CN114200844B - Intelligent household appliance control method based on dynamic priority ordering - Google Patents
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Abstract
The invention discloses a dynamic priority ordering-based intelligent household appliance control method, which utilizes an entropy weight-based improved approach ideal solution ordering method, carries out priority ordering on household appliances participating in peak shaving or absorption in each round through 4 indexes of user comfort, additional electricity cost/compensation cost, task urgency index and fixed priority index, can realize depth perception and accurate regulation of resident load appliance level, can meet the requirements of user comfort and economy, and has great significance in peak shaving and valley filling in cooperation with a power grid and improving clean energy absorption capacity.
Description
Technical Field
The invention relates to the technical field of intelligent power utilization, in particular to an intelligent household appliance control method based on dynamic priority ordering.
Background
The reform and development of the electric power market gradually diversifies the interest subjects of the electric power system, the importance of the demand side resources is also gradually highlighted, and Demand Response (DR) is generated. The traditional DR is to enable the power consumer to change the power consumption behavior in the power consumption peak period through price signals and an excitation mechanism, so as to relieve the supply pressure of the power grid energy. Along with the increase of power demand and the prominence of environmental problems, the popularization of new energy is expanded, and under the background that the power generation permeability of the new energy is gradually improved, the high-proportion new energy consumption is restricted by a series of problems of unreasonable energy structure, large new energy fluctuation, unmatched supply and demand space, imperfect market mechanism and the like. Therefore, the DR has new development, the new DR is to adjust the electricity consumption according to the price signal and the excitation mechanism, to realize peak clipping and valley filling, to restrain load fluctuation and to promote the high-proportion consumption of new energy. With the deep development of electric power reform and the improvement of the electrification level of a resident on the demand side, the load resource of the resident on the demand side becomes an important resource of demand response, and the resident household appliances participate in 'two-way interaction' of a power grid in a demand response mode, so that the contradiction of electric power supply tension can be effectively relieved, clean energy can be effectively consumed, and the safe and stable operation of an electric power system is improved.
The resident load participation demand response modes are mainly divided into two types: a direct participation mode and an indirect participation mode. The indirect participation mode is that the resident load participates in the demand response by a third party service representative of a load aggregator, an energy service provider, or the like. And the direct participation mode refers to that the resident load participates in demand response through a system such as home energy management (home energy management, HEM). The concept of resident users participating in DR activity through direct participation patterns and priorities has been studied extensively. Manisa Pipattanasomporn et al propose a preset home appliance priority management home load, which can ensure that the home energy is in a control range, but cannot give consideration to real-time changes of home appliances; qi Bing and the like propose a heuristic algorithm for intelligent negotiation control of household appliance loads for expanding OpenADR protocol under the condition of considering load dynamic priority and user satisfaction, so that peak-valley difference reduction can be realized, but the result has a space for improvement; shang Yi et al propose an intelligent home appliance management (home appliances management, HAM) control scheme based on the dynamic priority of the home appliance comfort index, which can better meet the user comfort, but the switching of the home appliance is too frequent, which is unfavorable for the service life of the home appliance, and in addition, the economical efficiency is not better considered; the UO et al propose a household equipment control (household appliance control, HAC) system and algorithm, which take the power and time-of-use electricity price of the household appliances into consideration to realize DR operation priority of the household appliances, can relieve the load curve of the power grid and save the cost, but has limited applicability; shi Tonghui and the like propose an intelligent home management control scheme aiming at high-power-consumption household appliances, comfort level, electricity cost, power-off time and the like are taken as input quantities, the priority of the household appliances is evaluated by using a fuzzy controller to achieve a regulation and control target, the electricity cost can be reduced, a load curve is relieved, but the reduction effect is required to be considered, and the condition of eliminating new energy is not considered.
