A building cell energy consumption analysis method considering micro-meteorology

Abstract

The present invention discloses a method for analyzing the energy consumption of building cells considering micro-meteorology. By modeling and studying building cells that comprehensively consider distributed photovoltaics, air conditioners, and electric vehicles, the influence of micro-meteorology on the source-load resource models in building cells is analyzed, and the calculation of the energy consumption of building cells and their ability to participate in demand response is realized. The method proposed by the present invention can calculate the electric energy consumption of building cells affected by micro-meteorology, aiming to reveal how micro-meteorological conditions affect the energy consumption behavior and response potential of building cells, provide a scientific basis for urban planners and building designers, promote the in-depth understanding of building energy consumption under urban micro-meteorological conditions, and provide a new perspective and method for realizing the sustainable utilization of building energy.

Description

Technical Field

[0001] The present invention belongs to the technical field of building energy consumption analysis, and specifically relates to a method for analyzing the energy consumption of building cells considering micro-meteorology. Background Art

[0002] Under the background of the accelerating urbanization process and climate change, buildings, as an important part of urban infrastructure, their energy consumption issues have increasingly become a key challenge for environmental sustainable development. Currently, the research on building energy consumption analysis does not fully consider the impact of micro-meteorology on the comprehensive energy consumption of each power generation or power consumption unit in the building, resulting in poor accuracy of energy consumption calculation for building cells, and the feasibility of proposing improvement measures for buildings based on the results of building cell energy consumption analysis is not high. The purpose of the present invention is to analyze the concept of micro-meteorology and its key factors, further explore the mechanism of how micro-meteorological conditions affect building energy consumption and demand response potential, and deeply study the quantitative impact of micro-climate conditions on building energy consumption, which can provide a scientific basis for urban planning and building design, provide a new perspective and method for accurately calculating building energy consumption and reducing building energy consumption, and is of great significance for realizing the sustainable development of cities. Summary of the Invention

[0003] To solve the above problems, the present invention discloses a method for analyzing the energy consumption of building cells considering micro-meteorology, which can formulate a more climate-adaptive building design scheme, effectively reduce energy consumption and improve the overall sustainability of the city.

[0004] The method for analyzing the energy consumption of building cells considering micro-meteorology includes the following steps:

[0005] Step 1, establish a distributed photovoltaic model of building cells affected by micro-meteorology, including:

[0006] Step 1.1, obtain distributed photovoltaic monitoring data;

[0007] Step 1.2, construct a distributed photovoltaic output model;

[0008] Step 1.3, construct a distributed photovoltaic model of building cells affected by micro-meteorology;

[0009] Step 2, establish an air-conditioning model of building cells affected by micro-meteorology, including:

[0010] Step 2.1, obtain air-conditioning electricity consumption monitoring data;

[0011] Step 2.2, construct an air-conditioning power model;

[0012] Step 2.3, construct an air-conditioning model of building cells affected by micro-meteorology;

[0013] Step 3, establish an electric vehicle model of building cells affected by micro-meteorology, including:

[0014] Step 3.1, obtain the charging pile monitoring data;

[0015] Step 3.2, construct the electric vehicle charging and discharging model;

[0016] Step 3.3, construct the building cell electric vehicle model affected by micro-meteorology;

[0017] Step 4, establish the building cell energy consumption analysis model affected by micro-meteorology;

[0018] Step 5, establish the building cell power demand response potential analysis model affected by micro-meteorology.

[0019] Further, in the step 1.1, obtaining the distributed photovoltaic monitoring data includes U a (t) and T a (t), where U a (t) represents the solar irradiance at time t, and T a (t) represents the external temperature at time t;

[0020] Further, in the step 1.2, construct the distributed photovoltaic output model, which mainly considers the influence of solar irradiance and external temperature on photovoltaic output. The specific calculation formula is as follows:

[0021]

[0022] Among them, P PV (t) represents the output power of traditional photovoltaic power generation at time t, with the unit of kW; U PV-STC is the solar irradiance index under standard conditions of photovoltaic power generation, and the unit is W / m 2 ; P PV-N is the rated output power of this photovoltaic, with the unit of kW; α PV-T represents the coefficient of the photovoltaic panel affected by temperature, generally taking -0.4%; T PV-STC represents the external temperature under standard conditions of photovoltaic power generation, and the unit is °C.

