Photovoltaic direct-drive multi-connected system and control method thereof

Abstract

This application discloses a photovoltaic direct-drive multi-split air conditioning system and its control method. The system includes a photovoltaic system, an energy manager, a power grid, energy storage equipment, a multi-split air conditioning system, and a control system. The multi-split air conditioning system includes an outdoor unit with a compressor and multiple indoor units with electronic expansion valves. The components interact with each other via the energy manager and communication lines. The control method is based on a preset adjustable superheat range and a thermal comfort temperature range. It collects system data in real time, uses a PID control algorithm to regulate the compressor speed, and combines fuzzy control and PID control algorithms to regulate the opening of the electronic expansion valves. This application achieves precise power regulation and reasonable distribution of cooling capacity in the multi-split air conditioning system. It can absorb photovoltaic power generation in real time while ensuring indoor thermal comfort and stable system operation, solving the problems of low power regulation accuracy and uneven cooling capacity distribution leading to weak photovoltaic absorption capacity in existing solutions. It is suitable for small and medium-sized commercial and public buildings.

Description

Technical Field

[0001] This application relates to the cross-technical field of photovoltaic energy utilization and air conditioning system control, and in particular to a photovoltaic direct-drive multi-split air conditioning system and its control method. Background Technology

[0002] As the penetration rate of photovoltaic power generation continues to increase, its intermittent, volatile, and uncertain characteristics easily cause frequent impacts on the power grid or related equipment, posing a significant challenge to the stable operation of the system. Air conditioning system loads, as typical flexible loads, have the potential to absorb distributed photovoltaic power generation and respond to dynamic grid demands through load regulation, thus helping grid-connected photovoltaic systems achieve balanced and flexible operation.

[0003] Multi-split air conditioning systems, also known as "one-to-many" or "variable refrigerant flow" systems, consist of one outdoor unit connected to two or more indoor units via piping. They are high-efficiency refrigerant air conditioning systems that control the refrigerant circulation volume of the compressor and the refrigerant flow rate into the indoor heat exchangers to meet the indoor cooling and heating load requirements in a timely manner. The electronic expansion valve in a multi-split air conditioning system is a key component for precisely controlling the refrigerant flow rate. By adjusting the valve opening, the flow of refrigerant into the indoor units is controlled, thus affecting the cooling capacity of the indoor units. Due to their excellent performance under partial load, flexible control, and convenient installation and maintenance, multi-split air conditioning systems have been widely used in small and medium-sized commercial and public buildings in recent years.

[0004] The human body has a certain acceptable range for ambient temperature, known as the thermal comfort temperature range. Due to the existence of the thermal comfort temperature range and the thermal inertia of buildings, users can adjust their air conditioning load within the thermal comfort temperature range to improve the matching degree between photovoltaic power generation and air conditioning power consumption without affecting their thermal comfort.

[0005] To fully utilize the load flexibility of multi-split air conditioning systems to achieve photovoltaic power generation, it is necessary to ensure indoor thermal comfort and stable and efficient system operation, while also achieving precise control of system power and reasonable distribution of cooling capacity among different indoor units. This is the core issue that urgently needs to be addressed.

[0006] Existing load regulation schemes for multi-split air conditioning systems have significant drawbacks: First, most rely on temperature control (changing the set temperature or pre-cooling / preheating) to regulate system power, which results in poor power regulation accuracy, long response time, and difficulty in effectively absorbing the frequent fluctuations in photovoltaic power generation. Second, some studies employ model predictive control methods to improve power response by pre-adjusting the temperature setpoint, but in practical engineering, it is difficult to obtain the data needed to establish the system model and train the predictive model, limiting its practicality. Third, a few direct power regulation schemes do not consider the coordinated control of different indoor units, which can easily lead to unreasonable distribution of cooling capacity and fail to fully leverage the load flexibility advantage of multiple indoor units in multi-split air conditioning systems.

[0007] Furthermore, in the conventional operation and control of multi-split air conditioning systems, the controlled variables are usually the compressor speed and the opening of the electronic expansion valve, while the indoor fan speed is adjusted by the user and is not considered a controlled variable. Existing solutions mostly control the compressor speed based on the suction pressure to meet the total cooling demand, and control the opening of the electronic expansion valve based on the indoor air temperature and the refrigerant superheat at the evaporator outlet to meet the cooling demand of each room. However, it is difficult to determine the optimal suction pressure setpoint to achieve a precise match between the compressor output capacity and the cooling load. Moreover, constant suction pressure, indoor temperature, and superheat setpoints prevent the system power from being actively adjusted, failing to fully utilize the flexibility of the building load, and consequently failing to provide a sufficient adjustable range for real-time absorption of photovoltaic power generation.

[0008] Therefore, there is an urgent need for a photovoltaic direct-drive multi-split system solution that can achieve efficient photovoltaic power generation while ensuring indoor thermal comfort and stable system operation. Summary of the Invention

[0009] In view of the problems in the existing technology, such as the impact of photovoltaic power generation volatility on grid stability, low power regulation accuracy of multi-split air conditioning systems, uneven distribution of indoor unit cooling capacity, and difficulty in utilizing load flexibility, this application aims to provide a photovoltaic direct-drive multi-split air conditioning system and its control method that takes into account both indoor thermal comfort and system stability, and achieves efficient photovoltaic absorption, precise control of the operating power of the multi-split air conditioning system, and reasonable distribution of indoor unit cooling capacity.

[0010] The first objective of this application is to provide a photovoltaic direct-drive multi-split system.

[0011] The aforementioned objective of this application is achieved through the following technical solution:

[0012] A photovoltaic direct-drive multi-split air conditioning system is disclosed. The system includes a photovoltaic system, an energy manager, a power grid, energy storage equipment, a multi-split air conditioning system, and a control system. The multi-split air conditioning system includes an outdoor unit and multiple indoor units. The outdoor unit is equipped with a compressor, and each indoor unit is equipped with an electronic expansion valve.

[0013] The photovoltaic system, power grid, energy storage device, and multi-split air conditioning system are all connected to the energy manager for power transmission. The energy manager and multi-split air conditioning system are also connected to the control system for communication.

[0014] The control system acquires the power generation of the photovoltaic system, the operating power of the multi-split air conditioning system, the energy storage device's power, the compressor speed, the opening degree of each electronic expansion valve, the indoor temperature of the room corresponding to each indoor unit, the indoor temperature change trend, and the refrigerant superheat at the evaporator outlet of the indoor unit. Based on the acquired data, it outputs corresponding control commands to control the operating status of the energy manager, compressor, and each electronic expansion valve. This ensures efficient photovoltaic power generation, precise compressor power control, and reasonable distribution of cooling capacity in the indoor units, while maintaining indoor thermal comfort in the rooms corresponding to each indoor unit and stable operation of the multi-split air conditioning system.