Disclosure of Invention
The invention discloses a dynamic priority ordering-based intelligent household appliance control method which can effectively solve the technical problems in the background technology.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a method for controlling intelligent household appliances based on dynamic priority ordering comprises the following steps:
step one, a user inputs the use requirements of all household appliances, wherein the use requirements comprise temperature and humidity settings, the use time ranges of all household appliances and the fixed use priorities of the household appliances in different time periods, and an intelligent household appliance control system receives response signals and electricity price information sent by a requirement response server;
step two, after entering a DR period, analyzing the regulation and control quantity of the time gap and determining the regulation and control type in the time gap according to the response signals and the electricity price information sent by the demand response server;
thirdly, prioritizing loads which can participate in response at the current moment based on an entropy weight improvement approximation ideal solution sorting method by determining four indexes of user comfort level, extra electricity cost/compensation cost, task urgency index and fixed priority index;
and fourthly, adjusting the running state of the household appliances according to the response priority of the household appliances, circulating the household appliances in a constraint range, and entering the next time interval until the whole period of demand response is finished after the household appliance decision is executed.
As a preferable improvement of the present invention, in the first step, the home appliance includes a water heater, a warm water dispenser, an air conditioner, an air humidifier and an electric vehicle, the control process is discretized into a plurality of time slots t, each time slot is a control period, and an intelligent home appliance control model is constructed as follows:
the on-off state of the water heater at time t can be expressed as:
wherein DeltaT EWH Setting a range for the temperature of the water heater; s is S EWH，t-1 The water heater is in a switching state at the time t-1; t (T) EWH，s Temperature value set for user, T EWH，t The temperature of the water heater at the moment t;
the on-off state of the warm water dispenser at the time t can be expressed as:
wherein DeltaT DF Setting a range for the temperature of the warm water dispenser; s is S DF，t-1 The water dispenser is in the on-off state at the time t-1; t (T) DF，s Temperature value set for user, T DF，t The temperature at the moment t of the water dispenser;
assuming that the air conditioner operates in a cooling mode, the on-off state of the air conditioner at time t can be expressed as:
wherein DeltaT AC Setting a range for the temperature of the air conditioner; s is S AC，t-1 The air conditioner is in a switching state at the time t-1; t (T) AC，s Temperature value set for user, T AC，t The temperature at the time t of the air conditioner;
the on-off state of the air humidifier at time t can be expressed as:
wherein DeltaH AH Setting a range for the humidity of the humidifier; s is S AH，t-1 The switching state of the humidifier at the moment t-1; h AH，s Humidity value H set for user AH，t The humidity at the moment t of the humidifier;
the switching state of the electric automobile at the time t can be expressed as:
wherein SOC is t For the charge quantity of the electric automobile in the time interval t, SOC max Showing the maximum value of the state of charge of the battery.
As a preferred improvement of the present invention, the second step specifically includes:
the control quantity in the time slot t is determined through real-time analysis, so that the control type in the time slot is determined, and the method can be expressed as follows:
P total (t)＝P base (t)+P target (t)
ΔP(t)＝P total (t)-P real (t)
wherein P is total (t) is the total target power within time interval t; p (P) base (t) is a load baseline of the household appliance within the time interval t; p (P) target (t) is the target consumption of the appliance in the time interval t; p (P) real (t) is the actual operating power in time interval t; Δp (t) is the control amount in time interval t;
if ΔP (t) >0, the household should be loaded during time interval t; ΔP (t) <0, the household should reduce the load during time interval t.
As a preferred improvement of the present invention, in step three, the user comfort for water heaters, warm water dispensers, air conditioners and air humidifiers can be calculated by the following formula:
the user comfort for an electric car can be calculated by the following formula:
in SOC min，t Representing the minimum value of the battery charge state of the electric automobile in the time interval t, if C β，t 1, indicating that the electric automobile cannot complete charging in a specified time, wherein the higher the comfort level of a user is, the lower the satisfaction level is;
if the load should be cut down in the time interval t, the additional electricity cost is calculated by the following formula:
M αc，t = (current electricity price-basic electricity price) ×household electrical appliance power×unit time length
If the load should be increased in the time interval t, the additional compensation cost is calculated by the following formula:
M βc，t = (basic electricity price-current electricity price) ×household electrical appliance power×unit time length
The task urgency index is expressed by the following formula:
wherein N is the planned use time of the household appliance load; τ is the time the home appliance has been running; t is t f The end time of the household appliance load allowed for the user; t is t n Is the actual time;
consider the failure frequency of household electrical appliance loadThe characteristic of start-stop is that for a certain load i in the family, the planned use time N i The runtime has the following constraints:
t i，s ≤t i，on ≤t i，off ≤t i，f
K i ≤J i
wherein t is i，s 、t i，f Starting and ending time of the home appliance i allowed by the user respectively; t is t i，on 、t i，off The actual on-off time of the household appliance i is respectively; k (K) i 、J i The actual interruption times and the allowed maximum interruption times of the household appliance i are respectively.
