Photovoltaic direct-driven multi-split air conditioning system and control method thereof

Abstract

The invention discloses a photovoltaic direct-drive multi-split air conditioning system and a control method thereof.The system comprises 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 comprises an outdoor unit with a compressor and a plurality of indoor units with electronic expansion valves; each component realizes energy and information interaction through an energy manager and a communication line; the control method is based on a preset superheat degree adjustable interval and a thermal comfort temperature interval, system data are collected in real time, the rotating speed of the compressor is regulated and controlled through a PID control algorithm, and the opening degree of the electronic expansion valve is regulated and controlled in combination with fuzzy control and the PID control algorithm. Precise regulation and control of the power of the multi-split air conditioning system and reasonable distribution of the cooling capacity of the indoor units are achieved, photovoltaic power generation can be consumed in real time on the premise that indoor thermal comfort and stable operation of the system are guaranteed, the problems that in an existing scheme, the power regulation precision is low, and the photovoltaic consumption capacity is weak due to uneven cooling capacity distribution are solved, and the energy consumption of the system is reduced. The system is suitable for small and medium-sized commercial and public buildings.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic energy utilization and air conditioning system control, in particular to a photovoltaic direct-drive multi-split system and a control method thereof. BACKGROUND

[0002] With the increasing penetration of photovoltaic power generation, its intermittent, volatile and uncertain characteristics are easy to cause frequent impact on the power grid or related equipment, bringing great challenges to the stable operation of the system. As a typical flexible load, air conditioning system load has the potential to absorb distributed photovoltaic power generation through load adjustment and respond to dynamic demand of the power grid, which can help grid-connected photovoltaic systems achieve balanced and flexible operation.

[0003] Multi-split air conditioning system, also known as "one-drag-many" air conditioner or "variable refrigerant flow" air conditioner, is a high-efficiency refrigerant air conditioning system in which one outdoor unit is connected to two or more indoor units through pipes. It can meet the indoor cooling and heating load requirements in a timely manner by controlling the refrigerant circulation amount of the compressor and the refrigerant flow entering the indoor heat exchanger. The electronic expansion valve in the multi-split air conditioning system is a key component for accurately controlling the refrigerant flow. By adjusting the opening of the valve port, the refrigerant flow entering the indoor unit is controlled, thereby affecting the refrigerating capacity of the indoor unit. Due to its 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 or public buildings in recent years.

[0004] The human body has a certain acceptable range of environmental temperature, i.e. the thermal comfort temperature interval. Due to the existence of the thermal comfort temperature interval and the building thermal inertia, users can adjust the air conditioning load within the thermal comfort temperature interval to improve the matching degree of photovoltaic power generation and air conditioning power consumption without affecting the user's thermal comfort feeling.

[0005] To fully utilize the load flexibility of multi-split air conditioning systems to achieve photovoltaic power generation consumption, it is necessary to achieve accurate system power control and reasonable distribution of cooling capacity among different indoor units while ensuring indoor environmental thermal comfort and stable and efficient operation of the system, which is a core problem to be solved at present.

[0006] The existing load adjustment scheme for multi-split air conditioning systems has obvious defects: first, most of them use temperature control method (change the set temperature or pre-cooling / pre-heating) to adjust the system operating power. This method has poor power adjustment accuracy and long response time, and it is difficult to effectively consume frequent fluctuating photovoltaic power generation; second, some studies use model predictive control method to improve power response effect by pre-controlling temperature set value, but it is difficult to obtain the data required for establishing system model and training prediction model in actual engineering, and the practicality is limited; third, a few direct power adjustment schemes do not consider the coordinated control of different indoor units, which easily leads to unreasonable distribution of cooling capacity and cannot fully exert the load flexibility advantage of multi-split air conditioning systems with multiple indoor units.

[0007] In addition, in the conventional operation control of the multi-split air conditioning system, the control variables are usually the compressor speed and the electronic expansion valve opening degree, and the indoor fan speed is adjusted by the user and is not used as a control variable. In the existing scheme, the compressor speed is controlled according to the suction pressure to meet the total refrigeration demand, and the electronic expansion valve opening degree is controlled according to the indoor air temperature and the evaporator outlet refrigerant superheat to meet the refrigeration demand of each room, but it is difficult to determine the optimal suction pressure set value to achieve precise matching of the compressor output capacity and the cooling load. The constant suction pressure, indoor temperature and superheat set value result in that the system power cannot be actively adjusted, the building load flexibility cannot be fully utilized, and thus the sufficient adjustable range cannot be provided for real-time consumption of photovoltaic power generation.

[0008] Therefore, there is an urgent need for a photovoltaic direct-drive multi-split system scheme that can realize efficient consumption of photovoltaic power generation while ensuring indoor thermal comfort and stable system operation. SUMMARY

[0009] In view of the problems of the existing technology, such as the influence of photovoltaic power generation volatility on grid stability, low power regulation accuracy of the multi-split air conditioning system, uneven distribution of indoor unit cooling capacity, and difficulty in utilizing load flexibility, the present application aims to provide a photovoltaic direct-drive multi-split system and a control method thereof, which can realize efficient consumption of photovoltaic power generation, precise regulation of the operation power of the multi-split air conditioning system, and reasonable distribution of indoor unit cooling capacity while considering indoor thermal comfort and system stability.

[0010] A first object of the present application is to provide a photovoltaic direct-drive multi-split system.