[0023] Further, in the step 1.3, construct the building cell distributed photovoltaic model affected by micro-meteorology. This model is a complex model that needs to consider multi-dimensional meteorological factors. When considering the influence of micro-meteorology on photovoltaic power generation, it analyzes the influence of five micro-meteorological factors, namely temperature, humidity, irradiance, wind speed, and dust accumulation degree, on the photovoltaic output model and the key parameter correction method. The specific calculation formula is as follows:

[0024]

[0025] Among them, Represents the output power of the photovoltaic panel at time t after being corrected according to micro-meteorological factors, with the unit of kW; Represents the coefficient comprehensively corrected by the actual solar irradiance and the solar irradiance under standard conditions at time t; Represents the coefficient comprehensively corrected by the actual temperature and the temperature influence under standard conditions at time t; Represents the rated output of the photovoltaic after being corrected considering the influence of dust accumulation at time t, with the unit of kW; The specific calculation method affected by micro-meteorology is as follows:

[0026]

[0027] Among them, ω PV-U Is the micro-meteorological correction coefficient of solar irradiance; Is the solar irradiance index under the corrected standard conditions; ω PV-T Is the micro-meteorological correction coefficient of temperature; Is the outside temperature index under the corrected standard conditions; D a (t) is the actual dust accumulation degree at time t, Is the dust accumulation degree under the standard conditions corrected by micro-meteorology, and the units are all g / m 2 ;

[0028] Furthermore, in the step 2.1, obtain the air-conditioning power consumption monitoring data, including T a-in (t - 1) and T a-in (t), where T a-in (t - 1) is the measured outside temperature at time t - 1, and T a-in (t) is the measured indoor temperature where the air conditioner is located, and the units are all °C.

[0029] Furthermore, in the step 2.2, construct an air-conditioning power model, which considers the influence of the outside temperature on the air-conditioning output, and for the influence of environmental factors on human energy consumption behavior, the specific calculation formula is as follows:

[0030]

[0031] Among them, L HVAC (t) represents the quantization coefficient of the traditional air-conditioning energy consumption behavior affected by temperature; β HVAC-L Represents the temperature influence index under HVAC standard conditions; T HVAC-STC Is the average temperature under HVAC standard conditions, with the unit of °C. Map the quantization coefficient to the power prediction model of the air conditioner, and the formula is as follows:

[0032]

[0033] Among them, P HVAC(t) represents the predicted power of the air conditioner at time t, with the unit of kW; α HVAC-P represents the heat transfer coefficient of the air conditioner output power and heat, with the unit of ℃ / kW.

[0034] Furthermore, in step 2.3, a building cell air conditioner model affected by micro-meteorology is constructed. This model is a complex model that needs to consider multi-dimensional meteorological factors. When considering the influence of micro-meteorology on the air conditioner output power, the influence of three micro-meteorological factors, namely temperature, humidity, and atmospheric pressure, on the air conditioner output power model and the key parameter correction method are analyzed. The specific calculation formula is as follows:

[0035]

[0036] Among them, represents the output power of the air conditioner at time t after being corrected according to micro-meteorological factors, with the unit of kW; represents the coefficient comprehensively corrected for the energy efficiency heat transfer coefficient of the air conditioner affected by micro-meteorology at time t; represents the coefficient corrected for the indoor and outdoor temperature difference considering the influence of micro-meteorology at time t; The specific calculation method affected by micro-meteorology is as follows:

[0037]

[0038] Among them, ω HVAC-U (t) is the micro-meteorological correction coefficient for the energy efficiency of the air conditioner; is the quantization coefficient of the energy consumption behavior of the air conditioner affected by temperature after micro-meteorological correction; ω HVAC-L (t) is the micro-meteorological correction coefficient of the energy consumption behavior of the air conditioner affected by temperature.

