An intelligent building heating ventilation and air conditioning system optimization control method and device

Abstract

The present application relates to the technical field of intelligent building HVAC system control and optimization, and discloses an intelligent building HVAC system optimization control method and device. The present application first acquires solar radiation intensity data and ambient temperature data of a current scheduling period; then inputs the solar radiation intensity data and ambient temperature data into a pre-constructed photovoltaic power generation model to obtain photovoltaic power generation power data; finally, taking the minimum total power consumption cost as an objective function, keeps the PMV comfort level of each room of the intelligent building within a comfort elasticity range as a constraint condition, and solves the air supply plan of the HVAC system; the total power consumption cost is the sum of the operation costs of each air supply period determined according to the photovoltaic power generation power data and the air conditioner power consumption data; the present application can fully utilize the photovoltaic power generation amount to reduce the power consumption cost under the premise of ensuring user comfort.

Description

Technical Field

[0001] This invention relates to the field of intelligent building HVAC system control and optimization technology, specifically to an intelligent building HVAC system optimization control method and device. Background Technology

[0002] With increasingly stringent energy-saving requirements for building equipment, and given that HVAC systems consume nearly half of a building's total energy consumption, more and more scholars are proposing more economical, reliable, environmentally friendly, and user-comfort-oriented optimized control strategies to reduce HVAC energy costs and improve energy utilization. Existing HVAC system control strategies can be divided into two categories based on the availability of a building thermal dynamics model: model-based HVAC system control methods and learning-based HVAC system control methods.

[0003] In model-based HVAC system control methods, Model Predictive Control (MPC) outperforms most other control methods. Although research on MPC in HVAC systems has made some progress, some significant drawbacks remain: In control strategies considering user comfort, most studies only consider indoor temperature as a single influencing factor, neglecting the significant impact of humidity on indoor comfort. Excessively dry or humid indoor environments can drastically reduce user comfort and even affect the lifespan of indoor equipment. Furthermore, in indoor temperature control strategies, taking summer as an example, most studies typically set 26 degrees Celsius as the optimal temperature, ignoring that user comfort temperature is a range and failing to fully explore its optimization potential, thus significantly impacting user comfort. Summary of the Invention

[0004] To address the aforementioned technical issues, this technical solution provides an optimized control method and device for intelligent building HVAC systems based on PMV (Predicted Mean Vote) comfort index. This method links PMV comfort to the temperature-humidity ratio of a room, sets a comfort elasticity range for PMV comfort, uses minimizing total electricity cost as the objective function, and constrains maintaining the PMV comfort of each room in the intelligent building within the comfort elasticity range. The solution then calculates the air supply plan for the HVAC system, enabling the reduction of electricity costs in intelligent buildings while ensuring PMV comfort.

[0005] In a first aspect, the present invention provides an optimized control method for an intelligent building HVAC system, comprising: Obtain solar radiation intensity data and ambient temperature data for the current scheduling cycle; The solar radiation intensity data and ambient temperature data are input into a pre-built photovoltaic power generation model to obtain photovoltaic power generation data; Using the minimum total electricity cost as the objective function and maintaining the PMV comfort level of each room in the smart building within the comfort elasticity range as a constraint, the air supply plan of the HVAC system is solved; whereby... The air supply plan includes the air volume and air temperature of each room in the smart building during each air supply period within the scheduling cycle. The total electricity cost is the sum of the operating costs for each air supply period determined based on photovoltaic power generation data and air conditioning power consumption data; wherein, the air conditioning power consumption data is determined based on the air supply plan; The PMV comfort level is determined based on the room's temperature and humidity ratio; for each room, the comfort flexibility range corresponding to each air supply period is determined based on photovoltaic power generation data, room type, and room occupancy.

[0006] Optionally, the expression for the photovoltaic power generation model is: ; ; in, Indicates photovoltaic power generation capacity; Indicates the power derating factor; Indicates photovoltaic installed capacity; This represents the actual solar radiation intensity; This indicates the intensity of solar radiation under standard test conditions; Indicates the temperature coefficient; This indicates the actual surface temperature of the photovoltaic panel; This indicates the surface temperature of the photovoltaic panel under standard test conditions; This indicates the actual ambient temperature around the photovoltaic panel; This indicates the surface temperature of the photovoltaic panel under standard operating conditions. Indicates the ambient temperature under standard operating conditions; This indicates the solar radiation intensity under standard operating conditions. This indicates the solar radiation absorption rate of the photovoltaic panel; This indicates the photoelectric conversion efficiency of the photovoltaic panel.

[0007] Alternatively, the expression for the objective function, which minimizes the total electricity cost, is as follows: ; ; ; in, Represent the objective function; Indicates the economic cost item; This indicates a penalty for insufficient air supply. Indicates the total number of air supply periods; Indicates the total number of rooms; Indicates the duration of the air supply period; This indicates the specific heat capacity of air; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in Supply air temperature for each air supply period; Indicates the first The room in Temperature during each air supply period; Indicates the energy efficiency ratio of the HVAC system; Indicates the first Photovoltaic power generation during each air supply period; Indicates the unit price of electricity; Indicates the unit price of electricity; Indicates the first The room in Occupancy factor for each air supply period; The penalty coefficient represents the air supply volume.

