Building energy management and control optimization method and system considering indoor heat transfer

Abstract

The invention discloses a building energy management and control optimization method and system considering indoor heat transfer, and the method comprises the steps: building a building third-order thermal parameter model according to a dynamic heat transfer process between rooms; a central air conditioner operation model comprising a water chilling unit energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model is constructed; according to the invention, the functions of improving the green low-carbon operation effect of the building and giving consideration to the comfort level of the user are realized; through the constructed building energy management and control optimization model, on the basis of considering photovoltaic power generation and rigid load uncertainty, diversified thermal comfort requirements of different rooms and building intra-day operation cost are considered, and multi-target optimization solution is carried out by adopting a deep strategic gradient decision, so that optimal low-carbon operation of the building is realized; the heat transfer effect of the room is considered, comfortable, green and low-carbon operation of the building is promoted, the energy management and control effect of the building is guaranteed, and the system is suitable for being widely popularized and used.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy management and optimization, and in particular to a building energy management and optimization method and system taking indoor heat transfer into consideration. Background Art

[0002] Carbon emissions from buildings account for a large proportion of the country's energy consumption, and carbon emissions during the building operation phase account for more than half of the carbon emissions during the building's entire life cycle. Therefore, how to formulate an efficient low-carbon energy management and control strategy for buildings is an effective strategy to promote green and low-carbon operation of buildings.

[0003] At present, most of the energy management and optimization of buildings consider the building as a whole for regulation, which makes it easy to ignore the different thermal comfort requirements of each room in the building. At the same time, the difference in cooling area of ​​each room also leads to different energy demand, and factors such as room orientation and heat radiation reception further increase the temperature change difference of each room. Not only will there be significant dynamic heat transfer between rooms, but the dynamic heat transfer process between rooms will also affect the cooling strategy of the two adjacent rooms. At the same time, conventional optimization methods are difficult to deal with the complex spatiotemporal coupling relationship of the building energy system when solving building optimization problems. This is very time-consuming when the solution space is very large, and it will also lead to difficult-to-resolve contradictions between the needs of multi-objective optimization and fast solution. Therefore, it is necessary to design a building energy management optimization method and system that considers indoor heat transfer. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and to better and more effectively solve the energy management and optimization of current buildings. Since most of the buildings are considered as a whole for regulation, it is easy to ignore the different thermal comfort requirements of each room in the building. At the same time, the difference in cooling area of ​​each room also leads to different energy requirements, and factors such as room orientation and heat radiation reception further increase the temperature change difference of each room. Not only will there be significant dynamic heat transfer between rooms, but the dynamic heat transfer process between rooms will also affect the cooling strategy of two adjacent rooms. At the same time, conventional optimization methods are difficult to handle the complex spatiotemporal coupling relationship of building energy systems when solving building optimization problems. This is very computationally intensive when the solution space is very large. When doing so, it will also lead to the problem of difficult-to-resolve contradictions between the needs of multi-objective optimization and rapid solution. A building energy management optimization method and system considering indoor heat transfer are provided, which realizes that the building energy management optimization method and system have the function of improving the green and low-carbon operation effect of the building and taking into account the comfort of users. The constructed building energy management optimization model can take into account the diverse thermal comfort needs of different rooms and the daily operation cost of the building on the basis of taking into account the uncertainty of photovoltaic power generation and rigid loads, and adopts deep strategic gradient decision-making to perform multi-objective optimization solution to achieve the optimal low-carbon operation of the building. It not only takes into account the heat transfer effect of the room, but also promotes the comfortable, green and low-carbon operation of the building, and ensures the energy management effect of the building.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A building energy management and control optimization method considering indoor heat transfer includes the following steps:

[0007] Step A, establishing a third-order thermal parameter model of the building according to the dynamic heat transfer process between rooms;

[0008] Step B, constructing a central air conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model;

[0009] Step C, based on the third-order thermal parameter model of the building and the central air-conditioning operation model, establish a building energy management optimization model according to the building operation cost and thermal comfort;

[0010] Step D, optimizing the building energy control by using the building energy control optimization model to obtain the building energy control optimization decision;

[0011] Step E: correct the building energy management optimization decision according to the uncertainty of building photovoltaic power generation and rigid load and obtain the corrected building energy management optimization decision, thereby completing the building energy management optimization operation.

