CN113991655B - Method, device and medium for evaluating load aggregation demand response potential of fixed-frequency air conditioner - Google Patents
Method, device and medium for evaluating load aggregation demand response potential of fixed-frequency air conditioner Download PDFInfo
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Abstract
The invention relates to a method, a device and a medium for evaluating load aggregation demand response potential of a fixed-frequency air conditioner, wherein the method comprises the following steps: establishing a cluster fixed-frequency air conditioner approximate aggregation model; calculating an initial adjustable margin of indoor temperature of a fixed-frequency air conditioner user and a user willingness degree influence factor; calculating the actual elastic controlled temperature range of the constant-frequency air conditioner load according to the indoor temperature initial adjustable margin and the user willingness degree influence factor; obtaining user controllability; according to the approximate aggregation model of the cluster fixed-frequency air conditioner and the actual elastic controlled temperature range of the user controllability, a fixed-frequency air conditioner load aggregation demand response potential evaluation model is established, and according to the model, the fixed-frequency air conditioner load elastic aggregation response potential adopting temperature control in a direct load control mode is calculated. Compared with the prior art, the method has the advantages of considering multiple response potential influence factors and being high in accuracy.
Description
Technical Field
The invention relates to the technical field of smart grids, in particular to a method, a device and a medium for evaluating load aggregation demand response potential of a fixed-frequency air conditioner.
Background
With the continuous improvement of the modernization level, the renewable energy source is developed greatly, and the improvement of the utilization efficiency of the energy source has become social consensus. Solar power generation and wind power generation are widely popularized. At present, the active regulation capability of a 'power supply side' in a high-proportion renewable energy power grid is degraded, and the stable and safe operation of the power grid is not favored by only depending on the regulation of the power supply side. Therefore, in order to ensure safe and effective operation of the power grid, it is imperative to develop the load side regulation capability.
The air conditioner load becomes an important demand response resource of the electric power system, the maximum load reduction capacity which can be achieved by the temperature control of a fixed-frequency air conditioner cluster in a certain distribution network area in a demand response event is quantitatively analyzed through the air conditioner load response potential evaluation, and the fixed-frequency air conditioner load is relatively scattered due to the fact that the type and the parameter of the fixed-frequency air conditioner load are different and the distribution of the fixed-frequency air conditioner load is relatively scattered, so that the electric power system dispatching center is difficult to acquire the aggregate power and the demand response potential of the electric power system dispatching center and develop dispatching control, and the response potential exertion is limited.
At present, scholars at home and abroad develop extensive research and engineering application aiming at large-scale air conditioner load response potential evaluation. At present, when the load response potential of the constant-frequency air conditioner is evaluated, only the influence of human body thermal comfort factors on the potential of the constant-frequency air conditioner to participate in the demand response is often considered, the response potential evaluation consideration factors are often single, and the factors influencing the constant-frequency air conditioner to participate in the demand response potential are not considered yet, so that the accuracy of an evaluation model is not high.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method, a device and a medium for evaluating the load aggregation demand response potential of a fixed-frequency air conditioner, which have multiple response potential influence factors and high accuracy.
The aim of the invention can be achieved by the following technical scheme:
a constant-frequency air conditioner load aggregation demand response potential evaluation method comprises the following steps:
establishing a cluster fixed-frequency air conditioner approximate aggregation model;
calculating an initial adjustable margin of indoor temperature of a fixed-frequency air conditioner user and a user willingness degree influence factor;
calculating the actual elastic controlled temperature range of the constant-frequency air conditioner load according to the indoor temperature initial adjustable margin and the user willingness degree influence factor;
obtaining user controllability;
according to the approximate aggregation model of the cluster fixed-frequency air conditioner and the actual elastic controlled temperature range of the user controllability, a fixed-frequency air conditioner load aggregation demand response potential evaluation model is established, and according to the model, the fixed-frequency air conditioner load elastic aggregation response potential adopting temperature control in a direct load control mode is calculated.