[0008] Optionally, the constraint that the PMV comfort level of each room in a smart building is kept within the comfort elasticity range can be expressed as: ; ; ; ; in, Indicates the first The room in PMV comfort level during each air supply period; Indicates the first The room in Function coefficient for each air supply period; The room in When the air supply period is used as a laboratory or conference room, the function factor is... Take the first coefficient value; the second... The room in When the air supply period is used as a studio, the functional coefficient Take the second coefficient value; the first coefficient value is greater than the second coefficient value; Indicates the first The lower limit benchmark value of PMV comfort for each air supply period. Indicates the first The upper limit benchmark value of PMV comfort for each air supply period; Indicates the first Photovoltaic power generation coefficient during each air supply period; Indicates the first Photovoltaic power generation during each air supply period; This represents the maximum photovoltaic power generation during all air supply periods within the current scheduling cycle; Indicates the first The room in Occupancy factor for each air supply period; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in The upper limit of air supply volume for each air supply period.

[0009] Optionally, the first The room in PMV comfort during each air supply period The expression is: ; in, Indicates the first The room in Temperature during each air supply period Indicates the first The room in The humidity ratio during each air supply period.

[0010] Optionally, occupancy factor The ways to obtain the value include: No. The room in When a ventilation period is occupied Take the third coefficient value; No. The room in When the air supply period is not occupied Take the fourth coefficient value; The third coefficient value is greater than the fourth coefficient value.

[0011] Optionally, the room temperature is determined based on a pre-built room thermal model, the expression of which is: ; in, Indicates the first The thermal capacity of the room; and They represent the first The room in The air supply period and the first Temperature during each air supply period; Indicates the first The collection of walls of each room; Indicates the first The first room The wall in the first Temperature during each air supply period; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first Window coefficient of each room; Indicates the first A collection of windows from each room; Indicates the first The first room The window in Temperature during each air supply period Indicates the first The first room Thermal resistance of the window; Indicates the first The indoor heat source power of each room; Indicates the first The room in Air volume for each air supply period; This indicates the specific heat capacity of air; Indicates the first The room in Supply air temperature for each air supply period; Indicates the first The first room The projection rate of each window; Indicates the first The first room The surface area of ​​each window; Indicates the first The first room The amount of solar radiation received by each window; Indicates the duration of the air supply period.

[0012] Optionally, the temperature of the room's interior walls is determined based on a pre-constructed thermal model of the room walls, the expression of which is: ; in, Indicates the first The first room The heat capacity of the wall surface; and They represent the first The first room The wall in the first The air supply period and the first Temperature during each air supply period Indicates the first The first room A group of adjacent rooms facing the same wall; Indicates the first The adjacent rooms in the Temperature during each air supply period; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first The first room Solar radiation receiving coefficient of the wall surface; Indicates the first The first room The heat absorption coefficient of the wall surface; Indicates the first The first room Surface area of ​​the wall; Indicates the first The first room The amount of solar radiation received by the wall; Indicates the duration of the air supply period.

[0013] Optionally, the room humidity ratio is determined according to a room humidity ratio model, the expression of which is: ; in, and They represent the first The room in The air supply period and the first The humidity ratio during each air supply period; The gas constant representing the partial pressure of dry air; Indicates the first The room in Temperature during each air supply period; Indicates the first The volume of the room; Indicates the partial pressure of dry air; Indicates the first The indoor humidity source in the first room The mass of water vapor generated during each air supply period; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in The humidity ratio of the supply air during each air supply period; Indicates the duration of the air supply period.

[0014] In a second aspect, the present invention provides an intelligent building HVAC system optimization control device, comprising: The acquisition module is used to acquire solar radiation intensity data and ambient temperature data for the current scheduling cycle; The power generation calculation module is used to input the solar radiation intensity data and ambient temperature data into a pre-built photovoltaic power generation model to obtain photovoltaic power generation data; The solution module is used to solve the air supply plan of the HVAC system with the objective function of minimizing total electricity cost and the constraint that the PMV comfort of each room in the smart building is kept within the comfort elasticity range. The air supply plan includes the air volume and temperature of each room in the smart building during each air supply period within the scheduling cycle. The total electricity cost is the sum of the operating costs for each air supply period, determined based on photovoltaic power generation data and air conditioning power consumption data. The air conditioning power consumption data is determined according to the air supply plan. The PMV comfort is determined based on the room's temperature and humidity ratio. For each room, the comfort elasticity range corresponding to each air supply period is determined based on photovoltaic power generation data, room type, and room occupancy.

