CN117313396A - Environmental temperature energy-saving optimization method and system considering multi-main-body demand response - Google Patents
Environmental temperature energy-saving optimization method and system considering multi-main-body demand response Download PDFInfo
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Abstract
The invention relates to the technical field of energy-saving optimization of central air conditioners, in particular to an environmental temperature energy-saving optimization method and system considering multi-main-body demand response, comprising the following steps: analyzing the main body characteristics of various loads at the load side of the target environment, and constructing a temperature regulation model by taking the minimum temperature control energy consumption as a target; generating expected scenes based on typical daily operation data of each season, and constructing an uncertainty set; taking the requirements of various types of load main bodies as a first-stage variable of a temperature regulation model, taking a temperature control terminal operation strategy as a second-stage decision variable of the temperature regulation model, taking the minimum energy consumption in a desired scene as an optimization target, taking a temperature control terminal operation limit and an uncertainty set as constraints, and constructing a two-stage robust optimization model; and solving the two-stage robust optimization model by using a CCG algorithm to obtain a target environment temperature regulation and control result which is suitable for the environment requirements of various types of load main bodies, thereby realizing the balance between the cold/hot comfortable temperature of the various types of load main bodies and the energy consumption of the central air conditioner.
Description
Technical Field
The invention relates to the technical field of energy-saving optimization of central air conditioners, in particular to an environment temperature energy-saving optimization method and system considering multi-main-body demand response.
Background
In order to create indoor human body cold/hot comfortable environment, central air conditioner is widely used in large building, but at the same time becomes main energy-consuming electric appliance, one of the reasons is that its internal equipment operates according to the set state all day, outputs constant power to cope with load demand. In fact, the central air conditioning terminal load is randomly varied by the external ambient temperature and the internal zone cold/hot load body flow conditions and labor properties.
Therefore, on the premise of ensuring indoor cold/hot comfort, the running state of the internal equipment of the central air conditioner is adjusted according to random factor change, and energy saving optimization aiming at the lowest energy consumption is implemented, so that the problem can be effectively relieved.
The random factors influencing the load change of the central air conditioner terminal have different realization times; from the viewpoint of heat transfer of the building, the central air conditioner needs to slowly change along with the external environment temperature in a longer time scale and relatively stably run to compensate the heat dissipation power of the building, so that the temperature in the area is maintained at a certain cold/hot comfort value; from the viewpoint of the flowing condition of the cold/hot load main body, the central air conditioner needs to randomly change along with the density of crowd/office equipment in the area, the labor property of the crowd/office equipment and the temperature demand difference of individuals in the main body in a shorter time scale, and the central air conditioner is relatively flexible to run so as to meet the cold/hot comfortable temperature demands of all the main bodies. However, in the current energy-saving optimization strategy for central air conditioner, no two random factors are considered.
Disclosure of Invention
The invention aims to provide an environment temperature energy-saving optimization method and system considering multi-subject demand response, so as to solve the problems pointed out in the background art.
The embodiment of the invention is realized by the following technical scheme: an environmental temperature energy-saving optimization method considering multi-subject demand response comprises the following steps:
step one, constructing a temperature regulation model by analyzing the main body characteristics of various types of loads at the load side of a target environment and taking the minimum temperature control energy consumption as a target;
step two, generating expected scenes based on typical daily operation data of each season, and constructing an uncertainty set;
step three, taking the requirements of various types of load main bodies as a first-stage variable of a temperature regulation model, taking a temperature control terminal operation strategy as a second-stage decision variable of the temperature regulation model, taking the minimum energy consumption of a target environment in an expected scene as an optimization target, taking a temperature control terminal operation limit and an uncertainty set as constraints, and constructing a target environment two-stage robust optimization model based on the expected scene;
and step four, solving a target environment two-stage robust optimization model based on a desired scene by utilizing a CCG algorithm to obtain a target environment temperature regulation and control result which is suitable for the requirements of various load main body environments.
