Method and device for determining adjusting potential of air conditioner

Abstract

The invention discloses a method and device for determining the adjusting potential of an air conditioner, and relates to the technical field of air conditioner load flexible adjusting potential, and the method comprises the steps that a target function is set, and according to the target function, the maximum value of a user comfort factor, an air conditioner fatigue factor and a user willingness factor is taken, and the minimum value of the operation cost of the air conditioner is taken; determining the corresponding operation power of the air conditioner when the optimal solution of the target function is taken as the upper limit value of the operation power of the air conditioner; and when a control instruction for the air conditioner is received, the operation power of the air conditioner is controlled based on the upper limit value of the operation power of the air conditioner. According to the method, the corresponding relation between the air conditioner and the time is obtained in advance, when the air conditioner power is determined, the performance such as the environment temperature, the user behavior and the equipment characteristics is considered, the uncertainty of the air conditioner caused by uncertain factors is reduced, the obtained upper limit of the air conditioner power is more accurate, and then scheduling is more reasonable when the air conditioner is controlled subsequently.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioner load flexible adjustment potential, and particularly relates to a method and device for determining air conditioner adjustment potential. BACKGROUND

[0002] With the evolution of power systems towards high proportions of renewable energy and distributed power sources, the importance of load-side flexibility is increasingly highlighted. Especially under the background of high proportion of new energy access, the balance of supply and demand and the task of peak load shifting of the power system become more complex and critical. Air conditioner load is considered as one of the core resources of demand side response due to its large installed capacity, strong thermal inertia and fast response speed, etc. Accurate evaluation of the adjustable potential of air conditioner load is related to the safety margin and economy of power grid dispatching. However, the callable boundary of air conditioner group is affected by the coupling of various factors such as environmental temperature, user behavior, device characteristics, etc., and these factors change dynamically over time. The existing evaluation method based on static statistics or a single scene is difficult to fully represent this cross-time and space uncertainty, which may easily lead to overestimation or underestimation of the potential, thereby weakening the effectiveness of dispatching and price incentives. Specifically, the callable boundary of air conditioner can be represented by the highest power output of air conditioner. SUMMARY

[0003] The purpose of the present application is to provide a method and device for determining air conditioner adjustment potential, which takes into account the performance of environmental temperature, user behavior, device characteristics, etc. when determining the power of air conditioner, reduces the uncertainty of air conditioner caused by uncertain factors, and obtains a more accurate upper limit of air conditioner power, thereby making the subsequent control of air conditioner more reasonable.

[0004] To solve the above technical problems, the present application provides a method for determining air conditioner adjustment potential, comprising:

[0005] determining user comfort factors, air conditioner fatigue factors and user willingness factors when the air conditioner is running at the upper limit of power, the user comfort factors being related to the indoor temperature of the space where the air conditioner is located, the air conditioner fatigue factors being related to the response frequency of the air conditioner, and the user willingness factors being related to the cost when the air conditioner is running;

[0006] setting a target function, the target function being the maximum value of the user comfort factors, the air conditioner fatigue factors and the user willingness factors and the minimum value of the running cost of the air conditioner;

[0007] determining the running power of the air conditioner corresponding to the optimal solution of the target function as the upper limit value of the running power of the air conditioner;

[0008] when receiving a control instruction for the air conditioner, controlling the running power of the air conditioner based on the upper limit value of the running power of the air conditioner.

[0009] In another aspect, the user comfort factor, the air conditioner fatigue factor and the user willingness factor when the air conditioner is running at the power upper limit are determined, comprising:

[0010] The air conditioner and the space where the air conditioner is located are equivalent to a circuit network, and parameters in the circuit network include capacitance, resistance, current and voltage;

[0011] The capacitance is the heat capacity of the space, the resistance is the thermal resistance of the building envelope of the space, the current is the refrigeration or heating power input, and the voltage is the temperature difference between the indoor temperature and the outdoor temperature;

[0012] The differential equation of the circuit network is:

[0013] ;

[0014] The differential equation of the circuit network represents the relationship between the indoor temperature and the refrigeration capacity of the air conditioner, T in is the indoor temperature, T out is the outdoor temperature, Q AC is the refrigeration capacity of the air conditioner, R1 is the equivalent impedance of the air conditioner, and C a is the equivalent specific heat capacity;

[0015] The relationship between the refrigeration capacity of the air conditioner and the power upper limit is determined based on the differential equation of the circuit network;

[0016] The user comfort factor, the air conditioner fatigue factor and the user willingness factor when the air conditioner is running at the power upper limit are determined based on the differential equation of the circuit network and the relationship between the refrigeration capacity of the air conditioner and the power upper limit.