[0039] Furthermore, in step 3.1, the charging pile monitoring data is obtained, including SOC EV (t) and SOC EV (0), where SOC EV (t) and SOC EV (0) respectively represent the electric vehicle battery capacity monitored by the charging pile at time t and the starting moment of the end of charging.

[0040] Furthermore, in step 3.2, a distributed photovoltaic output model is constructed. This model mainly considers the influence of solar irradiance and external temperature on the photovoltaic output. The specific calculation formula is as follows:

[0041]

[0042] Among them, α EV represents the power consumption per kilometer of the electric vehicle, with the unit of kWh / km; J EV,iis the mileage traveled by the electric vehicle during the i-th section, with the unit of km; Q EV-SOH represents the basic capacity of the power battery in the electric vehicle; n EV (t) is the number of trips traveled by the electric vehicle from the end of charging to the moment t; P EV (t) is the predicted result of the charging power of the electric vehicle, with the unit of kW; P EV-STC represents the standard power of the charging power of the electric vehicle in the traditional model, with the unit of kW; f EV (x EV ) is the charging probability distribution function of the electric vehicle, including Gaussian distribution and Poisson distribution probability models.

[0043] Furthermore, in step 3.3, a building cell electric vehicle model affected by micro-meteorology is constructed. This model is a complex model that needs to consider multi-dimensional meteorological factors. When considering the impact of micro-meteorology on the charging power of electric vehicles, the impact of micro-meteorological factors such as temperature and rainfall on the electric vehicle model and the key parameter correction methods are analyzed. The specific calculation formula is as follows:

[0044]

[0045] Among them, is the battery capacity of the electric vehicle at time t after being corrected by micro-meteorology; ω EV-α is the micro-meteorology correction coefficient of the power consumption per kilometer of the electric vehicle; is the power battery capacity in the electric vehicle after being affected and corrected by micro-meteorology; is the predicted result of the charging power of the electric vehicle at time t after being corrected by micro-meteorology, with the unit of kW; ω EV-P represents the micro-meteorology correction coefficient of the charging power of the electric vehicle.

[0046] Furthermore, in step 4, when calculating the energy consumption of the building cell, it is necessary to comprehensively consider the photovoltaic power generation, air conditioning, and electric vehicle charging power models affected by micro-meteorology. This model will consider factors such as the physical characteristics of the building, usage conditions, external climate conditions, and the efficiency of the energy system. The specific calculation formula is as follows:

[0047]

[0048] Among them, represents the power value of the energy consumption analysis of the building cell affected by urban micro-meteorology, with the unit of kW.

[0049] Further, in step 5, the demand response potential of the building cell refers to the response of the building to the power grid by changing its original electricity consumption behavior. The demand response potential refers to the ability of the building cell to participate in the load regulation of the power demand response, including two aspects: increasing the load and reducing the load. Considering the time characteristics of the demand response, the specific calculation formula is as follows:

[0050]

[0051] Wherein, is the calculation result of the demand response potential of the building cell at time t affected by the urban micro-meteorology, and the unit is kWh.

[0052] Advantages of the present invention:

[0053] By modeling the energy consumption of the building cell considering micro-meteorology, the present invention studies the influencing factors and influencing paths of micro-meteorology on the energy consumption of the building cell. By specifically constructing the correction models of photovoltaic, air-conditioning and electric vehicles in the building cell affected by micro-meteorology, an energy consumption analysis model of the building cell affected by micro-meteorology is constructed, realizing the accurate quantitative calculation of the energy consumption of the building cell. Based on the energy consumption calculation results, valuable data and suggestions can be provided for urban planners and building designers, so as to formulate a building design plan with higher climate adaptability, effectively reduce energy consumption and improve the overall sustainability of the city. Description of the drawings

[0054] Figure 1 is the flowchart of the energy consumption analysis method of the building cell considering micro-meteorology;