[0011] The above-mentioned first object of the present application is achieved by the following technical scheme: A photovoltaic direct-drive multi-split system, the system comprising 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 comprising an outdoor unit and a plurality of indoor units, the outdoor unit being provided with a compressor, and each indoor unit being provided with an electronic expansion valve, The photovoltaic system, the power grid, the energy storage device, and the multi-split air conditioning system are respectively electrically connected to the energy manager, and the energy manager and the multi-split air conditioning system are respectively communicatively connected to the control system, The control system acquires the power generation of the photovoltaic system, the operation power of the multi-split air conditioning system, the energy storage device power, the compressor speed, the opening degree of each electronic expansion valve, the indoor temperature of each indoor unit corresponding room, the indoor temperature change trend and the refrigerant superheat degree of the indoor unit evaporator outlet, and outputs corresponding control instructions to control the working state of the energy manager, the compressor and each electronic expansion valve according to the acquired data, so that the photovoltaic power generation is efficiently consumed, the compressor power of the multi-split air conditioning system is accurately controlled, and the indoor unit cooling capacity is reasonably distributed under the premise of ensuring the indoor environmental thermal comfort of each indoor unit corresponding room and the stable operation of the multi-split air conditioning system, wherein, The control instructions are used to control the photovoltaic direct-drive multi-split air conditioning system to work according to the following process: First, directly consume photovoltaic power generation by using the flexible adjustment capability of the multi-split air conditioning system; When the power generation of the photovoltaic system is greater than the maximum operation power of the multi-split air conditioning system or the indoor temperature is lower than the lower limit of the preset thermal comfort temperature interval, the excess power is stored in the energy storage device first, and the remaining power is uploaded to the power grid when the energy storage device is full; When the power generation of the photovoltaic system is less than the maximum operation power of the multi-split air conditioning system or the indoor temperature is higher than the upper limit of the preset thermal comfort temperature interval, the multi-split air conditioning system is preferentially powered by the energy storage device, and the power grid is used to supplement power to the multi-split air conditioning system when the energy storage device power is insufficient.

[0012] Preferably, the control system comprises a data acquisition module, a main controller, a fuzzy controller and a PID controller, the input end of the data acquisition module is connected with the energy manager and the multi-split air conditioning system respectively, the output end of the data acquisition module, the fuzzy controller, the PID controller, the energy manager and the multi-split air conditioning system are connected with the main controller respectively, and the fuzzy controller is further connected with the PID controller, wherein, The fuzzy controller is used to determine the refrigerant superheat degree setting value of the indoor unit evaporator outlet according to the indoor temperature of each indoor unit corresponding room and the indoor temperature change trend; The PID controller is used to output the initial control signal of the compressor speed according to the power generation of the photovoltaic system, the operation power of the multi-split air conditioning system and the indoor temperature of each indoor unit corresponding room, And output the target value of the expansion valve opening degree corresponding to the refrigerant superheat degree of the indoor unit evaporator outlet according to the refrigerant superheat degree setting value of the indoor unit evaporator outlet determined by the fuzzy controller; The main controller is configured to control the rotation speed of the compressor according to the compressor rotation speed initial control signal, the preset thermal comfort temperature interval, 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 demand, and when the rotation speed of the compressor reaches the preset upper limit of the rotation speed of the compressor, the energy manager is controlled to store the excess photovoltaic power generation to the energy storage device or upload to the power grid, and the electronic expansion valve opening degree of each indoor unit is adjusted according to the expansion valve opening degree control signal to realize accurate control of the superheat degree of the refrigerant at the outlet of the evaporator of the indoor unit.

[0013] Preferably, the energy manager is provided with a first one-way electricity meter, a second one-way electricity meter, and a bidirectional electricity meter. The first one-way electricity meter is configured to measure the power generation of the photovoltaic system, the second one-way electricity meter is configured to measure the operating power of the multi-connected air conditioning system, and the bidirectional electricity meter is configured to measure the charging / discharging power of the power grid.

[0014] The second object of the present application is to provide a control method of a photovoltaic direct-drive multi-connected air conditioning system.

[0015] The above-mentioned second application object of the present application is achieved by the following technical scheme. A control method of a photovoltaic direct-drive multi-connected air conditioning system according to any one of the above-mentioned embodiments, comprising: determining the superheat adjustable interval and the thermal comfort temperature interval of the multi-connected air conditioning system; obtaining the power generation of the photovoltaic system , the power consumption of the multi-connected air conditioning system , the indoor temperature of the room corresponding to each indoor unit , the temperature change trend of the room corresponding to each indoor unit , the energy storage device power, and the superheat degree of the refrigerant at the outlet of the evaporator of each indoor unit ; controlling the rotation speed of the compressor by using a PID control algorithm according to the power generation of the photovoltaic system , the power consumption of the multi-connected air conditioning system , the indoor temperature of the room corresponding to each indoor unit , the thermal comfort temperature interval , and the energy storage device power, and controlling the transmission of electric energy among the power grid, the energy storage device, and the energy manager; controlling the opening degree of each electronic expansion valve by using a PID control algorithm according to the indoor temperature of the room corresponding to each indoor unit , the temperature change trend of the room corresponding to each indoor unit , and the superheat degree of the refrigerant at the outlet of the evaporator of each indoor unit .

[0016] The power generation of the photovoltaic system The power consumption of the multi-connected air conditioning system The indoor temperature of the room corresponding to each indoor unit The thermal comfort temperature interval And the energy storage device power, the PID control algorithm is used to regulate the compressor speed, and the power transmission between the power grid, the energy storage device and the energy manager includes: The power generation of the photovoltaic system And the power consumption of the multi-connected air conditioning system Calculate the power deviation Wherein, ; According to the indoor temperature of the room corresponding to each indoor unit Calculate the indoor weighted average temperature ; According to the thermal comfort temperature interval Set the optimal thermal comfort temperature interval, which is Wherein, The safety buffer temperature threshold value; Analyze the relationship between the indoor weighted average temperature The thermal comfort temperature interval And the optimal thermal comfort temperature interval According to the analysis result, select the corresponding PID control strategy to regulate the compressor speed and control the power transmission between the power grid, the energy storage device and the energy manager, so as to realize the dynamic balance of photovoltaic power matching and indoor thermal comfort.

[0017] Preferably, the relationship between the indoor weighted average temperature The thermal comfort temperature interval And the optimal thermal comfort temperature interval According to the analysis result, select the corresponding PID control strategy to regulate the compressor speed and control the power transmission between the power grid, the energy storage device and the energy manager, so as to realize the dynamic balance of photovoltaic power matching and indoor thermal comfort includes: Analyze the relationship between the indoor weighted average temperature The thermal comfort temperature interval And the optimal thermal comfort temperature interval According to the analysis result and the preset input parameter model to determine the PID control input parameter, wherein, The input parameter model is as follows: , Wherein, The control priority switching parameter, and ; According to the determined PID control parameter selection, a corresponding PID control strategy is selected to calculate a compressor target speed value; According to the calculated compressor target speed value, the compressor speed is regulated and controlled, and the power transmission between the power grid, the energy storage device and the energy manager is controlled to realize dynamic balance of photovoltaic power matching and indoor thermal comfort.

