CN108122067B - Modeling method and system for building demand response dynamic process - Google Patents
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Abstract
The invention provides a modeling method and a system for a building demand response dynamic process, comprising the following steps: determining an electric power curve of the building electric equipment according to the temperature variation at each moment; comparing the power consumption curve with a pre-defined reference power curve to generate a demand response dynamic process simulation curve; determining fitting functions of each stage in the demand response dynamic process simulation curve; and establishing a demand response dynamic model based on the fitting function of each stage. The model can reflect complex thermodynamic relations and dynamic change processes among energy systems interacted in a building on one hand, and can meet the requirement of real-time dispatching of a power grid on the other hand, the calculation speed is high enough.
Description
Technical field:
the invention belongs to the technical field of power distribution network operation, and particularly relates to a modeling method and a system for a building demand response dynamic process.
Background
Building demand response modeling research is always one of research hotspots of students at home and abroad, and a modeling method mainly comprises a mechanism model, a data driving model or a simplified model. The mechanism model is based on the internal structure, parameters and mechanism of the building, and a corresponding thermodynamic physical model is established to accurately simulate the interaction relationship between each component and each subsystem in the system. Building load comfort represented by large markets, offices, hotels, residential houses and the like has high requirements and long continuous service time, wherein the energy consumption of isothermal control loads (Temperature Control Loads, TCLs) of a large air conditioning system accounts for more than 60% of the total energy consumption. On the premise of keeping the room temperature in the building in a comfortable range, the power consumption can be rapidly increased or reduced by adjusting the temperature set value change of the large air conditioning system, and the air conditioning system is a high-quality and precious demand response resource in a short time scale and can be used as an emergency demand response for running standby or participating in a power grid. However, for power grid dispatching, the model is relatively complex, and particularly when considering large-scale building group loads, the calculation load is greatly increased, and if specific climate conditions and household group characteristics are continuously considered, the timeliness of the result is seriously affected.
Disclosure of Invention
In order to overcome the defects that a building demand response model is relatively complex, particularly when a large-scale building group load is considered, the calculation burden is greatly increased, and meanwhile, if specific climatic conditions and household group characteristics are continuously considered, the timeliness of a result is seriously affected.
The invention aims at adopting the following technical scheme:
a method of modeling a building demand response dynamic process, the method comprising:
determining an electric power curve of the building electric equipment according to the temperature variation at each moment;
comparing the power consumption curve with a pre-defined reference power curve to generate a demand response dynamic process simulation curve;
determining fitting functions of each stage in the demand response dynamic process simulation curve;
and establishing a demand response dynamic model based on the fitting function of each stage.
Preferably, the determining the power consumption curve of the building electric equipment according to the temperature variation at each moment includes:
acquiring a temperature set value of building electric equipment at an acquisition time point within a preset sampling time range;
comparing the acquired temperature set value with a predefined reference set value to obtain a temperature change amount, and drawing a power consumption curve formed by the temperature change amount.
Further, the acquisition time point includes: defining an acquisition time point according to the current time h; if H 1 ≤h＜H 2 Defining the current time h as an acquisition time point; if h=h 2 Will be on the same day [ H 1 ,H 2 ]Each integral point in (a) is defined as an acquisition time point;
wherein H is 1 ,H 2 The upper limit and the lower limit of the normal operation time range are respectively; h is the time interval in hours.
Further, the predefined reference set point is an initial operating temperature of the building electrical equipment.
Preferably, the generating the demand response dynamic response process simulation curve includes:
simulating a comparison result of the power consumption curve and a predefined reference power curve;
and carrying out per unit processing on the curve obtained by simulation to obtain a demand response dynamic response process simulation curve.
Further, a demand response dynamic response process simulation curve is determined by:
wherein,for the base line power of the building k at the moment t, the temperature set value of the corresponding electric equipment is +.> For the electricity consumption power of the building k participating in the demand response dynamic response process at the moment t, the temperature change quantity of the corresponding electric equipment is as followsDR k (t) positive, indicating the load reduction amount of the building k participating in the demand response dynamic response process at the time t, if DR k And (t) negative indicates the load increase.
