Air conditioning demand response scheduling method and system considering user response willingness

Abstract

The present invention discloses a method and system for air conditioning demand response scheduling that takes into account user response willingness. The method comprises: obtaining air conditioning scheduling parameters and temperature parameters for the current scheduling period, as well as the historical cumulative response accuracy rate for the previous scheduling period, constructing a demand response scheduling model and corresponding constraints with the goal of maximizing the benefits obtained from user participation in scheduling and minimizing user room temperature dissatisfaction; then, when a first indoor temperature range meets the room temperature constraint, solving the demand response scheduling model under each constraint condition to obtain the air conditioning scheduling power value for each air conditioner in the current scheduling period, and sending the air conditioning scheduling power value to a demand response terminal device, so that the demand response terminal device schedules the operating power of each air conditioner. By implementing the present invention, the differences in the response willingness of different users to participate in air conditioning scheduling can be fully considered, reducing the deviation of air conditioning scheduling.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning demand response scheduling, and in particular to an air conditioning demand response scheduling method and system that takes user response willingness into consideration. Background Art

[0002] With economic and social development and improved living standards, electricity demand continues to rise, especially during the hot summer months. Excessive load pressure poses a challenge to the safe and stable operation of the power grid. To alleviate this pressure and improve the flexibility and efficiency of the power system, demand response scheduling has emerged. Demand response scheduling involves electricity users or load management systems voluntarily adjusting their electricity consumption patterns based on power availability, price signals, or other incentives to optimize the balance between supply and demand. Through appropriate scheduling strategies, users can be guided to adjust their air conditioning usage, reduce peak loads, and achieve a balanced supply and demand, while minimizing the impact on their comfort.

[0003] Existing technologies only consider the user's power adjustment constraints, revenue, and post-scheduled temperature comfort when calculating the power reduction value for the user's air conditioner. They fail to consider the differences in user willingness to adjust power. Even for users with the same objective conditions, varying willingness to respond can lead to variations in their performance for the same power reduction value, resulting in significant scheduling errors. Summary of the Invention

[0004] The present invention provides an air conditioning demand response scheduling method and system that takes into account user response willingness, which can fully consider the differences in response willingness of different users to participate in air conditioning scheduling, thereby reducing the deviation of air conditioning scheduling.

[0005] An embodiment of the present invention provides an air conditioning demand response scheduling method that takes into account user response willingness, including:

[0006] Obtain the air conditioning scheduling parameters for the current scheduling period, the temperature parameters at the start of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period; wherein the air conditioning scheduling parameters include: total scheduling power value, electricity price, unit incentive income, actual duration of the unit period, user response willingness probability value, maximum operating power, and minimum operating power; the temperature parameters include: indoor temperature, outdoor temperature, thermal resistance of indoor temperature change, and thermal capacity of outdoor temperature change; the historical cumulative response accuracy of the previous scheduling period is calculated by the demand response terminal device based on the actual air conditioning operating power at the start of the current scheduling period, the actual air conditioning operating power at the start of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period;

[0007] Based on the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, a demand response scheduling model and constraints of the demand response scheduling model are constructed with the goal of maximizing the benefits obtained by users participating in scheduling while minimizing users' room temperature dissatisfaction. The constraints include room temperature constraints, operating power constraints, and total scheduling response constraints.

[0008] Calculating a first indoor temperature range based on the maximum operating power, the minimum operating power, and the temperature parameter, and comparing the first indoor temperature range with the room temperature constraint;

[0009] When the above-mentioned first indoor temperature range meets the above-mentioned room temperature constraints, the above-mentioned demand response scheduling model is solved under each of the above-mentioned constraints to obtain the air-conditioning scheduling power value of each air-conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized, and the above-mentioned air-conditioning scheduling power value is sent to the above-mentioned demand response terminal device, so that the above-mentioned demand response terminal device schedules the operating power of each air-conditioner according to the above-mentioned air-conditioning scheduling power value.

[0010] Furthermore, based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period, the historical cumulative response accuracy of the previous scheduling period is calculated, including:

[0011] The response accuracy of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period;

[0012] According to the response accuracy rate of the previous scheduling period, the historical cumulative response accuracy rate of the previous scheduling period is calculated.

[0013] Furthermore, the objective function of the above demand response scheduling model is:

[0014] W n,t =(c t +π t )·ξ n,t ·Δt

[0015] S n,t =(θ n,t,end -26) 2

[0016]

[0017] p n,t,rum =p n,t -ξn,t

[0018] θ n,t,end =α n θ n,t,in +(1-α n )(θ n,t,out -R n p n,t,rum )

[0019]