[0017] In another aspect, the relationship between the refrigeration capacity of the air conditioner and the power upper limit is determined based on the differential equation of the circuit network, comprising:

[0018] The relationship between the refrigeration capacity of the air conditioner and the power upper limit of the air conditioner is:

[0019] ;

[0020] Wherein, is the power upper limit of the air conditioner, =k1f AC +l1, is the upper limit of the refrigeration capacity of the air conditioner, =k2f AC +l2, k1 is the first slope, k2 is the second slope, l1 is the first intercept, l2 is the second intercept, f AC is the frequency of the compressor of the air conditioner.

[0021] In another aspect, determining a user comfort factor during operation of the air conditioner, comprising:

[0022] Determining a set upper limit and a set lower limit of the air conditioner temperature determines a user comfort factor during operation of the air conditioner, the expression of the user comfort factor is:

[0023] ;

[0024] Wherein, E com The user comfort factor is T set,max The set upper limit of the air conditioner temperature is T set,min The set lower limit of the air conditioner temperature is T in The indoor temperature is T max The upper limit of the set temperature comfort zone is T min The lower limit of the set temperature comfort zone is.

[0025] In another aspect, determining an air conditioner fatigue factor during operation of the air conditioner, comprising:

[0026] According to the response time of the air conditioner, the air conditioner fatigue factor during operation of the air conditioner is determined, the expression of the air conditioner fatigue factor is:

[0027] ;

[0028] Wherein, E tired The air conditioner fatigue factor is t last The time of the last participation response is t set,RF The time of the desired recovery is t The time of the air conditioner participating in response.

[0029] In another aspect, determining a user willingness factor during operation of the air conditioner, comprising:

[0030] According to the electricity price, the user willingness factor during operation of the air conditioner is determined, the expression of the user willingness factor is:

[0031] ;

[0032] Wherein, E will The user willingness factor is β The price sensitivity of the user is p The current electricity price is p0 The average electricity price of the user.

[0033] In another aspect, setting a target function, the target function is that the user comfort factor, the air conditioner fatigue factor and the user willingness factor take the maximum value and the operation cost of the air conditioner takes the minimum value, comprising:

[0034] Setting a target function, the expression of the target function is:

[0035] ;

[0036] wherein, ΔP t represents the active regulation amount provided by the air conditioner cluster to the power grid in the tth time period, E com,t represents the user comfort factor at the tth time, E tired,t represents the air conditioner fatigue factor at the tth time, E will,t represents the user willingness factor at the tth time, p t represents the electricity price, k com represents the weight of the user comfort factor, k tired represents the weight of the air conditioner fatigue factor, p on,t represents the operation probability of the air conditioner at the tth time, the operation probability of the air conditioner P on is expressed as , T on represents the air conditioner opening time, T off represents the air conditioner closing time.

[0037] On the other hand, the operation power of the air conditioner corresponding to the optimal solution of the objective function is determined as the upper limit value of the operation power of the air conditioner.

[0038] Under the constraint condition, the operation power of the air conditioner corresponding to the optimal solution of the objective function is determined as the upper limit value of the operation power of the air conditioner.

[0039] The constraint condition includes a power upper limit, a temperature constraint, a threshold limit and a price limit.

[0040] The expression of the power upper limit is .

[0041] The expression of the temperature constraint is .

[0042] The expression of the threshold limit is and .

[0043] The expression of the price limit is .

[0044] wherein, ΔPt represents the active regulation amount provided by the air conditioner to the power grid in the tth time period, P on represents the operation probability of the air conditioner, represents the power of the air conditioner at the tth time, represents the indoor temperature at the tth time, T max represents the upper limit of the set temperature comfort zone, T min represents the lower limit of the set temperature comfort zone, E com,t represents the user comfort factor at the tth time, represents the minimum value of the user comfort factor, E tired,t represents the air conditioner fatigue factor at the tth time, is a maximum value of the air conditioner fatigue factor, p t is an electricity price, p min is a minimum electricity price, p max is a maximum electricity price.

[0045] In another aspect, determining the operating power of the air conditioner corresponding to the optimal solution of the objective function as the upper limit value of the operating power of the air conditioner comprises:

[0046] a set of the user comfort factors, the air conditioner fatigue factors and the user willingness factors as a particle;

[0047] initializing the iteration number;

[0048] randomly generating a value of a particle;

[0049] if the value of the particle satisfies the constraint, substituting the value of the particle into the objective function to obtain the solution of the current objective function;

[0050] adding one to the iteration number and returning to the step of randomly generating a value of a particle;

[0051] within the target iteration number, determining the value of the particle when the solution of the objective function takes a minimum value;

[0052] determining the power of the air conditioner corresponding to the value of the particle when the solution of the objective function takes the minimum value as the upper limit value of the operating power of the air conditioner.