[0012] The aforementioned building energy management optimization method considering indoor heat transfer, step A, establishes a third-order thermal parameter model of the building according to the dynamic heat transfer process between rooms. The specific steps are as follows:

[0013] Step A1, calculate the dynamic heat transfer Q between rooms change , as shown in formula (1),

[0014]

[0015] Among them, T1 is the indoor temperature of the first room, T2 is the indoor temperature of the second room, R ec1 is the equivalent convection thermal resistance of the first room, R ec2 is the equivalent convection thermal resistance of the second room, T iw is the inner wall temperature, R iw is the equivalent thermal resistance of the inner wall;

[0016] Step A2, calculate matrix A and matrix B as shown in formula (2) and formula (3) respectively,

[0017]

[0018]

[0019] Among them, R ec is the convection equivalent thermal resistance, R′ ew is half of the equivalent thermal resistance of the exterior wall, R′ iw is half of the equivalent thermal resistance of the inner wall, R gs is the equivalent thermal resistance of the window, C ew is the equivalent heat capacity of the exterior wall, C iw is the equivalent heat capacity of the inner wall, C in is the equivalent heat capacity of indoor air;

[0020] Step A3: Establish a third-order thermal parameter model of the building, as shown in formula (4):

[0021]

[0022] Among them, T ew is the external wall temperature, T in is the indoor temperature, T out is the outdoor temperature, T adj is the adjacent room temperature, I ew is the absorbed solar radiation of the exterior wall, I e is the solar radiation entering the room through the windows, I in is the load heat generated in the building, I t dev is the cooling capacity of the HVAC system.

[0023] The aforementioned building energy management and optimization method considering indoor heat transfer, step B, constructs a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model. The specific steps are as follows:

[0024] Step B1, constructing the chiller energy consumption model. The specific steps are as follows:

[0025] Step B11, calculate the partial load rate PLR ​​of the chiller chiller , as shown in formula (5),

[0026]

[0027] Among them, Q chiller is the actual cooling capacity of the water-cooled unit, a0, a1 and a2 are all partial load correction coefficients, Q nom is the rated cooling capacity of the chiller;

[0028] Step B12, calculate the chiller operating power W under rated conditions chiller , as shown in formula (6),

[0029]

[0030]

[0031] Among them, T chiller is the actual cooling temperature of the water cooling unit, T chws and T cws are the chilled water supply temperature and cooling water supply temperature respectively, b0, b1, b2, b3, b4 and b5 are temperature regression coefficients;

[0032] Step B13, constructing a chiller energy consumption model that reflects the relationship between the cooling load change and the chiller power consumption, as shown in formula (7),

[0033] P chiller =W chiller gPLR chiller (7)

[0034] Among them, P chiller is the actual operating power of the chiller, W chiller PLR is the chiller operating power under rated conditions. chiller is the partial load rate of the chiller;

[0035] Step B2, establish a variable frequency water pump energy consumption model, where the variable frequency water pump adjusts the motor speed by changing the current frequency to adjust the water flow of the water pump, and the actual power of the water pump is shown in formula (8):

[0036]

[0037]

[0038] Among them, P pump is the actual power of the pump, P pump.nom is the rated power of the pump, m nom Rated flow rate of the pump, m chw is the actual flow rate of the pump, PLR pump is the partial load rate of the water pump, d0, d1, d2 and d3 are all polynomial fitting coefficients;

[0039] Step B3, construct the cooling tower fan energy consumption model, as shown in formula (9),

[0040]

[0041]

[0042] Among them, P tfan is the power of the cooling tower fan, P tfan,nom is the rated power of the cooling tower fan, f0, f1, f2 and f3 are polynomial fitting coefficients, PLR tfan is the load factor of the fan, m atfan is the actual air volume of the fan, m atfan,nom is the rated air volume of the fan;

[0043] Step B4, establish the indoor unit fan energy consumption model, as shown in formula (10),

[0044]

[0045]

[0046] Among them, P cfan,nom Indicates the rated power of the fan, P cfan is the actual power of the wind turbine, g0, g1, g2 and g3 are the fitting coefficients of the polynomial model, PLR cfan is the load factor of the fan, m acfan,nom is the rated air volume of the fan, m acfan is the actual air volume of the fan.