When the fixed-frequency air conditioner load aggregation demand response potential evaluation model is established, the indoor temperature initial adjustable margin aiming at the user thermal comfort level, the user controllability representing the user participation degree and the user willingness degree influence factor aiming at the user participation response willingness degree are comprehensively considered, and multiple response potential influence factors are considered, so that the fixed-frequency air conditioner load aggregation response characteristic is comprehensively expressed, and the accuracy of the fixed-frequency air conditioner load response potential evaluation is improved.
Further, the cluster fixed-frequency air conditioner load aggregation power at the current moment is obtained through a cluster fixed-frequency air conditioner approximate aggregation model.
Further, the expression of the cluster fixed-frequency air conditioner approximate aggregation model is as follows:
wherein ,aggregating power estimation values for the loads of the fixed-frequency air conditioners, wherein N is the number of the fixed-frequency air conditioners, and the number of the fixed-frequency air conditioners is +.> and />The upper and lower bounds of the load aggregate power of N fixed-frequency air conditioners are respectively shown, E (X) and E (Y) are respectively the mathematical expectation of random variables X and Y, delta i 、η i and Ri The width of a temperature dead zone, the energy efficiency ratio of the air conditioner and the equivalent thermal resistance of a room corresponding to the ith fixed-frequency air conditioner are respectively theta set,i Setting value theta for temperature of ith fixed-frequency air conditioner a Is outdoor temperature;
the cluster fixed-frequency air conditioner load aggregation running power at the current moment can be obtained only through the outdoor temperature at the current moment and the air conditioner temperature set value, and the calculated amount of a dispatching center is greatly reduced.
Further, the alpha is 0.5, and the constant-frequency air conditioner has load elastic aggregation response potential delta L DPACmax The calculation formula of (2) is as follows:
wherein, xi is the user controllability, N is the number of fixed-frequency air conditioners, eta is the air conditioner energy efficiency ratio, R is the room equivalent thermal resistance, theta a Is the outdoor temperature, L t DPAC0 For the initial aggregate power of the air conditioner,is the upper limit of the actual elastic controlled temperature range.
Further, the calculating process of the indoor temperature initial adjustable margin comprises the following steps of;
constructing a predicted average vote number index PMV for describing the thermal comfort degree through a Franker thermal comfort degree equation, and quantifying the influence of indoor temperature on the human comfort degree of a user;
obtaining the value I of PMV PMV The relation expression with the indoor temperature theta is specifically as follows:
according to I PMV And the set threshold value of the fixed-frequency air conditioner indoor temperature initial adjustable margin is determined.
Further, the calculation formula of the user willingness degree influence factor is as follows:
wherein ,pbase The expected electricity price for the user, p real For the current electricity price, p max Mu, the highest electricity price i,t The user willingness degree influence factor of the ith air conditioner terminal user at the moment t is that E is the education level of the user, I is the household income of the user, A is the average age of the household of the user, and a 1 、a 2 、a 3 、a 4 、ω 1 、ω 2 、ω 3 and ω4 Is set as a value of 0 to a 1 ≤a 2 ≤a 3 ≤1，0≤a 4 ≤1；
When the current electricity price is higher than the expected electricity price of the user, the electricity cost is higher than the psychological expected electricity cost of the user, the user hopefully receives the instruction of the dispatching center to participate in the demand response to obtain subsidies, the electricity cost is reduced, the requirement on the thermal comfort degree is reduced, the indoor temperature adjustable margin is increased, otherwise, the user is more careful about the thermal comfort degree, the possibility of receiving participation in the demand response is lower, the indoor temperature adjustable margin is relatively reduced, in addition, the receiving degree of the user on the demand response is related to household income, education degree and age of the user, so that a user receiving degree model is established, the willingness degree of the user to accept the demand response control is described, and the accuracy is high.