As a preferred improvement of the present invention, in the third step, the entropy weight-based improvement approaches the ideal solution ordering method to dynamically prioritize the load participating in the response at the current time, and specifically includes the following steps:
the method comprises the following steps of assuming n loads capable of participating in response in a time interval t, assuming n is less than or equal to 6 and 4 evaluation indexes, namely user comfort level, extra electricity cost/compensation cost, task urgency index and fixed priority index, and using a matrix X= (X) for raw data ij ) n×4 Form representation, wherein i=1, 2, …, n; j=1, 2,3,4;
carrying out forward processing on the original matrix, and uniformly converting all index types into maximum indexes, wherein the minimum indexes are converted into maximum indexes:
obtaining a forward matrix as
Normalizing the forward matrix:
thereby, normalized matrix a= (a) is obtained ij ) n×4 ；
Calculating the proportion of the j-th index to the i household appliances in the index:
calculating entropy of the j-th index
Calculating a coefficient of variation:
d j ＝1-h j
weight of j-th evaluation index:
orthoideal solution A + And ideal negative solution A - ：
Distance of ith load from idealDistance from negative ideal solution->Expressed as:
the load dynamic priority ranking, the comprehensive evaluation index of the ith load is as follows:
the magnitude of the value determines the priority of the load,/->The larger the rank that accounts for the load, the higher.
As a preferred improvement of the present invention, the fourth step specifically includes:
according to the order of the priority of the household appliances from high to low, if the load should be increased in the time interval t, gradually starting the load; if load should be reduced in the time interval t, gradually closing the household appliances, selecting k household appliances from n household appliances capable of participating in DR according to priority order to participate in regulation, and re-opening or closing the household appliances, wherein the power respectively meets the following formula:
wherein P is APPi (t) re-opening or closing the household appliance power for the time interval t, entering the next time period to repeat the above after executing the household appliance control decisionAnd step, until the demand response is finished.
The beneficial effects of the invention are as follows: the improved approach ideal solution sequencing method (technique for order preference by similarity to ideal solution, TOPSIS) based on entropy weight is used, 4 indexes of user comfort, extra electricity cost/compensation cost, task urgency index and fixed priority index are used for carrying out priority sequencing on household appliances participating in peak shaving or absorption in each round, depth perception and accurate regulation of resident load appliance level can be achieved, requirements of user comfort and economy can be met, and the method has great significance in peak clipping and valley filling of a matched power grid and improving clean energy absorption capacity.
Drawings
For a clearer description of the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly introduced below, it being obvious that the drawings in the description below are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art, wherein:
FIG. 1 is a schematic diagram of an intelligent home appliance control system based on dynamic prioritization in the present invention;
FIG. 2 is a flow chart of a method for controlling intelligent home appliances based on dynamic prioritization in the present invention;
FIG. 3 is a schematic diagram of a dynamic priority evaluation system for home appliances according to the present invention;
FIG. 4 is a schematic diagram of task urgency in the present invention;
FIG. 5 is a graph of expected load dissipation in the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described in the following in conjunction with the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the intelligent home appliance control system can implement dynamic priority ordering of home appliance loads according to user demands by using electricity price information, and realize automatic DR control. The system comprises an intelligent socket, a bidirectional intelligent metering terminal, a router, a local information management terminal, a mobile terminal, a demand response server, a power grid control center and the like. The bidirectional intelligent metering terminal acquires DR event information and electricity price information from the demand response service center and feeds back user energy information; the mobile terminal provides a function of interaction with a user, acquires the electricity demand of the user and displays household energy information; the local information management terminal is core control equipment of the intelligent household appliance control system and is responsible for communication with the bidirectional intelligent metering terminal and the mobile terminal, and collection and switching of household appliance states are realized through the intelligent socket.