[0015] Compared to existing technologies, this invention has the following advantages: First, it acquires solar radiation intensity data and ambient temperature data for the current scheduling cycle. Then, it inputs these data into a pre-constructed photovoltaic power generation model to obtain photovoltaic power generation data. Finally, using the minimum total electricity cost as the objective function and maintaining the PMV comfort level of each room in the smart building within its comfort elasticity range as a constraint, it solves the air supply plan for the HVAC system. The air supply plan includes the air volume and temperature for each room in the smart building during each air supply period within the scheduling cycle. The total electricity cost is the sum of the operating costs for each air supply period determined based on the photovoltaic power generation data and the air conditioning power consumption data. The air conditioning power consumption data is determined according to the air supply plan. This invention utilizes the PMV comfort level, which is related to the room's temperature and humidity ratio, to construct the constraint conditions for solving the objective function, thus ensuring user comfort as much as possible. Furthermore, by using the minimum total electricity cost as the objective function, this invention can fully utilize photovoltaic power generation to reduce electricity costs. Attached Figure Description

[0016] Figure 1This is a flowchart illustrating an optimized control method for an intelligent building HVAC system according to an embodiment of the present invention. Figure 2 This is a graph showing the optimal air supply volume curves for each room in a smart building during the scheduling cycle, obtained from an embodiment of the present invention. Figure 3 This is a dynamic temperature curve of each room in a smart building according to an embodiment of the present invention during a scheduling cycle. Detailed Implementation

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0018] Combination Figure 1 This embodiment provides an optimized control method for an intelligent building HVAC system, the specific steps of which include: Step S1: Obtain solar radiation intensity data and ambient temperature data for the current scheduling cycle. In this embodiment, the duration of the scheduling cycle can be set according to actual needs. For example, the scheduling cycle can be set to one day. The solar radiation intensity data and ambient temperature data for the current scheduling cycle can be determined using typical local data published by the meteorological bureau. In addition, the solar radiation intensity data and ambient temperature data here can also be predicted from historical data.

[0019] Step S2: Input the solar radiation intensity data and ambient temperature data into the pre-built photovoltaic power generation model to obtain photovoltaic power generation data. In this embodiment, the output of the photovoltaic panels in the smart building is comprehensively considered, and the power loss caused by the increase in ambient temperature is quantified to establish a photovoltaic power generation model. The photovoltaic power generation model includes two parts: the photovoltaic power generation calculation formula and the photovoltaic panel surface temperature calculation formula.

[0020] The formula for calculating photovoltaic power generation is: ; in, Photovoltaic power generation capacity, It is a power derating factor used to correct power losses in actual photovoltaic operation, including line losses, inverter losses, etc. This refers to the photovoltaic installed capacity, which is the rated total power of photovoltaic modules; The actual solar radiation intensity is an environmental parameter collected hourly. This represents the solar radiation intensity under standard test conditions, and its value is [value missing]. ; The temperature coefficient represents the rate at which photovoltaic efficiency changes with temperature. The actual surface temperature of the photovoltaic panel needs to be calculated using the following formula; The surface temperature of the photovoltaic panel under standard test conditions.

[0021] The logic of the photovoltaic power generation calculation formula is as follows: First, based on the ratio of actual solar radiation intensity to solar radiation intensity under standard test conditions, and combined with the photovoltaic installed capacity, a basic output is obtained. Then, the influence of the actual surface temperature of the photovoltaic panel deviating from the standard test conditions is corrected by a temperature coefficient to reflect the attenuation effect of temperature on the power generation efficiency of the photovoltaic module. Finally, various additional losses such as line losses and inverter losses in the actual operation of the photovoltaic system are corrected by a power derating factor. Through this calculation formula, actual environmental parameters (solar radiation intensity, ambient temperature) and inherent characteristic parameters of photovoltaic modules (installed capacity, temperature coefficient) can be deeply coupled to accurately obtain the photovoltaic power generation at each moment.

[0022] The formula for calculating the surface temperature of a photovoltaic panel is: ; in, The actual ambient temperature around the photovoltaic panel is , and the environmental parameters are collected hourly. This refers to the surface temperature of the photovoltaic panel under standard operating conditions. This indicates the surface temperature of the photovoltaic panel under standard test conditions; The ambient temperature under standard operating conditions; This indicates the solar radiation intensity under standard operating conditions. The solar radiation absorptivity of a photovoltaic panel characterizes its ability to absorb solar radiation. This refers to the photoelectric conversion efficiency of the photovoltaic panel. The actual surface temperature of the photovoltaic panel can be determined based on ambient temperature data using a formula for calculating the surface temperature of the photovoltaic panel. Substituting this into the formula for calculating photovoltaic power generation yields the photovoltaic power output.

[0023] Step S3: Using the minimum total electricity cost as the objective function and maintaining the PMV comfort level of each room in the smart building within the comfort elasticity range as a constraint, the air supply plan of the HVAC system is solved. This embodiment uses a nonlinear solver to solve the objective function, where the PMV comfort level is determined based on the room's temperature and humidity ratio. This embodiment determines the temperature and humidity ratio of each room by constructing a thermal model and a humidity ratio model.