Further, the calculation formula of the actual elastic controlled temperature range of the constant-frequency air conditioner load is as follows:
wherein , and />The upper limit and the lower limit of the initial adjustable margin of the temperature of the ith constant-frequency air conditioner at the moment t are respectively, mu i,t User willingness influence factor of ith air conditioner terminal user at t moment +.> and />Respectively the upper limit and the lower limit of the actual elastic controlled temperature range, delta theta i,t And (5) adjusting the temperature margin of the terminal aiming at the ith constant-frequency air conditioner at the t moment.
Further, the user controllability is a user duty ratio provided with the terminal control device.
The constant-frequency air conditioner load aggregation demand response potential evaluation device comprises a memory and a processor, wherein the memory stores a computer program, and the processor calls the program instructions to execute the evaluation method.
A computer readable storage medium comprising a computer program executable by a processor to implement the described evaluation method.
Compared with the prior art, the invention has the following beneficial effects:
(1) When the fixed-frequency air conditioner load aggregation demand response potential evaluation model is built, the indoor temperature initial adjustable margin aiming at the user thermal comfort level, the user controllability for representing the user participation degree and the user willingness degree influence factor aiming at the user participation response willingness degree are comprehensively considered, and multiple response potential influence factors are considered, so that the fixed-frequency air conditioner load aggregation response characteristic is comprehensively expressed, and the accuracy of the fixed-frequency air conditioner load response potential evaluation is improved;
(2) According to the invention, the cluster fixed-frequency air conditioner load aggregation operation power at the current moment can be obtained only according to the outdoor temperature at the current moment and the air conditioner temperature set value through the cluster fixed-frequency air conditioner approximate aggregation model, so that the calculated amount of a dispatching center is greatly reduced;
(3) The user willingness influence factor considers the influence of the current electricity price on the user willingness, when the current electricity price is higher than the user expected electricity price, the electricity cost is higher than the user psychological expected electricity cost, the user hopefully accepts the scheduling center to instruct the participation demand response to acquire the subsidy, the electricity cost is reduced, the thermal comfort requirement is reduced, the indoor temperature adjustable margin is increased, otherwise, the user is more conscious of the thermal comfort level, the possibility of accepting the participation demand response is lower, the indoor temperature adjustable margin is relatively reduced, and the evaluation accuracy is improved;
(4) The user willingness degree influence factor considers the influence of education level, household income and average age of the user, and the accuracy of the evaluation result is high.
Drawings
FIG. 1 is a time graph of a single fixed frequency air conditioner on-off state;
FIG. 2 is a time graph of the indoor temperature corresponding to FIG. 1;
FIG. 3 is a user thermal comfort diagram;
FIG. 4 is a graph of aggregate power versus;
FIG. 5 is an aggregate power error analysis plot;
FIG. 6 is a typical day air conditioning load aggregate power map in summer;
FIG. 7 is a user acceptance graph;
FIG. 8 is a graph of an air conditioner temperature elastic adjustable interval;
FIG. 9 is a graph of response potential for each period;
FIG. 10 is a schematic flow chart of the method of the present invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
Example 1
A method for evaluating the load aggregation demand response potential of a constant-frequency air conditioner is shown in fig. 10, and comprises the following steps:
establishing a cluster fixed-frequency air conditioner approximate aggregation model;
calculating an initial adjustable margin of indoor temperature of a fixed-frequency air conditioner user and a user willingness degree influence factor;
calculating the actual elastic controlled temperature range of the constant-frequency air conditioner load according to the indoor temperature initial adjustable margin and the user willingness degree influence factor;
obtaining user controllability;
according to the approximate aggregation model of the cluster fixed-frequency air conditioner and the actual elastic controlled temperature range of the user controllability, a fixed-frequency air conditioner load aggregation demand response potential evaluation model is established, and according to the model, the fixed-frequency air conditioner load elastic aggregation response potential adopting temperature control in a direct load control mode is calculated.
When the fixed-frequency air conditioner load aggregation demand response potential evaluation model is established, the indoor temperature initial adjustable margin aiming at the user thermal comfort level, the user controllability representing the user participation degree and the user willingness degree influence factor aiming at the user participation response willingness degree are comprehensively considered, and multiple response potential influence factors are considered, so that the fixed-frequency air conditioner load aggregation response characteristic is comprehensively expressed, and the accuracy of the fixed-frequency air conditioner load response potential evaluation is improved.