[0053] In another aspect, determining the operating power of the air conditioner corresponding to the optimal solution of the objective function as the upper limit value of the operating power of the air conditioner comprises:

[0054] a set of the user comfort factors, the air conditioner fatigue factors and the user willingness factors as a particle;

[0055] initializing the iteration number;

[0056] randomly generating a value of a particle;

[0057] if the value of the particle satisfies the constraint, substituting the value of the particle into the objective function to obtain the solution of the current objective function;

[0058] adding one to the iteration number and returning to the step of randomly generating a value of a particle;

[0059] within the target iteration number, determining the value of the particle when the solution of the objective function takes a minimum value;

[0060] determining the power of the air conditioner corresponding to the value of the particle when the solution of the objective function takes the minimum value as the upper limit value of the operating power of the air conditioner.

[0061] To solve the above technical problems, the application further provides a device for determining air conditioner regulation potential, comprising:

[0062] a memory for storing a computer program;

[0063] a processor for implementing the steps of the above-mentioned method for determining air conditioner regulation potential when executing the computer program.

[0064] The application provides a method and device for determining air conditioner regulation potential, relating to the technical field of air conditioner load flexible regulation potential, comprising determining the corresponding relationship between the power of the air conditioner and time under ideal working conditions; setting a target function, which takes the maximum value of user comfort factors, air conditioner fatigue factors and user willingness factors and takes the minimum value of the operation cost of the air conditioner; determining the operation power of the air conditioner corresponding to the optimal solution of the target function as the upper limit value of the operation power of the air conditioner; when receiving the control instruction of the air conditioner, controlling the operation power of the air conditioner based on the upper limit value of the operation power of the air conditioner. The corresponding relationship between the air conditioner and time is obtained in advance, and the environmental temperature, user behavior, equipment characteristics and other performances are considered when determining the air conditioner power, thereby reducing the uncertainty of the air conditioner caused by uncertain factors, making the upper limit of the air conditioner power more accurate, and further making the scheduling more reasonable when controlling the air conditioner subsequently. BRIEF DESCRIPTION OF DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the application, the drawings needed to be used in the prior art and embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0066] Figure 1 A flow chart of the method for determining air conditioner regulation potential provided by the application;

[0067] Figure 2 A structural schematic diagram of the device for determining air conditioner regulation potential provided by the application. DETAILED DESCRIPTION

[0068] The core of the application is to provide a method and device for determining air conditioner regulation potential, which considers the environmental temperature, user behavior, equipment characteristics and other performances when determining the air conditioner power, thereby reducing the uncertainty of the air conditioner caused by uncertain factors, making the upper limit of the air conditioner power more accurate, and further making the scheduling more reasonable when controlling the air conditioner subsequently.

[0069] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0070] Figure 1 A flowchart of a method for determining air conditioning regulation potential provided by the present application, the method for determining air conditioning regulation potential comprises:

[0071] S11: determining a user comfort factor, an air conditioner fatigue factor and a user willingness factor when the air conditioner is in power upper limit operation, the user comfort factor being related to indoor temperature of a space where the air conditioner is located, the air conditioner fatigue factor being related to response frequency of the air conditioner, and the user willingness factor being related to cost when the air conditioner is operated;

[0072] The adjustable potential of the air conditioner is a power up / down adjustable curve that can be reliably provided under the premise of meeting the comfort, avoiding frequent start-stop and considering the electricity price willingness. Ultimately, the up / down adjustable power curve of the air conditioner cluster at each time period is obtained. The ultimate goal is to enable the air conditioner to respond to power according to the scheduling instruction under different electricity price scenarios, while maintaining temperature comfort, infrequent start-stop, economic efficiency and safety.

[0073] However, the power of the air conditioner is not only related to the actual output control instruction, but also related to other influencing factors, which will cause the actual power of the air conditioner to be different from the ideal state. Therefore, the present application determines the user comfort factor, the air conditioner fatigue factor and the user willingness factor of the air conditioner in the ideal working condition when the power is in the upper limit, and then adjusts the power upper limit based on the influencing factors.

[0074] The user comfort factor is mainly related to the indoor temperature when the air conditioner is working. The closer the temperature of the air conditioner is to the temperature set by the user, the higher the user comfort factor will be. In the demand response process, frequent response of air conditioner load will deepen the fatigue degree of the load. Therefore, the air conditioner fatigue factor is used to reflect the response fatigue problem caused by frequent participation of the air conditioner in response. The shorter the recovery interval after the air conditioner responds, the deeper the response fatigue degree. The user willingness factor is related to the electricity price. When the electricity price rises, the user tends to reduce the demand for the air conditioner, and vice versa.