[0018] Preferably, the indoor weighted average temperature The calculation model is as follows:

[0019] Wherein, Indicates the rated capacity of the indoor unit of the room, Indicates the indoor temperature of the room, Indicates the number of indoor units of the multi-connected air conditioning system.

[0020] Preferably, according to the indoor temperature of each indoor unit corresponding room , the temperature change trend of each indoor unit corresponding room And the refrigerant superheat degree of the evaporator outlet of each indoor unit , the opening of each electronic expansion valve is regulated and controlled by using PID control algorithm, including: According to the indoor temperature of each indoor unit corresponding room And the temperature change trend of each indoor unit corresponding room The superheat degree set value of each indoor unit is dynamically generated by using fuzzy control algorithm ; According to the refrigerant superheat degree of the evaporator outlet of each indoor unit And the superheat degree set value of the corresponding indoor unit The superheat degree deviation of each indoor unit is calculated , wherein, ; The superheat degree deviation of each indoor unit As input, the target opening value of the corresponding electronic expansion valve is calculated by using PID control algorithm; According to the calculated target opening value of the electronic expansion valve, the opening of the corresponding electronic expansion valve is regulated and controlled.

[0021] Preferably, according to the indoor temperature of each indoor unit corresponding room And the temperature change trend of each indoor unit corresponding room The superheat degree set value of each indoor unit is dynamically generated by using fuzzy control algorithm , including: The indoor temperature of each indoor unit corresponding room The temperature change trend of the room corresponding to each indoor unit The indoor temperature of the room corresponding to each indoor unit is obtained by performing the fuzzification processing The temperature change trend of the room corresponding to each indoor unit The membership degree under the respective multiple language variables; According to the indoor temperature of the room corresponding to each indoor unit The temperature change trend of the room corresponding to each indoor unit The membership degree under the respective multiple language variables The fuzzy set of the overheat degree setting value of each indoor unit is obtained by performing the fuzzy inference on the pre-constructed fuzzy control rule table The fuzzy set of the overheat degree setting value of each indoor unit is obtained by performing the fuzzy inference on the pre-constructed fuzzy control rule table The specific overheat degree setting value is obtained by performing the defuzzification processing on the fuzzy set of the overheat degree setting value of each indoor unit .

[0022] Preferably, the construction method of the fuzzy control rule table is as follows: According to the thermal comfort theory, the indoor temperature of the room corresponding to each indoor unit is Fuzzified into multiple room temperature language variables; The temperature change trend of the room corresponding to each indoor unit is Divided into multiple temperature change trend language variables; The overheat degree setting value of each indoor unit is Divided into multiple overheat degree setting value language variables; According to the combination of the room temperature language variable and the temperature change trend language variable, the fuzzy control rule table is constructed, wherein each combination of the room temperature language variable and the temperature change trend language variable in the fuzzy control rule table corresponds to an overheat degree setting value language variable.

[0023] The photovoltaic direct-drive multi-connected system and the control method thereof have the following significant advantages compared with the prior art through system architecture innovation and control logic optimization: 1. Efficiently consume photovoltaic power: through the collaborative control of compressor speed tracking photovoltaic power + energy storage buffering + power grid supplement, effectively cope with the intermittency and volatility of photovoltaic power, greatly improve the self-consumption rate of photovoltaic power, and reduce the impact of photovoltaic power generation on the power grid; 2. Accurate regulation of multi-connected air conditioning system power: the priority switching PID control based on the indoor weighted average temperature is adopted, which takes into account photovoltaic consumption and thermal comfort, and the power regulation response speed is fast and accurate, solving the drawbacks of traditional temperature control regulation; 3. Reasonable distribution of indoor unit cooling capacity: differential superheat set value generation based on fuzzy control, combined with superheat deviation tracking of PID control, to realize on-demand distribution of cooling capacity in each room, avoid uneven cooling capacity, and fully utilize the load flexibility advantage of multi-split system with multiple indoor units; 4. Ensure system stability and thermal comfort: through real-time monitoring of system parameters, collaborative work of multiple controllers, and control of multiple constraint conditions, ensure stable operation of air conditioning system, and meet human thermal comfort requirements; 5. Strong practicality: no need to rely on complex model training data, clear control logic, strong operability, suitable for multi-split application scenarios in small and medium-sized commercial or public buildings, easy to promote in engineering. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0025] Figure 1 A structure diagram of a photovoltaic direct-drive multi-split system in an embodiment of the present application; Figure 2 A flow of a control method of a photovoltaic direct-drive multi-split system in an embodiment of the present application; Figure 3 A compressor speed control principle diagram in an embodiment of the present application; Figure 4 An expansion valve opening degree control principle diagram in an embodiment of the present application; Figure 5 A superheat set value fuzzy control principle diagram in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only some of the embodiments of the present application, not all. According to the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0027] In the embodiments of the present application, it should be understood that the disclosed method and system can be implemented in other manners. The embodiments described are merely schematic. For example, the division of the units and modules is merely a logical function division. There can be another division manner for the actual implementation, for example, multiple units or modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed coupling, direct coupling or communication connection between the components can be indirect coupling or communication connection through some interfaces, devices or modules, and can be electrical, mechanical or other forms.

[0028] In addition, each of the functional units in the embodiments of the present application can be integrated in a processing device, each of the units can be a separate device, or two or more units can be integrated in a device. Each of the functional units in the embodiments of the present application can be implemented in the form of hardware, or in the form of hardware plus software function units.

[0029] It can be understood by those skilled in the art that all or part of the steps of the following method embodiments can be completed by program instructions and related hardware. The aforementioned program instructions can be stored in a computer readable storage medium, and the program instructions are executed to perform the steps of the method embodiments. The aforementioned storage medium includes mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, and various media that can store program codes.

[0030] In addition, the terms "first", "second", etc. are used only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" or "several" is two or more, unless otherwise explicitly specified.

[0031] The embodiments of the present application provide a photovoltaic direct-drive multi-connected system, as shown in the figure, which can include a photovoltaic system, an energy manager, a power grid, an energy storage device, a multi-connected air conditioning system, and a control system. The multi-connected air conditioning system includes an outdoor unit and a plurality of indoor units. The outdoor unit is provided with a compressor, and each indoor unit is provided with an electronic expansion valve. Figure 1

[0032] The photovoltaic system, the power grid, the energy storage device, and the multi-connected air conditioning system are respectively connected to the energy manager for power transmission. The energy manager and the multi-connected air conditioning system are respectively connected to the control system for communication.