And acquiring the load aggregation power of the cluster fixed-frequency air conditioner at the current moment through the cluster fixed-frequency air conditioner approximate aggregation model.
The monomer fixed-frequency air conditioner approximate polymerization model is often an equivalent thermal parameter model, the model is suitable for modeling of cold/heat load of residents or small commercial buildings, the first-order equivalent thermal parameter model can effectively describe the change of room temperature, and the expression is as follows:
Q＝ηP
wherein θ (t) and θ a (t) is the indoor temperature and the outdoor temperature at the moment t respectively, the unit is the room equivalent heat capacity, the unit is kW.h/DEGC, the unit is the room equivalent thermal resistance, the unit is the speed/kW, the unit is the refrigerating/heating power of the air conditioner, the unit is kW, eta is the air conditioner energy efficiency ratio, P is the electric power for a single fixed-frequency air conditioner, m (t) represents the on-off state of the fixed-frequency air conditioner, the values are 0 and 1 respectively represent the stop and start, epsilon is a time lag which is small enough, and can be equal to the simulation time step under the discrete simulation environment, theta - and θ+ And respectively representing upper and lower boundary values of indoor temperature in a normal running state of the air conditioner, wherein delta is the width of a temperature dead zone of the fixed-frequency air conditioner.
As shown in fig. 1 and 2, when the temperature set value is constant, the on-off state of the air conditioner is periodically changed, and the corresponding indoor temperature is also periodically changed within the upper and lower limits.
Solving the first-order equivalent thermal parameter model to obtain the starting period T of the air conditioner on And a shutdown period T off The method comprises the following steps of:
electric power P for single fixed-frequency air conditioner i The method can be obtained through the equivalent thermal parameter model, but for a power system dispatching center, how to obtain the aggregated power of a large number of fixed-frequency air conditioners after aggregation is the most concerned, and N fixed-frequency air conditioners are at tThe aggregate power at time instant can be expressed as:
wherein ,Pagg And (t) is the aggregate power of the fixed-frequency air conditioner at the moment t, and is only related to the quantity of the air conditioners in the starting state at the moment t.
Under the steady state condition, the average power consumption of the single fixed-frequency air conditioner is related to the duty ratio of the starting period to the whole operation period, so that the probability that the ith fixed-frequency air conditioner is in the starting state is Pon, i, and the operation duty ratio is expressed as:
considering that the number N of the fixed-frequency air conditioners is large enough, and each fixed-frequency air conditioner operates independently, when the external temperature is constant, according to the law of large numbers, the aggregate power of the N fixed-frequency air conditioners can be approximately expressed as:
the duty cycle can thus be further deduced:
at this time, according to the inequality transformation in higher mathematics, the above formula can be further transformed into:
and then push out:
the upper limit and the lower limit of the operation duty ratio of the cluster fixed-frequency air conditioner are deduced, and the upper limit and the lower limit of the operation power of the cluster fixed-frequency air conditioner can be estimated through the upper limit and the lower limit of the duty ratio:
wherein , and />Respectively the upper and lower bounds delta of N fixed-frequency air conditioner load aggregate powers i 、η i and Ri The width of a temperature dead zone, the energy efficiency ratio of the air conditioner and the equivalent thermal resistance of a room corresponding to the ith fixed-frequency air conditioner are respectively theta set,i Setting value theta for temperature of ith fixed-frequency air conditioner a For outdoor temperatures, E (X) and E (Y) are mathematical expectations of random variables X and Y, respectively, the calculation formulas are as follows,
wherein, the fixed frequency air conditioner load aggregate power estimated value available intervalExpressed as:
the above model is an approximate aggregation model of the cluster fixed-frequency air conditioner, according to which the load aggregation operation power of the cluster fixed-frequency air conditioner at the current moment can be obtained only through the outdoor temperature and the air conditioner temperature set value at the current moment, so that the calculated amount of a dispatching center is greatly reduced.