[0075] S12: setting a target function, the target function being the maximum value of the user comfort factor, the air conditioner fatigue factor and the user willingness factor and the minimum value of the operation cost of the air conditioner;

[0076] S13: determine the running power of the air conditioner corresponding to the optimal solution of the target function as the upper limit value of the running power of the air conditioner;

[0077] Wherein, the maximization of user comfort factor, air conditioner fatigue factor and user willingness factor is to pursue the maximization of user willingness benefit and comfort degree while inhibiting fatigue accumulation, and the minimum value of the running cost of the air conditioner is to optimize the electricity price scene, which not only guarantees the preference of maximum comfort and minimum fatigue of residents, but also allows them to be softened in the target function; all decisions and state quantities are constrained by the worst case, so that the model solution can realize the comprehensive optimization of the highest willingness, the best comfort and the lowest fatigue under the weight setting.

[0078] S14: when receiving the control instruction of the air conditioner, the running power of the air conditioner is controlled based on the upper limit value of the running power of the air conditioner.

[0079] Further, the upper limit value of the running power of the air conditioner obtained after considering various factors is more accurate, so the running power of the air conditioner is controlled below the upper limit value, so the air conditioner will not be adjusted beyond the power, and the efficiency of the control process of the air conditioner will be higher.

[0080] The application provides a method and device for determining air conditioner adjustment potential, relating to the technical field of air conditioner load flexible adjustment potential, comprising determining the corresponding relationship between the power of the air conditioner and the time under ideal working conditions; setting a target function, which is the maximum value of the user comfort factor, the air conditioner fatigue factor and the user willingness factor and the minimum value of the running cost of the air conditioner; determining the running power of the air conditioner corresponding to the optimal solution of the target function as the upper limit value of the running power of the air conditioner; when receiving the control instruction of the air conditioner, the running power of the air conditioner is controlled based on the upper limit value of the running power of the air conditioner. The corresponding relationship between the air conditioner and the time is obtained in advance, and the performance of the environmental temperature, user behavior and equipment characteristics is considered when determining the power of the air conditioner, thereby reducing the uncertainty of the air conditioner caused by uncertain factors, and the upper limit of the power of the air conditioner is more accurate, and the subsequent control of the air conditioner is more reasonable.

[0081] On the basis of the above embodiments:

[0082] In some embodiments, the user comfort factor, the air conditioner fatigue factor and the user willingness factor when the air conditioner is running at the upper limit of the power are determined, comprising:

[0083] The air conditioner and the space where the air conditioner is located are equivalent to a circuit network, and the parameters in the circuit network include capacitance, resistance, current and voltage;

[0084] Wherein, the capacitance is the heat capacity of the space, the resistance is the thermal resistance of the building envelope of the space, the current is the refrigeration or heating power input, and the voltage is the temperature difference between the indoor temperature and the outdoor temperature.

[0085] The differential equation of the circuit network is:

[0086]

[0087] wherein the differential equation of the circuit network represents a relationship between an indoor temperature and a refrigerating capacity of the air conditioner, T in is the indoor temperature, T out is an outdoor temperature, Q AC is the refrigerating capacity of the air conditioner, R1 is an equivalent impedance of the air conditioner, C a is an equivalent specific heat capacity;

[0088] determining a relationship between the refrigerating capacity of the air conditioner and the power upper limit based on the differential equation of the circuit network;

[0089] determining a user comfort factor, an air conditioner fatigue factor and a user willingness factor when the air conditioner is operated at the power upper limit based on the differential equation of the circuit network and the relationship between the refrigerating capacity of the air conditioner and the power upper limit.

[0090] The equivalent parameter modeling method based on the circuit simulation mainly abstracts the thermodynamic process of the air conditioner and its indoor environment into a circuit network, uses a capacitor to represent the heat capacity of the room, uses a resistor to represent the thermal resistance of the building envelope, uses a current to correspond to the refrigeration / heating power input, and uses a voltage to correspond to the indoor and outdoor temperature difference. That is, it simulates the process of the change of the indoor temperature with time under the operation of the air conditioner.

[0091] Specifically, the resistor corresponds to the thermal resistance, representing the ability to hinder heat transfer. The capacitor corresponds to the heat capacity, representing the ability to store heat. The voltage difference corresponds to the indoor and outdoor temperature difference, representing the driving force of heat transfer. The current corresponds to the refrigeration or heating power, representing the rate of heat transfer. By replacing thermodynamics with a circuit network, the modeling is more accurate.

[0092] In some embodiments, determining the relationship between the refrigerating capacity of the air conditioner and the power upper limit based on the differential equation of the circuit network comprises:

[0093] The relationship between the refrigerating capacity of the air conditioner and the power upper limit of the air conditioner is:

[0094]

[0095] wherein, is the power upper limit of the air conditioner, =k1f AC +l1, is the refrigerating capacity upper limit of the air conditioner, =k2f AC +l2, k1 is a first slope, k2 is a second slope, l1 is a first intercept, l2 is a second intercept, f AC ​​The frequency of the compressor of the air conditioner.