[0047] The aforementioned building energy management optimization method considering indoor heat transfer, step C, based on the building third-order thermal parameter model and the central air-conditioning operation model, establishes a building energy management optimization model according to the building operation cost and thermal comfort. The specific steps are as follows:

[0048] Step C1, calculate the total building comfort cost, where the total building comfort cost is the cumulative sum of the thermal comfort costs of all rooms, as shown in formula (11),

[0049]

[0050]

[0051]

[0052] Among them, C total is the total operating cost of the building, The cost of purchasing electricity or the income from selling electricity, The amount of electricity purchased is is the price of purchased electricity, For electricity sales, is the electricity selling price, G room (k) is the thermal comfort gain of the kth room, PMV(k) is the PMV value of the kth room;

[0053] Step C2, establish a building energy management optimization model, specifically, establish an optimization solution target P1 that takes into account both the optimal comfort of each room and the minimum building operation cost, and the constraints include the central air conditioning operation model, thermal comfort model and energy storage equipment model, as shown in formula (12),

[0054]

[0055] In the aforementioned building energy management optimization method considering indoor heat transfer, step D optimizes building energy management using a building energy management optimization model to obtain a building energy management optimization decision, wherein the building energy management optimization decision P2 is shown in formula (13):

[0056]

[0057] In the aforementioned building energy management optimization method considering indoor heat transfer, step E is to correct the building energy management optimization decision according to the uncertainty of building photovoltaic power generation and rigid load and obtain the corrected building energy management optimization decision to complete the building energy management optimization operation. The specific process of correcting the building energy management optimization decision is shown in formula (14):

[0058]

[0059] Among them, ω1 is the weight of the building energy cost, and ω2 is the total weight of the total comfort of each room in the building.

[0060] A building energy management and control optimization system considering indoor heat transfer, comprising a building third-order thermal parameter model establishment module, a central air-conditioning operation model construction module, a building energy management and control optimization model establishment module, a building energy management and control optimization module and an optimization correction module, wherein the building third-order thermal parameter model establishment module is used to establish a building third-order thermal parameter model according to a dynamic heat transfer process between rooms;

[0061] The central air-conditioning operation model construction module is used to construct a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model;

[0062] The building energy management optimization model establishment module is used to establish a building energy management optimization model based on the building third-order thermal parameter model and the central air-conditioning operation model and according to the building operation cost and thermal comfort;

[0063] The building energy management and control optimization module is used to optimize the building energy management and control using the building energy management and control optimization model and obtain the building energy management and control optimization decision;

[0064] The optimization correction module is used to correct the building energy management optimization decision according to the uncertainty of building photovoltaic power generation and rigid load and obtain the corrected building energy management optimization decision.

[0065] The beneficial effects of the present invention are as follows: a building energy management optimization method and system considering indoor heat transfer of the present invention first establishes a third-order thermal parameter model of the building according to the dynamic heat transfer process between rooms, and then constructs a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model; then, based on the third-order thermal parameter model of the building and the central air-conditioning operation model and according to the building operation cost and thermal comfort, a building energy management optimization model is established; then, the building energy management is optimized using the building energy management optimization model and a building energy management optimization decision is obtained; and then, the building energy management is optimized according to the building photovoltaic power generation and the rigid load uncertainty. The building energy management optimization decision is corrected and the corrected building energy management optimization decision is obtained, thereby completing the building energy management optimization operation; it is effectively realized that the building energy management optimization method and system have the function of improving the green and low-carbon operation effect of the building and taking into account the user comfort, and the constructed building energy management optimization model can take into account the diverse thermal comfort requirements of different rooms and the daily operation cost of the building on the basis of taking into account the uncertainty of photovoltaic power generation and rigid load, and adopts deep strategic gradient decision-making for multi-objective optimization solution to achieve the optimal low-carbon operation of the building. It not only takes into account the heat transfer effect of the room, but also promotes the comfortable green and low-carbon operation of the building, and ensures the building energy management effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is a flow chart of a building energy management and control optimization method considering indoor heat transfer of the present invention;

[0067] Figure 2 is a building room location diagram in an embodiment of the present invention;

[0068] Figure 3 is a flow chart of building energy management and control optimization considering indoor heat transfer in an embodiment of the present invention;

[0069] Figure 4 is a schematic diagram for comparative analysis of indoor temperature changes in rooms with and without considering heat transfer in an embodiment of the present invention;

[0070] Figure 5 is a schematic diagram of heat transfer between rooms in an embodiment of the present invention;

[0071] Figure 6 Schematic diagram of the power of each part of the internal unit of the central air conditioner in the embodiment of the present invention;

[0072] Figure 7 Schematic diagram of electric power balance in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] The present invention will be further described below in conjunction with the accompanying drawings.