Referring to fig. 2, the invention provides a smart home control method based on dynamic priority ordering, which specifically comprises the following steps:
step one, a user inputs the use requirements of all household appliances, wherein the use requirements comprise the temperature and humidity settings of the household appliances, the use time ranges of all household appliances and the fixed use priorities of the household appliances in different time periods, and an intelligent household appliance control system receives response signals and electricity price information sent by a requirement response server;
the user inputs the user demand of each household electrical appliances to wisdom household electrical appliances control system, specifically includes the setting temperature (humidity) of household electrical appliances such as water heater, warm type water dispenser, air conditioner, air humidifier to and water heater, warm type water dispenser, air conditioner, air humidifier, electric automobile's service time range, in addition the household electrical appliances of different periods of time are fixed to use the priority. The control process is discretized into a plurality of time slots t, each time slot is a control period, and an intelligent household appliance control model is constructed as follows:
1) The on-off state of the water heater at time t can be expressed as:
wherein DeltaT EWH Setting a range for the temperature of the water heater; s is S EWH，t-1 The water heater is in a switching state at the time t-1; t (T) EWH，s Temperature value set for user, T EWH，t The temperature of the water heater at the moment t;
2) The on-off state of the warm water dispenser at the time t can be expressed as:
wherein DeltaT DF Setting a range for the temperature of the warm water dispenser; s is S DF，t-1 The water dispenser is in the on-off state at the time t-1; t (T) DF，s Temperature value set for user, T DF，t The temperature at the moment t of the water dispenser;
3) Assuming that the air conditioner operates in a cooling mode, the on-off state of the air conditioner at time t can be expressed as:
wherein DeltaT AC Setting a range for the temperature of the air conditioner; s is S AC，t-1 The air conditioner is in a switching state at the time t-1; t (T) AC，s Temperature value set for user, T AC，t The temperature at the time t of the air conditioner;
4) The on-off state of the air humidifier at time t can be expressed as:
wherein DeltaH AH Setting a range for the humidity of the humidifier; s is S AH，t-1 The switching state of the humidifier at the moment t-1; h AH，s Humidity value H set for user AH，t The humidity at the moment t of the humidifier;
5) The switching state of the electric automobile at the time t can be expressed as:
wherein SOC is t For the charge quantity of the electric automobile in the time interval t, SOC max Showing the maximum value of the state of charge of the battery.
Step two, after entering the DR period, analyzing the regulation and control quantity of the time gap and determining the regulation and control type in the time slot according to the response signals and the electricity price information sent by the demand response server; the method specifically comprises the following steps:
real-time analysis determines the regulation and control quantity in the time slot t, thereby determining the regulation and control type in the time slot:
P total (t)＝P base (t)+P target (t)
ΔP(t)＝P total (t)-P real (t)
wherein P is total (t) is the total target power within time interval t; p (P) base (t) is a load baseline of the household appliance within the time interval t; p (P) target (t) is the target consumption of the appliance in the time interval t; p (P) real (t) is the actual operating power in time interval t; Δp (t) is the control amount in time interval t;
if ΔP (t) >0, the household should be loaded during time interval t; ΔP (t) <0, the household should reduce the load during time interval t.
Thirdly, prioritizing loads which can participate in response at the current moment based on an entropy weight improvement approximation ideal solution sorting method by determining four indexes of user comfort level, extra electricity cost/compensation cost, task urgency index and fixed priority index;
referring again to fig. 3, the method specifically includes: and respectively calculating Euclidean distances between each evaluation object and the positive ideal solution and between each evaluation object and the negative ideal solution to obtain the relative proximity degree of each evaluation object and the ideal solution, and taking the relative proximity degree as the basis of the load priority ranking which can participate in the demand response at the current moment.
1) In order to reasonably control each household appliance, the dynamic priority of the household appliance load is determined by a plurality of indexes, namely user comfort level, additional electricity consumption cost/compensation cost, task urgency index and fixed priority index:
(1) User comfort:
user comfort for water heaters, warm water dispensers, air conditioners, and air humidifiers can be calculated by the following formula:
the user comfort for an electric car can be calculated by the following formula:
in SOC min，t Representing the minimum value of the battery charge state of the electric automobile in the time interval t, if C β，t 1, indicating that the electric vehicle cannot complete charging at a prescribed time. The higher the user comfort, the lower the satisfaction of the instruction;
if the load should be increased in the time interval t, the higher the user comfort level is, the better; the lower the user comfort, the better if the load should be cut down in the time slot t.