[0020] Where W n,t represents the user economic value of the nth air conditioner in the current scheduling period t, c t represents the electricity price in the current dispatch period t, π t represents the unit incentive income in the current scheduling period t, Δt represents the actual duration of the current scheduling period t, S n,t represents the room temperature dissatisfaction corresponding to the nth air conditioner in the current scheduling period t, θ n,t,end It indicates the indoor temperature of the nth air conditioner at the end of the current scheduling period t, assuming that the user strictly follows the air conditioning scheduling power value of the current scheduling period. n represents the inertia coefficient of the nth air conditioner, R n Indicates the thermal resistance corresponding to the nth air conditioner, C n represents the heat capacity corresponding to the nth air conditioner, p n,t,rum It means that if the user strictly follows the air conditioning scheduling power value of the current scheduling period, the air conditioning operating power of the nth air conditioner in the current scheduling period t, p n,t represents the actual operating power of the nth air conditioner in the current scheduling period t, ξ n,t represents the air conditioning scheduling power value of the nth air conditioner in the current scheduling period t, θ n,t,in represents the indoor temperature corresponding to the nth air conditioner at the beginning of the current scheduling period t, θ n,t,out It represents the outdoor temperature of the nth air conditioner at the beginning of the current scheduling period t, N represents the total number of air conditioners to be scheduled, h n,t represents the user credibility of the nth air conditioner in the current scheduling period t, ρ n,t represents the probability value of the user's response willingness of the nth air conditioner in the current scheduling period t, T n,t-1 Indicates the historical cumulative response accuracy of the nth air conditioner in the previous scheduling period, Represents the weight coefficient between the user's response willingness probability value and the historical cumulative response accuracy rate of the previous scheduling period.

[0021] Furthermore, the room temperature constraint is:

[0022] 24.8≤θ n,t,end≤27.3

[0023] The above operating power constraints are:

[0024] p min ≤p n,t -ξ n,t ≤p max

[0025] The above total dispatch response constraint is:

[0026]

[0027] Where p min Indicates the minimum operating power, p max Indicates the maximum operating power, f t represents the total scheduling power value of the current scheduling period t, and φ3 represents the acceptable error coefficient.

[0028] Furthermore, it also includes:

[0029] In the case where the first indoor temperature range does not meet the room temperature constraint;

[0030] The air conditioner whose first indoor temperature range does not meet the room temperature constraint is used as the target air conditioner, and the air conditioner scheduling power value corresponding to the target air conditioner is set to 0;

[0031] The above-mentioned demand response scheduling model is solved under the above-mentioned constraints to obtain the air conditioning scheduling power values ​​of the air conditioners other than the target air conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized, and the above-mentioned air conditioning scheduling power values ​​are sent to the above-mentioned demand response terminal device, so that the above-mentioned demand response terminal device schedules the operating power of each air conditioner according to the above-mentioned air conditioning scheduling power values.

[0032] Furthermore, after the demand response terminal device schedules the operating power of each air conditioner according to the air conditioner scheduling power value, the demand response terminal device further includes:

[0033] Obtain the operating power of each air conditioner during the current scheduling period after scheduling;

[0034] The operating power of the current scheduling period and the air conditioning scheduling power value of the current scheduling period are stored.

[0035] Based on the above method embodiment, the present invention provides a corresponding device embodiment;

[0036] The present invention provides an air conditioning demand response scheduling system that takes into account user response willingness, comprising:

[0037] Demand response terminal equipment and demand response service platform;

[0038] The demand response terminal device is used to obtain the actual air-conditioning operating power at the beginning of the previous scheduling period, the air-conditioning scheduling power value of the previous scheduling period, the actual air-conditioning operating power at the beginning of the current scheduling period, the user response willingness probability value of the current scheduling period, the temperature parameter at the beginning of the current scheduling period, the maximum operating power and the minimum operating power of the current scheduling period; based on the actual air-conditioning operating power at the beginning of the current scheduling period, the actual air-conditioning operating power at the beginning of the previous scheduling period, and the air-conditioning scheduling power value of the previous scheduling period, calculate the historical cumulative response accuracy of the previous scheduling period, and send the historical cumulative response accuracy of the previous scheduling period, the temperature parameter at the beginning of the current scheduling period, the user response willingness probability value of the current scheduling period, the maximum operating power and the minimum operating power of the current scheduling period to the demand response service platform; wherein the temperature parameters include: indoor temperature, outdoor temperature, thermal resistance of indoor temperature change, and thermal capacity of outdoor temperature change;

[0039] The above-mentioned demand response service platform is used to obtain the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period; wherein the above-mentioned air conditioning scheduling parameters include: total scheduling power value, electricity price, unit incentive income, actual duration of unit period, user response willingness probability value, maximum operating power and minimum operating power; based on the above-mentioned air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, a demand response scheduling model is constructed with the goal of maximizing the benefits obtained by users participating in scheduling and minimizing users' room temperature dissatisfaction. model and the constraints of the demand response scheduling model; wherein the constraints include: room temperature constraints, operating power constraints, and total scheduling response constraints; based on the maximum operating power, minimum operating power, and temperature parameters, a first indoor temperature range is calculated, and the first indoor temperature range is compared with the room temperature constraints; when the first indoor temperature range meets the room temperature constraints, the demand response scheduling model is solved under the constraints to obtain the air conditioning scheduling power value of each air conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power value is sent to the demand response terminal device;

[0040] The above-mentioned demand response terminal device is also used to schedule the operating power of each air conditioner according to the above-mentioned air conditioner scheduling power value.

