CN-122015245-A - Control method of variable frequency air conditioner and photovoltaic air conditioner cooperative control system

CN122015245ACN 122015245 ACN122015245 ACN 122015245ACN-122015245-A

Abstract

The invention provides a control method of a variable frequency air conditioner and a photovoltaic air conditioner cooperative control system, wherein intelligent scheduling of load of the variable frequency air conditioner is realized by cooperative operation of a photovoltaic system, an energy storage battery, a power grid electricity price and the variable frequency air conditioner, in addition, a target set temperature is determined by a first optimization model with a longer duration and a second optimization model with a shorter duration, the variable frequency air conditioner is controlled according to target control parameters corresponding to the target set temperature, planning air conditioner operation strategies such as photovoltaic power generation and the power grid electricity price are fully utilized, the electricity consumption cost is reduced, and refined and flexible load adjustment of the variable frequency air conditioner is realized, so that deep cooperative intelligent control of the load of the variable frequency air conditioner and a new household energy system is realized on the basis of comprehensively considering economy, comfort and system constraint.

Inventors

ZHANG XUAN

Assignees

宁波奥克斯电气有限公司
奥克斯空调股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. A control method of a variable frequency air conditioner, the method comprising: The method comprises the steps of obtaining detection parameters at the current moment and prediction parameters in a first time length in the future, wherein the detection parameters comprise the current power generation power of a photovoltaic system, the current state of charge of an energy storage battery, the current indoor temperature, the current outdoor temperature and the current power consumption of a variable-frequency air conditioner; Determining a set temperature basic plan curve and a reference charge-discharge plan curve which correspond to the variable frequency air conditioner and the energy storage battery respectively in the future first time according to the detection parameters, the prediction parameters and a first optimization model, wherein the first optimization model is an optimization model corresponding to the future first time; determining a target set temperature at the current moment according to the set temperature basic planning curve, the prediction parameters and a second optimization model, wherein the second optimization model is an optimization model corresponding to a second future time length, and the second future time length is smaller than the first future time length; calculating to obtain a current temperature difference according to the target set temperature and the current indoor temperature, and determining a target control parameter corresponding to the current moment according to the current temperature difference and a preset threshold; And controlling the variable frequency air conditioner to operate according to the target control parameters.
2. The method according to claim 1, wherein determining a set temperature base plan curve and a reference charge-discharge plan curve of the variable frequency air conditioner and the energy storage battery, respectively, within the future first time period according to the detection parameter, the prediction parameter, and the first optimization model, comprises: dividing the future first time period into a plurality of first time periods, and acquiring first basic parameters, wherein the first basic parameters comprise the internet power price of each first time period, the electricity purchasing power from the power grid and the electricity selling power to the power grid; And calculating the set temperature basic planning curve and the reference charge-discharge planning curve according to the detection parameters, the prediction parameters, the first basic parameters and the first optimization model.
3. The method of claim 2, wherein determining the target set temperature at the current time based on the set temperature base plan curve, the prediction parameters, and a second optimization model comprises: Dividing the future second time length into a plurality of second time periods, and determining a set temperature basic value of the set temperature basic planning curve in each second time period; Acquiring a second basic parameter, wherein the second basic parameter comprises an electricity price predicted value of each second period and electricity purchasing power of a power grid; Calculating a set temperature sequence at the current moment according to the set temperature basic value, the second basic parameters, the prediction parameters and the second optimization model of each second period; and taking the first value in the set temperature sequence as the target set temperature at the current moment.
4. The method of any of claims 1-3, wherein the first optimization model and the second optimization model are each provided with constraints, wherein the constraints include a system power balance constraint, a battery energy storage constraint, an indoor temperature dynamic change constraint, and an indoor temperature comfort constraint.
5. The method of claim 1, wherein the preset threshold comprises a first threshold and the target control parameter comprises a first control parameter; the determining the target control parameter corresponding to the current moment according to the current temperature difference and a preset threshold value comprises the following steps: and if the current temperature difference is not smaller than the first threshold value, determining the target control parameter as the first control parameter.
6. The method of claim 5, wherein the preset threshold comprises a second threshold and the target control parameter comprises a second control parameter; the determining the target control parameter corresponding to the current moment according to the current temperature difference and a preset threshold value comprises the following steps: and if the current temperature difference is smaller than the first threshold value and not smaller than the second threshold value, determining the target control parameter as the second control parameter.
7. The method of claim 6, wherein the target control parameter comprises a third control parameter, wherein the determining the target control parameter corresponding to the current time according to the current temperature difference and a preset threshold value further comprises: and if the current temperature difference is smaller than the second threshold value, determining the target control parameter as the third control parameter.
8. The method of claim 1, wherein the target control parameters include a target frequency, a target rotational speed, and a target angle, and the variable frequency air conditioner includes a compressor, an indoor fan, and an air deflector; The control of the variable frequency air conditioner to operate according to the target control parameters comprises the following steps: and controlling the compressor to run according to the target frequency, controlling the indoor fan to run according to the target rotating speed, and controlling the air deflector to run according to the target angle.
9. A photovoltaic air conditioner cooperative control system is characterized by comprising a variable frequency air conditioner, an energy storage battery, a photovoltaic system and a controller, wherein the controller is used for controlling the variable frequency air conditioner by adopting the method of any one of claims 1-8.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the method of any of the preceding claims 1-8.