[0055] Figure 2 is the photovoltaic output curve of the building cell affected by micro-meteorology;

[0056] Figure 3 is the air-conditioning electricity consumption curve of the building cell affected by micro-meteorology;

[0057] Figure 4 is the charge and discharge curve of the electric vehicle of the building cell affected by micro-meteorology;

[0058] Figure 5 is the energy consumption and demand response potential diagram of the building cell affected by micro-meteorology. Detailed implementation manners

[0059] The present invention will be further clarified below in conjunction with the drawings and specific implementation manners. It should be understood that the following specific implementation manners are only used to illustrate the present invention and not to limit the scope of the present invention. It should be noted that the terms "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to the directions in the drawings, and the terms "inner" and "outer" respectively refer to the directions towards or away from the geometric center of a specific component.

[0060] As Figure 1 shown, the method for analyzing the energy consumption of building cells considering micro-meteorology in this embodiment includes the following steps:

[0061] Step 1: Establish a distributed photovoltaic model for building cells affected by micro-meteorology, including:

[0062] Step 1.1: Obtain distributed photovoltaic monitoring data;

[0063] In the above Step 1.1, obtaining the distributed photovoltaic monitoring data includes U a (t) and T a (t), where U a (t) represents the solar irradiance at time t, and T a (t) represents the external temperature at time t;

[0064] In the above Step 1.2, construct a distributed photovoltaic output model, and the specific calculation formula is as follows:

[0065]

[0066] Among them, P PV (t) represents the output power of traditional photovoltaic power generation at time t, with the unit of kW; U PV-STC is the solar irradiance index under standard conditions for photovoltaic power generation, and the unit is W / m 2 ; P PV-N is the rated output power of this photovoltaic, with the unit of kW; α PV-T represents the coefficient of the photovoltaic panel affected by temperature, generally taking -0.4%; T PV-STC represents the external temperature under standard conditions for photovoltaic power generation, and the unit is °C.

[0067] Step 1.2: Construct a distributed photovoltaic output model;

[0068] Step 1.3: Construct a distributed photovoltaic model for building cells affected by micro-meteorology; in the above Step 1.3, when constructing a distributed photovoltaic model for building cells affected by micro-meteorology, the influence of five micro-meteorological factors, namely temperature, humidity, irradiance, wind speed, and dust accumulation degree, on the photovoltaic output model and the key parameter correction method are analyzed, and the specific calculation formula is as follows:

[0069]

[0070] Among them, represents the output power of the photovoltaic panel corrected according to micro-meteorological factors at time t, with the unit of kW; represents the coefficient comprehensively corrected by the actual solar irradiance and the solar irradiance under standard conditions at time t; It represents the coefficient after comprehensive correction of the actual temperature at time t and the temperature influence under standard conditions; It represents the corrected rated photovoltaic output considering the influence of ash accumulation at time t, with the unit of kW; The specific calculation method affected by micro-meteorology is as follows:

[0071]

[0072] Among them, ω PV-U is the micro-meteorology correction coefficient of solar irradiance; is the solar irradiance index under the corrected standard conditions; ω PV-T is the micro-meteorology correction coefficient of temperature; is the outside temperature index under the corrected standard conditions; D a (t) is the actual ash accumulation degree at time t, is the ash accumulation degree under the standard conditions corrected by micro-meteorology, and the unit is g / m 2 .