The calculation process of the indoor temperature initial adjustable margin comprises the following steps of;
constructing a predicted average ballot number index (predicted mean vote, PMV) for describing the thermal comfort through a Franker thermal comfort equation, quantifying the influence of indoor temperature on the human comfort of a user, wherein the relation between a PMV value and human feel is shown in FIG. 3, and the smaller the PMV value, the higher the representing the user comfort;
obtaining the value I of PMV PMV The relation expression with the indoor temperature theta is specifically as follows:
the PMV value is minimum at room temperature of 26 ℃ according to I PMV The initial adjustable margin of the indoor temperature of the fixed-frequency air conditioner is determined by the set threshold value of the fixed-frequency air conditioner, when the value of the PMV given by the international standard ISO7730 is between minus 0.5 and 0.5, the user is in the optimal comfort state, and the corresponding indoor temperature is 24.8-27.3 ℃, namely the initial adjustable margin of the indoor temperature of the fixed-frequency air conditioner is obtained.
The calculation formula of the user willingness degree influence factor is as follows:
wherein ,pbase The expected electricity price for the user, p real For the current electricity price, p max Mu, the highest electricity price i,t The user willingness degree influence factor of the ith air conditioner terminal user at the moment t is that E is the education level of the user, I is the household income of the user, A is the average age of the household of the user, and a 1 、a 2 、a 3 、a 4 、ω 1 、ω 2 、ω 3 and ω4 Is set as a value of 0 to a 1 ≤a 2 ≤a 3 ≤1，0≤a 4 ≤1，ω 4 A threshold for user intent to be affected by household income. Mu (mu) i,t In order to be positive, the user has high acceptance of the demand response, and when mu is i,t When the value is negative, the user responds to the demand with a negative attitude, and the value reflects the degree of acceptance of the user.
When the current electricity price is higher than the expected electricity price of the user, the electricity cost is higher than the psychological expected electricity cost of the user, the user hopefully accepts the instruction of the dispatching center to participate in the demand response to acquire subsidies, the electricity cost is reduced, the requirement on the thermal comfort degree is reduced, the indoor temperature adjustable margin is increased, otherwise, the user is more careful about the thermal comfort degree level, the possibility of accepting the participation demand response is lower, the indoor temperature adjustable margin is relatively reduced, in addition, the acceptance degree of the user on the demand response is closely related to the household income, the education degree and the age of the user, and the high-income household user response compensation is not attractive and insensitive to the change of the electricity price; the users and young users with high education degree are faster to accept new things, and the users and young users are more active to participation response, and the influence of the factors is respectively based on the influence coefficient of the education level of the usersHousehold income influence coefficient->Mean age influence coefficient->To indicate that the three determine subjective response coefficient together>The acceptance of the user to the demand response of the power system is reflected, so that a user acceptance model is established, the willingness degree of the user to accept the demand response control is described, and the accuracy is high.
The calculation formula of the actual elastic controlled temperature range of the constant-frequency air conditioner load is as follows:
wherein , and />The upper limit and the lower limit of the initial adjustable margin of the temperature of the ith constant-frequency air conditioner at the moment t are respectively, mu i,t User willingness influence factor of ith air conditioner terminal user at t moment +.> and />Respectively the upper limit and the lower limit of the actual elastic controlled temperature range, delta theta i,t For the temperature margin adjustment quantity of the ith fixed-frequency air conditioner fixed terminal at the t moment, delta theta i,t Size and mu i,t Proportional to the ratio.