According to a preferred embodiment, the target environmental load side various types of load bodies include crowd heat dissipation loadsDevice heat dissipation load->Solar radiation load->Fresh air load->Building construction load->
In the above, Q t The instantaneous heat gain at the time t is indicated,indicating the cold load of crowd main body at t moment +.>Indicating the main body cooling load of the device at time t +.>Indicating the solar radiation cold load at time t +.>Indicating the cold load of the crowd at time t, +.>Indicating the cold load formed by sensible heat dissipation of crowd main body at t time +.>Indicating the cold load formed by latent heat radiation of crowd main body at time t, n t，D Indicating the number of people with labor property D at t time>Representing the cluster coefficients, +.>Indicating the sensible heat dissipation capacity of D labor property crowd at room temperature at t time>Represents the sensible heat radiation cold load coefficient of human body, +.>People representing D labor property at room temperature at t momentGroup latent heat dissipation capacity, < >>Indicating the device body cooling load at time t +.>Indicating the heat dissipation capacity of the electric heating device at time t +.>Electronic device heat dissipation capacity at time t>Indicating the heat dissipation capacity of the lighting device at time t +.>Representing the solar radiation cold load at time t, A w Indicating window area, C a Representing the effective area coefficient of the window, +.>Represents the comprehensive shielding coefficient of window glass at time t, D j Indicating the factors of solar heat and->Indicating the glazing cold load factor, < >>Represents the fresh air quantity at time t->Indicating the outdoor fresh air temperature at time t +.>The indoor air temperature at the time t is represented, j represents the j part of wall body of the building structure, N j Representing the total wall body of the building structure, A j Represents the surface area of the wall of part j, K j Representing the heat dissipation coefficient of the wall body of the section j, t R Indicating the indoor temperature, t w The outdoor temperature is represented, and α represents the temperature difference correction coefficient.
According to a preferred embodiment, the temperature control terminal operation limit in the third step includes a temperature control terminal operation parameter limit constraint, a power balance constraint, a temperature variation range constraint and a temperature range constraint; the operation parameter limit value is limited by the operation quantity of the internal equipment of the temperature control terminal, and the power balance constraint is that the temperature control terminal load at the time t+1 is equal to the instantaneous heat obtaining cold/hot load at the time t.
According to a preferred embodiment, said step three comprises:
taking comfort temperature representing the requirements of various types of load main bodies as a first-stage variable, and constructing a pre-control model of a target environment two-stage robust optimization model based on a desired scene;
and constructing a target environment optimization re-regulation model based on the expected scene based on the decision variable result of the first stage and the actual value revealed by the uncertain parameter.
According to a preferred embodiment, the first stage uses the temperature obtained by each type of load main body from the temperature control terminal as an optimal target function, and the expression is as follows:
in the above, T set Representing the cold/hot comfort temperature, Q, of various types of load bodies t，d The instant heat gain corresponding to the demand of the d-type main body at the t moment is represented, C represents the specific heat capacity and ρ t The air density at time t is indicated,the flow rate of the air supply at the time t is represented, alpha, beta and gamma represent normalized proportion coefficients, n t，d Representing the density of individuals in class D subjects at time t, D t，d Indicating the labor property of the class d main body at the time t, F t，d Indicating the difference in temperature demand of the individual in the class d subject at time t.