[0073] Step 2, establish a building cell air-conditioning model affected by micro-meteorology, including:

[0074] Step 2.1, obtain air-conditioning power consumption monitoring data;

[0075] In the said Step 2.1, obtaining air-conditioning power consumption monitoring data includes T a-in (t - 1) and T a-in (t), where T a-in (t - 1) is the measured outside temperature at time t - 1, and T a-in (t) is the measured indoor temperature where the air-conditioner is located, and the unit is °C;

[0076] Step 2.2, construct an air-conditioning power model;

[0077] In the said Step 2.2, constructing an air-conditioning power model, this model considers the influence of the outside temperature on the air-conditioning output, and for the influence of environmental factors on human energy consumption behavior, the specific calculation formula is as follows:

[0078]

[0079] Among them, L HVAC (t) represents the quantization coefficient of the traditional air-conditioning energy consumption behavior affected by temperature; β HVAC-L represents the temperature influence index under HVAC standard conditions; T HVAC-STC is the average temperature under HVAC standard conditions, with the unit of °C; Map the quantization coefficient to the air-conditioning power prediction model, and the formula is as follows:

[0080]

[0081] Among them, P HVAC (t) represents the predicted power of the air conditioner at time t, with the unit of kW; α HVAC-P represents the heat transfer coefficient of the air conditioner output power and heat, with the unit of ℃ / kW.

[0082] Step 2.3, construct a building cell air conditioner model affected by micro-meteorology;

[0083] In the said Step 2.3, when constructing a building cell air conditioner model affected by micro-meteorology, which is a complex model that needs to consider multi-dimensional meteorological factors, when considering the influence of micro-meteorology on the air conditioner output power, the influence of three micro-meteorological factors, namely temperature, humidity and atmospheric pressure, on the air conditioner output power model and the key parameter correction method are analyzed. The specific calculation formula is as follows:

[0084]

[0085] Among them, represents the output power of the air conditioner at time t after being corrected according to micro-meteorological factors, with the unit of kW; represents the coefficient comprehensively corrected for the energy efficiency heat transfer coefficient of the air conditioner affected by micro-meteorology at time t; represents the coefficient corrected for the indoor and outdoor temperature difference considering the influence of micro-meteorology at time t; The specific calculation method affected by micro-meteorology is as follows:

[0086]

[0087] Among them, ω HVAC-U (t) is the micro-meteorological correction coefficient for the energy efficiency of the air conditioner; is the quantization coefficient of the energy consumption behavior of the air conditioner affected by temperature after micro-meteorological correction; ω HVAC-L (t) is the micro-meteorological correction coefficient of the energy consumption behavior of the air conditioner affected by temperature.

[0088] Step 3, establish a building cell electric vehicle model affected by micro-meteorology, including:

[0089] Step 3.1, obtain the charging pile monitoring data;

[0090] In the said Step 3.1, when obtaining the charging pile monitoring data, it includes SOC EV (t) and SOC EV (0), where SOC EV (t) and SOC EV (0) respectively represent the electric vehicle battery capacity monitored by the charging pile at time t and at the start time of the end of charging.

[0091] Step 3.2, construct an electric vehicle charging and discharging model;

[0092] In step 3.2, a distributed photovoltaic output model is constructed. This model mainly considers the impacts of solar irradiance and ambient temperature on photovoltaic output. The specific calculation formula is as follows:

[0093]

[0094] Among them, α EV represents the power consumption per kilometer of the electric vehicle, with the unit of kWh / km; J EV,i is the mileage traveled by the electric vehicle during the i-th section of the journey, with the unit of km; Q EV-SOH represents the basic capacity of the power battery in the electric vehicle; n EV (t) is the number of trips made by the electric vehicle from the end of charging to time t; P EV (t) is the predicted result of the charging power of the electric vehicle, with the unit of kW; P EV-STC represents the standard power of the charging power of the electric vehicle in the traditional model, with the unit of kW; f EV (x EV ) is the charging probability distribution function of the electric vehicle, including Gaussian distribution and Poisson distribution probability models.

[0095] Step 3.3: Construct a building cell electric vehicle model affected by micro-meteorology;

[0096] In step 3.3, a building cell electric vehicle model affected by micro-meteorology is constructed. This model is a complex model that needs to consider multi-dimensional meteorological factors. When considering the impact of micro-meteorology on the charging power of electric vehicles, the impacts of micro-meteorological factors such as temperature and rainfall on the electric vehicle model and the key parameter correction methods are analyzed. The specific calculation formula is as follows:

[0097]

[0098] Among them, is the battery capacity of the electric vehicle at time t after being corrected by micro-meteorology; ω EV-α is the micro-meteorology correction coefficient of the power consumption per kilometer of the electric vehicle; is the power battery capacity in the electric vehicle after being corrected by the impact of micro-meteorology; is the predicted result of the charging power of the electric vehicle at time t after being corrected by micro-meteorology, with the unit of kW; ω EV-P represents the micro-meteorology correction coefficient of the charging power of the electric vehicle.