[0033] ​The control system is responsible for acquiring the power generation of the photovoltaic system, the operation power of the multi-split air conditioning system, the energy storage device power, the compressor speed, the opening degree of each electronic expansion valve, the indoor temperature of each room corresponding to the indoor unit, the indoor temperature change trend, and the refrigerant superheat degree at the outlet of the indoor unit evaporator, and outputs corresponding control instructions to control the working state of the energy manager, the compressor and each electronic expansion valve according to the acquired data, so that the photovoltaic power generation is efficiently consumed, the compressor power of the multi-split air conditioning system is accurately controlled, and the indoor unit cooling capacity is reasonably distributed under the premise of ensuring the indoor environmental thermal comfort of each room corresponding to the indoor unit and the stable operation of the multi-split air conditioning system, wherein, The control instructions are used to control the photovoltaic direct-drive multi-split air conditioning system to work according to the following process: First, directly consume photovoltaic power generation by using the flexible adjustment capability of the multi-split air conditioning system; 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 power is stored in the energy storage device, and the remaining power is uploaded to the power grid when the energy storage device is full; 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 preferentially supplies power to the multi-split air conditioning system, and the power grid supplies power to the multi-split air conditioning system when the energy storage device power is insufficient.

[0034] In this embodiment, the control system is the core hub, which dynamically judges the matching state of photovoltaic power and air conditioning load, the energy storage device power level and the indoor thermal environment by real-time acquisition of key operating parameters of the whole system. For the energy manager, adjust the power flow through the control instruction to realize the orderly switching of "photovoltaic power supply-energy storage buffer-power grid supplement"; for the compressor and electronic expansion valve, adjust the operating state through the precise control instruction, so that the air conditioning system power adapts to the photovoltaic fluctuation, while meeting the cooling capacity demand of each room, and finally maximize the consumption of photovoltaic power under the premise of ensuring thermal comfort and system stability.

[0035] The photovoltaic direct-drive multi-split air conditioning system of this embodiment builds a collaborative energy utilization architecture of "photovoltaic-energy storage-air conditioning-power grid", solves the influence of photovoltaic volatility on power supply stability, improves the utilization rate of photovoltaic power; realizes the hierarchical distribution and dynamic adjustment of electric energy, reduces the frequent interaction between the system and the power grid, and reduces the operating pressure of the power grid; provides a hardware foundation and data support for the accurate power control of the multi-split air conditioning system and the reasonable distribution of indoor unit cooling capacity.

[0036] In one embodiment, the control system comprises a data acquisition module, a main controller, a fuzzy controller and a PID controller, the input end of the data acquisition module is connected with the energy manager and the multi-connected air conditioning system respectively, the output end of the data acquisition module, the fuzzy controller, the PID controller, the energy manager and the multi-connected air conditioning system are connected with the main controller respectively, and the fuzzy controller is further connected with the PID controller, wherein, The fuzzy controller is used to determine the refrigerant superheat degree setting value of the indoor unit evaporator outlet according to the indoor temperature and the indoor temperature change trend of the room corresponding to each indoor unit; The PID controller is used to output the corresponding compressor speed initial control signal to the main controller according to the power generation of the photovoltaic system, the operating power of the multi-connected air conditioning system and the indoor temperature of the room corresponding to each indoor unit, and output the corresponding expansion valve opening degree target value according to the refrigerant superheat degree setting value of the indoor unit evaporator outlet determined by the fuzzy controller and the refrigerant superheat degree of the indoor unit evaporator outlet; The main controller is used to regulate the speed of the compressor according to the compressor speed initial control signal, the preset thermal comfort temperature interval and the preset safety buffer temperature threshold value, so that the indoor temperature in the room corresponding to each indoor unit meets the human thermal comfort demand, and when the speed of the compressor reaches the preset compressor speed upper limit value, the energy manager is controlled to store the excess photovoltaic power generation to the energy storage device or upload to the power grid, and adjust the opening degree of each electronic expansion valve according to the expansion valve opening degree control signal to realize accurate control of the refrigerant superheat degree of the indoor unit evaporator outlet.

[0037] In this embodiment, the data acquisition module provides a comprehensive and real-time data source for control decision; the fuzzy controller dynamically generates personalized superheat degree setting values for the differentiated thermal state of each room to adapt to the cooling demand of different rooms; the PID controller uses its precise tracking characteristics to realize closed-loop control of the compressor speed and the electronic expansion valve opening degree respectively; the main controller undertakes the coordination and scheduling function, integrates the signals of each controller, optimizes the control instructions combined with the preset constraints (thermal comfort temperature interval, speed upper limit), and ensures the realization of multi-objective coordination.

[0038] This embodiment clarifies the division of labor and cooperation logic of each component of the control system, avoids the functional limitations of a single controller, and improves the professionalism and accuracy of the control scheme; the combination of the fuzzy controller and the PID controller not only solves the control problems caused by the nonlinearity and uncertainty of the room thermal state, but also guarantees the stability and accuracy of the control process; the overall scheduling function of the main controller realizes the dynamic balance of the multi-objective of "photovoltaic power consumption, power control, cooling distribution and thermal comfort guarantee", and improves the overall operation performance of the system.

[0039] In one embodiment, the energy manager is provided with a first unidirectional electricity meter, a second unidirectional electricity meter and a bidirectional electricity meter, wherein, The first unidirectional electricity meter is used to measure the power generation of the photovoltaic system, the second unidirectional electricity meter is used to measure the running power of the multi-connected air conditioning system, and the bidirectional electricity meter is used to measure the charging / discharging power of the power grid.

[0040] In this embodiment, the input of photovoltaic energy, the energy consumption of the air conditioning system and the energy exchange between the system and the power grid are obtained through accurate measurement of the three types of electricity meters. These data are transmitted to the control system in real time to provide accurate data support for judging the matching relationship between photovoltaic power and air conditioning load, determining the charging / discharging strategy of the energy storage device and the interaction time of the power grid, avoiding the deviation of control decision caused by inaccurate power data, realizing the accurate monitoring and differentiation of power data in each link, solving the problem of power measurement ambiguity in the traditional scheme, providing data guarantee for the accurate operation of the control algorithm, and facilitating the subsequent statistical analysis of key indicators such as photovoltaic consumption rate and system energy consumption level, and providing data basis for system optimization operation.