(2) If load should be reduced in the time interval t, calculating extra electricity cost:
M αc，t = (current electricity price-basic electricity price) ×household electrical appliance power×unit time length
If the load should be increased in the time interval t, calculating additional compensation cost:
M βc，t = (basic electricity price-current electricity price) ×household electrical appliance power×unit time length
The lower the additional electricity costs, the better and the higher the additional compensation costs.
(3) Task urgency index
Wherein N is the planned use time of the household appliance load; τ is when the household appliance is already operatingA compartment; t is t f The end time of the household appliance load allowed for the user; t is t n Is the actual time.
Task urgency is shown in FIG. 4, t s Start time of home appliance load allowed for user, t f Start time of home appliance load allowed for user, at t n At this time, if a load has been operated for a period of τ, the task urgency index of the load is represented by expression (12).
Considering the characteristic that the household appliance load cannot be frequently started and stopped, the planned use time N of a certain load i in the household i The runtime has the following constraints:
t i，s ≤t i，on ≤t i，off ≤t i，f
K i ≤J i
wherein t is i，s 、t i，f Starting and ending time of the home appliance i allowed by the user respectively; t is t i，on 、t i，off The actual on-off time of the household appliance i is respectively; k (K) i 、J i The actual interruption times and the allowed maximum interruption times of the household appliance i are respectively.
If the load should be increased in the time interval t. The higher the task urgency index, the better; if the load should be reduced in the time interval t, the lower the task urgency index is, the better.
(4) Fixed priority index
The index characterizes the electricity utilization habit of the user, the user designates in advance, and the load priorities of different time periods can be different. If the load should be increased in the time interval t, the higher the fixed priority index is, the better; if the load should be cut down in the time slot t, the lower the fixed priority index is, the better.
2) The improved TOPSIS method based on the entropy weight carries out dynamic priority ordering on loads participating in response, and specifically comprises the following steps:
(1) Assuming n loads that can participate in the response within the time slot t,assuming n is less than or equal to 6,4 evaluation indexes, namely user comfort, extra electricity cost/compensation cost, task urgency index and fixed priority index, the original data is represented by matrix X= (X) ij ) n×4 Form representation, wherein i=1, 2, …, n; j=1, 2,3,4;
(2) Carrying out forward processing on the original matrix, and uniformly converting all index types into maximum indexes, wherein the minimum indexes are converted into maximum indexes:
obtaining a forward matrix as
(3) Normalizing the forward matrix:
thereby, normalized matrix a= (a) is obtained ij ) n×4 。
(4) Calculating the proportion of the j-th index to the i household appliances in the index:
(5) Calculating entropy of the j-th index
(6) Calculating a coefficient of variation:
d j ＝1-h j
(7) Weight of j-th evaluation index:
(8) Orthoideal solution A + And ideal negative solution A - ：
(9) Distance of ith load from idealDistance from negative ideal solution->Expressed as:
(10) The load dynamic priority ranking, the comprehensive evaluation index of the ith load is as follows:
the magnitude of the value determines the priority of the load,/->The larger the rank that accounts for the load, the higher.
And step four, adjusting the running state of the household appliances according to the response priority of the household appliances, circulating the household appliances in a constraint range, and entering the next time interval until the whole period of demand response is finished after the household appliance decision is executed.
The method specifically comprises the following steps: according to the order of the priority of the household appliances from high to low, if the load should be increased in the time interval t, gradually starting the load; if load should be reduced in the time interval t, gradually closing the household appliances, selecting k household appliances from n household appliances capable of participating in DR according to priority order to participate in regulation, and re-opening or closing the household appliances, wherein the power respectively meets the following formula:
wherein P is APPi (t) re-opening or closing the household appliance power for the time interval t. And after the household appliance control decision is executed, the next period is started to repeat the steps until the demand response is finished, and the expected load absorption condition in the invention is shown in fig. 5.
The beneficial effects of the invention are as follows: the improved approach ideal solution sequencing method (technique for order preference by similarity to ideal solution, TOPSIS) based on entropy weight is used, 4 indexes of user comfort, extra electricity cost/compensation cost, task urgency index and fixed priority index are used for carrying out priority sequencing on household appliances participating in peak shaving or absorption in each round, depth perception and accurate regulation of resident load appliance level can be achieved, requirements of user comfort and economy can be met, and the method has great significance in peak clipping and valley filling of a matched power grid and improving clean energy absorption capacity.