[0099] Step 4: Establish a building cell energy consumption analysis model affected by micro-meteorology;

[0100] In Step 4, to calculate the energy consumption of building cells, it is necessary to comprehensively consider the photovoltaic power generation, air conditioning, and electric vehicle charging power models affected by micro-meteorology. This model will consider factors such as the physical characteristics of the building, usage conditions, external climate conditions, and the efficiency of the energy system. The specific calculation formula is as follows:

[0101]

[0102] Among them, represents the power value of the building cell energy consumption analysis affected by urban micro-meteorology, and the unit is kW.

[0103] Step 5, establish an analysis model for the potential of building cell power demand response affected by micro-meteorology.

[0104] In Step 5, the demand response potential of building cells refers to the response of the building to the power grid by changing its original electricity consumption behavior. The demand response potential refers to the ability of building cells to participate in the load regulation of power demand response, including two aspects: increasing load and reducing load; considering the time characteristics of demand response, the specific calculation formula is as follows:

[0105]

[0106] Among them, is the calculation result of the demand response potential of the building cell at time t affected by urban micro-meteorology, and the unit is kWh.

[0107] As shown in Figure 2 , they are the photovoltaic output power curves and the cumulative photovoltaic power generation curves of building cells under 4 different micro-meteorological influence scenarios. It can be seen that the photovoltaic output power and cumulative power generation in Scenario 1 are the smallest, while those in Scenario 3 are the largest, which is determined by the different micro-meteorological influence factors of irradiance, temperature, and dust accumulation degree.

[0108] As shown in Figure 3 , they are the air conditioning power consumption curves and the external temperature curves of building cells under 3 different micro-meteorological influence scenarios. It can be seen that the air conditioning power consumption in Scenario 1 is the largest and the external temperature is the highest, while the air conditioning power consumption in Scenario 3 is the smallest and the external temperature is the lowest.

[0109] As shown in Figure 4As shown, it is the curves of the charging and discharging amounts of electric vehicles in building cells at different times under the influence of three different micro-meteorological conditions. It can be seen that the charging of electric vehicles in Scenario 1 mainly concentrates between 19:00 and 22:00 at night and the charging and discharging amounts are relatively large. The charging of electric vehicles in Scenario 2 mainly concentrates between 17:00 and 19:00 at night and the charging and discharging amounts are relatively small. The charging of electric vehicles in Scenario 3 mainly concentrates between 19:00 and 22:00 at night and the charging and discharging amounts are also relatively small, which is determined by the different influencing factors of the two micro-meteorological conditions of temperature and rainfall.

[0110] As Figure 5 shown, it is the curves of the energy consumption and demand response potential of building cells under the influence of three different micro-meteorological conditions, comprehensively considering the influence of micro-meteorology on distributed photovoltaics, air conditioners and electric vehicles in building cells, and reflecting that the influence range of different micro-meteorological conditions on the demand response potential of building cells is between 12 - 28 kW.

[0111] The technical means disclosed in the solution of the present invention are not limited to the technical means disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features.