[0015] The control commands are used to control the photovoltaic direct-drive multi-split system to operate according to the following process:

[0016] First, utilize the flexible adjustment capability of multi-split air conditioning systems to directly absorb photovoltaic power generation;

[0017] When the power generation of the photovoltaic system is greater than the maximum operating power of the multi-split air conditioning system or the indoor temperature is lower than the lower limit of the preset thermal comfort temperature range, the excess electricity is stored in the energy storage device first. After the energy storage device is fully charged, the remaining electricity is uploaded to the grid.

[0018] When the power generation of the photovoltaic system is less than the maximum operating power of the multi-split air conditioning system or the indoor temperature is higher than the upper limit of the preset thermal comfort temperature range, the energy storage device will be given priority to supplement the power supply to the multi-split air conditioning system. When the energy storage device is insufficient, it will draw power from the grid to supplement the power supply to the multi-split air conditioning system.

[0019] Preferably, the control system includes a data acquisition module, a main controller, a fuzzy controller, and a PID controller. The input terminals of the data acquisition module are connected to the energy manager and the multi-split air conditioning system, respectively. The output terminals of the data acquisition module, the fuzzy controller, the PID controller, the energy manager, and the multi-split air conditioning system are all connected to the main controller. The fuzzy controller is also connected to the PID controller.

[0020] The fuzzy controller is used to determine the refrigerant superheat setting value at the evaporator outlet of the indoor unit based on the indoor temperature of the room corresponding to each indoor unit and the indoor temperature change trend.

[0021] The PID controller is used to output an initial control signal for the compressor speed based on the power generation of the photovoltaic system, the operating power of the multi-split air conditioning system, and the indoor temperature of the room corresponding to each indoor unit.

[0022] And the target value of expansion valve opening corresponding to the refrigerant superheat setting value at the indoor unit evaporator outlet and the refrigerant superheat output at the indoor unit evaporator outlet determined by the fuzzy controller.

[0023] The main controller is used to adjust the compressor speed according to the initial compressor speed control signal, the preset thermal comfort temperature range, and the preset safety buffer temperature threshold, so as to ensure that the indoor temperature in the room corresponding to each indoor unit meets the human thermal comfort requirements. When the compressor speed reaches the preset compressor speed upper limit, the controller controls the energy manager to store the excess photovoltaic power generation in the energy storage device or upload it to the grid.

[0024] And for adjusting the opening degree of each electronic expansion valve according to the expansion valve opening degree control signal, so as to achieve precise control of the refrigerant superheat at the outlet of the indoor unit evaporator.

[0025] Preferably, the energy manager is equipped with a first unidirectional meter, a second unidirectional meter, and a bidirectional meter, wherein,

[0026] The first unidirectional meter is used to measure the power generation of the photovoltaic system, the second unidirectional meter is used to measure the operating power of the multi-split air conditioning system, and the bidirectional meter is used to measure the charging / discharging power of the power grid.

[0027] The second objective of this application is to provide a control method for a photovoltaic direct-drive multi-unit system.

[0028] The second objective of this application is achieved through the following technical solution:

[0029] A control method for a photovoltaic direct-drive multi-split system as described in any one of the above claims, comprising:

[0030] Determine the adjustable superheat range and thermal comfort temperature range of the multi-split air conditioning system;

[0031] Obtain the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Temperature variation trend of each indoor unit in the corresponding room Energy storage device power consumption, refrigerant superheat at the indoor unit evaporator outlet. ;

[0032] Based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Thermal comfort temperature range The compressor speed is adjusted using a PID control algorithm to control the power of the energy storage device and the power transmission between the power grid, the energy storage device and the energy manager.

[0033] Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trend of each indoor unit in the corresponding room and the refrigerant superheat at the evaporator outlet of each indoor unit The opening degree of each electronic expansion valve is controlled by a PID control algorithm.

[0034] Preferably, the method based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Thermal comfort temperature range The system controls the power supply of energy storage devices, employs a PID control algorithm to regulate compressor speed, and manages power transmission between the grid, energy storage devices, and energy managers, including:

[0035] Based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Calculate power deviation ,in, ;

[0036] Based on the indoor temperature of the room corresponding to each indoor unit Calculate indoor weighted average temperature ;

[0037] Based on thermal comfort temperature range The optimal thermal comfort temperature range is defined as follows: ,in, A safe buffer temperature threshold;

[0038] Analysis of indoor weighted average temperature thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between the two is analyzed, and the corresponding PID control strategy is selected based on the analysis results to regulate the compressor speed and control the power transmission between the power grid, energy storage equipment and energy manager, so as to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

[0039] Preferably, the weighted average temperature in the analysis chamber thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between the two is analyzed, and the corresponding PID control strategy is selected based on the analysis results to regulate the compressor speed and control the power transmission between the power grid, energy storage equipment and energy manager, so as to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

[0040] Analysis of indoor weighted average temperature thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between them is analyzed, and the PID control input parameters are determined based on the analysis results and the preset input parameter model.

[0041] The input parameter model is as follows:

[0042] ,

[0043] in, To control priority switching parameters, and have

[0044] ;

[0045] The target compressor speed is calculated by selecting the corresponding PID control strategy based on the determined PID control parameters.

[0046] The compressor speed is regulated based on the calculated target compressor speed value, and the power transmission between the power grid, energy storage equipment and energy manager is controlled to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

[0047] Preferably, the indoor weighted average temperature The calculation model is as follows:

[0048]

[0049] in, Indicates the first The rated capacity of the indoor unit in each room. Indicates the first The indoor temperature of each room, This indicates the number of indoor units in a multi-split air conditioning system.

[0050] Preferably, the step is based on the indoor temperature of the room corresponding to each indoor unit. Temperature variation trend of each indoor unit in the corresponding room and the refrigerant superheat at the evaporator outlet of each indoor unit The PID control algorithm is used to regulate the opening degree of each electronic expansion valve, including:

[0051] Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trends of the corresponding rooms for each indoor unit The superheat setpoint for each indoor unit is dynamically generated using a fuzzy control algorithm. ;

[0052] Based on the refrigerant superheat at the evaporator outlet of each indoor unit and the corresponding superheat setting value of the indoor unit Calculate the superheat deviation of each indoor unit. ,in, ;

[0053] The overheating deviation of each indoor unit As input, a PID control algorithm is used to calculate the target opening value of the corresponding electronic expansion valve;

[0054] The opening degree of the corresponding electronic expansion valve is adjusted according to the calculated target opening degree value.