[0041] Furthermore, the calculation of the historical cumulative response accuracy rate of the previous scheduling period includes:

[0042] The response accuracy of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period;

[0043] According to the response accuracy rate of the previous scheduling period, the historical cumulative response accuracy rate of the previous scheduling period is calculated.

[0044] Furthermore, the above-mentioned demand response service platform is also used to:

[0045] In the case where the first indoor temperature range does not meet the room temperature constraint;

[0046] The air conditioner scheduling power value corresponding to the air conditioner whose first indoor temperature range does not meet the room temperature constraint is set to 0;

[0047] The air conditioner whose first indoor temperature range does not meet the room temperature constraint is used as the target air conditioner, and the air conditioner scheduling power value corresponding to the target air conditioner is set to 0;

[0048] The above-mentioned demand response scheduling model is solved under the above-mentioned constraints to obtain the air conditioning scheduling power values ​​of the air conditioners other than the target air conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized, and the above-mentioned air conditioning scheduling power values ​​are sent to the above-mentioned demand response terminal device, so that the above-mentioned demand response terminal device schedules the operating power of each air conditioner according to the above-mentioned air conditioning scheduling power values.

[0049] Furthermore, after scheduling the operating power of each air conditioner according to the air conditioner scheduling power value, the demand response terminal device is further configured to:

[0050] Obtain the operating power of each air conditioner during the current scheduling period after scheduling;

[0051] The operating power of the current scheduling period and the air conditioning scheduling power value of the current scheduling period are stored.

[0052] The embodiments of the present invention have the following beneficial effects:

[0053] The present invention provides an air conditioning demand response scheduling method that takes into account the user's willingness to respond. The above method includes: obtaining the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period; wherein the above air conditioning scheduling parameters include: total scheduling power value, electricity price, unit incentive income, actual duration of unit period, user response willingness probability value, maximum operating power and minimum operating power; the above temperature parameters include: indoor temperature, outdoor temperature, thermal resistance of indoor temperature change, and thermal capacity of outdoor temperature change; the historical cumulative response accuracy of the previous scheduling period is calculated by the demand response terminal device based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period; then, based on the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, the demand response terminal device calculates the response accuracy of the previous scheduling period based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period. With the goal of maximizing the benefits of user participation in scheduling and minimizing user room temperature dissatisfaction, a demand response scheduling model and the constraints of the demand response scheduling model are constructed; wherein the constraints include: room temperature constraint, operating power constraint, and total scheduling response constraint; then, based on the maximum operating power, minimum operating power, and temperature parameters, a first indoor temperature range is calculated, and the first indoor temperature range is compared with the room temperature constraint; finally, when the first indoor temperature range meets the room temperature constraint, the demand response scheduling model is solved under the constraints to obtain the air conditioning scheduling power value of each air conditioner in the current scheduling period when the benefits are maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power value is sent to the demand response terminal device so that the demand response terminal device schedules the operating power of each air conditioner according to the air conditioning scheduling power value. Therefore, by obtaining the user's response willingness and calculating the user credibility used to construct the demand response scheduling model based on this response willingness, the air conditioning scheduling power value finally obtained by the present invention fully considers the differences in the response willingness of different users to participate in air conditioning scheduling, thereby reducing scheduling deviation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of an air conditioning demand response scheduling method that takes into account user response willingness, provided by one embodiment of the present invention.

[0055] Figure 2 1 is a schematic structural diagram of an air conditioning demand response scheduling system that takes into account user response willingness, provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0057] like Figure 1 As shown, an embodiment of the present invention provides an air conditioning demand response scheduling method that takes into account user response willingness, including:

[0058] Step S101: Acquire the air conditioning scheduling parameters for the current scheduling period, the temperature parameters at the start of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period; wherein the air conditioning scheduling parameters include: total scheduling power value, electricity price, unit incentive income, actual duration of the unit period, user response willingness probability value, maximum operating power, and minimum operating power; the temperature parameters include: indoor temperature, outdoor temperature, thermal resistance of indoor temperature change, and thermal capacity of outdoor temperature change; the historical cumulative response accuracy of the previous scheduling period is calculated by the demand response terminal device based on the actual air conditioning operating power at the start of the current scheduling period, the actual air conditioning operating power at the start of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period;

[0059] Specifically, a scheduling period is 0.25 hours. The above user response willingness probability value ranges from 0 to 1. At the beginning of scheduling, users can set it in the demand response terminal device according to their own situation. Users can also modify the set user response willingness probability value during the scheduling process.

[0060] In a preferred embodiment, the historical cumulative response accuracy of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period, including:

[0061] The response accuracy of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period;

[0062] Specifically, the response accuracy of the previous scheduling period is calculated according to the following formula:

[0063]

[0064] Where A ccn,t-1 represents the response accuracy of the nth air conditioner in the previous scheduling period, p n,t-1Indicates the actual operating power of the nth air conditioner in the previous scheduling period, p n,t represents the actual operating power of the nth air conditioner at the beginning of the current scheduling period t, ξ n,t-1 Indicates the air conditioning scheduling power value of the nth air conditioner in the previous scheduling period.