[0074] like Figure 1 As shown, a building energy management and control optimization method and system considering indoor heat transfer of the present invention includes the following steps:

[0075] Step A: Establish a third-order thermal parameter model of the building based on the dynamic heat transfer process between rooms. The specific steps are as follows:

[0076] Step A1, calculate the dynamic heat transfer Q between rooms change , as shown in formula (1),

[0077]

[0078] Among them, T1 is the indoor temperature of the first room, T2 is the indoor temperature of the second room, R ec1 is the equivalent convection thermal resistance of the first room, R ec2 is the equivalent convection thermal resistance of the second room, T iw is the inner wall temperature, R iw is the equivalent thermal resistance of the inner wall;

[0079] Step A2, calculate matrix A and matrix B as shown in formula (2) and formula (3) respectively,

[0080]

[0081]

[0082] Among them, R ec is the convection equivalent thermal resistance, R′ ew is half of the equivalent thermal resistance of the exterior wall, R′ iw is half of the equivalent thermal resistance of the inner wall, R gs is the equivalent thermal resistance of the window, C ew is the equivalent heat capacity of the exterior wall, C iw is the equivalent heat capacity of the inner wall, C in is the equivalent heat capacity of indoor air;

[0083] Step A3: Establish a third-order thermal parameter model of the building, as shown in formula (4):

[0084]

[0085] Among them, T ew is the external wall temperature, T in is the indoor temperature, T out is the outdoor temperature, T adj is the adjacent room temperature, I ew is the absorbed solar radiation of the exterior wall, I e is the solar radiation entering the room through the windows, I in is the load heat generated in the building, is the cooling capacity of the HVAC system.

[0086] Step B, constructing a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model. The specific steps are as follows:

[0087] Step B1, constructing the chiller energy consumption model. The specific steps are as follows:

[0088] Step B11, calculate the partial load rate PLR ​​of the chiller chiller , as shown in formula (5),

[0089]

[0090] Among them, Q chiller is the actual cooling capacity of the water-cooled unit, a0, a1 and a2 are all partial load correction coefficients, Q nom is the rated cooling capacity of the chiller;

[0091] Step B12, calculate the chiller operating power W under rated conditions chiller , as shown in formula (6),

[0092]

[0093]

[0094] Among them, T chiller is the actual cooling temperature of the water cooling unit, T chws and T cws are the chilled water supply temperature and cooling water supply temperature respectively, b0, b1, b2, b3, b4 and b5 are temperature regression coefficients;

[0095] Step B13, constructing a chiller energy consumption model that reflects the relationship between the cooling load change and the chiller power consumption, as shown in formula (7),

[0096] P chiller =W chiller gPLR chiller (7)

[0097] Among them, P chiller is the actual operating power of the chiller, W chiller PLR is the chiller operating power under rated conditions. chiller is the partial load rate of the chiller;

[0098] Step B2, establish a variable frequency water pump energy consumption model, where the variable frequency water pump adjusts the motor speed by changing the current frequency to adjust the water flow of the water pump, and the actual power of the water pump is shown in formula (8):

[0099]

[0100]

[0101] Among them, P pump is the actual power of the pump, P pump.nom is the rated power of the pump, m nom Rated flow rate of the pump, m chw is the actual flow rate of the pump, PLR pump is the partial load rate of the water pump, d0, d1, d2 and d3 are all polynomial fitting coefficients;

[0102] Step B3, construct the cooling tower fan energy consumption model, as shown in formula (9),

[0103]

[0104]

[0105] Among them, P tfan is the power of the cooling tower fan, P tfan,nom is the rated power of the cooling tower fan, f0, f1, f2 and f3 are polynomial fitting coefficients, PLR tfanis the load factor of the fan, m atfan is the actual air volume of the fan, m atfan,nom is the rated air volume of the fan;

[0106] Step B4, establish the indoor unit fan energy consumption model, as shown in formula (10),

[0107]

[0108]

[0109] Among them, P cfan,nom Indicates the rated power of the fan, P cfan is the actual power of the wind turbine, g0, g1, g2 and g3 are the fitting coefficients of the polynomial model, PLR cfan is the load factor of the fan, m acfan,nom is the rated air volume of the fan, m acfan is the actual air volume of the fan.