[0055] Preferably, the step is based on the indoor temperature of the room corresponding to each indoor unit. Temperature variation trends of the corresponding rooms for each indoor unit The superheat setpoint for each indoor unit is dynamically generated using a fuzzy control algorithm. include:

[0056] Set the indoor temperature of the room corresponding to each indoor unit. Temperature variation trends of the corresponding rooms for each indoor unit After fuzzification, the indoor temperature of each indoor unit corresponding to the room is obtained. Temperature variation trends of the corresponding rooms for each indoor unit Membership degree under their respective multiple linguistic variables;

[0057] Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trends of the corresponding rooms for each indoor unit By invoking a pre-built fuzzy control rule table based on the membership degrees of each of its multiple linguistic variables, fuzzy inference is performed to obtain the overheat setpoint of each indoor unit. fuzzy sets;

[0058] Set the superheat setting value for each indoor unit The fuzzy set is defuzzified to obtain the specific superheat set value. .

[0059] Preferably, the method for constructing the fuzzy control rule table is as follows:

[0060] Based on thermal comfort theory, the indoor temperature of each indoor unit corresponds to the room temperature. Fuzzyize into multiple room temperature linguistic variables;

[0061] Temperature variation trends of each indoor unit in the corresponding room Divided into multiple linguistic variables representing temperature change trends;

[0062] Within the adjustable superheat range, set the superheat value for each indoor unit. Divide into multiple language variables for overheat setting values;

[0063] The fuzzy control rule table is constructed based on the combination of the room temperature linguistic variable and the temperature change trend linguistic variable. In the fuzzy control rule table, each combination of the room temperature linguistic variable and the temperature change trend linguistic variable corresponds to a superheat setpoint linguistic variable.

[0064] The photovoltaic direct-drive multi-split system and its control method of the present invention have the following significant advantages over the prior art through system architecture innovation and control logic optimization:

[0065] 1. Efficiently absorbs photovoltaic power: Through the coordinated control of compressor speed tracking photovoltaic power, energy storage buffer, and grid supplementation, it effectively copes with the intermittency and volatility of photovoltaic power, significantly improves the self-consumption rate of photovoltaic power, and reduces the impact of photovoltaic power generation on the grid;

[0066] 2. Precise control of multi-split air conditioning system power: It adopts priority switching PID control based on indoor weighted average temperature, taking into account both photovoltaic absorption and thermal comfort. The power adjustment response is fast and accurate, solving the shortcomings of traditional temperature control.

[0067] 3. Rational allocation of indoor unit cooling capacity: Based on the generation of differentiated superheat setpoints using fuzzy control, combined with superheat deviation tracking using PID control, the cooling capacity of each room is allocated as needed, avoiding uneven cooling capacity and fully leveraging the load flexibility advantage of multiple indoor units in a multi-split system.

[0068] 4. Ensure system stability and thermal comfort: Through real-time monitoring of all system parameters, collaborative work of multiple controllers, and control under multiple constraints, ensure the stable operation of the air conditioning system while meeting the thermal comfort needs of the human body;

[0069] 5. High practicality: It does not rely on complex model training data, has clear control logic and strong operability, is suitable for multi-unit application scenarios in small and medium-sized commercial or public buildings, and is easy to promote in engineering. Attached Figure Description

[0070] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0071] Figure 1 This is a schematic diagram of the structure of a photovoltaic direct-drive multi-split air conditioning system according to an embodiment of this application;

[0072] Figure 2 This is a flowchart of a control method for a photovoltaic direct-drive multi-split air conditioning system in an embodiment of this application;

[0073] Figure 3 This is a schematic diagram of the compressor speed control principle in an embodiment of this application;

[0074] Figure 4 This is a schematic diagram of the expansion valve opening control principle in an embodiment of this application;

[0075] Figure 5 This is a schematic diagram of the fuzzy control principle for the superheat setpoint in the embodiments of this application. Detailed Implementation

[0076] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0077] In the embodiments provided in this application, it should be understood that the disclosed methods and systems can be implemented in other ways. The system embodiments described below are merely illustrative. For example, the division of units and modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or modules can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, and can be electrical, mechanical, or other forms.

[0078] In addition, each functional unit in the various embodiments of this application can be integrated into a single processor, or each unit can be a separate device, or two or more units can be integrated into a single device; each functional unit in the various embodiments of this application can be implemented in hardware or in the form of hardware plus software functional units.

[0079] Those skilled in the art will understand that all or part of the steps of the following method embodiments can be implemented by program instructions and related hardware. The aforementioned program instructions can be stored in a computer-readable storage medium. When the program instructions are executed, they perform the steps of the following method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0080] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "a plurality of" or "several" means two or more, unless otherwise explicitly specified.

[0081] This application provides a photovoltaic direct-drive multi-split system, such as... Figure 1 As shown, the photovoltaic direct-drive multi-split air conditioning system may include a photovoltaic system, an energy manager, a power grid, an energy storage device, a multi-split air conditioning system and a control system. The multi-split air conditioning system includes an outdoor unit and multiple indoor units. The outdoor unit is equipped with a compressor, and each indoor unit is equipped with an electronic expansion valve.

[0082] The photovoltaic system, power grid, energy storage equipment, and multi-split air conditioning system are each connected to the energy manager for power transmission. The energy manager and multi-split air conditioning system are each connected to the control system for communication.

[0083] The control system is responsible for acquiring data such as the power generation of the photovoltaic system, the operating power of the multi-split air conditioning system, the energy storage device's power, the compressor speed, the opening degree of each electronic expansion valve, the indoor temperature of the room corresponding to each indoor unit, the indoor temperature change trend, and the refrigerant superheat at the evaporator outlet of the indoor unit. Based on the acquired data, it outputs corresponding control commands to control the operating status of the energy manager, compressor, and each electronic expansion valve. This ensures efficient photovoltaic power generation, precise compressor power control, and reasonable distribution of cooling capacity in the indoor units, while maintaining indoor thermal comfort in the rooms corresponding to each indoor unit and stable operation of the multi-split air conditioning system.

[0084] The control commands are used to control the photovoltaic direct-drive multi-split system to operate according to the following process:

[0085] First, utilize the flexible adjustment capability of multi-split air conditioning systems to directly absorb photovoltaic power generation;

[0086] When the power generation of the photovoltaic system is greater than the maximum operating power of the multi-split air conditioning system or the indoor temperature is lower than the lower limit of the preset thermal comfort temperature range, the excess electricity is stored in the energy storage device first. After the energy storage device is fully charged, the remaining electricity is uploaded to the grid.