According to a preferred embodiment, the second stage optimizes and prepares the operation strategy of the temperature control terminal at each time according to the cold/hot comfortable temperature and the current environment temperature of each type of load main body determined in the first stage, and takes the minimum energy consumption newly added on the same day as an objective function, and the expression is as follows:
in the above formula, tr represents a temperature interval constituted by cold/hot comfort temperatures of various types of load main bodies,indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R Power consumption when intermittently operating with minimum cooling/heating capacity in semi-cold/semi-hot mode of operation, n tr The refrigerating time is represented, n represents the temperature interval when the cold/hot comfortable temperature of various load main bodies and the minimum refrigerating/heating capacity of the temperature control terminal in the semi-cold/semi-hot running mode tend to be balanced, and>indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R When the power consumption continuously operates with the minimum refrigerating/heating capacity in the full-cooling/full-heating operation mode, k represents the temperature interval between the cold/hot comfortable temperature of various types of load main bodies and the temperature interval when the temperature control terminal is balanced with the minimum refrigerating/heating capacity in the full-cooling/full-heating operation mode>Indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R When the power consumption continuously operates with the medium refrigerating/heating capacity in the full-cooling/full-heating operation mode, m represents the temperature interval between the cold/hot comfortable temperature of each type of load main body and the temperature control terminal when the medium refrigerating/heating capacity in the full-cooling/full-heating operation mode tends to be balanced, and the temperature control terminal is in the full-cooling/full-heating operation mode>Indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R In all-cold/all-hot mode of operationThe maximum cooling/heating capacity continuously operates power consumption, g represents the temperature interval between the cool/heat comfort temperature of various types of load main bodies and the maximum cooling/heating capacity of the temperature control terminal in the full cooling/full heating operation mode towards balance.
The invention also provides an ambient temperature energy saving optimization system taking into account multi-body demand response, comprising a processor and a memory, said memory storing a computer program, said processor executing the steps of the method as described above when running said computer program.
The technical scheme of the embodiment of the invention has at least the following advantages and beneficial effects: the invention provides an environmental temperature energy-saving optimization method and system taking into account multi-main body demand response, which realize energy-saving optimization of a central air conditioner in a target environment; the first stage optimizes the central air conditioner operation parameters according to the initial environment main body information and the equipment/personnel main body information at each moment, and the second stage optimizes and adjusts the central air conditioner operation parameters based on the decision variable results of the first stage and the actual values revealed by the uncertain parameters, so that the balance of the cold/hot comfortable temperature of various load main bodies in each season and the energy consumption of the central air conditioner is realized.
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Fig. 1 is a flow chart of an environmental temperature energy-saving optimization method taking into account multi-subject demand response provided in embodiment 1 of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
The embodiment provides an environmental temperature energy-saving optimization method considering multi-subject demand response, as shown in fig. 1, fig. 1 is a flow chart of the environmental temperature energy-saving optimization method considering multi-subject demand response provided in embodiment 1 of the invention.
Specifically, the method comprises the following steps:
step one, constructing a temperature regulation model by analyzing the main body characteristics of various types of loads at the load side of a target environment and taking the minimum temperature control energy consumption as a target;
step two, generating expected scenes based on typical daily operation data of each season, and constructing an uncertainty set;
step three, taking the requirements of various types of load main bodies as a first-stage variable of a temperature regulation model, taking a temperature control terminal operation strategy as a second-stage decision variable of the temperature regulation model, taking the minimum energy consumption of a target environment in an expected scene as an optimization target, taking a temperature control terminal operation limit and an uncertainty set as constraints, and constructing a target environment two-stage robust optimization model based on the expected scene;
and step four, solving a target environment two-stage robust optimization model based on a desired scene by utilizing a CCG algorithm to obtain a target environment temperature regulation and control result which is suitable for the requirements of various load main body environments.
In the present embodiment, by analyzing the characteristics of the load main bodies of the respective types on the target environmental load side, specifically, the load main bodies of the respective types on the target environmental load side include the crowd heat radiation loadDevice heat dissipation load->Solar radiation load->Fresh air load->Building construction load->
Wherein, crowd heat dissipation loadThe expression of (2) is as follows:
in the above, Q t The instantaneous heat gain at the time t is indicated,indicating the cold load of crowd main body at t moment +.>Indicating the main body cooling load of the device at time t +.>Indicating the solar radiation cold load at time t +.>Indicating the cold load of the crowd at time t, +.>Indicating the cold load formed by sensible heat dissipation of crowd main body at t time +.>Indicating the cold load formed by latent heat radiation of crowd main body at time t, n t,D Indicating the number of people with labor property D at t time>Representing the cluster coefficients, +.>Indicating the sensible heat dissipation capacity of D labor property crowd at room temperature at t time>Represents the sensible heat radiation cold load coefficient of human body, +.>And the latent heat radiating capacity of the crowd with the labor property D at room temperature at the moment t is shown.