[0110] Step C: Based on the third-order thermal parameter model of the building and the central air-conditioning operation model, a building energy management optimization model is established according to the building operation cost and thermal comfort. The specific steps are as follows:

[0111] Step C1, calculate the total building comfort cost, where the total building comfort cost is the cumulative sum of the thermal comfort costs of all rooms, as shown in formula (11),

[0112]

[0113]

[0114]

[0115] Among them, C total is the total operating cost of the building, The cost of purchasing electricity or the income from selling electricity, The amount of electricity purchased is is the price of purchased electricity, For electricity sales, is the electricity selling price, G room (k) is the thermal comfort gain of the kth room, PMV(k) is the PMV value of the kth room;

[0116] Step C2, establish a building energy management optimization model, specifically, establish an optimization solution target P1 that takes into account both the optimal comfort of each room and the minimum building operation cost, and the constraints include the central air conditioning operation model, thermal comfort model and energy storage equipment model, as shown in formula (12),

[0117]

[0118] Step D, using the building energy control optimization model to optimize the building energy control, and obtain the building energy control optimization decision, where the building energy control optimization decision P2 is shown in formula (13):

[0119]

[0120] Step E: According to the uncertainty of building photovoltaic power generation and rigid load, the building energy control optimization decision is corrected and the corrected building energy control optimization decision is obtained to complete the building energy control optimization operation. The specific process of correcting the building energy control optimization decision is shown in formula (14):

[0121]

[0122] Among them, ω1 is the weight of the building energy cost, and ω2 is the total weight of the total comfort of each room in the building.

[0123] A building energy management and control optimization system considering indoor heat transfer comprises a building third-order thermal parameter model establishment module, a central air-conditioning operation model construction module, a building energy management and control optimization model establishment module, a building energy management and control optimization module and an optimization correction module, wherein the building third-order thermal parameter model establishment module is used to establish a building third-order thermal parameter model according to a dynamic heat transfer process between rooms; the central air-conditioning operation model construction module is used to construct a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model; the building energy management and control optimization model establishment module is used to establish a building energy management and control optimization model based on the building third-order thermal parameter model and the central air-conditioning operation model and according to the building operation cost and thermal comfort; the building energy management and control optimization module is used to optimize the building energy management using the building energy management and control optimization model and obtain the building energy management and control optimization decision; the optimization correction module is used to correct the building energy management and control optimization decision according to the uncertainty of building photovoltaic power generation and rigid load and obtain the corrected building energy management and control optimization decision.

[0124] In order to better illustrate the use effect of the present invention, a specific embodiment of the present invention is introduced below.

[0125] The basic parameter settings of this embodiment include: taking a certain building as the calculation scene, the total building area is 528.08m2, the height is 7.2m, and there are two floors above ground. The building is equipped with photovoltaic power generation equipment, wind power generation equipment and energy storage equipment. The building envelope has undergone energy-saving transformation, including the exterior wall, interior wall, and window transmittance, and has good thermal insulation properties. The building is mainly used for meetings and offices. Room 1 has an area of ​​72m2, room 2 has an area of ​​34.08m2, room 3 has an area of ​​21.9m2, room 4 has an area of ​​7m2, room 5 has an area of ​​15.3m2, and room 6 has an area of ​​25.2m2. The position relationship between the rooms is as follows: Figure 2 The building energy control period is 8:00-9:00, and the optimization time is 15 minutes. The implementation process of this embodiment is shown in Figure 3.