[0087] When the power generation of the photovoltaic system is less than the maximum operating power of the multi-split air conditioning system or the indoor temperature is higher than the upper limit of the preset thermal comfort temperature range, the energy storage device will be given priority to supplement the power supply to the multi-split air conditioning system. When the energy storage device is insufficient, it will draw power from the grid to supplement the power supply to the multi-split air conditioning system.

[0088] In this embodiment, the control system acts as the core hub, dynamically assessing the matching status of photovoltaic power and air conditioning load, the energy storage device's power level, and the indoor thermal environment by collecting key operating parameters of the entire system in real time. For the energy manager, control commands are used to adjust the flow of electrical energy, achieving an orderly switching between "photovoltaic power supply - energy storage buffer - grid supplementation." For the compressor and electronic expansion valve, precise control commands are used to adjust their operating states, ensuring the air conditioning system's power adapts to photovoltaic fluctuations while meeting the cooling needs of each room. Ultimately, this maximizes the absorption of photovoltaic power while ensuring thermal comfort and system stability.

[0089] The photovoltaic direct-drive multi-split air conditioning system in this embodiment constructs a collaborative energy utilization architecture of "photovoltaic-energy storage-air conditioning-grid", which solves the impact of photovoltaic volatility on power supply stability and improves the utilization rate of photovoltaic power. It realizes the hierarchical distribution and dynamic adjustment of power, reduces the frequent interaction between the system and the grid, and reduces the operating pressure on the grid. It provides the hardware foundation and data support for the precise power control and reasonable distribution of indoor unit cooling capacity of the multi-split air conditioning system.

[0090] In one embodiment, the control system includes a data acquisition module, a main controller, a fuzzy controller, and a PID controller. The input terminals of the data acquisition module are connected to the energy manager and the multi-split air conditioning system, respectively. The output terminals of the data acquisition module, the fuzzy controller, the PID controller, the energy manager, and the multi-split air conditioning system are all connected to the main controller. The fuzzy controller is also connected to the PID controller.

[0091] The fuzzy controller is used to determine the refrigerant superheat setting value at the evaporator outlet of the indoor unit based on the indoor temperature of the room corresponding to each indoor unit and the indoor temperature change trend.

[0092] The PID controller is used to output an initial control signal for the compressor speed to the main controller based on the power generation of the photovoltaic system, the operating power of the multi-split air conditioning system, and the indoor temperature of each room corresponding to the indoor unit.

[0093] And the target value of the expansion valve opening corresponding to the refrigerant superheat setting value at the indoor unit evaporator outlet and the refrigerant superheat output at the indoor unit evaporator outlet, determined according to the fuzzy controller.

[0094] The main controller adjusts the compressor speed based on the initial compressor speed control signal, the preset thermal comfort temperature range, and the preset safety buffer temperature threshold, so that the indoor temperature in the room corresponding to each indoor unit meets the human thermal comfort requirements. When the compressor speed reaches the preset upper limit, the controller controls the energy manager to store excess photovoltaic power generation in energy storage devices or upload it to the grid.

[0095] And it is used to adjust the opening degree of each electronic expansion valve according to the expansion valve opening degree control signal, so as to achieve precise control of the refrigerant superheat at the outlet of the indoor unit evaporator.

[0096] In this embodiment, the data acquisition module provides a comprehensive and real-time data source for control decisions; the fuzzy controller dynamically generates personalized superheat setpoints based on the different thermal states of each room to adapt to the cooling needs of different rooms; the PID controller utilizes its precise tracking characteristics to achieve closed-loop control of the compressor speed and the opening of the electronic expansion valve; the main controller undertakes the coordination and scheduling function, integrates the signals of each controller, and optimizes the control commands in combination with preset constraints (thermal comfort temperature range, speed limit) to ensure the coordinated achievement of multiple objectives.

[0097] This embodiment clarifies the division of labor and cooperation logic of each component of the control system, avoiding the functional limitations of a single controller and improving the professionalism and accuracy of the control scheme. The combination of fuzzy controller and PID controller not only solves the control problems caused by the nonlinearity and uncertainty of the room's thermal state, but also ensures the stability and accuracy of the control process. The overall scheduling function of the main controller realizes the dynamic balance of multiple objectives such as "photovoltaic absorption, power control, cooling distribution, and thermal comfort guarantee", thereby improving the overall operating performance of the system.

[0098] In one embodiment, the energy manager includes a first unidirectional meter, a second unidirectional meter, and a bidirectional meter, wherein...

[0099] The first unidirectional meter is used to measure the power generation of the photovoltaic system, the second unidirectional meter is used to measure the operating power of the multi-split air conditioning system, and the bidirectional meter is used to measure the charging / discharging power of the power grid.

[0100] In this embodiment, the photovoltaic energy input, air conditioning system energy consumption, and energy exchange between the system and the grid are obtained through the precise measurement of three types of electricity meters. This data is transmitted to the control system in real time, providing accurate data support for determining the matching relationship between photovoltaic power and air conditioning load, determining the charging and discharging strategy of energy storage devices, and the timing of grid interaction. This avoids control decision deviations caused by inaccurate power data, achieving precise monitoring and differentiation of power data at each stage. It solves the problem of ambiguous power metering in traditional solutions, provides data assurance for the precise operation of the control algorithm, and facilitates subsequent statistical analysis of key indicators such as photovoltaic absorption rate and system energy consumption level, providing data basis for system optimization.

[0101] like Figure 2 As shown in the embodiments of this application, a control method for a photovoltaic direct-drive multi-split system is provided, which may include:

[0102] S1, determine the adjustable superheat range and thermal comfort temperature range of the multi-split air conditioning system;

[0103] S2, Obtain the power generation of the photovoltaic system. Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Temperature variation trend of each indoor unit in the corresponding room Energy storage device power consumption, refrigerant superheat at the indoor unit evaporator outlet. ;

[0104] S3, based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Thermal comfort temperature range The compressor speed is adjusted using a PID control algorithm to control the power of the energy storage device and the power transmission between the power grid, the energy storage device and the energy manager.

[0105] S4, based on the indoor temperature of the room corresponding to each indoor unit. Temperature variation trend of each indoor unit in the corresponding room and the refrigerant superheat at the evaporator outlet of each indoor unit The opening degree of each electronic expansion valve is controlled by a PID control algorithm.

[0106] The control method in this embodiment first defines the control boundaries (adjustable superheat range and thermal comfort temperature range) through preset intervals, then acquires various input parameters required for control through data acquisition, and finally implements control in two layers: the upper layer adapts to photovoltaic power fluctuations by controlling the compressor speed, and the lower layer controls the distribution of cooling capacity by controlling the opening of the electronic expansion valve. The two layers of control work together to achieve multi-objective optimization. Precise and rapid regulation of system power is achieved through direct speed control, and the opening of the indoor unit's expansion valve is adjusted based on indoor temperature and superheat, taking into account indoor thermal comfort theory to fully utilize the system's load flexibility.