[0024] The thermal model is divided into two parts: a room wall thermal model and a room thermal model. The room wall thermal model is represented as follows: ; in, Indicates the first The first room The heat capacity of the wall surface is used to characterize the heat storage capacity of the wall. Indicates the first The first room The rate of temperature change of the wall surface; express Time of the first The first room Temperature of the wall Indicates the first The first room A group of adjacent rooms facing the same wall; express Time of the first The temperature of the adjacent rooms; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first The first room The solar radiation receiving coefficient of a wall is 1 if it receives solar radiation, and 0 otherwise. Indicates the first The first room The heat absorption coefficient of the wall surface; Indicates the first The first room Surface area of ​​the wall; Indicates the first The first room The amount of solar radiation received by the wall. The room wall thermal model considers that the heat storage change of the wall is determined by the heat exchange through conduction between adjacent nodes and the heat gain of the wall by solar radiation, thus realizing the quantification of the dynamic changes in wall temperature.

[0025] The room thermal model is represented as follows: ; in, Indicates the first The heat capacity of a room represents its heat storage capacity; express Time of the first Temperature change rate of each room; Indicates the first The collection of walls of each room; express Time of the first The first room Temperature of the wall express Time of the first The temperature of each room; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first The window coefficient of the first room, the first In the case of a room without windows Select 0 otherwise select 1; Indicates the first A collection of windows from each room; express Time of the first The temperature of the window Indicates the first The first room Thermal resistance of the window; Indicates the first The indoor heat source power of each room; express Time of the first Air supply volume for each room; This indicates the specific heat capacity of air; express Time of the first The air supply temperature of each room; Indicates the first The first room The projection rate of each window; Indicates the first The first room The surface area of ​​each window; Indicates the first The first room The amount of solar radiation received by each window. The room thermal model comprehensively depicts the dynamic response of room temperature throughout the day.

[0026] The humidity ratio model in this embodiment fully considers indoor humidity sources and the humidity delivery capacity of the HVAC system; the humidity ratio model is expressed as follows: ; The humidity ratio is defined as the ratio of water vapor mass to dry air mass. This humidity ratio model is a key component of the optimized control in this embodiment. By accurately predicting the room's humidity ratio, the energy efficiency of the HVAC system in handling latent heat load is significantly improved. Where: express Time of the first The humidity ratio of each room; The gas constant representing the partial pressure of dry air; express Time of the first The temperature of each room; Indicates the first The volume of the room; Indicates the partial pressure of dry air; express Time of the first The mass of water vapor generated by the indoor humidity source in each room; express Time of the first Air supply volume for each room; express Time of the first The humidity ratio of the air supplied to each room.

[0027] PMV comfort is a comprehensive indicator that links comfort to multiple factors using a single formula. These factors include indoor temperature, clothing, human activity level, and the partial pressure of water vapor in the air. In this embodiment, to control temperature and humidity to meet user comfort, the temperature and humidity ratio are included in the PMV comfort calculation formula. Among the relevant factors in the original PMV comfort formula, temperature and water vapor partial pressure are the parameters related to temperature and humidity. Therefore, this embodiment first fits the PMV comfort into an expression based on room temperature and water vapor partial pressure: ; in, Indicates PMV comfort level. Indicates temperature. This indicates the partial pressure of water vapor.

[0028] Water vapor partial pressure Compared with humidity The following relationship exists: ; in, Let be the total air pressure. Under normal engineering conditions, the total air pressure changes very little and can be considered a constant. Using humidity ratio The expression for PMV comfort has been adjusted to: ; Thus, PMV comfort is linked to the ratio of room temperature and humidity, and indoor PMV comfort can be ensured by controlling indoor temperature and humidity.

[0029] Furthermore, this embodiment uses the minimum total electricity cost as the objective function. The total electricity cost is the sum of the operating costs for each air supply period, determined based on photovoltaic power generation data and air conditioning power consumption data. The air conditioning power consumption data is determined according to the air supply plan, which includes the air volume and temperature for each room in the smart building during each air supply period within the scheduling cycle. As an example, such as... Figure 2The figure shown is a curve of the optimal air supply volume for each room obtained by solving the problem in a specific embodiment.

[0030] The basic logic of the total electricity cost of a smart building is as follows: when the photovoltaic power generation is less than the power consumption of the HVAC system, the smart building needs to buy electricity from the grid. When the photovoltaic power generation is greater than the power consumption of the HVAC system, the excess electricity can be sold back to the grid. The total electricity cost of the HVAC system can then be obtained by adding the electricity purchase expenditure and electricity sales revenue for all air supply periods within a scheduling cycle.

[0031] Since both the thermal dynamics model and the humidity ratio model are the result of dynamic evolution, as an example, such as Figure 3 The diagram shows the temperature dynamics curves for each room in a specific embodiment. For ease of subsequent calculation, this embodiment assumes that the room temperature and humidity ratio remain constant within this step size (corresponding to one air supply period), and the photovoltaic power generation is also assumed to remain constant within this step size (corresponding to one air supply period), i.e., every step size... The solution calculates the photovoltaic power generation and the temperature and humidity ratio of each room. The result represents the photovoltaic power generation and the temperature and humidity ratio of each room during the air supply period corresponding to this step size.