Claims

1. A building cell energy consumption analysis method considering microclimate, characterized by: The steps include: Step 1: Establish a building cellular distributed photovoltaic model affected by micro-meteorology, including: Step 1.1, obtaining distributed photovoltaic monitoring data; in step 1.1, obtaining distributed photovoltaic monitoring data includes U a (t) and T a (t), where U a (t) represents the solar irradiance at time t, T a (t) represents the outside temperature at time t; Step 1.2, constructing a distributed photovoltaic output model; In step 1.2, constructing a distributed photovoltaic output model, the specific calculation formula is as follows: Among them, P PV (t) represents the output power of traditional photovoltaic power generation at time t, in kW; U PV-STC It is the solar irradiance index under standard conditions for photovoltaic power generation, and the unit is W / m 2 ;P PV-N is the rated output power of the photovoltaic system, in kW; α PV-T The coefficient that indicates the effect of temperature on the photovoltaic panel is -0.4%; T PV-STC Indicates the outside temperature under standard conditions of photovoltaic power generation, the unit is ℃; Step 1.3, constructing a building cellular distributed photovoltaic model under the influence of micrometeorology; In step 1.3, a building cellular distributed photovoltaic model under the influence of micrometeorology is constructed, and the influence of five micrometeorological factors, namely temperature, humidity, irradiance, wind speed and dust accumulation degree, on the photovoltaic output model and the key parameter correction method are analyzed. The specific calculation formula is as follows: in, It represents the output power of the photovoltaic panel at time t after correction according to micro-meteorological factors, in kW; It represents the coefficient after comprehensive correction of the actual solar irradiance at time t and the solar irradiance under standard conditions; It represents the coefficient after comprehensive correction of the actual temperature and the temperature effect under standard conditions at time t; It represents the PV rated output corrected after considering the influence of dust accumulation at time t, in kW. The specific calculation method affected by micro-meteorology is as follows: Among them, ω PV-U is the solar radiation micrometeorological correction coefficient; is the solar irradiance index under the corrected standard conditions; ω PV-T is the temperature micrometeorological correction coefficient; It is the external temperature index under the corrected standard conditions; D a (t) is the actual dust accumulation degree at time t, It is the dust accumulation degree under standard conditions after micro-meteorological correction, and the unit is g / m 2 ; Step 2: Establish a building cellular air conditioning model affected by micro-meteorology; including: Step 2.1, obtaining air conditioning power consumption monitoring data; Step 2.2, constructing an air conditioning power model; Step 2.3, construct a building cellular air conditioning model under the influence of micro-meteorology; Step 3: Establish a building cellular electric vehicle model affected by micrometeorology, including: Step 3.1, obtain charging pile monitoring data; Step 3.2, constructing an electric vehicle charging and discharging model; Step 3.3, construct a building cellular electric vehicle model under the influence of micrometeorology; Step 4, establish a building cell energy consumption analysis model affected by micro-meteorology; Step 5: Establish a building cell electricity demand response potential analysis model affected by micrometeorology.

2. The building cell energy consumption analysis method considering microclimate according to claim 1 is characterized by: Step 2.1, obtain air conditioning power consumption monitoring data; obtain air conditioning power consumption monitoring data, including T a-in (t-1) and T a-in (t), where T a-in (t-1) is the measured external temperature at time t-1, T a-in (t) is the measured temperature in the room where the air conditioner is located, in °C; Step 2.2, constructing an air conditioning power model; in step 2.2, constructing an air conditioning power model, the model takes into account the impact of the outside temperature on the air conditioning output, and the impact of environmental factors on human energy consumption behavior, the specific calculation formula is as follows: Among them, L HVAC (t) represents the quantitative coefficient of the influence of temperature on the energy consumption behavior of traditional air conditioners; β HVAC-L Indicates the temperature impact index under HVAC standard conditions; T HVAC-STC is the average temperature under HVAC standard conditions, in °C; the quantization coefficient is mapped to the power prediction model of the air conditioner, and the formula is as follows: Among them, P HVAC (t) represents the predicted air conditioning power at time t, in kW; α HVAC-P It indicates the heat transfer coefficient between the air conditioner output power and heat, in units of ℃ / kW.