[0041] As shown in Figure 2 , the present application provides a control method for a photovoltaic direct-drive multi-connected air conditioning system, which can include: S1, determining the overheating degree adjustable interval and the thermal comfort temperature interval of the multi-connected air conditioning system; S2, obtaining the power generation of the photovoltaic system , the power consumption of the multi-connected air conditioning system , the indoor temperature of the room corresponding to each indoor unit , the temperature change trend of the room corresponding to each indoor unit , the electric quantity of the energy storage device, and the refrigerant superheat degree at the outlet of the evaporator of the indoor unit ; S3, according to the power generation of the photovoltaic system , the power consumption of the multi-connected air conditioning system , the indoor temperature of the room corresponding to each indoor unit , the thermal comfort temperature interval and the electric quantity of the energy storage device, adopting a PID control algorithm to regulate the compressor speed and control the electric energy transmission between the power grid, the energy storage device and the energy manager; S4, according to the indoor temperature of the room corresponding to each indoor unit , the temperature change trend of the room corresponding to each indoor unit and the refrigerant superheat degree at the outlet of the evaporator of each indoor unit , adopting a PID control algorithm to regulate the opening degree of each electronic expansion valve.

[0042] The control method of the embodiment first determines the control boundary (overheating degree adjustable range, thermal comfort temperature range) through a preset range, then obtains various input parameters required for control through data acquisition, and finally realizes control in two layers: the upper layer controls the photovoltaic power fluctuation through compressor speed control, and the lower layer controls the distribution of cold energy through electronic expansion valve opening control. The two layers of control work together to realize multi-objective optimization. Through direct speed control, the system power is accurately and quickly regulated, and on the basis of speed regulation, the indoor unit expansion valve opening is adjusted according to the indoor temperature and overheating degree. By considering the indoor environmental thermal comfort theory, the system load flexibility is fully utilized.

[0043] Specifically, the indoor refrigerating capacity is directly related to the evaporator outlet overheating degree. The smaller the overheating degree, the greater the refrigerant flow and the stronger the refrigerating capacity. However, too low overheating degree is easy to cause compressor liquid knock, and too high overheating degree will reduce system energy efficiency. Considering the actual load demand of the room, system operation energy efficiency and operation stability, the overheating degree adjustable range is determined through test, and the optimal range is 1-15℃ (which can be adjusted according to the specific unit model).

[0044] Indoor thermal comfort temperature range: According to the Code for Design of Heating Ventilation and Air Conditioning of Civil Buildings and the indoor environmental thermal comfort theory, combined with the building use scene (such as office building), the thermal comfort temperature range is determined to be 23-28℃.

[0045] In one embodiment, according to the power generation of the photovoltaic system , the power consumption of the multi-split air conditioning system , the indoor temperature of the room corresponding to each indoor unit , the thermal comfort temperature range and the energy storage device power, the PID control algorithm is used to regulate the compressor speed, and the power transmission between the power grid, the energy storage device and the energy manager is controlled, including: According to the power generation of the photovoltaic system and the power consumption of the multi-split air conditioning system , the power deviation is calculated , wherein, ; According to the indoor temperature of the room corresponding to each indoor unit , the indoor weighted average temperature is calculated ; According to the thermal comfort temperature range , the optimal thermal comfort temperature range is set, and the optimal thermal comfort temperature range is , wherein, is a safety buffer temperature threshold; The indoor weighted average temperature is analyzed in combination with the thermal comfort temperature range and the optimal thermal comfort temperature range relationship between the indoor weighted average temperature and the thermal comfort temperature interval and the optimal thermal comfort temperature interval, and selecting a corresponding PID control strategy according to an analysis result to regulate the compressor rotating speed and control the power transmission among the power grid, the energy storage device and the energy manager, so as to realize dynamic balance of photovoltaic power matching and indoor thermal comfort.

[0046] The embodiment determines the supply-demand relationship between photovoltaic and air conditioning load through power deviation, reflects the overall indoor thermal environment state through indoor weighted average temperature, and defines the thermal environment boundary for preferential photovoltaic consumption through the optimal thermal comfort temperature interval. When the indoor weighted average temperature is in the optimal thermal comfort interval, the PID control strategy preferentially adapts to the power deviation to maximize the consumption of photovoltaic; when the indoor weighted average temperature exceeds the optimal thermal comfort interval but is still within the thermal comfort temperature interval, the PID control strategy preferentially adjusts the indoor temperature to ensure thermal comfort while coordinating the energy storage and the power grid to supplement or store power.

[0047] In the embodiment, the safety buffer temperature threshold for priority switching of the compressor rotating speed control is set to 1℃.

[0048] The embodiment introduces the indoor weighted average temperature, avoids the interference of abnormal temperature of a single room on overall control decision, and improves the accuracy of thermal environment judgment; the optimal thermal comfort temperature interval is used to realize priority switching of photovoltaic consumption and thermal comfort guarantee, and solves the problem of losing one side for the single control target; in combination with power transmission control, the power regulation-power balance is coordinated, and the photovoltaic consumption capacity and system operation stability are further improved.

[0049] In one embodiment, the indoor weighted average temperature is analyzed in relation to the thermal comfort temperature interval and the optimal thermal comfort temperature interval , and a corresponding PID control strategy is selected according to an analysis result to regulate the compressor rotating speed and control the power transmission among the power grid, the energy storage device and the energy manager, so as to realize dynamic balance of photovoltaic power matching and indoor thermal comfort, including: analyzing the indoor weighted average temperature in relation to the thermal comfort temperature interval and the optimal thermal comfort temperature interval , and determining PID control input parameters according to an analysis result and a preset input parameter model, wherein, the input parameter model is as follows: , wherein, is a control priority switching parameter, and has ; ​According to the determined PID control parameter selection, a corresponding PID control strategy is selected to calculate a compressor target speed value; According to the calculated compressor target speed value, the compressor speed is regulated and controlled, and the power transmission between the power grid, the energy storage device and the energy manager is controlled, so as to realize dynamic balance of photovoltaic power matching and indoor thermal comfort.