[0032] The discretized thermal model of the room walls is represented as follows: ; Among them, the discretized room wall thermal model It no longer indicates the time, but rather the number. One air supply period; Indicates the first The first room The heat capacity of the wall surface; and They represent the first The first room The wall in the first The air supply period and the first Temperature during each air supply period Indicates the first The first room A group of adjacent rooms facing the same wall; Indicates the first The adjacent rooms in the Temperature during each air supply period; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first The first room The solar radiation receiving coefficient of a wall is 1 if it receives solar radiation, and 0 otherwise. Indicates the first The first room The heat absorption coefficient of the wall surface; Indicates the first The first room Surface area of ​​the wall; Indicates the first The first room The amount of solar radiation received by the wall.

[0033] The discretized room thermal model is expressed as: ; in, Indicates the first The thermal capacity of the room; and They represent the first The room in The air supply period and the first Temperature during each air supply period; Indicates the first The collection of walls of each room; Indicates the first The first room The wall in the first Temperature during each air supply period Indicates the first The first room Thermal resistance of the wall surface; Indicates the first Window coefficient of each room; Indicates the first A collection of windows from each room; Indicates the first The first room The window in Temperature during each air supply period; Indicates the first The first room Thermal resistance of the window; Indicates the first The indoor heat source power of each room; Indicates the first The room in Air volume for each air supply period; This indicates the specific heat capacity of air; Indicates the first The room in Supply air temperature for each air supply period; Indicates the first The first room The projection rate of each window; Indicates the first The first room The surface area of ​​each window; Indicates the first The first room The amount of solar radiation received by each window.

[0034] Similarly, the humidity ratio model is also discretized, and the expression is: ; in, and They represent the first The room in The air supply period and the first The humidity ratio during each air supply period; The gas constant representing the partial pressure of dry air; Indicates the first The room in Temperature during each air supply period; Indicates the first The volume of the room; Indicates the partial pressure of dry air; Indicates the first The indoor humidity source in the first room The mass of water vapor generated during each air supply period; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in The air supply humidity ratio during each air supply period.

[0035] The total power consumption of the HVAC system during all air supply periods Represented as: ; In the above formula: Indicates the energy efficiency ratio of the HVAC system. This indicates the total number of rooms. This indicates the total number of air supply periods within the scheduling cycle; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in Supply air temperature for each air supply period; Indicates the first The room in Temperature during each air supply period; This indicates the specific heat capacity of air.

[0036] Based on this, to better integrate photovoltaic power and reduce electricity costs, this embodiment classifies the rooms in the smart building according to their functions. Different room categories have different comfort requirements, thus their power consumption also differs. When studios, laboratories, and meeting rooms are unoccupied, the HVAC system can shut down the corresponding fans, reducing the airflow to zero, thereby reducing energy consumption. When studios, laboratories, and meeting rooms are occupied, the HVAC system fans need to be turned on to supply air. However, the comfort elasticity range of PMV (particulate matter volume) differs for each room. This is because when laboratories or meeting rooms are occupied, especially laboratories, the experimental equipment and environment have strict temperature and humidity requirements, so the PMV comfort needs to be limited to a strict comfort elasticity range, resulting in high PMV comfort. When studios are occupied, the PMV constraint is not as strict; only upper and lower limits need to be specified to ensure that the corresponding humidity ratio and temperature do not exceed the limits. Based on this mechanism, this embodiment incorporates a functional coefficient into the constraint conditions. and occupancy factor .

[0037] The constraint that keeps the PMV comfort level of each room in a smart building within the comfort elasticity range is expressed as: ; ; ; ; in, Indicates the first The room in PMV comfort level during each air supply period; Functionality coefficient To accommodate the PMV comfort requirements of different room types, which vary depending on functional zoning, the PMV comfort requirements for each room also differ. The room in When the air supply period is used as a laboratory and conference room A value of 0.8 indicates high requirements for PMV comfort because laboratory equipment must be kept at a stable temperature; otherwise, it will be damaged and its lifespan reduced. When meeting rooms are occupied, the comfort requirements of meeting participants must be strictly enforced; otherwise, meeting efficiency will be affected. The room in When the air supply period is used as a studio You can set it to 0, as long as the PMV comfort level does not exceed the limit; Indicates the first The lower limit benchmark value of PMV comfort for each air supply period. Indicates the first The upper limit benchmark value of PMV comfort for each air supply period; Indicates the first The room in The upper limit of air supply volume for each air supply period.

[0038] In the context of specific scheduling scenarios, the first The room in PMV comfort during each air supply period The expression is: ; in, Indicates the first The room in Temperature during each air supply period Indicates the first The room in The humidity ratio during each air supply period.