[0065] Specifically, the response accuracy of the previous scheduling period is calculated starting from the second scheduling period. The response accuracy is a value in the range of 0 to 1.

[0066] According to the response accuracy rate of the previous scheduling period, the historical cumulative response accuracy rate of the previous scheduling period is calculated.

[0067] Specifically, the historical cumulative response accuracy of the previous scheduling period is calculated according to the following formula:

[0068]

[0069] Where, T n,t-1 represents the historical cumulative response accuracy of the nth air conditioner in the previous scheduling period, φ1 represents the attenuation coefficient, T n,t-2 Indicates the historical cumulative response accuracy of the nth air conditioner in the previous scheduling period.

[0070] Specifically, if the current scheduling period is the second scheduling period, the response accuracy of the first scheduling period will be used as the historical cumulative response accuracy of the previous scheduling period; if the current scheduling period is the scheduling period after the second scheduling period, the historical cumulative response accuracy of the previous scheduling period will be calculated based on the response accuracy of the previous scheduling period and the historical cumulative response accuracy of the previous scheduling period.

[0071] In this preferred embodiment, the historical cumulative response accuracy of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period.

[0072] Step S102: Based on the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, a demand response scheduling model and constraints of the demand response scheduling model are constructed with the goal of maximizing the benefits obtained by users participating in scheduling while minimizing users' room temperature dissatisfaction. The constraints include room temperature constraints, operating power constraints, and total scheduling response constraints.

[0073] In a preferred embodiment, the objective function of the demand response scheduling model is:

[0074] W n,t=(c t +π t )·ξ n,t ·Δt

[0075] S n,t =(θ n,t,end -26) 2

[0076]

[0077] p n,t,rum =p n,t -ξ n,t

[0078] θ n,t,end =α n θ n,t,in +(1-α n )(θ n,t,out -R n p n,t,rum )

[0079]

[0080] Where W n,t represents the user economic value of the nth air conditioner in the current scheduling period t, c t represents the electricity price in the current dispatch period t, π t represents the unit incentive income in the current scheduling period t, Δt represents the actual duration of the current scheduling period t, which is 0.25h, and S n,t represents the room temperature dissatisfaction corresponding to the nth air conditioner in the current scheduling period t, θ n,t,end It indicates the indoor temperature of the nth air conditioner at the end of the current scheduling period t, assuming that the user strictly follows the air conditioning scheduling power value of the current scheduling period. n represents the inertia coefficient of the nth air conditioner, R n Indicates the thermal resistance corresponding to the nth air conditioner, C n represents the heat capacity corresponding to the nth air conditioner, p n,t,rum It means that if the user strictly follows the air conditioning scheduling power value of the current scheduling period, the air conditioning operating power of the nth air conditioner in the current scheduling period t, p n,t represents the actual operating power of the nth air conditioner in the current scheduling period t, ξ n,t represents the air conditioning scheduling power value of the nth air conditioner in the current scheduling period t, θ n,t,in represents the indoor temperature corresponding to the nth air conditioner at the beginning of the current scheduling period t, θ n,t,out It represents the outdoor temperature of the nth air conditioner at the beginning of the current scheduling period t, N represents the total number of air conditioners to be scheduled, h n,trepresents the user credibility of the nth air conditioner in the current scheduling period t, ρ n,t represents the probability value of the user's response willingness of the nth air conditioner in the current scheduling period t, T n,t-1 Indicates the historical cumulative response accuracy of the nth air conditioner in the previous scheduling period, Represents the weight coefficient between the user's response willingness probability value and the historical cumulative response accuracy rate of the previous scheduling period.

[0081] Specifically, the objective function considers the benefits users gain from participating in the response, namely the user economic value, as well as room temperature dissatisfaction. The user economic value is composed of the electricity cost savings from participating in the response, namely the electricity price, and the incentive compensation benefits received, namely the unit incentive benefit. Room temperature dissatisfaction is the deviation of the indoor temperature from the optimal temperature of 26 degrees Celsius at the end of the current scheduling period, assuming that the user executes the air conditioning scheduling work according to the air conditioning scheduling power value.

[0082] Specifically, users with higher user credibility are more reliable in performing response tasks. Therefore, they are considered to attach more importance to the benefits of participating in the response when making response decisions. Users with lower user credibility attach more importance to the comfort level of indoor temperature. Under this setting, even if all other parameters of the two air conditioners are the same, the amount of response tasks allocated to users with higher user credibility will be higher than that of users with lower user credibility. Based on this, the objective function of the above demand response scheduling model is constructed.

[0083] Specifically, the objective function of the demand response scheduling model aims to maximize the benefits users gain from participating in the response while minimizing user dissatisfaction. In addition, the evaluated user credibility is taken into account in the objective function in a weighted manner to represent the differences in the degree to which different users attach importance to economy and room temperature dissatisfaction.

[0084] In this preferred embodiment, an objective function of the demand response scheduling model is constructed.