[0126] from Figure 4 It can be concluded that due to the different thermal comfort gains in each room, the cooling strategy of each room is different, and the indoor temperature changes of the rooms are also different. Room 1 has the largest area, followed by Room 2, and the indoor temperature fluctuations of these two rooms are relatively gentle. Therefore, the larger the area of ​​the room, the slower the cooling effect of the air conditioner. The areas of Room 4 and Room 5 are relatively small, which shows that the indoor temperature fluctuations of these two rooms are large. Therefore, the smaller the area of ​​the room, the more significant the cooling effect. Room 6 has a larger thermal comfort gain value than Room 3, which makes the temperature fluctuations of the two rooms more significant when the room areas are similar. Therefore, the thermal comfort gain has a positive feedback effect on the control of room temperature. From Figure 4 It can be concluded that the temperature curve of each room plots the temperature curve when the building is considered as a whole room. When the building is regarded as a whole for optimization and regulation, there is no heat transfer between the rooms, so the temperature of each room should be the same, and the indoor temperature fluctuation of the room is small. Because the overall area of ​​the building is large, the entire building is equivalent to a large room, and the cooling effect of the air conditioner is not significant. At this time, even if the thermal comfort gain is increased, the comfort effect of the building is not obvious, and it cannot meet the diverse comfort needs of different users in different rooms of the building.

[0127] from Figure 5It can be concluded that room1-room3 represents the amount of heat transfer from room 1 to room 3. During the intelligent building optimization, room 3 basically transfers cold energy to room 1, and room 2 also basically transfers cold energy to room 1. Because room 1 has a large area and a slow cooling effect, and rooms 2 and 3 have small areas and fast cooling effects, so during the optimization period, rooms 2 and 3 have a certain auxiliary effect on the cooling of room 1, saving the cooling capacity required for room 1, and reducing the central air-conditioning power of room 1. The heat transfer process between room 3 and room 4 is more complicated. The two rooms transfer cold energy alternately. The reason is that the area of ​​room 4 is very small and the cooling effect is very significant. When the set temperature of room 4 is lowered, the temperature drops rapidly and soon falls below room 3, so it transfers cold energy to room 3. Then the set temperature is raised, and the indoor temperature gradually rises. When it exceeds room 4, room 4 transfers cold energy to room 3 in turn, and this process is repeated alternately. The heat exchange between room 2 and room 5 is also alternated, but because the difference in room area is small, the alternation process is not particularly significant. For room 5 and room 6, since the thermal comfort gain of room 6 is larger, the temperature of room 6 drops faster at the beginning, and room 5 transfers heat to room 6. At noon, because room 6 has a larger room area and window area, it receives more solar radiation and the temperature rises, and room 6 transfers heat to room 5. As the solar radiation gradually decreases in the afternoon, the temperature of room 6 drops again, and room 5 transfers heat to room 6.

[0128] from Figure 6 It can be concluded that the power relationship between the units inside the central air conditioner is that the power consumed by the chiller accounts for most of the central air conditioner power, followed by the power consumed by the water pump, and the power consumed by the cooling tower fan and indoor fan is relatively small. At the same time, it can be seen that no matter whether the total power of the central air conditioning system increases or decreases, a certain proportional relationship is still maintained between the units.

[0129] from Figure 7The balance of electric power between the internal systems of the building energy management model can be obtained. The building energy management is from 9:00 to 18:00, and the control interval is 15 minutes. It can be seen that there is a certain connection between photovoltaic power generation and central air-conditioning power. In the morning, as the photovoltaic power increases, the outdoor temperature gradually rises. In order to reduce the indoor temperature and ensure the comfort of the room, the air-conditioning power also increases, increasing the cooling capacity, so that the temperature of each room in the building drops rapidly. At noon, the photovoltaic power generation is at its peak and the outdoor temperature is also high, so the central air-conditioning power is also large at this time. In the afternoon, as the photovoltaic power gradually decreases and the outdoor temperature decreases, and considering the insulation characteristics of the building enclosure, the maintenance of the indoor temperature no longer requires a large cooling capacity, so the central air-conditioning power also gradually decreases. From the figure, it can also be concluded that the energy storage system plays an important role in building energy management. It stores photovoltaic power when photovoltaic power is sufficient or the electricity price is low, and releases energy to supplement the building consumption when photovoltaic power is insufficient or the electricity price is high, which fully absorbs new energy and saves the building energy cost.