[0107] Specifically, the cooling capacity of the indoor unit is directly related to the superheat at the evaporator outlet. The lower the superheat, the greater the refrigerant flow and the stronger the cooling capacity. However, excessively low superheat can easily lead to compressor liquid slugging, while excessively high superheat will reduce system energy efficiency. Taking into account the actual load demand of the room, system operating energy efficiency, and operating stability, the adjustable range of superheat is determined through experiments, preferably 1~15℃ (which can be adjusted according to the specific unit model).

[0108] Indoor thermal comfort temperature range: Based on the "Code for Design of Heating, Ventilation and Air Conditioning of Civil Buildings" and the theory of indoor environmental thermal comfort, combined with the building usage scenario (such as office buildings), the thermal comfort temperature range is determined to be 23~28℃.

[0109] In one embodiment, based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Thermal comfort temperature range The system controls the power supply of energy storage devices, employs a PID control algorithm to regulate compressor speed, and manages power transmission between the grid, energy storage devices, and energy managers, including:

[0110] Based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Calculate power deviation ,in, ;

[0111] Based on the indoor temperature of the room corresponding to each indoor unit Calculate indoor weighted average temperature ;

[0112] Based on thermal comfort temperature range Set the optimal thermal comfort temperature range; the optimal thermal comfort temperature range is... ,in, A safe buffer temperature threshold;

[0113] Analysis of indoor weighted average temperature thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between the two is analyzed, and the corresponding PID control strategy is selected based on the analysis results to regulate the compressor speed and control the power transmission between the power grid, energy storage equipment and energy manager, so as to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

[0114] This embodiment determines the supply and demand relationship between photovoltaic (PV) and air conditioning loads by power deviation, reflects the overall indoor thermal environment status by indoor weighted average temperature, and defines the thermal environment boundary for priority PV absorption by the optimal thermal comfort temperature range. When the indoor weighted average temperature is within the optimal thermal comfort range, the PID control strategy prioritizes adapting to power deviation to maximize PV absorption; when the indoor weighted average temperature exceeds the optimal thermal comfort range but is still within it, the PID control strategy prioritizes adjusting the indoor temperature to ensure thermal comfort, while coordinating energy storage and the grid for energy supplementation or storage.

[0115] In this embodiment, the safety buffer temperature threshold for priority switching of compressor speed control is specified. Set to 1℃.

[0116] This embodiment introduces indoor weighted average temperature to avoid interference from abnormal temperatures in a single room on overall control decisions and improves the accuracy of thermal environment assessment. By using the optimal thermal comfort temperature range, it achieves priority switching between photovoltaic absorption and thermal comfort assurance, solving the problem of neglecting one aspect for another caused by a single control objective. Combined with power transmission control, it realizes the synergy of power regulation and power balance, further improving photovoltaic absorption capacity and system operation stability.

[0117] In one embodiment, the indoor weighted average temperature is analyzed. thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between the two is analyzed, and the corresponding PID control strategy is selected based on the analysis results to regulate the compressor speed and control the power transmission between the power grid, energy storage equipment and energy manager, so as to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

[0118] Analysis of indoor weighted average temperature thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between them is analyzed, and the PID control input parameters are determined based on the analysis results and the preset input parameter model.

[0119] The input parameter model is as follows:

[0120] ,

[0121] in, To control priority switching parameters, and have

[0122] ;

[0123] The target compressor speed is calculated by selecting the corresponding PID control strategy based on the determined PID control parameters.

[0124] The compressor speed is regulated based on the calculated target compressor speed value, and the power transmission between the power grid, energy storage equipment and energy manager is controlled to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

[0125] In this embodiment, the priority switching parameter is controlled. This is the core of achieving the switching between prioritizing photovoltaic (PV) power consumption and prioritizing thermal comfort. When α=1, the input parameter is mainly the power deviation ΔP, and the PID controller focuses on adjusting the compressor speed to match the PV power, achieving efficient PV power consumption; when α=0, the input parameter is mainly the indoor weighted average temperature. Primarily focused on adjusting compressor speed to quickly correct indoor temperature and ensure thermal comfort, the PID controller prioritizes this function. Through this model, the PID controller can dynamically adjust its control focus based on the indoor thermal environment, achieving multi-objective collaborative optimization.

[0126] This embodiment proposes a concise and efficient PID control input parameter model, through... The coefficient enables smooth switching of control priorities, avoiding system fluctuations caused by sudden changes in control modes; it improves the accuracy and flexibility of compressor speed control, enabling it to quickly track photovoltaic power fluctuations and respond promptly to changes in indoor temperature, thus balancing photovoltaic absorption efficiency and thermal comfort.

[0127] Considering that the rated capacity of indoor units in different rooms varies, their weighting in influencing the overall air conditioning system load and indoor thermal environment differs. This embodiment uses the rated capacity of the indoor units as the weight, performs a weighted summation of the indoor temperatures in each room, and then takes the average value. This provides a more objective and comprehensive reflection of the overall thermal environment of the building, avoiding the distortion in thermal environment judgment caused by simply averaging and ignoring differences in room loads.

[0128] This embodiment provides a scientific and reasonable overall thermal environment evaluation index, which provides an accurate basis for the priority switching of compressor speed control and improves the rationality of control decisions; it takes into account the load differences of different rooms, making the overall control strategy more in line with the actual operating scenario and ensuring the thermal comfort experience of most rooms.

[0129] The compressor speed control principle of this application embodiment is as follows: Figure 3 As shown, the power difference between photovoltaic power generation and the power consumption of the multi-split air conditioning system is calculated in relation to the indoor weighted average temperature. The compressor speed is then adjusted based on the indoor weighted average temperature and the power difference. First, when the indoor weighted average temperature is within the optimal thermal comfort temperature range, the compressor speed of the multi-split air conditioning system is controlled by a PID controller based on the power difference between the photovoltaic system's power generation and the multi-split air conditioning system's power consumption. When the compressor speed reaches its upper limit, excess photovoltaic power generation is stored in the battery or fed into the grid. When the system superheat approaches the upper or lower limit of the thermal comfort temperature range, the compressor speed is adjusted using the weighted average temperature to quickly restore the indoor temperature to the thermal comfort temperature range. Under this control condition, excess / deficient photovoltaic power generation is stored / released using the battery.

[0130] PID controller settings: Input parameters are When the indoor weighted average temperature In When within the interval, That is, based on the power difference Power tracking control is achieved by regulating the compressor speed using PID controller 1; when In When within the interval, That is, based on the indoor weighted average temperature The compressor speed is adjusted by PID controller 2 to ensure that the indoor temperature meets the human body's thermal comfort requirements.