Heat dissipation load of equipmentThe expression of (2) is as follows:
in the above-mentioned method, the step of,indicating the device body cooling load at time t +.>The heat dissipation capacity of the electric heating device at the time t is represented,electronic device heat dissipation capacity at time t>The heat dissipation of the lighting device at time t is indicated.
Solar radiation loadThe expression of (2) is as follows:
in the above-mentioned method, the step of,representing the solar radiation cold load at time t, A w Indicating window area, C a Representing the effective area coefficient of the window, +.>Represents the comprehensive shielding coefficient of window glass at time t, D j Indicating the factors of solar heat and->Indicating the glazing cold load factor.
Fresh air loadThe expression of (2) is as follows:
in the above-mentioned method, the step of,represents the fresh air quantity at time t->Indicating the outdoor fresh air temperature at time t +.>The indoor air temperature at time t is indicated.
Building structure loadThe expression of (2) is as follows:
in the above description, j represents the j part of the wall body of the building structure, N j Representing the total wall body of the building structure, A j Represents the surface area of the wall of part j, K j Representing the heat dissipation coefficient of the wall body of the section j, t R Indicating the indoor temperature, t w The outdoor temperature is represented, and α represents the temperature difference correction coefficient.
Further, the temperature control terminal operation limit in the third step comprises temperature control terminal operation parameter limit value constraint, power balance constraint, temperature change amplitude constraint and temperature range constraint; the operation parameter limit value is limited by the operation quantity of the internal equipment of the temperature control terminal, and the power balance constraint is that the temperature control terminal load at the time t+1 is equal to the instantaneous heat obtaining cold/hot load at the time t.
In the third step, taking comfort temperature representing the requirements of various types of load main bodies as a first-stage variable, and constructing a pre-control model of a target environment two-stage robust optimization model based on a desired scene.
The first stage takes the optimal temperature obtained by various types of load main bodies from a temperature control terminal as an objective function, and the expression is as follows:
in the above, T set Representing the cold/hot comfort temperature, Q, of various types of load bodies t，d The instant heat gain corresponding to the demand of the d-type main body at the t moment is represented, C represents the specific heat capacity and ρ t The air density at time t is indicated,the flow rate of the air supply at the time t is represented, alpha, beta and gamma represent normalized proportion coefficients, n t，d Representing the density of individuals in class D subjects at time t, D t，d Indicating the labor property of the class d main body at the time t, F t，d Indicating the difference in temperature demand of the individual in the class d subject at time t.
And the second stage is based on the decision variable result of the first stage and the actual value revealed by the uncertain parameters, and a target environment optimization re-regulation model based on the expected scene is constructed. Specifically, the second stage optimizes and prepares the operation strategy of the temperature control terminal at each moment according to the cold/hot comfortable temperature and the current environment temperature of each type of load main body determined in the first stage, and takes the minimum energy consumption newly added on the same day as an objective function, and the expression is as follows:
in the above formula, tr represents a temperature interval constituted by cold/hot comfort temperatures of various types of load main bodies,indicating temperature controlThe terminal t time participates in d type load main body demand response at the environment temperature t R Power consumption when intermittently operating with minimum cooling/heating capacity in semi-cold/semi-hot mode of operation, n tr The refrigerating time is represented, n represents the temperature interval when the cold/hot comfortable temperature of various load main bodies and the minimum refrigerating/heating capacity of the temperature control terminal in the semi-cold/semi-hot running mode tend to be balanced, and>indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R When the power consumption continuously operates with the minimum refrigerating/heating capacity in the full-cooling/full-heating operation mode, k represents the temperature interval between the cold/hot comfortable temperature of various types of load main bodies and the temperature interval when the temperature control terminal is balanced with the minimum refrigerating/heating capacity in the full-cooling/full-heating operation mode>Indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R When the power consumption continuously operates with the medium refrigerating/heating capacity in the full-cooling/full-heating operation mode, m represents the temperature interval between the cold/hot comfortable temperature of each type of load main body and the temperature control terminal when the medium refrigerating/heating capacity in the full-cooling/full-heating operation mode tends to be balanced, and the temperature control terminal is in the full-cooling/full-heating operation mode>Indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R And g represents the temperature interval between the cold/hot comfortable temperature of each type of load main body and the temperature control terminal when the maximum refrigerating/heating capacity in the full-cold/full-hot operation mode tends to be balanced.