[0130] In summary, the present invention provides a building energy management optimization method and system considering indoor heat transfer, firstly, a third-order thermal parameter model of the building is established according to the dynamic heat transfer process between rooms, and then a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model is constructed, and then a building energy management optimization model is established based on the third-order thermal parameter model of the building and the central air-conditioning operation model and according to the building operation cost and thermal comfort, and then the building energy management is optimized using the building energy management optimization model and the building energy management optimization decision is obtained, and then the building energy management is optimized according to the building photovoltaic power generation and the rigid load uncertainty. The control optimization decision is corrected and the corrected building energy control optimization decision is obtained, thereby completing the building energy control optimization operation; it is effectively realized that the building energy control optimization method and system have the function of improving the green and low-carbon operation effect of the building and taking into account the user comfort, and the constructed building energy control optimization model can take into account the diverse thermal comfort requirements of different rooms and the daily operation cost of the building on the basis of taking into account the uncertainty of photovoltaic power generation and rigid load, and adopts deep strategic gradient decision-making for multi-objective optimization solution to achieve the optimal low-carbon operation of the building. It not only takes into account the heat transfer effect of the room, but also promotes the comfortable green and low-carbon operation of the building, and ensures the energy control effect of the building.

[0131] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A building energy management and control optimization method considering indoor heat transfer, characterized in that: The following steps are included: Step A, establishing a third-order thermal parameter model of the building according to the dynamic heat transfer process between rooms; Step B, constructing a central air conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model; Step C, based on the third-order thermal parameter model of the building and the central air-conditioning operation model, establish a building energy management optimization model according to the building operation cost and thermal comfort; Step D, optimizing the building energy control by using the building energy control optimization model to obtain the building energy control optimization decision; Step E: correct the building energy management optimization decision according to the uncertainty of building photovoltaic power generation and rigid load and obtain the corrected building energy management optimization decision, thereby completing the building energy management optimization operation.

2. A building energy management and optimization method considering indoor heat transfer according to claim 1, characterized in that: Step A: Establish a third-order thermal parameter model of the building based on the dynamic heat transfer process between rooms. The specific steps are as follows: Step A1, calculate the dynamic heat transfer Q between rooms change , as shown in formula (1), Among them, T1 is the indoor temperature of the first room, T2 is the indoor temperature of the second room, R ec1 is the equivalent convection thermal resistance of the first room, R ec2 is the equivalent convection thermal resistance of the second room, T iw is the inner wall temperature, R iw is the equivalent thermal resistance of the inner wall; Step A2, calculate matrix A and matrix B as shown in formula (2) and formula (3) respectively, Among them, R ec is the convection equivalent thermal resistance, R′ ew is half of the equivalent thermal resistance of the exterior wall, R′ iw is half of the equivalent thermal resistance of the inner wall, R gs is the equivalent thermal resistance of the window, C ew is the equivalent heat capacity of the exterior wall, C iw is the equivalent heat capacity of the inner wall, C in is the equivalent heat capacity of indoor air; Step A3: Establish a third-order thermal parameter model of the building, as shown in formula (4): Among them, T ew is the external wall temperature, T in is the indoor temperature, T out is the outdoor temperature, T adj is the adjacent room temperature, I ew is the absorbed solar radiation of the exterior wall, I e is the solar radiation entering the room through the windows, I in is the load heat generated in the building, is the cooling capacity of the HVAC system.