Preferably, the fitted function for each stage in the demand response dynamic process simulation curve is determined by:
wherein, the funDR (t, OAT) is the DR of the strain by adopting a regression analysis method k (t)% regression approximation fittingFitting a function in a demand response dynamic response process; t is a certain time in a day, OAT represents outdoor environment temperature at t, and fun1, fun2 and fun3 respectively represent a climbing period fitting function, a stable response period fitting function and a recovery period fitting function corresponding to three phases of a climbing period, a stable response period and a recovery period according to t in a demand response dynamic response process; t (T) 1 Indicating the moment of the start of the response, T 2 Indicating the end of the response, T start Indicating duration of climbing period, T restore Indicating the duration of the recovery period.
Further, establishing a demand response dynamic model according to fitting functions fun1, fun2 and fun3 of each stage in the demand response dynamic process simulation curve, including:
the demand response dynamic model of the climbing period is determined by:
the demand response dynamic model for the stable response period is determined by:
fun2(t,OAT)＝a 2,h (h,OAT)+b 2,h (h,OAT)OAT,t∈h (5)
the demand response dynamic model for the recovery period is determined by:
wherein a is 1,h 、b 1,h A represents a temperature time-varying parameter corresponding to a fun1 hill climbing response function 2,h And b 2,h Representing a temperature time-varying constant corresponding to the fun2 stable response function; a, a 3,h 、b 3,h Representing a temperature time-varying parameter corresponding to a fun3 response recovery function, a 3,h ＜0。
Further, the predefined reference power curve is obtained by simulating annual historical electric power of the building electric equipment based on energy plus software.
A modeling system for a building demand response dynamic process, comprising:
the determining module is used for determining the power utilization curve of the building electric equipment according to the temperature variation at each moment;
the comparison module is used for comparing the power consumption curve with a predefined reference power curve to generate a demand response dynamic process simulation curve;
the fitting module is used for determining fitting functions of all stages in the simulation curve of the demand response dynamic process;
and the construction module is used for constructing a demand response dynamic model based on the fitting function of each stage.
Preferably, the determining module includes:
the acquisition unit is used for acquiring a temperature set value of the building electric equipment at an acquisition time point within a preset sampling time range;
the comparison unit is used for respectively comparing the temperature set values at different moments with a predefined reference set value to obtain the temperature variation at each moment;
and a drawing unit for drawing a power consumption curve constituted by the temperature variation.
Compared with the closest prior art, the invention has the beneficial effects that:
the modeling method and the modeling system for the building demand response dynamic process provided by the invention are used for determining the power utilization curve of the building electric equipment according to the temperature variation at each moment; comparing the power consumption curve with a pre-defined reference power curve to generate a demand response dynamic process simulation curve; determining fitting functions of each stage in the demand response dynamic process simulation curve; on the basis of the fitting function of each stage, a demand response dynamic model is established, so that on one hand, the calculation load is greatly reduced, the real-time scheduling requirement and timeliness of a power grid are guaranteed, and on the other hand, the severe fluctuation of load power caused by participation of building load in demand response in the control process can be avoided, and the demand response dynamic model becomes a reliable demand response resource on a short time scale.
According to the modeling method and system for the building demand response dynamic process, key influence factors influencing the commercial building demand response dynamic process can be analyzed based on the fitting function of each stage, and a demand response dynamic model is built. The method specifically comprises the steps of establishing fitting functions of a climbing period, a stable response period and a recovery period, simplifying a demand response dynamic simulation process, reflecting complex thermodynamic relation and dynamic change process among interactive energy systems in a building, enabling calculation to be fast enough, meeting the requirement of power grid real-time scheduling, adding the dynamic process of demand response into the construction of a model, and respectively formulating power grid control strategies according to model characteristics of each stage, so that the power grid control strategies corresponding to the model can be executed in time intervals or simultaneously, the flexibility is high, the pertinence and the effectiveness of power grid power balance control are improved, and accordingly the impact of steep rise and steep fall of aggregate power on a power grid is effectively relieved.
Drawings
FIG. 1 is a flow chart of a modeling method of a building demand response dynamic process provided in an embodiment of the present invention;
FIG. 2 is a schematic diagram of a dynamic response process for a typical building participation demand response provided in an embodiment of the present invention;
the specific embodiment is as follows:
the active participation of the demand response resources in the power balance control of the power grid has a positive effect on the system operation, however, the steep rise and steep fall of the aggregate power in the dynamic response process of a large amount of demand response resources often have a great impact on the active balance of the power grid.