[0085] In another preferred embodiment, the room temperature constraint is:

[0086] 24.8≤θ n,t,end ≤27.3

[0087] The above operating power constraints are:

[0088] p min ≤p n,t -ξ n,t ≤p max

[0089] The above total dispatch response constraint is:

[0090]

[0091] Where p min Indicates the minimum operating power, p max Indicates the maximum operating power, f t represents the total scheduling power value of the current scheduling period t, and φ3 represents the acceptable error coefficient, which ranges from 0 to 1.

[0092] Specifically, the sum of the dispatch power values ​​of the air conditioners dispatched during each dispatch period should strive to meet the total dispatch power value issued by the power grid at the beginning of that dispatch period, thus obtaining the aforementioned total dispatch response constraint. The left side of the total dispatch response constraint is given in absolute terms to account for positive and negative errors, while the right side considers that when an increase is required, the total dispatch power value will be a negative value. If the total dispatch response constraint cannot be met, it indicates that the total dispatch power value at that time exceeds the cumulative adjustable range of the participating air conditioners, and the total dispatch power value should be reset.

[0093] Specifically, the human body's acceptable range of indoor temperature refers to the following PMV formula:

[0094]

[0095] Where, I PMV represents the average thermal sensation index, and θ represents temperature.

[0096] Specifically, it is generally believed that I PMV When the value is less than 0.5, the corresponding temperature is the human comfort temperature. Therefore, according to the calculation of the above formula, it can be obtained that the human comfort temperature is in the range of 24.8°C to 27.3°C, thus obtaining the above room temperature constraint. The above room temperature constraint indicates that if the user strictly schedules the air conditioner according to the air conditioner scheduling power value of the current scheduling period, then at the end of the scheduling period, the indoor temperature should meet the above room temperature constraint.

[0097] Step S103: Calculating a first indoor temperature range based on the maximum operating power, the minimum operating power, and the temperature parameter, and comparing the first indoor temperature range with the room temperature constraint;

[0098] Specifically, this step is actually to substitute the above maximum operating power, minimum operating power and temperature parameters into the following formula:

[0099] θ′ n,t,end =α n θ n,t,in +(1-α n )(θ n,t,out -R n p n,t,rum )

[0100] pn,t,rum =p n,t -ξ n,t

[0101]

[0102] p min ≤p n,t -ξ n,t ≤p max

[0103] Specifically, the calculated θ′ n,t,end The value of is used as the first indoor temperature to determine whether this indoor temperature meets the room temperature constraint. Based on the comparison result, it is determined whether the actual operating power range of the current air conditioner after participating in the scheduling can make the indoor temperature meet the comfort range corresponding to the room temperature constraint.

[0104] Step S104: When the first indoor temperature range meets the room temperature constraint, the demand response scheduling model is solved under the constraint conditions to obtain the air-conditioning scheduling power value of each air-conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air-conditioning scheduling power value is sent to the demand response terminal device so that the demand response terminal device schedules the operating power of each air-conditioner according to the air-conditioning scheduling power value.

[0105] Specifically, if the first indoor temperature range meets the room temperature constraint, it indicates that the air conditioner can make the indoor temperature meet the comfort range corresponding to the room temperature constraint within the actual operating power range after participating in the scheduling.

[0106] Specifically, the above constraints are all linearly constrained quadratic programming problems, and the decision variable ξ n,t Expressed as a vector form ξ, the above objective function and the above constraints are transformed into the quadratic form as shown below:

[0107]

[0108] Wherein, P, Q, G, H, A and B represent the transformed matrices.

[0109] Specifically, the quadratic objective function and constraints are solved in Python using the qp solver in cvxopt to obtain the air conditioning scheduling power value of each air conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized.

[0110] In this preferred embodiment, the above-mentioned demand response scheduling model is solved under the above-mentioned constraints to obtain the air-conditioning scheduling power value of each air-conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized, and the obtained air-conditioning scheduling power value is sent to the demand response terminal device to adjust the corresponding operating power of each air-conditioner.

[0111] In another preferred embodiment, it further comprises:

[0112] In the case where the first indoor temperature range does not meet the room temperature constraint;

[0113] The air conditioner whose first indoor temperature range does not meet the room temperature constraint is used as the target air conditioner, and the air conditioner scheduling power value corresponding to the target air conditioner is set to 0;

[0114] The above-mentioned demand response scheduling model is solved under the above-mentioned constraints to obtain the air conditioning scheduling power values ​​of the air conditioners other than the target air conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized, and the above-mentioned air conditioning scheduling power values ​​are sent to the above-mentioned demand response terminal device, so that the above-mentioned demand response terminal device schedules the operating power of each air conditioner according to the above-mentioned air conditioning scheduling power values.

[0115] Specifically, if the first indoor temperature range does not meet the room temperature constraint, it indicates that after the air conditioner is scheduled, the actual operating power range cannot make the indoor temperature meet the comfort range corresponding to the room temperature constraint. In this case, these air conditioners that do not meet the room temperature constraint will no longer be scheduled.