[0131] In one embodiment, indoor weighted average temperature The calculation model is as follows:

[0132]

[0133] in, Indicates the first The rated capacity of the indoor unit in each room. Indicates the first The indoor temperature of each room, This indicates the number of indoor units in a multi-split air conditioning system.

[0134] In one embodiment, based on the indoor temperature of the room corresponding to each indoor unit. Temperature variation trend of each indoor unit in the corresponding room and the refrigerant superheat at the evaporator outlet of each indoor unit The PID control algorithm is used to regulate the opening degree of each electronic expansion valve, including:

[0135] Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trends of the corresponding rooms for each indoor unit The superheat setpoint for each indoor unit is dynamically generated using a fuzzy control algorithm. ;

[0136] Based on the refrigerant superheat at the evaporator outlet of each indoor unit and the corresponding superheat setting value of the indoor unit Calculate the superheat deviation of each indoor unit. ,in, ;

[0137] The overheating deviation of each indoor unit As input, a PID control algorithm is used to calculate the target opening value of the corresponding electronic expansion valve;

[0138] The opening degree of the corresponding electronic expansion valve is adjusted according to the calculated target opening degree value.

[0139] Superheat is directly related to the cooling capacity of the indoor unit; the lower the superheat, the greater the cooling capacity. Through a fuzzy control algorithm, personalized superheat setpoints are generated for each room based on their unique thermal states (temperature and temperature change trends), achieving precise matching of cooling demand. Then, a PID control algorithm tracks superheat deviations, dynamically adjusting the opening of the electronic expansion valve to control refrigerant flow, ensuring that the measured superheat quickly approaches the setpoint, ultimately achieving on-demand distribution of cooling capacity to each room.

[0140] This embodiment achieves differentiated and precise distribution of cooling capacity in each room, solving the problem of some rooms being too cold or too hot due to uneven distribution of cooling capacity in traditional solutions; the combination of fuzzy control and PID control not only adapts to the nonlinearity and uncertainty of the room's thermal state, but also ensures the stability and rapid response of overheat control, thereby improving the overall thermal comfort level.

[0141] In one embodiment, based on the indoor temperature of the room corresponding to each indoor unit. Temperature variation trends of the corresponding rooms for each indoor unit The superheat setpoint for each indoor unit is dynamically generated using a fuzzy control algorithm. include:

[0142] Set the indoor temperature of the room corresponding to each indoor unit. Temperature variation trends of the corresponding rooms for each indoor unit After fuzzification, the indoor temperature of each indoor unit corresponding to the room is obtained. Temperature variation trends of the corresponding rooms for each indoor unit Membership degree under their respective multiple linguistic variables;

[0143] Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trends of the corresponding rooms for each indoor unit By invoking a pre-built fuzzy control rule table based on the membership degrees of each of its multiple linguistic variables, fuzzy inference is performed to obtain the overheat setpoint of each indoor unit. fuzzy sets;

[0144] Based on the superheat setting value of each indoor unit The superheat setpoint of each indoor unit is obtained by defuzzifying the fuzzy set. .

[0145] Indoor temperature and temperature change trends are precise quantities that change continuously, while fuzzy controllers make inference decisions using linguistic variables. This embodiment first uses fuzzification to convert precise temperature and temperature change rates into linguistic variables (such as "cold," "hot," and "temperature rise") and their corresponding membership degrees that the fuzzy controller can recognize, quantifying the degree to which they belong to each linguistic variable. Then, based on a preset fuzzy control rule table, fuzzy inference is used to comprehensively determine the fuzzy set of superheat that should be matched under the current thermal state. Finally, a defuzzification method (such as the centroid method) is used to convert the fuzzy set into precise superheat values, which serve as the specific target for control execution.

[0146] This embodiment effectively addresses the nonlinearity, uncertainty, and ambiguity of indoor thermal conditions, and can dynamically generate appropriate superheat setpoints based on the real-time thermal conditions of the room, thereby improving the flexibility and targeting of cooling capacity control. It also provides a scientifically reasonable target value for the precise control of the opening of the electronic expansion valve, ensuring the accuracy of cooling capacity distribution and a comfortable thermal experience.

[0147] In one embodiment, the fuzzy control rule table is constructed as follows:

[0148] Based on thermal comfort theory, the indoor temperature of each indoor unit corresponds to the room temperature. Fuzzyize into multiple room temperature linguistic variables;

[0149] Temperature variation trends of each indoor unit in the corresponding room Divided into multiple linguistic variables representing temperature change trends;

[0150] Within the adjustable superheat range, set the superheat value for each indoor unit. Divide into multiple language variables for overheat setting values;

[0151] A fuzzy control rule table is constructed based on the combination of room temperature linguistic variable and temperature change trend linguistic variable. In the fuzzy control rule table, each combination of room temperature linguistic variable and temperature change trend linguistic variable corresponds to a superheat setpoint linguistic variable.

[0152] In this embodiment, the fuzzy control rule table is the core basis for fuzzy inference. Its construction logic is based on thermal comfort requirements and the operating principle of air conditioning: when the room temperature is low, a larger superheat setpoint is used to reduce the cooling capacity; when the room temperature is high, a smaller superheat setpoint is used to increase the cooling capacity; when the temperature is rising, the superheat setpoint is appropriately reduced to anticipate the cooling demand; when the temperature is falling, the superheat setpoint is appropriately increased to avoid overcooling. By comprehensively covering combined scenarios of room temperature and temperature change trends, it ensures that a reasonable superheat setpoint can be matched under different thermal conditions.

[0153] This embodiment provides a systematic and comprehensive basis for fuzzy reasoning, ensuring the consistency and rationality of the superheat setpoint generation and avoiding the subjectivity and randomness of control decisions. The rule table logic is aligned with thermal comfort requirements and air conditioning operating characteristics, enabling the fuzzy control algorithm to respond quickly and accurately to changes in room thermal state, ensuring the accuracy of cooling capacity distribution and thermal comfort experience.

[0154] The principle of electronic expansion valve opening control in this implementation is as follows:

[0155] Taking a specific room as an example, first, its indoor temperature is collected. This value is then input as one of the input variables to the fuzzy controller. The fuzzy controller dynamically generates the superheat setpoint for the indoor unit of the room based on the room temperature and its changing trends. ,like Figure 5 As shown. Subsequently, the deviation between the measured superheat at the indoor unit outlet and the setpoint given by the fuzzy controller is calculated, and this deviation is used as an input signal to adjust the opening of the electronic expansion valve via the PID controller, thereby achieving precise tracking and control of the superheat. Figure 4 As shown in the figure. This "fuzzy setpoint + PID control" framework enables smooth adjustment of the indoor unit's expansion valve opening under different operating conditions.