The user controllability is the user duty ratio provided with the terminal control equipment, the rich practical experience of the demand response test point project is developed for many times abroad, the intelligent power grid construction and the rapid development of the intelligent Internet of things in recent ten years of China are comprehensively considered, and reasonable assumption can be made on the user duty ratio provided with the terminal control equipment. The SmartAC project of PG & E in 2009 controls the air conditioning load under four distribution feeders and evaluates its potential to participate in auxiliary services, and the results show that: the controllability of two feeder lines reaches 80%, and the controllability of the other two feeder lines approaches 60%. Although the actual implementation Demand Response (DR) projects of China are fewer, the proportion of users with terminal control equipment is relatively low, the intelligent power grid construction and the rapid development of the intelligent internet of things in recent decade of China are comprehensively considered, great progress is made, and the current user controllability xi is reasonably assumed to be 60%.
When the initial temperature of the air conditioner is set to be theta in the period t set,i Simulation comparison determines that the approximate aggregation model of the cluster fixed-frequency air conditioner is most accurate when alpha is 0.5, and at this timeThe method comprises the following steps:
air conditioner aggregate power L t DPAC The adjustable interval of (2) is as follows:
wherein , and />The lower limit and the upper limit of the air conditioner aggregate power adjustable interval are respectively +.>To set the value of theta at the initial temperature set,i And when the initial aggregate power of the air conditioner is the same, the maximum load reduction capacity of the cluster air conditioner load, namely the maximum potential of demand response is as follows:
in the embodiment, simulation analysis is performed by taking a distribution network system containing a large number of fixed-frequency air conditioner loads as an example, the accuracy of the provided fixed-frequency air conditioner load aggregation demand response potential evaluation method based on the influence of multiple factors of users is verified, and 10000 fixed-frequency air conditioners are assumed to be contained in a distribution network district, and parameters of the 10000 fixed-frequency air conditioners are uniformly distributed in the range of a table 1;
table 1 air conditioner load parameter ranges
And (3) verifying an approximate polymerization model of the monomer fixed-frequency air conditioner: and establishing a monomer fixed-frequency air conditioner approximate polymerization model for the fixed-frequency air conditioner in the distribution network system, performing polymerization simulation by adopting a Monte Carlo method, obtaining actual power, and comparing the polymerization power with the actual power by taking the actual power as a reference. The outdoor temperature was considered to be approximately constant over a time span of one hour, and the simulation results are shown in fig. 4 with the outdoor temperature being 32 ℃.
As can be seen from fig. 4, after the load of 10000 fixed-frequency air conditioners is approximately aggregated, the upper limit and the lower limit of the aggregated power are 4237KW and 3721KW respectively, when alpha is 0.5, the estimated value of the aggregated power is 3979KW, the actual running power value of the fixed-frequency air conditioner is well enveloped in the upper limit and the lower limit of the estimated value, the error between the estimated value and the estimated value is as shown in fig. 5, and as can be seen from fig. 5, the relative error between the estimated value of the aggregated power and the actual value of Monte Carlo simulation is lower than 5%, the aggregated precision can meet the requirement of a dispatching center of an electric power system, and the outdoor temperature theta at the current moment is only used α And the air conditioner temperature set value theta set The cluster fixed-frequency air conditioner load aggregate power at the current moment can be calculated, and the calculation complexity of acquiring a large amount of fixed-frequency air conditioner aggregate power in the district by the power system dispatching center is greatly reduced. The daily constant-frequency air conditioner load aggregate power is obtained through the model aggregate by combining the typical daily outdoor temperature change in summer, and is shown in figure 6.
Analysis of polymerization response potential: to evaluate the actual aggregate response potential of the regular frequency air conditioner clusters in the power distribution network, the electric charge p is based on the time-of-day electric charge in the time-of-use electric charge based on the actual data of education level, income, age and the like of household users in Shanghai region base The acceptance of the user participation demand response in each period is analyzed as shown in fig. 7, wherein the time-of-use electricity prices are shown in table 2:
TABLE 2 time-of-use electricity price
In the period of 24:00-7:00, the electricity price is lower than the basic electricity price, and the user willingness degree influence factor is-0.1663, so that the user is negative in participation in demand response willingness in the period; in the time periods of 7:00-10:00, 13:00-16:00 and 21:00-24:00, the electricity price is equal to the basic electricity price, the user willingness degree influence factor is 0, and the user participation demand response willingness is in a neutral attitude in the time period; in the time periods of 10:00-15:00 and 18:00-21:00, the electricity price is higher than the basic electricity price, and the influence factor of the user willingness degree is 0.2439, so that the user is positive in demand response attitude.