[0116] In this preferred embodiment, when the first indoor temperature range does not meet the room temperature constraint, the air conditioning scheduling power value of the target air conditioner is set to 0, and the above-mentioned demand response scheduling model is solved under the above-mentioned constraints to obtain the air conditioning scheduling power values ​​of the remaining air conditioners except the target air conditioner in the current scheduling period, and the air conditioning scheduling power values ​​are sent together with the air conditioning scheduling power values ​​to the demand response terminal device for power scheduling.

[0117] In another preferred embodiment, after the demand response terminal device schedules the operating power of each air conditioner according to the air conditioner scheduling power value, it further includes:

[0118] Obtain the operating power of each air conditioner during the current scheduling period after scheduling;

[0119] The operating power of the current scheduling period and the air conditioning scheduling power value of the current scheduling period are stored.

[0120] Specifically, after scheduling the operating power of the corresponding air conditioner according to the air conditioner scheduling power value, the demand response terminal stores the air conditioner scheduling power value of the current scheduling period and the operating power of the air conditioner corresponding to the current scheduling period after scheduling.

[0121] In this preferred embodiment, after scheduling the operating power of each air conditioner, the demand response terminal device also stores the air conditioner scheduling power value corresponding to the current scheduling period of each air conditioner and the operating power of the air conditioner after scheduling.

[0122] Based on the above method embodiment, the present invention provides a corresponding device embodiment;

[0123] The present invention provides an air conditioning demand response scheduling system that takes into account user response willingness, comprising:

[0124] Demand response terminal equipment and demand response service platform;

[0125] The demand response terminal device is used to obtain the actual air-conditioning operating power at the beginning of the previous scheduling period, the air-conditioning scheduling power value of the previous scheduling period, the actual air-conditioning operating power at the beginning of the current scheduling period, the user response willingness probability value of the current scheduling period, the temperature parameter at the beginning of the current scheduling period, the maximum operating power and the minimum operating power of the current scheduling period; based on the actual air-conditioning operating power at the beginning of the current scheduling period, the actual air-conditioning operating power at the beginning of the previous scheduling period, and the air-conditioning scheduling power value of the previous scheduling period, calculate the historical cumulative response accuracy of the previous scheduling period, and send the historical cumulative response accuracy of the previous scheduling period, the temperature parameter at the beginning of the current scheduling period, the user response willingness probability value of the current scheduling period, the maximum operating power and the minimum operating power of the current scheduling period to the demand response service platform; wherein the temperature parameters include: indoor temperature, outdoor temperature, thermal resistance of indoor temperature change, and thermal capacity of outdoor temperature change;

[0126] The above-mentioned demand response service platform is used to obtain the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period; wherein the above-mentioned air conditioning scheduling parameters include: total scheduling power value, electricity price, unit incentive income, actual duration of unit period, user response willingness probability value, maximum operating power and minimum operating power; based on the above-mentioned air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, a demand response scheduling model is constructed with the goal of maximizing the benefits obtained by users participating in scheduling and minimizing users' room temperature dissatisfaction. model and the constraints of the demand response scheduling model; wherein the constraints include: room temperature constraints, operating power constraints, and total scheduling response constraints; based on the maximum operating power, minimum operating power, and temperature parameters, a first indoor temperature range is calculated, and the first indoor temperature range is compared with the room temperature constraints; when the first indoor temperature range meets the room temperature constraints, the demand response scheduling model is solved under the constraints to obtain the air conditioning scheduling power value of each air conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power value is sent to the demand response terminal device;

[0127] The above-mentioned demand response terminal device is also used to schedule the operating power of each air conditioner according to the above-mentioned air conditioner scheduling power value.

[0128] In a preferred embodiment, the calculation of the historical cumulative response accuracy rate in the previous scheduling period includes:

[0129] The response accuracy of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period;

[0130] According to the response accuracy rate of the previous scheduling period, the historical cumulative response accuracy rate of the previous scheduling period is calculated.

[0131] In another preferred embodiment, the above-mentioned demand response service platform is further used to:

[0132] In the case where the first indoor temperature range does not meet the room temperature constraint;

[0133] The air conditioner scheduling power value corresponding to the air conditioner whose first indoor temperature range does not meet the room temperature constraint is set to 0;

[0134] The air conditioner whose first indoor temperature range does not meet the room temperature constraint is used as the target air conditioner, and the air conditioner scheduling power value corresponding to the target air conditioner is set to 0;

[0135] The above-mentioned demand response scheduling model is solved under the above-mentioned constraints to obtain the air conditioning scheduling power values ​​of the air conditioners other than the target air conditioner in the current scheduling period when the above-mentioned benefit is maximized and the above-mentioned room temperature dissatisfaction is minimized, and the above-mentioned air conditioning scheduling power values ​​are sent to the above-mentioned demand response terminal device, so that the above-mentioned demand response terminal device schedules the operating power of each air conditioner according to the above-mentioned air conditioning scheduling power values.