[0096] The expression of the relationship between the refrigerating capacity of the air conditioner and the power of the air conditioner is:

[0097]

[0098] P = k1 * f + l1 AC The power of the air conditioner, k1 is the first slope, k2 is the second slope, l1 is the first intercept, and l2 is the second intercept;

[0099] The corresponding relationship between the power of the air conditioner and time includes:

[0100]

[0101] P = k1 * f + l1 The energy stored by the virtual energy storage of the air conditioner load at time t, The upper limit of the load electric power of the air conditioner, The upper limit of the refrigerating capacity of the air conditioner, A is the first energy relationship constant, and B is the second energy relationship constant;

[0102] The expression of the first energy relationship constant is:

[0103]

[0104] The expression of the second energy relationship constant is:

[0105]

[0106] T = T0 + (T1 - T0) * e^(-t / T) in,0 The initial indoor temperature, The indoor temperature at time t, The indoor temperature at time t, T0 is the initial indoor temperature, max The upper limit of the set temperature comfort zone.

[0107] The electric power and the refrigerating capacity of the variable frequency air conditioner are related to the frequency of the compressor, and the relationship is According to the above two formulas, the expression of the relationship between the refrigerating capacity of the air conditioner and the power of the air conditioner is .

[0108] The energy stored by the virtual energy storage of a single air conditioner load is defined as the energy consumed when the indoor temperature drops from the upper limit of the temperature comfort zone to the current temperature when the air conditioner operates at the maximum power. According to the differential equation and Taylor expansion, the corresponding relationship between the power of the air conditioner and time is obtained.

[0109] In addition, the constraint condition must also be met, The electric power of the air conditioner at time t, ​​​​​Lower limit of air conditioning load power.

[0110] In some embodiments, determining a user comfort factor when the air conditioner is running includes:

[0111] Determining a set upper limit and a set lower limit of the air conditioner temperature determines a user comfort factor when the air conditioner is running, and an expression of the user comfort factor is:

[0112] ;

[0113] Wherein, E com is the user comfort factor, T set,max is the set upper limit of the air conditioner temperature, T set,min is the set lower limit of the air conditioner temperature, T in is the indoor temperature, T max is the upper limit of the set temperature comfort zone, and T min is the lower limit of the set temperature comfort zone.

[0114] The potential of the air conditioning load is not only affected by the start-stop factor, but also depends on the indoor temperature change and the degree of frequent response of the air conditioning load in the demand response process. The acceptance of the user to the temperature change determines the stability of the air conditioning response, and therefore E com is defined as the user comfort factor.

[0115] In some embodiments, determining an air conditioning fatigue factor when the air conditioner is running includes:

[0116] Determining an air conditioning fatigue factor when the air conditioner is running according to the response time of the air conditioner, and an expression of the air conditioning fatigue factor is:

[0117] ;

[0118] Wherein, E tired is the air conditioning fatigue factor, t last is the time of the last participation in response, t set,RF is the time of the expected recovery, and t is the time of the air conditioning participation in response.

[0119] In the demand response process, the frequent response of the air conditioning load will deepen the fatigue degree of the load. Therefore, a fatigue factor is adopted to reflect the response fatigue problem caused by the frequent participation of the air conditioning in response, and the shorter the recovery interval after the air conditioning response, the deeper the degree of response fatigue, and E tired is defined as the air conditioning fatigue factor.

[0120] In some embodiments, determining a user willingness factor when the air conditioner is running includes:

[0121] Determining a user willingness factor when the air conditioner is running according to the electricity price, and an expression of the user willingness factor is:

[0122] ;

[0123] wherein E will is the user's willingness factor, β is the user's price sensitivity, p is the current electricity price, and p0 is the user's average electricity price.

[0124] In addition to the above factors, the user's willingness to participate in the response also needs to be considered. The user's response willingness is not only affected by the comfort factor, but also related to the economic factor and the current electricity price. When the electricity price is higher than the user's average electricity price, the user tends to reduce the electricity bill by participating in the response; when the electricity price is lower, the user pays more attention to his own comfort. Therefore, E will is defined as the user's willingness factor.

[0125] β represents the user's sensitivity to changes in electricity prices, and the smaller β is, the more sensitive it is, and the larger β is, the more sluggish it is. kcom and ktired are weights that convert comfort and fatigue into power comparability: the larger kcom is, the more it is inclined to preserve comfort and less effort, and the larger ktired is, the more it inhibits frequent start-stop and prefers less income.