The actual elastic controlled temperature range of the fixed-frequency air conditioner load is shown in fig. 8, and as can be seen from fig. 8, in the period that the user has low acceptance of participation demand response, the temperature of the fixed-frequency air conditioner is not excessively regulated by the user, the adjustable range is 25.2-26.9 ℃, and the adjustable range is slightly smaller than the initial adjustable margin of the indoor temperature of the fixed-frequency air conditioner; in the period of taking the electricity price as the basic electricity price, the user acceptance parameter is 0, the participation demand response is kept in a neutral attitude, and the aggregator is allowed to control on the premise of ensuring the basic thermal comfort demand; during periods of high user acceptance, it is desirable to sacrifice a portion of thermal comfort appropriately in exchange for subsidy, where the adjustable temperature range is 24.2-27.9 ℃.
Assuming that the initial temperature set values of the set-frequency air conditioner clusters are uniformly distributed within 25-27 ℃, wherein the initial temperature set values are expected to be 26 ℃, the current user controllability is considered to be 60%, the maximum load reduction capacity of the set-frequency air conditioners in each time period is calculated by the cluster set-frequency air conditioner approximate aggregation model provided by the embodiment, the calculation result is shown in fig. 9, the observation of fig. 9 is available, the user acceptability is low in time period, the temperature adjustable range is small, and the response potential is only 368.3KW; the user participates in the demand response and maintains the neutral attitude period, the temperature adjustment needs to meet the basic thermal comfort demand of the user, and the response potential is 518.7KW at the moment; the user acceptance is higher, the temperature adjustable interval is further expanded, the response potential reaches 739.1KW, and therefore, the evaluation method provided by the embodiment can further mine the elastic temperature adjustable range which can be embodied by the user for the electricity price and the acceptance degree of the self-participation demand response at different moments on the basis of the traditional evaluation method only based on the user thermal comfort response potential, and the load elastic aggregation response potential of the constant-frequency air conditioner at different time intervals can be accurately and effectively evaluated by combining with the user controllability.
Example 2
A constant frequency air conditioner load aggregate demand response potential evaluation device comprises a memory and a processor, wherein the memory stores a computer program, and the processor calls the program instructions to execute the evaluation method in the embodiment 1.
Example 3
A computer-readable storage medium comprising a computer program executable by a processor to implement the evaluation method of embodiment 1.
The embodiment 1, the embodiment 2 and the embodiment 3 provide a method, a device and a medium for evaluating the load aggregation demand response potential of a fixed-frequency air conditioner, on the basis of analyzing the influence of various factors of a user angle on the load aggregation demand response potential of the fixed-frequency air conditioner, a cluster fixed-frequency air conditioner approximate aggregation model is established by adopting a large number theorem and inequality derivation based on a first-order equivalent thermal parameter model of the fixed-frequency air conditioner, and the running power of a fixed-frequency air conditioner load cluster is obtained; based on the aggregation model, multiple factors such as user comfort, acceptance and controllability are comprehensively considered, a constant-frequency air conditioner load aggregation demand response potential evaluation model under the influence of multiple factors of a user is established, and constant-frequency air conditioner aggregation response potential is excavated, so that multiple response potential influence factors are considered, the load aggregation response characteristic of the constant-frequency air conditioner is comprehensively expressed, and the accuracy of constant-frequency air conditioner load response potential evaluation is improved.