[0156] In multi-room operation, the system generates differentiated superheat target values ​​for each indoor unit to achieve adaptive refrigerant flow distribution and coordinated control of cooling capacity between rooms. This method not only meets the different load requirements of each room but also improves the overall thermal comfort level of the system while ensuring individual comfort.

[0157] The fuzzy control method for superheat regulation is described in detail below:

[0158] (1) Determining input and output variables

[0159] In this embodiment, the input variables of the fuzzy controller include indoor temperature. With indoor temperature change trend The output variable is the superheat setpoint of the indoor unit. .

[0160] 1) Input variable 1: Indoor temperature

[0161] According to thermal comfort theory, indoor temperature can be fuzzified into five linguistic variables, each representing a different level of comfort:

[0162]

[0163] in, They represent cold, cool, neutral, warm, and hot, respectively.

[0164] 2) Input variable 2: Indoor temperature change trend

[0165] The trend of room temperature change was divided into three linguistic variables:

[0166]

[0167] in, This indicates a drop in temperature. This indicates that the temperature is stable. This indicates a rise in temperature.

[0168] 3) Output variable: Superheat setpoint

[0169] Within a suitable adjustable range for overheating, the overheating setpoint is divided into five language variables:

[0170]

[0171] in, These represent the maximum superheat setting value, the larger superheat setting value, the moderate superheat setting value, the smaller superheat setting value, and the minimum superheat setting value, respectively.

[0172] (2) Construction of fuzzy control rule table

[0173] A fuzzy control rule table is constructed based on the combination of indoor temperature and temperature change rate. Fuzzy Relationship The mapping relationship between input and output is shown in Table 1.

[0174] Table 1 Fuzzy Control Rules

[0175]

[0176] The rule table mainly reflects the following control logic: when the room temperature is significantly low, the superheat setting value should be kept at a high level to limit the refrigerant flow and reduce the cooling capacity; when the room temperature is in the neutral range, the superheat setting value should be kept at a medium level; when the room temperature is high or trending upward, the superheat setting value should be gradually reduced to increase the refrigerant flow and prioritize the cooling capacity supply to the room.

[0177] (3) Fuzzy reasoning and decision making

[0178] In the actual execution process, the input variables are first... and Fuzzification is performed to obtain the membership degree of each linguistic variable. Then, fuzzy inference is performed using the fuzzy control rule table to synthesize the output fuzzy set. Finally, the corresponding overheat setting value is obtained through defuzzification.

[0179] Taking a small office building in Changsha as an example, the thermal comfort temperature range is set at 23~28℃. The indoor temperature at time t can be fuzzily categorized as follows: 23~24℃ is "cold", 24~25℃ is "cool", 25~26℃ is "neutral", 26~27℃ is "warm", and 27~28℃ is "hot". The difference between the current and previous indoor temperatures is used as the rate of change of indoor temperature at time t. A rate of change less than zero indicates a "temperature decrease" in the room; a rate of change equal to zero indicates a "temperature stability"; and a rate of change greater than zero indicates a "temperature increase". The control variable is the superheat setpoint, the adjustable range of which can be determined based on the actual unit being used. For example, for a certain unit, the range is 1~15℃. When the indoor temperature is "cold" and the indoor temperature change rate is "temperature decrease", it indicates that the current indoor temperature is low and the cooling capacity is too large. It is necessary to reduce the cooling capacity of the room to a greater extent. Therefore, the superheat setting value of the indoor unit in this room should be the maximum value at this moment, that is, the "maximum superheat setting value". After clarification, it can be found that the superheat setting of the indoor unit should be set to 15℃.

[0180] 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 they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0181] 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.

[0182] 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.

[0183] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A photovoltaic direct-drive multi-split system, characterized in that, This includes a photovoltaic system, an energy manager, a power grid, energy storage equipment, a multi-split air conditioning system, and a control system. The multi-split air conditioning system includes an outdoor unit and multiple indoor units. The outdoor unit is equipped with a compressor, and each indoor unit is equipped with an electronic expansion valve. The photovoltaic system, power grid, energy storage device, and multi-split air conditioning system are all connected to the energy manager for power transmission. The energy manager and multi-split air conditioning system are also connected to the control system for communication. The control system acquires the power generation of the photovoltaic system, the operating power of the multi-split air conditioning system, the energy storage device's power, the compressor frequency or speed, the opening degree of each electronic expansion valve, the indoor temperature of the room corresponding to each indoor unit, and the refrigerant superheat at the evaporator outlet of the indoor unit. Based on the acquired data, it outputs corresponding control commands to control the operating status of the energy manager, compressor, and each electronic expansion valve. This ensures efficient photovoltaic power generation, precise compressor power control, and reasonable distribution of cooling capacity in the indoor units, while maintaining indoor thermal comfort in the rooms corresponding to each indoor unit and stable operation of the multi-split air conditioning system. The control commands are used to control the photovoltaic direct-drive multi-split system to operate according to the following process: First, utilize the flexible adjustment capability of multi-split air conditioning systems to directly absorb photovoltaic power generation; When the power generation of the photovoltaic system is greater than the maximum operating power of the multi-split air conditioning system or the indoor temperature is lower than the lower limit of the preset thermal comfort temperature range, the excess electricity is stored in the energy storage device first. After the energy storage device is fully charged, the remaining electricity is uploaded to the grid. When the power generation of the photovoltaic system is less than the maximum operating power of the multi-split air conditioning system or the indoor temperature is higher than the upper limit of the preset thermal comfort temperature range, the energy storage device will be given priority to supplement the power supply to the multi-split air conditioning system. When the energy storage device is insufficient, it will draw power from the grid to supplement the power supply to the multi-split air conditioning system.

2. The photovoltaic direct-drive multi-split system according to claim 1, characterized in that, The control system includes a data acquisition module, a main controller, a fuzzy controller, and a PID controller. The input terminals of the data acquisition module are connected to the energy manager and the multi-split air conditioning system, respectively. The output terminals of the data acquisition module, the fuzzy controller, the PID controller, the energy manager, and the multi-split air conditioning system are all connected to the main controller. The fuzzy controller is also connected to the PID controller. The fuzzy controller is used to determine the refrigerant superheat setting value at the evaporator outlet of the indoor unit based on the indoor temperature of the room corresponding to each indoor unit and the indoor temperature change trend. The PID controller is used to output the corresponding initial control signal for compressor speed based on the power generation of the photovoltaic system, the operating power of the multi-split air conditioning system, and the indoor temperature of the room corresponding to each indoor unit. And to output the corresponding expansion valve opening target value based on the refrigerant superheat setting value and the refrigerant superheat at the indoor unit evaporator outlet determined by the fuzzy controller. The main controller is used to adjust the compressor speed according to the initial compressor speed control signal, the preset thermal comfort temperature range, and the preset safety buffer temperature threshold, so as to ensure that the indoor temperature in the room corresponding to each indoor unit meets the human thermal comfort requirements. When the compressor speed reaches the preset compressor speed upper limit, the controller controls the energy manager to store the excess photovoltaic power generation in the energy storage device or upload it to the grid. And for adjusting the opening degree of each electronic expansion valve according to the expansion valve opening degree control signal, so as to achieve precise control of the refrigerant superheat at the outlet of the indoor unit evaporator.