[0126] In some embodiments, a target function is set, which is the maximum of the user comfort factor, the air conditioner fatigue factor and the user's willingness factor, and the minimum of the running cost of the air conditioner, comprising:

[0127] The target function is set, and the expression of the target function is:

[0128] ;

[0129] wherein ΔP t represents the active regulation amount provided by the air conditioner cluster to the power grid in the tth time period, E com,t is the user's comfort factor at t time, E tired,t is the air conditioner's fatigue factor at t time, E will,t is the user's willingness factor at t time, p t is the electricity price, k com is the weight of the user's comfort factor, k tired is the weight of the air conditioner's fatigue factor, P on,t is the running probability of the air conditioner at t time, and the expression of the running probability P on of the air conditioner is , T on is the air conditioner's on time, and T off is the air conditioner's off time.

[0130] The outer max pursues the maximization of the user's willingness benefit and comfort at the same time, and through the punishment weight The fatigue accumulation is inhibited, the inner min is optimized to ensure the robust feasibility for the electricity price scenario, and the method can ensure the preferences of maximum comfort and minimum fatigue, and allows them to be softened and adjusted in the objective function; all decisions and state quantities are constrained by the worst case, which is the The adjustment power can be realized, and the comprehensive optimization of the highest willingness, the best comfort and the lowest fatigue is realized under the weight setting.

[0131] Based on the thermal model, comfort, fatigue and user willingness formula in the document, the double-layer model of outer max (comfort + willingness - fatigue) - inner min (electricity price scenario) is converted into a single-layer problem: the worst electricity price is explicitly traversed (or approximated by a scenario set) in the fitness function (the above target) for each particle, so as to embed the robustness into the objective function, and the power upper limit, temperature interval, threshold, electricity price boundary and other constraints are written as explicit inequalities or penalty functions. Each part exceeding the constraint range is converted into a non-negative violation quantity, and the violation quantity is squared or weighted and added to the fitness function as a penalty term, so as to automatically tend to meet the constraints in the optimization process.

[0132] For each particle, the indoor temperature trajectory is recursively calculated by using the heat balance differential equation, and then the corresponding comfort, fatigue, start-stop probability and user willingness index are calculated; on a given electricity price scenario set, the total revenue is calculated for each scenario and the worst value is taken; finally, the fitness function is constructed, and the original maximization problem is changed into minimization and any constraint violation is punished with a large penalty coefficient.

[0133] In some embodiments, the running power of the air conditioner corresponding to the optimal solution of the objective function is determined as the upper limit value of the running power of the air conditioner, including:

[0134] In some embodiments, the running power of the air conditioner corresponding to the optimal solution of the objective function is determined as the upper limit value of the running power of the air conditioner under the constraint condition;

[0135] The constraint condition includes the power upper limit, temperature constraint, threshold limit and electricity price limit;

[0136] The expression of the power upper limit is ;

[0137] The expression of the temperature constraint is ;

[0138] The expression of the threshold limit is and ;

[0139] The expression of the electricity price limit is ;

[0140] Where, ΔPt represents the active adjustment amount of the air conditioner to the power grid in the tth time period, P ona running probability of the air conditioner, a power of the air conditioner at t, an indoor temperature at t, T max an upper limit of a set temperature comfort zone, T min a lower limit of the set temperature comfort zone, E com,t a user comfort factor at t, a minimum value of the user comfort factor, E tired,t an air conditioner fatigue factor at t, a maximum value of the air conditioner fatigue factor, p t an electricity price, p min a minimum electricity price, p max a maximum electricity price.

[0141] The adjustment process of the air conditioner needs to be within a certain power range, the temperature needs to be adjusted within the set temperature comfort zone, the user comfort factor has a certain lower limit value, that is, the user cannot be too uncomfortable, the air conditioner fatigue factor has a certain upper limit value, that is, the air conditioner cannot be adjusted too frequently, and the electricity price also needs to be within a certain range.

[0142] In some embodiments, the running power of the air conditioner corresponding to the optimal solution of the objective function is determined as an upper limit value of the running power of the air conditioner, comprising:

[0143] A group of user comfort factors, air conditioner fatigue factors and user willingness factors are taken as a particle;

[0144] The iteration number is initialized;

[0145] A value of a particle is randomly generated;

[0146] If the value of the particle satisfies the constraint, the value of the particle is substituted into the objective function to obtain the solution of the current objective function;

[0147] The iteration number is incremented by one, and the step of randomly generating a value of a particle is returned;

[0148] Within the target iteration number, the value of the particle when the solution of the objective function takes the minimum value is determined;

[0149] The power of the air conditioner corresponding to the value of the particle when the solution of the objective function takes the minimum value is taken as the upper limit value of the running power of the air conditioner.