[0039] In the expression of the constraint condition The photovoltaic power generation coefficient is expressed using the first... The photovoltaic (PV) power generation during a single air supply period is divided by the maximum PV power generation during all air supply periods within the dispatch cycle. The PV power generation coefficient reflects the idea of ​​adjusting power consumption based on PV output, which is beneficial for PV integration: when... When the photovoltaic power generation is high, i.e., when the photovoltaic power generation during the current air supply period is high, the PMV comfort requirements become more stringent, the fans in the HVAC system will increase the air supply volume, and the power consumption of the HVAC system will increase. When the photovoltaic (PV) power generation is low, i.e., when the PV power generation during the current air supply period is low, the PMV comfort requirements become more relaxed, and the HVAC system's fans will correspondingly reduce the air supply volume, thus reducing the power consumption of the HVAC system. This embodiment effectively improves the PV absorption rate by setting a PV power generation coefficient, while also ensuring that indoor PMV comfort does not fluctuate significantly. The room in When a ventilation period is not occupied, the occupancy factor is... It can be set to a small value close to 0, the first The room in Air volume during each air supply period Very small, even close to 0, which greatly reduces power consumption. The room in When a ventilation period is occupied Take 1.

[0040] Taking a scheduling cycle of one day as an example, with a resolution of half an hour per day, the total electricity cost for 48 steps (corresponding to 48 air supply periods) can be accurately calculated from the power consumption of the air conditioner in each step.

[0041] The calculation logic for operating costs during each air supply period is as follows: When the power generation of the photovoltaic panels is less than the power consumption of the HVAC system, the building needs to buy electricity from the grid. When the photovoltaic power generation is greater than the power consumption of the HVAC system, the excess electricity can be sold back to the grid.

[0042] Economic cost item The expression is: ; in, This indicates the total number of air supply periods within the scheduling cycle; This indicates the total number of rooms. Indicates the duration of the air supply period; This indicates the specific heat capacity of air; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in Supply air temperature during each air supply period Indicates the first The room in Temperature during each air supply period; Indicates the energy efficiency ratio of the HVAC system; Indicates the first Photovoltaic power generation during each air supply period; Indicates the unit price of electricity; This indicates the unit price of electricity.

[0043] This embodiment takes into account room occupancy and adds an air supply volume penalty term to the objective function. The expression is: ; Among them, the The room in When the air supply period is not occupied ,at this time The air volume penalty will take effect in the objective function. It is the penalty coefficient for air supply volume; Indicates the first The room in The air supply volume for each air supply period; when the air supply volume penalty term is in effect, it will make the air supply volume of the unoccupied room in the solution result as close to 0 as possible, thereby reducing electricity costs.

[0044] The expression for the objective function, which minimizes the total electricity cost, is as follows: ; in, This represents the objective function.

[0045] This embodiment also sets an indoor temperature constraint, expressed as follows: ; in, Indicates the first The temperature of each room and These represent the lower and upper limits of the room temperature, respectively. The comfortable temperature for the human body is a range, but the indoor temperature should not be too high or too low. This constraint prevents the temperature from exceeding the limits, preventing extreme conditions from causing the indoor environment to feel too hot or too cold, leading to a decrease in comfort. All rooms have the same upper and lower temperature limits.

[0046] This embodiment also sets an indoor humidity ratio constraint, expressed as: ; in, Indicates the first The humidity ratio of each room, and These represent the lower and upper limits of the room's humidity ratio, respectively. This constraint prevents the room's humidity ratio from being too high or too low, avoiding a decrease in indoor comfort due to excessively humid or dry air. The upper and lower limits of the humidity ratio are the same for all rooms.

[0047] This embodiment also sets a limit on the temperature change between the two optimization cycles, expressed as: ; in, and They represent the first The room in The air supply period and the first Temperature during each air supply period; For the rate of temperature change, This represents the temperature change coefficient. This constraint prevents the temperature difference between two consecutive optimizations from exceeding the limit, as an excessive temperature difference would affect the indoor comfort of the residents.

[0048] This embodiment also sets a limit on the change in the optimized air supply volume between the two optimizations, expressed as follows: ; in, The rate of change of air supply volume. and They represent the first The room in The air supply period and the first The air volume during each air supply period; this constraint can prevent excessive changes in air volume between two consecutive periods. Since the adjustment range of the fan is limited, exceeding the limit may cause damage to the equipment.

[0049] This embodiment also sets a limit on the air supply volume of the fan, expressed as: ; Due to the factory design of the air outlets, the air volume delivered by the fans in the HVAC system is limited and cannot be adjusted without limit. Indicates the first The room in Air volume per air supply period; occupancy factor This represents the occupancy status of rooms. In smart buildings, the daily occupancy is mostly fixed. When a room is not occupied, the occupancy coefficient is... If we set the value to 0, the air volume delivered by the fan approaches 0, and the power consumption of the air conditioner in this room is approximately 0, which can effectively save on electricity costs. Indicates the first The room in The upper limit of air supply volume for each air supply period.