Description

Control method of variable frequency air conditioner and photovoltaic air conditioner cooperative control system Technical Field The invention relates to the technical field of intelligent home energy management, in particular to a control method of a variable frequency air conditioner and a photovoltaic air conditioner cooperative control system. Background With the popularity of home distributed photovoltaic and energy storage systems, how to efficiently utilize clean power and reduce electricity costs is an important issue. As a main consumer of the home, the air conditioner has a large adjustable potential in load. However, the existing air conditioner and new energy cooperative control method mainly has the following defects that ① control strategies are simple, most schemes adopt start-stop control of an air conditioner during photovoltaic power generation and a Guan Kongdiao device during no light, electricity price signals, battery energy storage states and indoor thermal inertia are not considered, economic optimization is insufficient, ② lacks predictive optimization, the existing schemes only perform reactive control according to the current state, cannot perform prospective scheduling by utilizing photovoltaic power generation prediction and time-sharing electricity price information, cross-period energy transfer is difficult to achieve, ③ comfort degree is greatly sacrificed, in order to respond to power grid requirements or save electricity fees, the existing schemes often adopt a mode of directly closing the air conditioner or greatly adjusting set temperature, user comfort experience is seriously affected, ④ control dimension is single, the existing schemes generally only control the start-stop or set temperature of the air conditioner, and multi-variable cooperative adjustment capabilities such as compressor frequency, fan rotating speed and the like of the variable-frequency air conditioner are not fully utilized. Therefore, how to realize the deep cooperation of the air conditioner load and the home new energy system is a problem to be solved. Disclosure of Invention Accordingly, the present invention is directed to a control method of a variable frequency air conditioner and a photovoltaic air conditioner cooperative control system, so as to alleviate at least some of the above technical problems. The embodiment of the invention provides a control method of a variable frequency air conditioner, which comprises the steps of obtaining detection parameters at a current moment and prediction parameters in a first time in the future, wherein the detection parameters comprise current power generation power of a photovoltaic system, current charge state of an energy storage battery, current indoor temperature, current outdoor temperature and current power consumption of the variable frequency air conditioner, the prediction parameters comprise a power generation power prediction value of the photovoltaic system and a power price prediction value of a power grid, determining a set temperature basic planning curve and a reference charge-discharge planning curve which correspond to the variable frequency air conditioner and the energy storage battery respectively in the first time in the future according to the detection parameters, the prediction parameters and the first optimization model, determining a target set temperature at the current moment according to the set temperature basic planning curve, the prediction parameters and the second optimization model, wherein the second optimization model is an optimization model corresponding to the second time in the future and is smaller than the first time in the future, calculating to obtain the current temperature difference according to the target set temperature and the current indoor temperature, determining a target control parameter corresponding to the current moment according to the current temperature difference and a preset threshold, and controlling the variable frequency air conditioner according to the target control parameter. The method comprises the steps of dividing a future first time period into a plurality of first time periods and obtaining first basic parameters, wherein the first basic parameters comprise the internet power price, the electricity purchasing power from a power grid and the electricity selling power to the power grid in each first time period, and calculating to obtain a set temperature basic planning curve and a reference charge-discharge planning curve according to the detection parameters, the prediction parameters, the first basic parameters and the first optimization model. Preferably, the determining the target set temperature at the current moment according to the set temperature basic planning curve, the predicted parameters and the second optimization model comprises dividing a future second time period into a plurality of second time periods, determining set temperature basic values of the set temper