponding to the preset main activity area within the preset thermal comfort temperature range within a preset time.

[0098] In one specific embodiment, the device may further include:

[0099] The fourth temperature calculation unit is used to maintain the temperature of the target room where the target photovoltaic air conditioner is located within the corresponding preset thermal comfort temperature range when the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, if there is a target photovoltaic air conditioner with a zero probability of being turned on.

[0100] The power generation surplus statistics unit is used to count the real-time power generation surplus of all photovoltaic air conditioners;

[0101] The power generation surplus storage unit is used to store the real-time power generation surplus of all photovoltaic air conditioners according to a preset energy storage method.

[0102] Furthermore, embodiments of this application also disclose an electronic device, Figure 5This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0103] Figure 5 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the photovoltaic air conditioning energy control method disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0104] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0105] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0106] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the photovoltaic air conditioning energy control method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.

[0107] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned photovoltaic air conditioning energy control method. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0108] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0109] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0110] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0111] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0112] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for controlling the operation of a photovoltaic air conditioner, comprising: The application relates to a method for controlling a plurality of photovoltaic air conditioners. The method comprises: establishing an opening probability model of the photovoltaic air conditioners at different time points according to the activity rules, the staying time and the number of people in different rooms; when each of the photovoltaic air conditioners only uses the electric energy generated by real-time photovoltaic power generation to work, calculating a target real-time indoor temperature corresponding to a preset main activity area room based on the power of each photovoltaic air conditioner and indoor and outdoor conditions in combination with the opening probability model; controlling the power of the photovoltaic air conditioners based on a preset thermal comfort temperature range, the target real-time indoor temperature and the opening probability model; wherein, when each of the photovoltaic air conditioners only uses the electric energy generated by real-time photovoltaic power generation to work, the target real-time indoor temperature corresponding to the preset main activity area room is calculated based on the power of each photovoltaic air conditioner and indoor and outdoor conditions in combination with the opening probability model, which comprises: when each of the photovoltaic air conditioners only uses the electric energy generated by real-time photovoltaic power generation to work, predicting a first real-time indoor temperature corresponding to each room based on the power of the photovoltaic air conditioner and indoor and outdoor conditions; establishing a correlation model between the first real-time indoor temperature and the indoor and outdoor conditions; calculating a second real-time indoor temperature corresponding to each room according to the correlation model in combination with the opening probability model, and screening a target real-time indoor temperature corresponding to a preset main activity area room from the second real-time indoor temperature corresponding to each room; wherein, the controlling the power of the photovoltaic air conditioners based on a preset thermal comfort temperature range, the target real-time indoor temperature and the opening probability model, comprises: judging whether the target real-time indoor temperature is within the preset thermal comfort temperature range; if the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, then opening the photovoltaic air conditioner corresponding to the opening probability model with a probability of zero; 2. The photovoltaic air conditioning energy control method according to claim 1, wherein, if the target real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, then closing the photovoltaic air conditioner corresponding to the opening probability model with a probability lower than a preset opening probability. The method for establishing an opening probability model of the photovoltaic air conditioners at different time points according to the activity rules, the staying time and the number of people in different rooms, comprises: generating a preset thermal comfort demand target corresponding to different rooms according to the activity rules, the staying time and the number of people in different rooms based on a Markov chain model; the preset thermal comfort demand target comprises a thermal comfort temperature range and a thermal comfort time length; 3. The photovoltaic air conditioning energy control method according to claim 1, wherein, establishing an opening probability model of the photovoltaic air conditioners at different time points according to the preset thermal comfort demand target. After opening the photovoltaic air conditioner corresponding to the opening probability model with a probability of zero, the method further comprises: recalculating a third real-time indoor temperature corresponding to the preset main activity area room; 4. The photovoltaic air conditioning energy control method of claim 1, wherein, if the third real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, then reducing the power consumption of the photovoltaic air conditioner corresponding to the preset main activity area room to form a corresponding real-time power generation surplus, and saving the real-time power generation surplus in a preset power storage mode. After closing the photovoltaic air conditioner corresponding to the opening probability model with a probability lower than a second opening probability, the method further comprises: recalculating a fourth real-time indoor temperature corresponding to the preset main activity area room; If the fourth real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range, it is determined that the current all photovoltaic air conditioners are insufficient in power generated by real-time photovoltaic power generation, and a corresponding power gap is calculated; The power gap is supplemented by a preset power supplementing mode to control the real-time indoor temperature of the preset main activity area room within the preset thermal comfort temperature range within a preset time.

5. The photovoltaic air conditioning energy control method according to claim 1, wherein, Further comprising: When the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range, if there is a target photovoltaic air conditioner with a zero opening probability, the temperature of the target room where the target photovoltaic air conditioner is located is maintained at the corresponding preset thermal comfort temperature range by using the target real-time power generation of the target photovoltaic air conditioner, and then the real-time power generation surplus of all photovoltaic air conditioners is counted. The real-time power generation surplus of all photovoltaic air conditioners is saved according to a preset power storage mode.

6. A photovoltaic air conditioning energy control device, characterized by, Comprise: An opening probability model establishing module is configured to establish an opening probability model of photovoltaic air conditioners at different times according to the activity rules, stay duration and number of people in different rooms; A temperature calculation module is configured to calculate a target real-time indoor temperature of a preset main activity area room based on the power of each photovoltaic air conditioner and indoor and outdoor conditions in combination with the opening probability model when each photovoltaic air conditioner only uses power generated by real-time photovoltaic power generation to work; A power control module is configured to control the power of the photovoltaic air conditioner based on a preset thermal comfort temperature range, the target real-time indoor temperature and the opening probability model; The temperature calculation module comprises: A temperature prediction unit is configured to predict a first real-time indoor temperature of each room based on the power of the photovoltaic air conditioner and indoor and outdoor conditions when each photovoltaic air conditioner only uses power generated by real-time photovoltaic power generation to work; An association model establishing unit is configured to establish an association model between the first real-time indoor temperature and the indoor and outdoor conditions; A first temperature calculation unit is configured to calculate a second real-time indoor temperature of each room according to the association model in combination with the opening probability model; A temperature screening unit is configured to screen a target real-time indoor temperature of a preset main activity area room from the second real-time indoor temperature of each room; The power control module comprises: A temperature judgment unit is configured to determine whether the target real-time indoor temperature is within the preset thermal comfort temperature range; An air conditioner opening unit is configured to open a photovoltaic air conditioner with a zero probability according to the opening probability model when the target real-time indoor temperature is less than the lower limit of the preset thermal comfort temperature range; An air conditioner closing unit is configured to close a photovoltaic air conditioner with a probability lower than a preset opening probability according to the opening probability model when the target real-time indoor temperature is greater than the upper limit of the preset thermal comfort temperature range.

7. An electronic device, comprising: Comprise: A memory is configured to save a computer program; A processor is configured to execute the computer program to implement the photovoltaic air conditioner power control method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, A computer program product for saving a computer program which, when executed by a processor, implements the method for controlling the energy consumption of a photovoltaic air conditioner according to any one of claims 1 to 5.

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