In order to facilitate a dispatching center to analyze, predict and master the aggregation characteristics of demand response dynamic processes of large-scale diversified building loads in time, the invention provides a modeling method and a modeling system of a building demand response dynamic process, and the modeling method and the modeling system are described below.
Example 1,
As shown in fig. 1, the modeling method of the building demand response dynamic process may include:
s1, determining an electric power curve of typical building electric equipment according to the temperature variation at each moment;
acquiring a temperature set value of building electric equipment at an acquisition time point within a preset sampling time range;
comparing the acquired temperature set value with a predefined reference set value to obtain a temperature change amount, and drawing a power consumption curve formed by the temperature change amount. The predefined reference set point is the initial operating temperature of the construction consumer.
The acquisition time points include: defining an acquisition time point according to the current time h; if H 1 ≤h＜H 2 Defining the current time h as an acquisition time point; if h=h 2 Will be on the same day [ H 1 ,H 2 ]Each integral point in (a) is defined as an acquisition time point;
wherein H is 1 ,H 2 The upper limit and the lower limit of the normal operation time range are respectively; h is the time interval in hours.
S2, comparing the power consumption curve with a predefined reference power curve to generate a demand response dynamic process simulation curve;
generating a demand response dynamic response process simulation curve includes: simulating a comparison result of the power consumption curve and a predefined reference power curve;
and carrying out per unit processing on the curve obtained by simulation to obtain a demand response dynamic response process simulation curve.
Determining a demand response dynamic response process simulation curve by:
wherein,for the base line power of the typical building k at the time t, the temperature set value of the corresponding electric equipment is +.> For the power consumption of building k participating in the demand response dynamic response process at time t, the temperature change quantity of the corresponding electric equipment is +>DR k (t) positive, indicating the load reduction amount of the building k participating in the demand response dynamic response process at the time t, if DR k And (t) negative indicates the load increase.
S3, determining fitting functions of each stage of the simulation curve of the demand response dynamic process; determined by the following formula:
wherein, the funDR (t, OAT) is the DR of the strain by adopting a regression analysis method k (t)% fitting a fitting function of a dynamic response process of the demand response obtained by regression approximation fitting; t is a certain time of day, OAT represents outdoor ambient temperature at t, and is a key influencing factor affecting the dynamic process of response of commercial building demands. As known from a large number of mechanism model simulations based on energy plus, the building demand response dynamic process is divided into three stages of a climbing stage, a stable response stage and a recovery stage according to t, the climbing stage and the recovery stage can be approximately fitted by using exponential functions, and the stable response stage can be approximately fitted by using piecewise linear functions. Therefore, in the formula, fun1 represents a climbing fitting function, can be represented by an exponential function based on stable response, fun2 represents a stable fitting function of a stable response period, fun3 represents a response recovery fitting function of a dynamic change process, T 1 Indicating the moment of the start of the response, T 2 Indicating the end of the response, T start Indicating duration of climbing period, T restore Indicating the duration of the recovery period.
As shown by the above extensive studies, the external ambient temperature (Outside air temperature, OAT) is a key factor affecting the response of the demand response, and the effects of OAT are reflected in all of fun1, fun2 and fun 3. And analyzing parameters to be fitted and key influencing factors in the three-stage characterization function at the t moment, and establishing a functional relation between the parameters and the main influencing factors.
S4, building a demand response dynamic model based on the fitting function of each stage.
As shown in fig. 2, the dynamic response process of the typical building participating in the demand response can be divided into three phases of a climbing phase, a stable response phase and a recovery phase according to t, so that the demand response dynamic model of the typical building specifically comprises a demand response dynamic sub-model of the three phases;
establishing a demand response dynamic model according to fitting functions fun1, fun2 and fun3 of a climbing period, a stable response period and a recovery period in the demand response dynamic response process, wherein the method comprises the following steps:
the demand response dynamic model of the climbing period is determined by:
the demand response dynamic model for the stable response period is determined by:
fun2(t,OAT)＝a 2,h (h,OAT)+b 2,h (h,OAT)OAT,t∈h (5)
the demand response dynamic model for the recovery period is determined by:
wherein a is 1,h 、b 1,h A represents a temperature time-varying parameter corresponding to a fun1 hill climbing response function 2,h And b 2,h Representing a temperature time-varying constant corresponding to the fun2 stable response function; a, a 3,h 、b 3,h Representing a temperature time-varying parameter corresponding to a fun3 response recovery function, a 3,h ＜0。
Based on the model, according to the real-time power generation/power utilization balance requirement of the power grid, a reasonable building demand response control strategy can be formulated for smooth control, so that on one hand, the calculation load is greatly reduced, the real-time scheduling requirement and timeliness of the power grid are guaranteed, on the other hand, the severe fluctuation of load power caused by participation of building load in demand response in the control process can be avoided, and the power grid is a reliable demand response resource on a short time scale.