[0150] Specifically, a blank interface is created in a simulation platform to prepare for input parameters and model building;

[0151] The parameters required for air conditioner potential evaluation are collected and read in the simulation platform in an external file interaction manner;

[0152] Explicitly regulate the upper limit of power configuration method, embed the behavior factor into the power feasible region; set the robust optimization objective structure according to the possible interval of electricity price; all constraint conditions (power upper and lower limits, temperature, fatigue, willingness) are written into explicit inequalities or penalty functions, which are used for fitness evaluation, reference power upper limit, bit density constraint, threshold limit, electricity price limit constraint condition. The value to be solved is the up / down adjustment curve at each period, which maximizes the comfort + willingness - fatigue of the outer layer, and the minimum target optimal and all constraint feasible of the electricity price scene of the inner layer

[0153] Known quantities: thermal model and initial temperature, air conditioner and building parameters, comfort interval and threshold, behavior weight kcom, ktired and penalty coefficient, power upper limit and electricity price scene or electricity price interval boundary.

[0154] Unknown quantities: decision variable PD (t).

[0155] Initialize the population according to the particle swarm algorithm, each particle represents a feasible scheduling scheme, randomly generate particle position and velocity, and calculate the fitness value;

[0156] For each particle, the indoor temperature trajectory is derived using the heat balance equation; the comfort, fatigue and willingness level at each time is calculated according to the trajectory, and the overall target value is aggregated;

[0157] Update the particle velocity and position, adjust the strategy according to the individual optimal and global optimal information; calculate the new objective function value of the particle, check the constraint condition, and apply the penalty function to the infeasible solution; update the non-dominated solution in the archive, if the archive exceeds the capacity, delete the solution according to the deletion strategy; in each iteration, dynamically adjust the inertia weight and learning factor of the algorithm to balance the global search and local search ability:

[0158] Determine whether the iteration reaches the maximum number or meets the convergence condition. If yes, go to the next step; otherwise, return;

[0159] Check the scheduling result to confirm whether it meets the system demand and constraint condition; if not, adjust the algorithm parameters and recalculate.

[0160] Output the optimization result, including outputting the global optimal particle [P1, P2,..., PT] and its corresponding temperature trajectory, comprehensive utility value and worst electricity price scene; use the thermal model to replay once to verify that all soft and hard constraints are met; finally, give the optimal regulation power curve and "willingness-comfort-fatigue" three index evaluation results that the air conditioner group can achieve.

[0161] Figure 2 The air conditioner regulation potential determination device provided by the application has the advantages that the air conditioner regulation potential determination device provided by the application has the advantages that

[0162] a memory 21 for storing a computer program;

[0163] a processor 22 for executing the computer program to implement the steps of the method for determining air conditioning regulation potential.

[0164] The determination device for air conditioning regulation potential provided in the present application is described above in the embodiments, and will not be described here again.

[0165] It should also be noted that the terms such as first and second, etc. are merely used to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. In addition, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0166] The skilled person can further realize that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in general terms in the above description. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0167] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application should not be limited to the embodiments shown herein, but should be consistent with the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining the conditioning potential of an air conditioner, comprising: The method comprises the following steps: determining a user comfort factor, an air conditioner fatigue factor and a user willingness factor when the air conditioner is running at a power upper limit, wherein the user comfort factor is related to the indoor temperature of the space where the air conditioner is located, the air conditioner fatigue factor is related to the response frequency of the air conditioner, and the user willingness factor is related to the cost when the air conditioner is running; setting a target function, wherein the target function takes the maximum value of the user comfort factor, the air conditioner fatigue factor and the user willingness factor, and takes the minimum value of the running cost of the air conditioner; determining the running power of the air conditioner corresponding to the optimal solution of the target function as the running power upper limit value of the air conditioner; controlling the running power of the air conditioner based on the running power upper limit value of the air conditioner when a control instruction of the air conditioner is received.

2. The method for determining the air conditioning regulation potential as described in claim 1, characterized in that, The method comprises the following steps: equivalent the air conditioner and the space where the air conditioner is located to a circuit network, wherein the parameters in the circuit network include capacitance, resistance, current and voltage; wherein the capacitance is the heat capacity of the space, the resistance is the thermal resistance of the building envelope of the space, the current is the refrigeration or heating power input, and the voltage is the temperature difference between the indoor temperature and the outdoor temperature; the differential equation of the circuit network is: ； wherein the differential equation of the circuit network represents a relationship between the indoor temperature and the refrigerating capacity of the air conditioner, T in is the indoor temperature, T out is the outdoor temperature, Q AC is the refrigerating capacity of the air conditioner, R1 is the equivalent impedance of the air conditioner, C a is the equivalent specific heat capacity; determining the relationship between the refrigerating capacity of the air conditioner and the power upper limit based on the differential equation of the circuit network; determining the user comfort factor, the air conditioner fatigue factor and the user willingness factor when the air conditioner is running at a power upper limit based on the differential equation of the circuit network and the relationship between the refrigerating capacity of the air conditioner and the power upper limit.