3. The building cell energy consumption analysis method considering micro-meteorology according to claim 2 is characterized by: In step 2.3, a building cellular air conditioning model under the influence of micrometeorology is constructed. This model is a complex model that needs to consider multi-dimensional meteorological factors. When considering the influence of micrometeorology on the air conditioning output power, the influence of three micrometeorological factors, temperature, humidity and atmospheric pressure, on the air conditioning output power model and the key parameter correction method are analyzed. The specific calculation formula is as follows: in, It represents the output power of the air conditioner at time t after correction based on micro-meteorological factors, in kW; It represents the coefficient of comprehensive correction of the air conditioning energy efficiency heat exchange coefficient under the influence of micro-meteorology at time t; It represents the coefficient of the indoor and outdoor temperature difference corrected by micro-meteorological factors at time t. The specific calculation method affected by micro-meteorological factors is as follows: Among them, ω HVAC-U (t) is the air conditioning energy efficiency heat exchange micro-meteorological correction coefficient; is the quantitative coefficient of the influence of temperature on the air conditioning energy consumption behavior after micro-meteorological correction; ω HVAC-L (t) is the micro-meteorological correction coefficient for the air conditioning energy consumption behavior affected by temperature.

4. The building cell energy consumption analysis method considering micro-meteorology according to claim 3 is characterized by: In step 3.1, the charging pile monitoring data is obtained, including SOC EV (t) and SOC EV (0), where SOC EV (t) and SOC EV (0) respectively represent the battery capacity of the electric vehicle monitored by the charging pile at time t and the start time of charging completion.

5. The building cell energy consumption analysis method considering micro-meteorology according to claim 4 is characterized by: In step 3.2, a distributed photovoltaic output model is constructed, which takes into account the impact of solar irradiance and external temperature on photovoltaic output. The specific calculation formula is as follows: Among them, α EV Indicates the power consumption of electric vehicles per kilometer, in kWh / km; J EV,i is the mileage of the electric vehicle in the i-th segment, in km; Q EV-SOH Indicates the basic capacity of the power battery in electric vehicles; n EV (t) is the number of trips that the electric vehicle travels from the time the electric vehicle is charged to time t; P EV (t) is the prediction result of electric vehicle charging power, in kW; P EV-STC represents the standard power of electric vehicle charging power in the traditional model, in kW; f EV (x EV ) is the probability distribution function of electric vehicle charging, including Gaussian distribution and Poisson distribution probability modes.

6. The building cell energy consumption analysis method considering micro-meteorology according to claim 5 is characterized by: In step 3.3, a building cellular electric vehicle model under the influence of micrometeorology is constructed. This model is a complex model that needs to consider multi-dimensional meteorological factors. When considering the impact of micrometeorology on the charging power of electric vehicles, the impact of temperature and rainfall on the electric vehicle model and the key parameter correction method are analyzed. The specific calculation formula is as follows: in, is the battery capacity of the electric vehicle at time t after micro-meteorological correction; ω EV-α The micro-meteorological correction coefficient for the power consumption of electric vehicles per kilometer traveled; The power battery capacity of electric vehicles corrected for the influence of micro-meteorology; is the prediction result of the electric vehicle charging power at time t after micro-meteorological correction, in kW; ω EV-P Represents the micro-meteorological correction factor for electric vehicle charging power.

7. The building cell energy consumption analysis method considering micro-meteorology according to claim 6 is characterized by: In step 4, the energy consumption of building cells is calculated by comprehensively considering the photovoltaic power generation, air conditioning and electric vehicle charging power models affected by micro-meteorology. The model will consider the physical characteristics, usage, external climate conditions and efficiency of the energy system of the building. The specific calculation formula is as follows: in, It represents the power value of building cell energy consumption analysis under the influence of urban microclimate, in kW.

8. The building cell energy consumption analysis method considering microclimate according to claim 7 is characterized by: In step 5, the demand response potential of the building cell refers to the response of the building to the power grid by changing the original electricity consumption behavior. The demand response potential refers to the ability of the building cell to participate in load regulation of power demand response, including increasing and reducing loads. Considering the time characteristics of demand response, the specific calculation formula is as follows: in, It is the calculation result of the demand response potential of the building cell under the influence of urban micrometeorology at time t, in kWh.

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