Based on the characteristics of the model, accurate electricity consumption change conditions, temperature time-varying parameters and the like in different demand response stages can be obtained. For example, the crowd temperature comfort level of the range of the building can be effectively analyzed according to the model parameters, the building room temperature is adjusted based on the temperature comfort level range, and the optimized response management of the resource at the demand side is realized, so that the energy consumption cost in the whole dispatching period is reduced. In summer, an actual power grid dispatching order is issued two hours in advance, and the actual power grid dispatching order can be to increase electricity price within one hour after the response of power demand begins. At this time, the temperature of the fresh air provided by the air conditioning system can be reduced as much as possible within the temperature comfort level range within two hours in advance, and the temperature of the fresh air provided by the air conditioning system can be closed or raised as much as possible within one hour of the power demand response. Since the indoor temperature has been low before, even if the air conditioner is turned off during the power demand response period, due to the above-described cold storage capacity, the comfort of the indoor temperature can be ensured, and at the same time, the use of expensive power supply during the power demand response period is avoided. Thereby achieving the beneficial effects of meeting the power grid dispatching instruction requirement, improving the indoor temperature and humidity comfort level and reducing the electricity consumption.
Embodiment 2, based on the same inventive concept, the present invention further provides a modeling system of a building demand response dynamic process, which may include:
the determining module is used for determining the power utilization curve of the building electric equipment according to the temperature variation at each moment;
the comparison module is used for comparing the power consumption curve with a predefined reference power curve to generate a demand response dynamic process simulation curve;
the fitting module is used for determining fitting functions of all stages in the simulation curve of the demand response dynamic process;
and the construction module is used for constructing a demand response dynamic model based on the fitting function of each stage.
Wherein, the determining module may include:
the acquisition unit is used for acquiring a temperature set value of the building electric equipment at an acquisition time point within a preset sampling time range;
the comparison unit is used for respectively comparing the temperature set values at different moments with a predefined reference set value to obtain the temperature variation at each moment;
and a drawing unit for drawing a power consumption curve constituted by the temperature variation.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application and not for limiting the scope thereof, and although the present application is described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: various alterations, modifications, and equivalents may be suggested to the particular embodiments of the application described herein, which would occur to persons skilled in the art upon reading the foregoing description and are within the scope of the claims appended hereto.
Claims (6)
1. A method of modeling a building demand response dynamic process, the method comprising:
determining an electric power curve of the building electric equipment according to the temperature variation at each moment;
comparing the power consumption curve with a pre-defined reference power curve to generate a demand response dynamic process simulation curve;
determining fitting functions of each stage in the demand response dynamic process simulation curve;
based on the fitting function of each stage, establishing a demand response dynamic model;
the method for determining the power consumption curve of the building electric equipment according to the temperature variation at each moment comprises the following steps:
acquiring a temperature set value of building electric equipment at an acquisition time point within a preset sampling time range;
comparing the acquired temperature set value with a predefined reference set value to obtain a temperature variation, and drawing a power consumption curve formed by the temperature variation;
the acquisition time point comprises: defining an acquisition time point according to the current time h; if H 1 ≤h＜H 2 Defining the current time h as an acquisition time point; if h=h 2 Will be on the same day [ H 1 ,H 2 ]Each integral point in (a) is defined as an acquisition time point;
wherein H is 1 ,H 2 The upper limit and the lower limit of the normal operation time range are respectively; h is a time interval in hours;
determining a fitting function of each stage in the demand response dynamic process simulation curve by the following formula:
wherein, the funDR (t, OAT) is the DR of the strain by adopting a regression analysis method k (t)% fitting a fitting function of a dynamic response process of the demand response obtained by regression approximation fitting; t is a certain time in a day, OAT represents outdoor environment temperature at t, and fun1, fun2 and fun3 respectively represent a climbing period fitting function, a stable response period fitting function and a recovery period fitting function corresponding to three phases of a climbing period, a stable response period and a recovery period according to t in a demand response dynamic response process; t (T) 1 Indicating the moment of the start of the response, T 2 Indicating the end of the response, T start Indicating duration of climbing period, T restore Representing a recovery period duration;
establishing a demand response dynamic model according to fitting functions fun1, fun2 and fun3 of each stage in the demand response dynamic process simulation curve, wherein the method comprises the following steps:
the demand response dynamic model of the climbing period is determined by:
the demand response dynamic model for the stable response period is determined by:
fun2(t,OAT)＝a 2,h (h,OAT)+b 2,h (h,OAT)OAT,t∈h (5)
the demand response dynamic model for the recovery period is determined by:
wherein a is 1,h 、b 1,h A represents a temperature time-varying parameter corresponding to a fun1 hill climbing response function 2,h And b 2,h Representing a temperature time-varying constant corresponding to the fun2 stable response function; a, a 3,h 、b 3,h Representing a temperature time-varying parameter corresponding to a fun3 response recovery function, a 3,h ＜0。
2. The method of claim 1, wherein the predefined baseline setting is an initial operating temperature of a construction powered device.