[0050] In this embodiment, the control priority switching parameter is the core of realizing switching of photovoltaic consumption priority and thermal comfort priority. When α = 1, the input parameter is mainly the power deviation ΔP, the PID controller focuses on adjusting the compressor speed to match the photovoltaic power, and realizes efficient photovoltaic consumption; when α = 0, the input parameter is mainly the indoor weighted average temperature , the PID controller focuses on adjusting the compressor speed to quickly correct the indoor temperature, and guarantees thermal comfort. Through the model, the PID controller can dynamically adjust the control focus according to the indoor thermal environment state, and realizes multi-objective collaborative optimization.

[0051] The embodiment proposes a simple and efficient PID control input parameter model, which realizes smooth switching of control priority through the coefficient, avoids system fluctuations caused by sudden changes in control mode, improves the accuracy and flexibility of compressor speed control, can quickly track photovoltaic power fluctuations, and can respond to indoor temperature changes in time, and takes into account photovoltaic consumption efficiency and thermal comfort experience.

[0052] Considering that the rated capacities of indoor units in different rooms are different, the influence weights of the indoor units on the overall air conditioning system load and the indoor thermal environment are different. In this embodiment, the indoor temperatures of each room are weighted and averaged by taking the rated capacity of the indoor unit as the weight, which can more objectively and comprehensively reflect the overall thermal environment state of the building, and avoids the distortion of the thermal environment caused by the simple arithmetic average ignoring the load difference of the rooms.

[0053] The embodiment provides a scientific and reasonable overall thermal environment evaluation index, which provides an accurate basis for switching of the priority of the compressor speed control, and improves the rationality of the control decision; taking into account the load difference of different rooms, the overall control strategy is more suitable for actual operation scenarios, and the thermal comfort experience of most rooms is guaranteed.

[0054] The compressor speed control principle of the embodiment of the application is as follows Figure 3As 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.

[0055] 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.

[0056] In one embodiment, indoor weighted average temperature The calculation model is as follows:

[0057] 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.

[0058] 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: 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. ; According to the refrigerant superheat degree at the outlet of the evaporator of each indoor unit And the superheat degree set value of the corresponding indoor unit Calculate the superheat degree deviation of each indoor unit Wherein, ; The superheat degree 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; According to the calculated target opening value of the electronic expansion valve, the opening of the corresponding electronic expansion valve is adjusted.

[0059] The superheat degree is directly related to the refrigerating capacity of the indoor unit. The smaller the superheat degree, the greater the refrigerating capacity. Through the fuzzy control algorithm, personalized superheat degree set values are generated for the differentiated thermal state (temperature and temperature change trend) of each room, so as to realize accurate matching of cold quantity demand; then, through the PID control algorithm, the superheat degree deviation is tracked, the opening of the electronic expansion valve is dynamically adjusted, the refrigerant flow is controlled, the measured superheat degree is quickly approached to the set value, and finally the cold quantity of each room is distributed on demand.

[0060] The embodiment realizes differentiated and accurate distribution of cold quantity of each room, solves the problem of overcooling or overheating of some rooms caused by uneven distribution of cold quantity in the traditional scheme; the combination of fuzzy control and PID control not only adapts to the nonlinearity and uncertainty of the thermal state of the room, but also guarantees the stability and rapid response of the superheat degree control, and improves the overall thermal comfort level.

[0061] In one embodiment, according to the indoor temperature of the room corresponding to each indoor unit And the temperature change trend of the room corresponding to each indoor unit A fuzzy control algorithm is used to dynamically generate the superheat degree set value of each indoor unit Including: The indoor temperature of the room corresponding to each indoor unit And the temperature change trend of the room corresponding to each indoor unit Are fuzzified to obtain the indoor temperature of the room corresponding to each indoor unit And the temperature change trend of the room corresponding to each indoor unit Membership under a plurality of linguistic variables respectively; According to the indoor temperature of the room corresponding to each indoor unit And the temperature change trend of the room corresponding to each indoor unit Membership under a plurality of linguistic variables respectively, a pre-constructed fuzzy control rule table is called for fuzzy reasoning to obtain a fuzzy set of the superheat degree set value of each indoor unit ; According to the superheat degree set value of each indoor unit The superheat setpoint of each indoor unit is obtained by defuzzifying the fuzzy set. .

[0062] 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.

[0063] 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.

[0064] In one embodiment, the fuzzy control rule table is constructed as follows: 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; 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.

[0065] 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.

[0066] The embodiment provides a system, a comprehensive fuzzy reasoning basis, ensures consistency and rationality of the superheat setting value generation, avoids subjectivity and randomness of control decisions; the rule table logic is in line with the thermal comfort demand and the air conditioner operation characteristics, so that the fuzzy control algorithm can quickly and accurately respond to the room heat state change, and the accuracy of cold distribution and the thermal comfort experience are guaranteed.

[0067] The electronic expansion valve opening control principle of the embodiment is as follows: Taking a room as an example, first, the indoor temperature of the room is collected , and the indoor temperature is taken as one of the input variables and input into the fuzzy controller. The fuzzy controller dynamically generates the superheat setting value of the indoor unit of the room according to the room temperature and the change trend of the room temperature , as shown in the formula (1). Figure 5 Subsequently, the deviation between the measured superheat at the outlet of the indoor unit and the given setting value of the fuzzy controller is calculated, and the deviation is taken as an input signal, and the opening of the electronic expansion valve is adjusted through the PID controller, so that the superheat is accurately tracked and controlled, as shown in the formula (2). Figure 4 The "fuzzy setting value + PID control" framework constructed in this way can realize smooth adjustment of the opening of the indoor unit expansion valve under different operating conditions.

[0068] In the multi-room working condition, the system generates differentiated superheat target values for each indoor unit to realize adaptive distribution of refrigerant flow and coordinated regulation and control of cold between rooms. This method not only meets the different load demands of each room, but also improves the overall thermal comfort level while ensuring individual comfort.

[0069] The fuzzy control method of the superheat regulation is described as follows: (1) Determination of input and output variables In the embodiment, the input variables of the fuzzy controller include the indoor temperature and the change trend of the indoor temperature , and the output variable is the superheat setting value of the indoor unit .

[0070] 1) Input variable 1: indoor temperature

[0071] According to the thermal comfort theory, the indoor temperature can be fuzzified into five language variables, which represent different comfort feelings respectively:

[0072] Among them, cold, cool, neutral, warm, and hot, respectively.