3. The photovoltaic direct-drive multi-split system according to claim 1, characterized in that, The energy manager is equipped with a first one-way meter, a second one-way meter, and a two-way meter, wherein... The first unidirectional meter is used to measure the power generation of the photovoltaic system, the second unidirectional meter is used to measure the operating power of the multi-split air conditioning system, and the bidirectional meter is used to measure the charging / discharging power of the power grid.

4. A control method for a photovoltaic direct-drive multi-split air conditioning system according to any one of claims 1-3, characterized in that, include: Determine the adjustable superheat range and thermal comfort temperature range of the multi-split air conditioning system; Obtain the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Temperature variation trend of each indoor unit in the corresponding room Energy storage device power consumption, refrigerant superheat at the indoor unit evaporator outlet. ; Based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Thermal comfort temperature range The compressor speed is adjusted using a PID control algorithm to control the power of the energy storage device and the power transmission between the power grid, the energy storage device and the energy manager. Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trend of each indoor unit in the corresponding room and the refrigerant superheat at the evaporator outlet of each indoor unit The opening degree of each electronic expansion valve is controlled by a PID control algorithm.

5. The control method for a photovoltaic direct-drive multi-split system according to claim 4, characterized in that, The power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Indoor temperature of each room corresponding to each indoor unit Thermal comfort temperature range The system controls the power supply of energy storage devices, employs a PID control algorithm to regulate compressor speed, and manages power transmission between the grid, energy storage devices, and energy managers, including: Based on the power generation of the photovoltaic system Power consumption of multi-split air conditioning systems Calculate power deviation ,in, ; Based on the indoor temperature of the room corresponding to each indoor unit Calculate indoor weighted average temperature ; Based on thermal comfort temperature range The optimal thermal comfort temperature range is defined as follows: ,in, A safe buffer temperature threshold; Analysis of indoor weighted average temperature thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between the two is analyzed, and the corresponding PID control strategy is selected based on the analysis results to regulate the compressor speed and control the power transmission between the power grid, energy storage equipment and energy manager, so as to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

6. The control method for a photovoltaic direct-drive multi-split system according to claim 5, characterized in that, The weighted average temperature in the analysis room thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between the two is analyzed, and the corresponding PID control strategy is selected based on the analysis results to regulate the compressor speed and control the power transmission between the power grid, energy storage equipment and energy manager, so as to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort. Analysis of indoor weighted average temperature thermal comfort temperature range and the optimal thermal comfort temperature range The relationship between them is analyzed, and the PID control input parameters are determined based on the analysis results and the preset input parameter model. The input parameter model is as follows: ， in, To control priority switching parameters, and have ； The target compressor speed is calculated by selecting the corresponding PID control strategy based on the determined PID control parameters. The compressor speed is regulated based on the calculated target compressor speed value, and the power transmission between the power grid, energy storage equipment and energy manager is controlled to achieve a dynamic balance between photovoltaic power matching and indoor thermal comfort.

7. The control method for a photovoltaic direct-drive multi-split system according to claim 5, characterized in that, The indoor weighted average temperature The calculation model is as follows: ； in, Indicates the first The rated capacity of the indoor unit in each room. Indicates the first The indoor temperature of each room, This indicates the number of indoor units in a multi-split air conditioning system.

8. The control method for a photovoltaic direct-drive multi-split system according to claim 4, characterized in that, The indoor temperature of the room corresponding to each indoor unit is as follows. Temperature variation trend of each indoor unit in the corresponding room and the refrigerant superheat at the evaporator outlet of each indoor unit The PID control algorithm is used to regulate the opening degree of each electronic expansion valve, including: Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trends of the corresponding rooms for each indoor unit The superheat setpoint for each indoor unit is dynamically generated using a fuzzy control algorithm. ; Based on the refrigerant superheat at the evaporator outlet of each indoor unit and the corresponding superheat setting value of the indoor unit Calculate the superheat deviation of each indoor unit. ,in, ; The overheating deviation of each indoor unit As input, a PID control algorithm is used to calculate the target opening value of the corresponding electronic expansion valve; The opening degree of the corresponding electronic expansion valve is adjusted according to the calculated target opening degree value.

9. The control method for a photovoltaic direct-drive multi-split system according to claim 8, characterized in that, The indoor temperature of the room corresponding to each indoor unit is as follows. Temperature variation trends of the corresponding rooms for each indoor unit The superheat setpoint for each indoor unit is dynamically generated using a fuzzy control algorithm. include: Set the indoor temperature of the room corresponding to each indoor unit. Temperature variation trends of the corresponding rooms for each indoor unit After fuzzification, the indoor temperature of each indoor unit corresponding to the room is obtained. Temperature variation trends of the corresponding rooms for each indoor unit Membership degree under their respective multiple linguistic variables; Based on the indoor temperature of the room corresponding to each indoor unit Temperature variation trends of the corresponding rooms for each indoor unit By invoking a pre-built fuzzy control rule table based on the membership degrees of each of its multiple linguistic variables, fuzzy inference is performed to obtain the overheat setpoint of each indoor unit. fuzzy sets; Set the superheat setting value for each indoor unit The fuzzy set is defuzzified to obtain the specific superheat set value. .

10. The control method for a photovoltaic direct-drive multi-split system according to claim 9, characterized in that, Based on thermal comfort theory, the indoor temperature of each indoor unit corresponds to the room temperature. Fuzzyize into multiple room temperature linguistic variables; Temperature variation trends of each indoor unit in the corresponding room Divided into multiple linguistic variables representing temperature change trends; Within the adjustable superheat range, set the superheat value for each indoor unit. Divide into multiple language variables for overheat setting values; The fuzzy control rule table is constructed based on the combination of the room temperature linguistic variable and the temperature change trend linguistic variable. In the fuzzy control rule table, each combination of the room temperature linguistic variable and the temperature change trend linguistic variable corresponds to a superheat setpoint linguistic variable.

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