3. The method for determining the air conditioning regulation potential as described in claim 2, characterized in that, The method comprises the following steps: determining the relationship between the refrigerating capacity of the air conditioner and the power upper limit based on the differential equation of the circuit network comprises: ； wherein, is a power upper limit of the air conditioner, = k1f AC + l1, is a refrigerating capacity upper limit of the air conditioner, = k2f AC + l2, k1 is a first slope, k2 is a second slope, l1 is a first intercept, l2 is a second intercept, f AC is a frequency of a compressor of the air conditioner.

4. The method for determining the air conditioning regulation potential as described in claim 1, characterized in that, the relationship between the refrigerating capacity of the air conditioner and the power upper limit of the air conditioner is: The method comprises the following steps: ； wherein E com is the user comfort factor, T set,max is the upper limit of the air conditioning temperature setting, T set,min is the lower limit of the air conditioning temperature setting, T in is the indoor temperature, T max is the upper limit of the set temperature comfort zone, T min is the lower limit of the set temperature comfort zone.

5. The method for determining the air conditioning regulation potential as described in claim 1, characterized in that, determining the user comfort factor when the air conditioner is running comprises: determining the upper limit and the lower limit of the air conditioner temperature to determine the user comfort factor when the air conditioner is running, and the expression of the user comfort factor is: ； Wherein, E tired is the fatigue factor of the air conditioner, t last is the time of the last participation response, t set,RF is the time of the expected recovery, t is the time of the air conditioner participation response.

6. The method for determining the air conditioning regulation potential as described in claim 1, characterized in that, determining the air conditioner fatigue factor when the air conditioner is running comprises: determining the air conditioner fatigue factor when the air conditioner is running according to the response time of the air conditioner, and the expression of the air conditioner fatigue factor is: ； where E will is the user's willingness factor, β is the user's price sensitivity, p is the current electricity price, and p0is the user's average electricity price.

7. The method for determining the air conditioning regulation potential as described in claim 1, characterized in that, determining the user willingness factor when the air conditioner is running comprises: determining the user willingness factor when the air conditioner is running according to the electricity price, and the expression of the user willingness factor is: ； wherein, ΔP t represents the active regulation amount provided by the air conditioning cluster to the power grid in the tth time period, E com,t is the user comfort factor at time t, E tired,t is the air conditioning fatigue factor at time t, E will,t is the user willingness factor at time t, p t is the electricity price, k com is the weight of the user comfort factor, k tired is the weight of the air conditioning fatigue factor, P on,t is the operation probability of the air conditioner at time t, the operation probability P on of the air conditioner is expressed as , T on is the air conditioner on time, T off is the air conditioner off time.

8. The method for determining the air conditioning regulation potential as described in any one of claims 1 to 7, characterized in that, setting a target function, wherein the target function takes the maximum value of the user comfort factor, the air conditioner fatigue factor and the user willingness factor, and takes the minimum value of the running cost of the air conditioner, comprises: setting the expression of the target function is: determining the running power of the air conditioner corresponding to the optimal solution of the target function as the running power upper limit value of the air conditioner comprises: determining the running power of the air conditioner corresponding to the optimal solution of the target function as the running power upper limit value of the air conditioner under the condition that the constraint condition is met; the constraint condition comprises the power upper limit, the temperature constraint, the threshold limit and the electricity price limit; The expression of the upper power limit is ; The expression of the temperature constraint is ; The expression of the threshold limit is and ; The expression of the electricity price limit is ; wherein, ΔPt represents the active regulation amount provided by the air conditioner to the power grid in the tth time period, P on is the running probability of the air conditioner, is the power of the air conditioner at t moment, is the indoor temperature at t moment, T max is the upper limit of the set temperature comfort zone, T min is the lower limit of the set temperature comfort zone, E com,t is the user comfort factor at t moment, is the minimum value of the user comfort factor, E tired,t is the air conditioner fatigue factor at t moment, is the maximum value of the air conditioner fatigue factor, p t is the electricity price, p min is the minimum electricity price, p max is the maximum electricity price.

9. The method for determining the air conditioning regulation potential as described in claim 8, characterized in that, determining the running power of the air conditioner corresponding to the optimal solution of the target function as the upper limit value of the running power of the air conditioner, comprising: a set of the user comfort factors, the air conditioner fatigue factors and the user willingness factors as a particle; initializing the iteration number; randomly generating a value of a particle; if the value of the particle satisfies the constraint, substituting the value of the particle into the target function to obtain the solution of the current target function; increasing the iteration number by one and returning to the step of randomly generating a value of a particle; determining the value of the particle corresponding to the minimum value of the solution of the target function within the target iteration number; determining the power of the air conditioner corresponding to the value of the particle corresponding to the minimum value of the solution of the target function as the upper limit value of the running power of the air conditioner.

10. An apparatus for determining the conditioning potential of an air conditioner, comprising: comprising: a memory for storing a computer program; a processor for executing the computer program to realize the steps of the air conditioner regulation potential determination method according to any one of claims 1 to 9.

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