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (4)
1. The method for evaluating the load aggregation demand response potential of the constant-frequency air conditioner is characterized by comprising the following steps of:
establishing a cluster fixed-frequency air conditioner approximate aggregation model;
calculating an initial adjustable margin of indoor temperature of a fixed-frequency air conditioner user and a user willingness degree influence factor;
calculating the actual elastic controlled temperature range of the constant-frequency air conditioner load according to the indoor temperature initial adjustable margin and the user willingness degree influence factor;
obtaining user controllability;
establishing a fixed-frequency air conditioner load aggregation demand response potential evaluation model according to an approximate aggregation model of the cluster fixed-frequency air conditioner and an actual elastic controlled temperature range of user controllability, and calculating fixed-frequency air conditioner load elastic aggregation response potential adopting temperature control in a direct load control mode according to the model;
the expression of the approximate aggregation model of the cluster fixed-frequency air conditioner is as follows:
wherein ,aggregating power estimation values for the loads of the fixed-frequency air conditioners, wherein N is the number of the fixed-frequency air conditioners, and the number of the fixed-frequency air conditioners is +.> and />The upper and lower bounds of the load aggregate power of N fixed-frequency air conditioners are respectively shown, E (X) and E (Y) are respectively the mathematical expectation of random variables X and Y, delta i 、η i and Ri The width of a temperature dead zone, the energy efficiency ratio of the air conditioner and the equivalent thermal resistance of a room corresponding to the ith fixed-frequency air conditioner are respectively theta set,i Setting value theta for temperature of ith fixed-frequency air conditioner a Is outdoor temperature, delta is the width of the dead zone of the temperature of the fixed-frequency air conditioner, theta set Setting the temperature of the air conditioner;
the constant-frequency air conditioner load elastic aggregation response potential delta L DPACmax The calculation formula of (2) is as follows:
wherein, xi is the user controllability, N is the number of fixed-frequency air conditioners, eta is the air conditioner energy efficiency ratio, R is the room equivalent thermal resistance, theta a For the outdoor temperature to be the same,for the initial aggregate power of the air conditioner, +.>Is the upper limit of the actual elastic controlled temperature range;
the calculation process of the indoor temperature initial adjustable margin comprises the following steps of;
constructing a predicted average vote count index PMV for describing the thermal comfort degree through a Franker thermal comfort degree equation;
obtaining the value I of PMV PMV The relation expression with the indoor temperature theta is specifically as follows:
according to I PMV Determining an initial adjustable margin of the indoor temperature of the fixed-frequency air conditioner;
the calculation formula of the user willingness degree influence factor is as follows:
wherein ,pbase The expected electricity price for the user, p real For the current electricity price, p max Mu, the highest electricity price i,t The user willingness degree influence factor of the ith air conditioner terminal user at the moment t is that E is the education level of the user, I is the household income of the user, A is the average age of the household of the user, and a 1 、a 2 、a 3 、a 4 、ω 1 、ω 2 、ω 3 and ω4 Is set as a value of 0 to a 1 ≤a 2 ≤a 3 ≤1，0≤a 4 ≤1；
The calculation formula of the actual elastic controlled temperature range of the constant-frequency air conditioner load is as follows:
wherein , and />The upper limit and the lower limit of the initial adjustable margin of the temperature of the ith constant-frequency air conditioner at the moment t are respectively, mu i,t User willingness influence factor of ith air conditioner terminal user at t moment +.> and />Respectively the upper limit and the lower limit of the actual elastic controlled temperature range, delta theta i,t The temperature margin adjustment quantity of the terminal is determined for the ith fixed-frequency air conditioner at the t moment;
the user controllability is the user duty ratio of the terminal control equipment.
2. The method for evaluating the load aggregation demand response potential of the constant-frequency air conditioner according to claim 1, wherein the cluster constant-frequency air conditioner load aggregation power at the current moment is obtained through a cluster constant-frequency air conditioner approximate aggregation model.
3. A constant frequency air conditioner load aggregate demand response potential evaluation device, comprising a memory and a processor, the memory storing a computer program, the processor invoking the program instructions capable of performing the evaluation method of any of claims 1-2.
4. A computer readable storage medium comprising a computer program executable by a processor to implement the assessment method of any of claims 1-2.
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