[0136] In another preferred embodiment, after scheduling the operating power of each air conditioner according to the air conditioner scheduling power value, the demand response terminal device is further configured to:

[0137] Obtain the operating power of each air conditioner during the current scheduling period after scheduling;

[0138] The operating power of the current scheduling period and the air conditioning scheduling power value of the current scheduling period are stored.

[0139] It should be noted that the device embodiment described above is merely illustrative, wherein the modules described above as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiment provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement it without making any creative effort. The above schematic diagram is merely an example of an air-conditioning demand response scheduling system that takes into account the user's response intention, and does not constitute a limitation on an air-conditioning demand response scheduling system that takes into account the user's response intention. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components.

[0140] Compared with the prior art, by implementing the above-mentioned embodiments of the present invention, the differences in the response willingness of different users to participate in air conditioning scheduling can be fully considered, thereby reducing the deviation of air conditioning scheduling.

[0141] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. An air conditioning demand response scheduling method considering user response willingness, characterized in that: include: Obtain the air conditioning scheduling parameters for the current scheduling period, the temperature parameters at the start of the current scheduling period, and the historical cumulative response accuracy rate for the previous scheduling period; wherein the air conditioning scheduling parameters include: the total scheduling power value, the electricity price, the unit incentive income, the actual duration of the unit period, the probability value of the user's response willingness, the maximum operating power, and the minimum operating power; the temperature parameters include: the indoor temperature, the outdoor temperature, the thermal resistance of the indoor temperature change, and the thermal capacity of the outdoor temperature change; the historical cumulative response accuracy rate for the previous scheduling period is calculated by the demand response terminal device based on the actual air conditioning operating power at the start of the current scheduling period, the actual air conditioning operating power at the start of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period; Based on the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, a demand response scheduling model and constraints of the demand response scheduling model are constructed with the goal of maximizing the benefits obtained by users participating in scheduling while minimizing users' room temperature dissatisfaction; wherein the constraints include: room temperature constraints, operating power constraints, and total scheduling response constraints; Calculating a first indoor temperature range according to the maximum operating power, the minimum operating power, and the temperature parameter, and comparing the first indoor temperature range with the room temperature constraint; When the first indoor temperature range meets the room temperature constraint, the demand response scheduling model is solved under each constraint condition to obtain the air conditioning scheduling power value of each air conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power value is sent to the demand response terminal device, so that the demand response terminal device schedules the operating power of each air conditioner according to the air conditioning scheduling power value.

2. The air conditioning demand response scheduling method considering user response willingness according to claim 1, characterized in that: The historical cumulative response accuracy rate of the previous scheduling period is calculated based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period, including: Calculate the response accuracy of the previous scheduling period based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period; The historical cumulative response accuracy rate of the previous scheduling period is calculated according to the response accuracy rate of the previous scheduling period.

3. The air conditioning demand response scheduling method considering user response willingness according to claim 2, characterized in that: The objective function of the demand response scheduling model is: W n，t =(c t +p t )·ξ n，t ·Δt S n，t =(θ n，t，end -26) 2 p n，t，rum =p n，t -x n，t i n，t，end =a n i n，t，in +(1-a n )(θ n，t，out -R n p n，t，rum ) Where W n，t represents the user economic value of the nth air conditioner in the current scheduling period t, c t represents the electricity price in the current dispatch period t, π t represents the unit incentive income in the current scheduling period t, Δt represents the actual duration of the current scheduling period t, S n，t represents the room temperature dissatisfaction corresponding to the nth air conditioner in the current scheduling period t, θ n,t,end It indicates the indoor temperature of the nth air conditioner at the end of the current scheduling period t, assuming that the user strictly follows the air conditioning scheduling power value of the current scheduling period. n represents the inertia coefficient of the nth air conditioner, R n Indicates the thermal resistance corresponding to the nth air conditioner, C n represents the heat capacity corresponding to the nth air conditioner, p n,t,rum It means that if the user strictly follows the air conditioning scheduling power value of the current scheduling period, the air conditioning operating power of the nth air conditioner in the current scheduling period t, p n,t represents the actual operating power of the nth air conditioner in the current scheduling period t, ξ n,t represents the air conditioning scheduling power value of the nth air conditioner in the current scheduling period t, θ n,t,in represents the indoor temperature corresponding to the nth air conditioner at the beginning of the current scheduling period t, θ n,t,out It represents the outdoor temperature of the nth air conditioner at the beginning of the current scheduling period t, N represents the total number of air conditioners to be scheduled, h n,t represents the user credibility of the nth air conditioner in the current scheduling period t, ρ n,t represents the probability value of the user's response willingness of the nth air conditioner in the current scheduling period t, T n,t-1 Indicates the historical cumulative response accuracy of the nth air conditioner in the previous scheduling period, Represents the weight coefficient between the user's response willingness probability value and the historical cumulative response accuracy rate of the previous scheduling period.

4. The air conditioning demand response scheduling method considering user response willingness according to claim 3 is characterized in that: The room temperature constraint is: 24.8≤θ n,t,end ≤27.3 The operating power constraint is: p min ≤p n,t -x n,t ≤p max The overall dispatch response constraint is: Where p min Indicates the minimum operating power, p max Indicates the maximum operating power, f t represents the total scheduling power value of the current scheduling period t, and φ3 represents the acceptable error coefficient.