In summary, the invention provides an environmental temperature energy-saving optimization method and system considering multi-main body demand response, which realizes energy-saving optimization of a central air conditioner in a target environment; the first stage optimizes the central air conditioner operation parameters according to the initial environment main body information and the equipment/personnel main body information at each moment, and the second stage optimizes and adjusts the central air conditioner operation parameters based on the decision variable results of the first stage and the actual values revealed by the uncertain parameters, so that the balance of the cold/hot comfortable temperature of various load main bodies in each season and the energy consumption of the central air conditioner is realized.
The embodiment of the invention also provides an environment temperature energy-saving optimization system considering multi-main body demand response, which comprises a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the method when running the computer program.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The environment temperature energy-saving optimization method considering multi-main body demand response is characterized by comprising the following steps of:
step one, constructing a temperature regulation model by analyzing the main body characteristics of various types of loads at the load side of a target environment and taking the minimum temperature control energy consumption as a target;
step two, generating expected scenes based on typical daily operation data of each season, and constructing an uncertainty set;
step three, taking the requirements of various types of load main bodies as a first-stage variable of a temperature regulation model, taking a temperature control terminal operation strategy as a second-stage decision variable of the temperature regulation model, taking the minimum energy consumption of a target environment in an expected scene as an optimization target, taking a temperature control terminal operation limit and an uncertainty set as constraints, and constructing a target environment two-stage robust optimization model based on the expected scene;
and step four, solving a target environment two-stage robust optimization model based on a desired scene by utilizing a CCG algorithm to obtain a target environment temperature regulation and control result which is suitable for the requirements of various load main body environments.
2. The method for optimizing environmental temperature and energy conservation taking account of multi-subject demand response as in claim 1 wherein each type of load subject on the target environmental load side comprises a crowd heat dissipation loadDevice heat dissipation load->Solar radiation load->Fresh air load->Building construction load->
In the above, Q t The instantaneous heat gain at the time t is indicated,indicating the cold load of crowd main body at t moment +.>Indicating the main body cooling load of the device at time t +.>Indicating the solar radiation cold load at time t +.>Indicating the cold load of the crowd at time t, +.>Indicating the cold load formed by sensible heat dissipation of crowd main body at t time +.>Indicating the cold load formed by latent heat radiation of crowd main body at time t, n t,D Indicating the number of people with labor property D at t time>Representing the cluster coefficients, +.>Indicating the sensible heat dissipation capacity of D labor property crowd at room temperature at t time>Represents the sensible heat radiation cold load coefficient of human body, +.>Indicating the latent heat radiating capacity of D labor property crowd at room temperature at t time>Indicating the device body cooling load at time t +.>Indicating the heat dissipation capacity of the electric heating device at time t +.>Electronic device heat dissipation capacity at time t>Indicating the heat dissipation capacity of the lighting device at time t +.>Representing the solar radiation cold load at time t, A w Indicating window area, C a Representing the effective area coefficient of the window, +.>Represents the comprehensive shielding coefficient of window glass at time t, D j Indicating the factors of solar heat and->Indicating the glazing cold load factor, < >>Represents the fresh air quantity at time t->Indicating the outdoor fresh air temperature at time t +.>The indoor air temperature at the time t is represented, j represents the j part of wall body of the building structure, N j Representing the total wall body of the building structure, A j Represents the surface area of the wall of part j, K j Representing the heat dissipation coefficient of the wall body of the section j, t R Indicating the indoor temperature, t w The outdoor temperature is represented, and α represents the temperature difference correction coefficient.