[0050] This embodiment also sets a limit on the total air supply volume of the HVAC system, expressed as: ; in, This indicates the upper limit of the total air supply volume of the HVAC system.

[0051] Analyzing a specific implementation example, this example divides a 24-hour day into 48 time periods. The time-of-use pricing policy adopts the Jiangsu industrial and commercial electricity price, as shown in Table 1. The time-of-use pricing is divided into three periods: peak period, off-peak period, and low-peak period. Peak electricity consumption is generally in summer, and typical summer day data from Jiangsu Province is selected as the standard.

[0052]

[0053] This embodiment performs simulation verification and verifies the effectiveness of the proposed strategy by setting the following two comparative examples: Comparative Example 1: Based on empirical values, the humidity ratio and temperature of the room are set to be controlled at a fixed value; Comparative Example 2: Ignoring room comfort constraints, only considering minimizing electricity costs.

[0054] Since PMV comfort can be positive or negative, and its logic is that the smaller the absolute value of PMV comfort, the more comfortable the indoor environment, in order to measure the comfort of each room throughout the day, we use the sum of the squares of the PMV comfort values ​​of each room at each time period to evaluate comfort, rather than relying on subjective feelings or simply maintaining a set temperature, which is more objective and accurate.

[0055] Through simulation verification, the total electricity cost and PMV comfort square of this embodiment are compared with those of the two comparative cases, as shown in Table 2.

[0056]

[0057] Referring to Table 2, Comparative Example 2 has the lowest total electricity cost because it doesn't consider indoor comfort. The total comfort value for the entire day reaches 3525.05, indicating a poor user comfort experience. Comparative Example 1 has the highest total electricity cost at 150.45, and its PMV comfort value sum of squares is 2029.65, indicating a poorer indoor comfort adjustment effect compared to this embodiment, with users feeling slightly warm or slightly cold. In contrast, this embodiment has a PMV comfort value sum of squares of 1028.05, significantly better than both Comparative Example 1 and Comparative Example 2. This embodiment minimizes total electricity costs while ensuring indoor resident comfort.

[0058] The methods, steps, and data described in this invention are merely specific embodiments of the invention and are illustrative examples. Those skilled in the art can make various modifications or additions to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the inventive concept or exceed the scope defined in this specification, they should all fall within the protection scope of this invention.

Claims

1. A method for optimal control of a smart building HVAC system, the method comprising: include: ​ Obtain solar radiation intensity data and ambient temperature data for the current scheduling cycle; The solar radiation intensity data and ambient temperature data are input into a pre-built photovoltaic power generation model to obtain photovoltaic power generation data; Using the minimum total electricity cost as the objective function and maintaining the PMV comfort level of each room in the smart building within the comfort elasticity range as a constraint, the air supply plan of the HVAC system is solved; whereby... The air supply plan includes the air volume and air temperature of each room in the smart building during each air supply period within the scheduling cycle. The total electricity cost is the sum of the operating costs for each air supply period determined based on photovoltaic power generation data and air conditioning power consumption data; wherein, the air conditioning power consumption data is determined based on the air supply plan; The PMV comfort level is determined based on the room's temperature and humidity ratio; for each room, the comfort flexibility range corresponding to each air supply period is determined based on photovoltaic power generation data, room type, and room occupancy. The constraint that keeps the PMV comfort level of each room in a smart building within the comfort elasticity range is expressed as: ； ； ； ； in, Indicates the first The room in PMV comfort level during each air supply period; Indicates the first The room in Function coefficient for each air supply period; The room in When the air supply period is used as a laboratory or conference room, the function factor is... Take the first coefficient value, the second... The room in When the air supply period is used as a studio, the functional coefficient Take the second coefficient value; the first coefficient value is greater than the second coefficient value; Indicates the first The lower limit benchmark value of PMV comfort for each air supply period. Indicates the first The upper limit benchmark value of PMV comfort for each air supply period; Indicates the first Photovoltaic power generation coefficient during each air supply period; Indicates the first Photovoltaic power generation during each air supply period; This represents the maximum photovoltaic power generation during all air supply periods within the current scheduling cycle; Indicates the first The room in Occupancy factor for each air supply period; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in The upper limit of air supply volume for each air supply period.

2. The intelligent building HVAC system optimization control method according to claim 1, characterized in that, The expression for the photovoltaic power generation model is: ； ； in, Indicates photovoltaic power generation capacity; Indicates the power derating factor; Indicates photovoltaic installed capacity; This represents the actual solar radiation intensity; This indicates the intensity of solar radiation under standard test conditions; Indicates the temperature coefficient; This indicates the actual surface temperature of the photovoltaic panel; This indicates the surface temperature of the photovoltaic panel under standard test conditions; This indicates the actual ambient temperature around the photovoltaic panel; This indicates the surface temperature of the photovoltaic panel under standard operating conditions. Indicates the ambient temperature under standard operating conditions; This indicates the solar radiation intensity under standard operating conditions. This indicates the solar radiation absorption rate of the photovoltaic panel; This indicates the photoelectric conversion efficiency of the photovoltaic panel.