5. The air conditioning demand response scheduling method considering user response willingness according to claim 1, characterized in that: Also includes: In the case where the first indoor temperature range does not meet the room temperature constraint; The air conditioner whose first indoor temperature range does not meet the room temperature constraint is used as the target air conditioner, and the air conditioner scheduling power value corresponding to the target air conditioner is set to 0; The demand response scheduling model is solved under the constraints to obtain the air conditioning scheduling power values ​​of the air conditioners other than the target air conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power values ​​are sent to the demand response terminal device so that the demand response terminal device schedules the operating power of each air conditioner according to the air conditioning scheduling power values.

6. The air conditioning demand response scheduling method considering user response willingness according to claim 5, characterized in that: After the demand response terminal device schedules the operating power of each air conditioner according to the air conditioner scheduling power value, the demand response terminal device further includes: Obtain the operating power of each air conditioner during the current scheduling period after scheduling; The operating power of the current scheduling period and the air conditioning scheduling power value of the current scheduling period are stored.

7. An air conditioning demand response scheduling system that takes into account user response willingness, characterized in that: include: Demand response terminal equipment and demand response service platform; The demand response terminal device is used to obtain the actual air conditioning operating power at the beginning of the previous scheduling period, the air conditioning scheduling power value of the previous scheduling period, the actual air conditioning operating power at the beginning of the current scheduling period, the user response willingness probability value of the current scheduling period, the temperature parameter at the beginning of the current scheduling period, the maximum operating power and the minimum operating power of the current scheduling period; Based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period, the historical cumulative response accuracy of the previous scheduling period is calculated, and the historical cumulative response accuracy of the previous scheduling period, the temperature parameter at the beginning of the current scheduling period, the user response willingness probability value of the current scheduling period, the maximum operating power and the minimum operating power of the current scheduling period are sent to the demand response service platform; wherein the temperature parameters include: indoor temperature, outdoor temperature, thermal resistance of indoor temperature change, and thermal capacity of outdoor temperature change; The demand response service platform is used to obtain the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period; wherein the air conditioning scheduling parameters include: total scheduling power value, electricity price, unit incentive income, actual duration of unit period, user response willingness probability value, maximum operating power and minimum operating power; based on the air conditioning scheduling parameters of the current scheduling period, the temperature parameters at the beginning of the current scheduling period, and the historical cumulative response accuracy of the previous scheduling period, a demand response scheduling model is constructed with the goal of maximizing the benefits obtained by users participating in scheduling and minimizing users' room temperature dissatisfaction. model and the constraints of the demand response scheduling model; wherein the constraints include: room temperature constraints, operating power constraints and total scheduling response constraints; according to the maximum operating power, minimum operating power and temperature parameters, a first indoor temperature range is calculated, and the first indoor temperature range is compared with the room temperature constraints; when the first indoor temperature range meets the room temperature constraints, the demand response scheduling model is solved under each of the constraints to obtain the air conditioning scheduling power value of each air conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power value is sent to the demand response terminal device; The demand response terminal device is further used to schedule the operating power of each air conditioner according to the air conditioner scheduling power value.

8. The air conditioning demand response scheduling system considering user response willingness according to claim 7, characterized in that: The calculation of the historical cumulative response accuracy rate of the previous scheduling period includes: Calculate the response accuracy of the previous scheduling period based on the actual air conditioning operating power at the beginning of the current scheduling period, the actual air conditioning operating power at the beginning of the previous scheduling period, and the air conditioning scheduling power value of the previous scheduling period; The historical cumulative response accuracy rate of the previous scheduling period is calculated according to the response accuracy rate of the previous scheduling period.

9. The air conditioning demand response scheduling system considering user response willingness according to claim 7, characterized in that: The demand response service platform is also used to: In the case where the first indoor temperature range does not meet the room temperature constraint; The air conditioner scheduling power value corresponding to the air conditioner whose first indoor temperature range does not meet the room temperature constraint is set to 0; The air conditioner whose first indoor temperature range does not meet the room temperature constraint is used as the target air conditioner, and the air conditioner scheduling power value corresponding to the target air conditioner is set to 0; The demand response scheduling model is solved under the constraints to obtain the air conditioning scheduling power values ​​of the air conditioners other than the target air conditioner in the current scheduling period when the benefit is maximized and the room temperature dissatisfaction is minimized, and the air conditioning scheduling power values ​​are sent to the demand response terminal device so that the demand response terminal device schedules the operating power of each air conditioner according to the air conditioning scheduling power values.

10. An air conditioning demand response scheduling system considering user response willingness according to claim 9, characterized in that: After scheduling the operating power of each air conditioner according to the air conditioner scheduling power value, the demand response terminal device is further used to: Obtain the operating power of each air conditioner during the current scheduling period after scheduling; The operating power of the current scheduling period and the air conditioning scheduling power value of the current scheduling period are stored.

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