3. The energy-saving optimization method for environmental temperature taking into account multi-subject demand response according to claim 2 wherein the temperature-controlled terminal operation constraints in step three include temperature-controlled terminal operation parameter limit constraints, power balance constraints, temperature variation amplitude constraints, and temperature range constraints; the operation parameter limit value is limited by the operation quantity of the internal equipment of the temperature control terminal, and the power balance constraint is that the temperature control terminal load at the time t+1 is equal to the instantaneous heat obtaining cold/hot load at the time t.
4. A method of energy efficient optimization of ambient temperature taking into account multi-subject demand response as defined in any one of claims 2 to 3 wherein said step three comprises:
taking comfort temperature representing the requirements of various types of load main bodies as a first-stage variable, and constructing a pre-control model of a target environment two-stage robust optimization model based on a desired scene;
and constructing a target environment optimization re-regulation model based on the expected scene based on the decision variable result of the first stage and the actual value revealed by the uncertain parameter.
5. The energy-saving optimization method for environmental temperature taking into account multi-body demand response according to claim 4, wherein the first stage uses the optimal temperature obtained from the temperature control terminal by each type of load body as an objective function, and the expression is as follows:
in the above, T set Representing the cold/hot comfort temperature, Q, of various types of load bodies t,d The instant heat gain corresponding to the demand of the d-type main body at the t moment is represented, C represents the specific heat capacity and ρ t The air density at time t is indicated,the flow rate of the air supply at the time t is represented, alpha, beta and gamma represent normalized proportion coefficients, n t,d Representing the density of individuals in class D subjects at time t, D t,d Indicating the labor property of the class d main body at the time t, F t,d Indicating the difference in temperature demand of the individual in the class d subject at time t.
6. The energy-saving optimization method for environmental temperature taking into account multi-main body demand response according to claim 5, wherein the second stage optimizes and prepares the operation strategy of the temperature control terminal at each moment according to the cold/hot comfort temperature and the current environmental temperature of each type of load main body determined in the first stage, and takes the minimum energy consumption newly added on the same day as an objective function, and the expression is as follows:
in the above formula, tr represents various types of load bodiesA temperature range constituted by the cold/hot comfort temperature of (c),indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R Power consumption when intermittently operating with minimum cooling/heating capacity in semi-cold/semi-hot mode of operation, n tr Indicating the refrigerating time period, n indicating the temperature interval between the cold/hot comfortable temperature of various load main bodies and the minimum refrigerating/heating capacity of the temperature control terminal in the semi-cold/semi-hot operation mode,indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R The power consumption of continuous operation with the minimum refrigerating/heating capacity in the full-cooling/full-heating operation mode is shown in k, wherein k represents the temperature interval between the cold/hot comfortable temperature of each type of load main body and the temperature control terminal when the minimum refrigerating/heating capacity in the full-cooling/full-heating operation mode tends to be balanced,indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R When the power consumption continuously operates with the medium refrigeration/heating capacity in the full-cold/full-hot operation mode, m represents the temperature interval between the cold/hot comfortable temperature of each type of load main body and the temperature of the temperature control terminal when the medium refrigeration/heating capacity in the full-cold/full-hot operation mode tends to be balanced,indicating that the temperature control terminal t participates in d-type load main body demand response at the environment temperature t R And g represents the temperature interval between the cold/hot comfortable temperature of each type of load main body and the temperature control terminal when the maximum refrigerating/heating capacity in the full-cold/full-hot operation mode tends to be balanced.
7. An ambient temperature energy saving optimization system accounting for multi-body demand response, comprising a processor and a memory, the memory storing a computer program, the processor performing the steps of the method of any one of claims 1 to 6 when the computer program is run.
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| CN117784736B (en) * | 2024-02-23 | 2024-04-26 | 连云港智拓节能电气有限公司 | Intelligent building energy management method based on Internet of things technology |
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