3. A building energy management and control optimization method considering indoor heat transfer according to claim 2, characterized in that: Step B, constructing a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model. The specific steps are as follows: Step B1, constructing the chiller energy consumption model. The specific steps are as follows: Step B11, calculate the partial load rate PLR ​​of the chiller chiller , as shown in formula (5), Among them, Q chiller is the actual cooling capacity of the water-cooled unit, a0, a1 and a2 are partial load correction coefficients, Q nom is the rated cooling capacity of the chiller; Step B12, calculate the chiller operating power W under rated conditions chiller , as shown in formula (6), Among them, T chiller is the actual cooling temperature of the water cooling unit, T chws and T cws are the chilled water supply temperature and cooling water supply temperature respectively, b0, b1, b2, b3, b4 and b5 are temperature regression coefficients; Step B13, constructing a chiller energy consumption model that reflects the relationship between the cooling load change and the chiller power consumption, as shown in formula (7), P chiller =W chiller gPLR chiller (7) Among them, P chiller is the actual operating power of the chiller, W chiller PLR is the chiller operating power under rated conditions. chiller is the partial load rate of the chiller; Step B2, establish a variable frequency water pump energy consumption model, where the variable frequency water pump adjusts the motor speed by changing the current frequency to adjust the water flow of the water pump, and the actual power of the water pump is shown in formula (8): Among them, P pump is the actual power of the pump, P pump.nom is the rated power of the pump, m nom Rated flow rate of the pump, m chw is the actual flow rate of the pump, PLR pump is the partial load rate of the water pump, d0, d1, d2 and d3 are all polynomial fitting coefficients; Step B3, construct the cooling tower fan energy consumption model, as shown in formula (9), Among them, P tfan is the power of the cooling tower fan, P tfan,nom is the rated power of the cooling tower fan, f0, f1, f2 and f3 are polynomial fitting coefficients, PLR tfan is the load factor of the fan, m atfan is the actual air volume of the fan, m atfan,nom is the rated air volume of the fan; Step B4, establish the indoor unit fan energy consumption model, as shown in formula (10), Among them, P cfan,nom Indicates the rated power of the fan, P cfan is the actual power of the wind turbine, g0, g1, g2 and g3 are the fitting coefficients of the polynomial model, PLR cfan is the load factor of the fan, m acfan,nom is the rated air volume of the fan, m acfan is the actual air volume of the fan.

4. A building energy management and control optimization method considering indoor heat transfer according to claim 3, characterized in that: Step C: Based on the third-order thermal parameter model of the building and the central air-conditioning operation model, a building energy management optimization model is established according to the building operation cost and thermal comfort. The specific steps are as follows: Step C1, calculate the total building comfort cost, where the total building comfort cost is the cumulative sum of the thermal comfort costs of all rooms, as shown in formula (11), Among them, C total is the total operating cost of the building, is the cost of purchased electricity or the income from electricity sales, P t buy,grid The amount of electricity purchased is is the price of purchased electricity, P t sell,grid For electricity sales, is the electricity selling price, G room (k) is the thermal comfort gain of the kth room, PMV(k) is the PMV value of the kth room; Step C2, establish a building energy management optimization model, specifically, establish an optimization solution target P1 that takes into account both the optimal comfort of each room and the minimum building operation cost, and the constraints include the central air conditioning operation model, thermal comfort model and energy storage equipment model, as shown in formula (12), 5. A building energy management and control optimization method considering indoor heat transfer according to claim 4, characterized in that: Step D, using the building energy control optimization model to optimize the building energy control, and obtain the building energy control optimization decision, where the building energy control optimization decision P2 is shown in formula (13):

6. A building energy management and control optimization method considering indoor heat transfer according to claim 5, characterized in that: Step E: According to the uncertainty of building photovoltaic power generation and rigid load, the building energy control optimization decision is corrected and the corrected building energy control optimization decision is obtained to complete the building energy control optimization operation. The specific process of correcting the building energy control optimization decision is shown in formula (14): Among them, ω1 is the weight of the building energy cost, and ω2 is the total weight of the total comfort of each room in the building.

7. A building energy management and optimization system considering indoor heat transfer, wherein the optimization process of the building energy management and optimization system is based on the building energy management and optimization method according to any one of claims 1 to 6, characterized in that: It includes a building third-order thermal parameter model establishment module, a central air-conditioning operation model construction module, a building energy management and control optimization model establishment module, a building energy management and control optimization module and an optimization correction module. The building third-order thermal parameter model establishment module is used to establish a building third-order thermal parameter model according to the dynamic heat transfer process between rooms; The central air-conditioning operation model construction module is used to construct a central air-conditioning operation model including a chiller energy consumption model, a variable frequency water pump energy consumption model, a cooling tower fan energy consumption model and an indoor unit fan energy consumption model; The building energy management optimization model establishment module is used to establish a building energy management optimization model based on the building third-order thermal parameter model and the central air-conditioning operation model and according to the building operation cost and thermal comfort; The building energy management and control optimization module is used to optimize the building energy management and control using the building energy management and control optimization model and obtain the building energy management and control optimization decision; The optimization correction module is used to correct the building energy management optimization decision according to the uncertainty of building photovoltaic power generation and rigid load and obtain the corrected building energy management optimization decision.

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