3. The method of claim 1, wherein generating a demand response dynamic response process simulation curve comprises:
simulating a comparison result of the power consumption curve and a predefined reference power curve;
and carrying out per unit processing on the curve obtained by simulation to obtain a demand response dynamic response process simulation curve.
4. The method of claim 3 wherein the demand response dynamic response process simulation curve is determined by:
wherein,at tSetting the temperature setting value of corresponding electric equipment to be +.> For the power consumption of building k participating in the demand response dynamic response process at time t, the temperature change quantity of the corresponding electric equipment is +>DR k (t) positive, indicating the load reduction amount of the building k participating in the demand response dynamic response process at the time t, if DR k And (t) negative indicates the load increase.
5. The method of claim 2, wherein the predefined reference power curve is obtained by simulating annual historical electric power usage of the construction consumer based on energy plus software.
6. A modeling system for a building demand response dynamic process, comprising:
the determining module is used for determining the power utilization curve of the building electric equipment according to the temperature variation at each moment;
the comparison module is used for comparing the power consumption curve with a predefined reference power curve to generate a demand response dynamic process simulation curve;
the fitting module is used for determining fitting functions of all stages in the simulation curve of the demand response dynamic process;
the building module is used for building a demand response dynamic model based on the fitting function of each stage;
the determining module includes:
the acquisition unit is used for acquiring a temperature set value of the building electric equipment at an acquisition time point within a preset sampling time range;
the comparison unit is used for respectively comparing the temperature set values at different moments with a predefined reference set value to obtain the temperature variation at each moment;
a drawing unit for drawing a power consumption curve constituted by the temperature variation;
determining a fitting function of each stage in the demand response dynamic process simulation curve by the following formula:
wherein, the funDR (t, OAT) is the DR of the strain by adopting a regression analysis method k (t)% fitting a fitting function of a dynamic response process of the demand response obtained by regression approximation fitting; t is a certain time in a day, OAT represents outdoor environment temperature at t, and fun1, fun2 and fun3 respectively represent a climbing period fitting function, a stable response period fitting function and a recovery period fitting function corresponding to three phases of a climbing period, a stable response period and a recovery period according to t in a demand response dynamic response process; t (T) 1 Indicating the moment of the start of the response, T 2 Indicating the end of the response, T start Indicating duration of climbing period, T restore Representing a recovery period duration;
establishing a demand response dynamic model according to fitting functions fun1, fun2 and fun3 of each stage in the demand response dynamic process simulation curve, wherein the method comprises the following steps:
the demand response dynamic model of the climbing period is determined by:
the demand response dynamic model for the stable response period is determined by:
fun2(t,OAT)＝a 2,h (h,OAT)+b 2,h (h,OAT)OAT,t∈h (5)
the demand response dynamic model for the recovery period is determined by:
wherein a is 1,h 、b 1,h A represents a temperature time-varying parameter corresponding to a fun1 hill climbing response function 2,h And b 2,h Representing a temperature time-varying constant corresponding to the fun2 stable response function; a, a 3,h 、b 3,h Representing a temperature time-varying parameter corresponding to a fun3 response recovery function, a 3,h ＜0。
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