[0073] 2) Input variable 2: change trend of indoor temperature

[0074] The trend of room temperature change is divided into three linguistic variables:

[0075] Among them, represents temperature drop, represents temperature stability, represents temperature rise.

[0076] 3) Output variable: superheat setting value In the appropriate superheat adjustable interval, the superheat setting value is divided into five linguistic variables:

[0077] Among them, respectively 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.

[0078] (2) Fuzzy control rule table construction Based on the combination of indoor temperature and temperature change rate, the fuzzy control rule table is constructed. The fuzzy relationship represents the mapping relationship between input and output, as shown in Table 1.

[0079] Table 1 Fuzzy control rule table

[0080] This rule table mainly embodies 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 interval, the superheat setting value is maintained at a moderate level; when the room temperature is high or shows an upward trend, the superheat setting value gradually decreases to increase the refrigerant flow and prioritize the cooling supply of the room.

[0081] (3) Fuzzy reasoning and decision-making In the specific implementation process, first, the input variables and are fuzzified to obtain their membership degrees in each linguistic variable. Then, fuzzy reasoning is performed using the fuzzy control rule table to obtain the fuzzy set of the output. Finally, the corresponding superheat setting value is obtained through the defuzzification method.

[0082] Taking a small office building in Changsha as an example, the thermal comfort temperature interval is set to 23-28℃. The indoor temperature at time t can be fuzzily processed as "cold" between 23-24℃, "cool" between 24-25℃, "neutral" between 25-26℃, "warm" between 26-27℃, and "hot" between 27-28℃. The indoor temperature difference between the current time and the last time is used as the indoor temperature change rate at time t. If the change rate is less than zero, it is considered that the room is in "temperature drop"; if the change rate is equal to zero, it is considered that the room is in "temperature stability"; and if the change rate is greater than zero, it is considered that the room is in "temperature rise". The control variable is the overheat degree set value, which can be determined according to the adjustable range of the actual use unit. Taking a unit as an example, the range is 1-15℃. When the indoor temperature is "cold" and the indoor temperature change rate is "temperature drop", it indicates that the current indoor temperature is low and the cooling capacity is large, and the cooling capacity of the room needs to be reduced to a large extent, so that the indoor unit overheat degree set value at this time should be the maximum value, i.e. "maximum overheat degree set value", and after clarification, the indoor unit overheat degree should be set to 15℃.

[0083] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0084] The skilled person can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of the two. In order to clearly show the interchangeability of hardware and software, the composition and steps of each example have been described in the above description. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0085] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, software modules executed by a processor, or a combination of the two. The software modules can be placed in random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art.

[0086] The foregoing description of the disclosed embodiments enables a person skilled in the art to make or use the application. Modifications of these embodiments will occur to persons of skill in the art, and that the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Therefore, the present application is not intended 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-inverter system, characterized in that, The photovoltaic system, energy manager, power grid, energy storage device, multi-connected air conditioning system and control system are connected in power transmission, and the energy manager and multi-connected air conditioning system are connected in communication with the control system, The control system acquires the power generation of the photovoltaic system, the operation power of the multi-connected air conditioning system, the energy storage device, the frequency or rotating speed of the compressor, the opening degree of each electronic expansion valve, the indoor temperature of the room corresponding to each indoor unit and the superheat degree of the refrigerant at the outlet of the indoor unit evaporator, and outputs corresponding control instructions to control the working states of the energy manager, compressor and each electronic expansion valve, so as to realize efficient consumption of photovoltaic power generation, accurate regulation of the compressor power of the multi-connected air conditioning system and reasonable distribution of indoor unit cooling capacity under the premise of ensuring the indoor environmental thermal comfort of the room corresponding to each indoor unit and stable operation of the multi-connected air conditioning system, wherein The control instructions are used to control the photovoltaic direct-drive multi-connected air conditioning system to work according to the following process: First, directly consume photovoltaic power generation by using the flexible adjustment capacity of the multi-connected air conditioning system; When the power generation of the photovoltaic system is greater than the maximum operation power of the multi-connected air conditioning system or the indoor temperature is lower than the lower limit of the preset thermal comfort temperature interval, the excess power is stored in the energy storage device in priority, and the remaining power is uploaded to the power grid after the energy storage device is full; When the power generation of the photovoltaic system is less than the maximum operation power of the multi-connected air conditioning system or the indoor temperature is higher than the upper limit of the preset thermal comfort temperature interval, the energy storage device is preferentially used to supplement power to the multi-connected air conditioning system, and the power grid is used to supplement power to the multi-connected air conditioning system when the energy storage device is insufficient. The control system comprises a data acquisition module, a main controller, a fuzzy controller and a PID controller, the input end of the data acquisition module is connected with the energy manager and multi-connected air conditioning system, the output end of the data acquisition module, fuzzy controller, PID controller, energy manager and multi-connected air conditioning system are connected with the main controller, and the fuzzy controller is further connected with the PID controller, wherein 2. The PV direct drive multi-split system according to claim 1, characterized in that, The fuzzy controller is used to determine the refrigerant superheat degree setting value at the outlet of the indoor unit evaporator according to the indoor temperature and indoor temperature change trend of the room corresponding to each indoor unit; The PID controller is used to output the corresponding compressor rotating speed initial control signal according to the power generation of the photovoltaic system, the operation power of the multi-connected air conditioning system and the indoor temperature of the room corresponding to each indoor unit, And output the corresponding expansion valve opening degree target value according to the refrigerant superheat degree setting value at the outlet of the indoor unit evaporator and the refrigerant superheat degree at the outlet of the indoor unit evaporator determined by the fuzzy controller. ​ The main controller is configured to control the rotation speed of the compressor according to the compressor rotation speed initial control signal, the preset thermal comfort temperature interval, 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 demand, and when the rotation speed of the compressor reaches the preset upper limit of the rotation speed of the compressor, the energy manager is controlled to store the excess photovoltaic power generation into the energy storage device or upload to the power grid, And the electronic expansion valve opening degree is adjusted according to the expansion valve opening degree control signal to realize accurate control of the superheat degree of the refrigerant at the outlet of the indoor unit evaporator.

3. The PV direct drive multi-split system according to claim 1, wherein, The energy manager is provided with a first one-way electric meter, a second one-way electric meter and a bidirectional electric meter, wherein, The first one-way electric meter is configured to measure the power generation of the photovoltaic system, the second one-way electric meter is configured to measure the operation power of the multi-split air conditioning system, and the bidirectional electric meter is configured to measure the charge / discharge power of the power grid.