3. The intelligent building HVAC system optimization control method according to claim 1, characterized in that, The expression for the objective function, which minimizes the total electricity cost, is as follows: ； ； ； in, Represent the objective function; Indicates the economic cost item; This indicates a penalty for insufficient air supply. Indicates the total number of air supply periods; Indicates the total number of rooms; Indicates the duration of the air supply period; This indicates the specific heat capacity of air; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in Supply air temperature for each air supply period; Indicates the first The room in Temperature during each air supply period; Indicates the energy efficiency ratio of the HVAC system; Indicates the first Photovoltaic power generation during each air supply period; Indicates the unit price of electricity; Indicates the unit price of electricity; Indicates the first The room in Occupancy factor for each air supply period; The penalty coefficient represents the air supply volume.

4. The intelligent building HVAC system optimization control method according to claim 1, characterized in that, No. The room in PMV comfort during each air supply period The expression is: ； in, Indicates the first The room in Temperature during each air supply period Indicates the first The room in The humidity ratio during each air supply period.

5. The intelligent building HVAC system optimization control method according to claim 3, characterized in that, Occupancy factor The ways to obtain the value include: No. The room in When a ventilation period is occupied Take the third coefficient value; No. The room in When the air supply period is not occupied Take the fourth coefficient value; The third coefficient value is greater than the fourth coefficient value.

6. The intelligent building HVAC system optimization control method according to claim 1, characterized in that, The room temperature is determined based on a pre-built room thermal model, the expression of which is: ； in, Indicates the first The thermal capacity of the room; and They represent the first The room in The air supply period and the first Temperature during each air supply period; Indicates the first The collection of walls of each room; Indicates the first The first room The wall in the first Temperature during each air supply period; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first Window coefficient of each room; Indicates the first A collection of windows from each room; Indicates the first The first room The window in Temperature during each air supply period Indicates the first The first room Thermal resistance of the window; Indicates the first The indoor heat source power of each room; Indicates the first The room in Air volume for each air supply period; This indicates the specific heat capacity of air; Indicates the first The room in Supply air temperature for each air supply period; Indicates the first The first room The projection rate of each window; Indicates the first The first room The surface area of ​​each window; Indicates the first The first room The amount of solar radiation received by each window; Indicates the duration of the air supply period.

7. The intelligent building HVAC system optimization control method according to claim 6, characterized in that, The temperature of the room's interior walls is determined based on a pre-constructed thermal model of the room walls, the expression of which is: ； in, Indicates the first The first room The heat capacity of the wall surface; and They represent the first The first room The wall in the first The air supply period and the first Temperature during each air supply period Indicates the first The first room A group of adjacent rooms facing the same wall; Indicates the first The adjacent rooms in the Temperature during each air supply period; Indicates the first The first room Thermal resistance of the wall surface; Indicates the first The first room Solar radiation receiving coefficient of the wall surface; Indicates the first The first room The heat absorption coefficient of the wall surface; Indicates the first The first room Surface area of ​​the wall; Indicates the first The first room The amount of solar radiation received by the wall; Indicates the duration of the air supply period.

8. The intelligent building HVAC system optimization control method according to claim 1, characterized in that, The room's humidity ratio is determined based on a room humidity ratio model, the expression of which is: ； in, and They represent the first The room in The air supply period and the first The humidity ratio during each air supply period; The gas constant representing the partial pressure of dry air; Indicates the first The room in Temperature during each air supply period; Indicates the first The volume of the room; Indicates the partial pressure of dry air; Indicates the first The indoor humidity source in the first room The mass of water vapor generated during each air supply period; Indicates the first The room in Air volume for each air supply period; Indicates the first The room in The humidity ratio of the supply air during each air supply period; Indicates the duration of the air supply period.

9. An intelligent building HVAC system optimization control device, characterized in that, For executing the intelligent building HVAC system optimization control method according to any one of claims 1-8, the control device comprises: The acquisition module is used to acquire solar radiation intensity data and ambient temperature data for the current scheduling cycle; The power generation calculation module is used to input the solar radiation intensity data and ambient temperature data into a pre-built photovoltaic power generation model to obtain photovoltaic power generation data; The solution module is used to solve the air supply plan of the HVAC system with the objective function of minimizing total electricity cost and the constraint that the PMV comfort of each room in the smart building is kept within the comfort elasticity range. The air supply plan includes the air volume and temperature of each room in the smart building during each air supply period within the scheduling cycle. The total electricity cost is the sum of the operating costs for each air supply period, determined based on photovoltaic power generation data and air conditioning power consumption data. The air conditioning power consumption data is determined according to the air supply plan. The PMV comfort is determined based on the room's temperature and humidity ratio. For each room, the comfort elasticity range corresponding to each air supply period is determined based on photovoltaic power generation data, room type, and room occupancy.

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