4. A control method of the photovoltaic direct-drive multi-connected system according to any one of claims 1 to 3, characterized in that, It comprises: determining the superheat adjustable interval and the thermal comfort temperature interval of the multi-split air conditioning system; Obtaining power generation of a photovoltaic system , power consumption of a multi-connected air conditioning system , indoor temperature of a room corresponding to each indoor unit , temperature change trend of a room corresponding to each indoor unit , electric quantity of an energy storage device, and refrigerant superheat degree at outlet of an evaporator of an indoor unit ; According to the power generation of a photovoltaic system , the power consumption of a multi-connected air conditioning system , the indoor temperature of the room corresponding to each indoor unit , the thermal comfort temperature interval and the energy storage device power, the PID control algorithm is used to regulate the compressor speed, and the power transmission between the power grid, the energy storage device and the energy manager is controlled. According to the indoor temperature of the room corresponding to each indoor unit , the temperature change trend of the room corresponding to each indoor unit , and the refrigerant superheat degree at the outlet of the evaporator of each indoor unit , a PID control algorithm is adopted to regulate the opening degree of each electronic expansion valve.

5. The control method of a photovoltaic direct drive multi-connected system according to claim 4, characterized in that, The power generation of the photovoltaic system The power consumption of the multi-connected air conditioning system The indoor temperature of the room corresponding to each indoor unit The thermal comfort temperature interval And the energy storage device power, the PID control algorithm is adopted to control the compressor speed, and the power transmission between the power grid, the energy storage device and the energy manager comprises: Generating power according to a photovoltaic system and power consumption of a multi-split air conditioning system Calculating power deviation wherein ; According to the indoor temperature of the room corresponding to each indoor unit Calculating the indoor weighted average temperature ; According to the thermal comfort temperature interval An optimal thermal comfort temperature interval is set, which is wherein, is a safety buffer temperature threshold; analyzing the indoor weighted average temperature the relationship between the thermal comfort temperature interval and the optimal thermal comfort temperature interval and selecting the corresponding PID control strategy according to the analysis result to regulate the compressor speed and control the power transmission between the power grid, the energy storage device and the energy manager, so as to realize the dynamic balance of photovoltaic power matching and indoor thermal comfort.

6. The control method of a photovoltaic direct drive multi-connected system according to claim 5, wherein, The weighted average temperature in the analysis room The relationship between the thermal comfort temperature interval And the optimal thermal comfort temperature interval And according to the analysis result, select the corresponding PID control strategy to regulate the compressor speed and control the power transmission between the power grid, energy storage device and energy manager, to realize the dynamic balance of photovoltaic power matching and indoor thermal comfort. analyzing the indoor weighted average temperature the relationship between the thermal comfort temperature interval and the optimal thermal comfort temperature interval and determining the PID control input parameters according to the analysis result and the preset input parameter model, wherein, The input parameter model is as follows: ， wherein is a control priority switching parameter, and has ； According to the determined PID control parameter selection, the corresponding PID control strategy is selected to calculate the target rotation speed value of the compressor; According to the calculated target rotation speed value of the compressor, the rotation speed of the compressor is regulated, and the transmission of electric energy among the power grid, the energy storage device and the energy manager is controlled to realize the dynamic balance of photovoltaic power matching and indoor thermal comfort.

7. The control method of a photovoltaic direct drive multi-inverter system according to claim 5, wherein, The indoor weighted average temperature The calculation model is as follows: ； wherein, represents the rated capacity of the indoor unit of the room, represents the indoor temperature of the room, represents the number of indoor units of the multi-split air conditioning system. 8.The control method of a photovoltaic direct-drive multi-type air conditioning system according to claim 4, wherein, The indoor temperature of the room corresponding to each indoor unit The temperature change trend of the room corresponding to each indoor unit The refrigerant superheat degree at the outlet of the evaporator of each indoor unit The PID control algorithm is adopted to regulate the opening degree of each electronic expansion valve According to the indoor temperature of the room corresponding to each indoor unit and the temperature change trend of the room corresponding to each indoor unit Generate the overheat degree set value of each indoor unit dynamically by using a fuzzy control algorithm ; According to the refrigerant superheat degree at the outlet of the evaporator of each indoor unit and the superheat degree set value of the corresponding indoor unit calculating the superheat degree deviation of each indoor unit wherein ; The overheat degree deviation of each indoor unit is corrected As input, a PID control algorithm is used to calculate a target opening degree value corresponding to the electronic expansion valve; According to the calculated target opening degree value of the electronic expansion valve, the opening degree of the corresponding electronic expansion valve is regulated. 9.The control method of the photovoltaic direct-drive multi-type inverter system according to claim 8, wherein, The indoor temperature of the room corresponding to each indoor unit The temperature change trend of the room corresponding to each indoor unit The overheat degree set value of each indoor unit is dynamically generated by using a fuzzy control algorithm The method comprises the steps of: the indoor temperature of the room corresponding to each indoor unit the temperature change trend of the room corresponding to each indoor unit the indoor temperature of the room corresponding to each indoor unit the temperature change trend of the room corresponding to each indoor unit the membership degree under each of the plurality of language variables According to the indoor temperature of the room corresponding to each indoor unit and the temperature change trend of the room corresponding to each indoor unit The membership degree under each language variable is called to pre-construct a fuzzy control rule table for fuzzy inference, and the overheat degree setting value of each indoor unit is obtained fuzzy set The superheat degree set value of each indoor unit is de-fuzzified from the fuzzy set of the superheat degree set value to obtain a specific superheat degree set value . 10.The control method of a photovoltaic direct-drive multi-type inverter system according to claim 9, wherein, According to the thermal comfort theory, the indoor temperature of the room corresponding to each indoor unit is fuzzed into a plurality of room temperature linguistic variables; temperature change trend of each room is divided into a plurality of temperature change trend language variables; In the superheat adjustable interval, set the superheat value of each indoor unit Divide into multiple superheat set value language variables; According to the combination of the room temperature language variable and the temperature change trend language variable, the fuzzy control rule table is constructed, wherein each combination of the room temperature language variable and the temperature change trend language variable in the fuzzy control rule table corresponds to a superheat set value language variable.

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