The embodiments disclosed above, but not limited to the use as set forth in the description and the embodiments, are well suited to various fields of use for the invention, and additional modifications will readily occur to those skilled in the art, and therefore the invention is not limited to the specific details and illustrations shown and described herein, without departing from the general concepts defined by the claims and the equivalents thereof.
Claims (4)
1. The intelligent household appliance control method based on dynamic priority ordering is characterized by comprising the following steps of:
step one, a user inputs the use requirements of all household appliances, wherein the use requirements comprise temperature and humidity settings, the use time ranges of all household appliances and the fixed use priorities of the household appliances in different time periods, and an intelligent household appliance control system receives response signals and electricity price information sent by a requirement response server;
step two, after entering a DR period, analyzing the regulation and control quantity of the time gap and determining the regulation and control type in the time gap according to the response signals and the electricity price information sent by the demand response server;
thirdly, prioritizing the load which can participate in response at the current moment based on an entropy weight improvement approximation ideal solution sorting method by determining four indexes of user comfort level, extra electricity cost/compensation cost, task urgency index and fixed priority index, wherein the method specifically comprises the following steps:
user comfort for water heaters, warm water dispensers, air conditioners, and air humidifiers can be calculated by the following formula:
the user comfort for an electric car can be calculated by the following formula:
in SOC t For the charge quantity of the electric automobile in the time interval t, SOC min,t Representing the minimum value of the battery charge state of the electric automobile in the time interval t, if C β,t 1, the electric automobile can not complete charging in a specified time, the higher the comfort level of the user is, sayThe lower the degree of satisfaction is;
if the load should be cut down in the time interval t, the additional electricity cost is calculated by the following formula:
M αc,t = (current electricity price-basic electricity price) ×household electrical appliance power×unit time length
If the load should be increased in the time interval t, the additional compensation cost is calculated by the following formula:
M βc,t = (basic electricity price-current electricity price) ×household electrical appliance power×unit time length
The task urgency index is expressed by the following formula:
wherein N is the planned use time of the household appliance load; τ is the time the home appliance has been running; t is t f The end time of the household appliance load allowed for the user; t is t n Is the actual time;
considering the characteristic that the household appliance load cannot be frequently started and stopped, the planned use time N of a certain load i in the household i The runtime has the following constraints:
t i,s ≤t i,on ≤t i,off ≤t i,f
K i ≤J i
wherein t is j,s 、t i,f Starting and ending time of the home appliance i allowed by the user respectively; t is t i,on 、t i,off The actual on-off time of the household appliance i is respectively; k (K) i 、J i The actual interruption times and the allowed maximum interruption times of the household appliance i are respectively;
the load n which can participate in response in the time interval r is assumed, and n is not more than 6,4 evaluation indexes are assumed, namely user comfort level, extra electricity cost/compensation cost, task urgency index, fixed priority index and original numberData matrix x= (X) ij ) n×4 Form representation, wherein i=1, 2, …, n; j=1, 2,3,4;
carrying out forward processing on the original matrix, and uniformly converting all index types into maximum indexes, wherein the minimum indexes are converted into maximum indexes:
obtaining a forward matrix as
Normalizing the forward matrix:
thereby, normalized matrix a= (a) is obtained ij ) n×4 ；
Calculating the proportion of the j-th index to the i household appliances in the index:
calculating entropy of the j-th index
Calculating a coefficient of variation:
d j ＝1-h j
weight of j-th evaluation index:
ideal and positiveSolution A + And ideal negative solution A - ：
Distance of ith load from idealDistance from negative ideal solution->Expressed as:
the load dynamic priority ranking, the comprehensive evaluation index of the ith load is as follows:
the magnitude of the value determines the priority of the load,/->The larger the rank that accounts for the load, the higher the rank;
and fourthly, adjusting the running state of the household appliances according to the response priority of the household appliances, circulating the household appliances in a constraint range, and entering the next time interval until the whole period of demand response is finished after the household appliance decision is executed.
2. The intelligent home appliance control method based on dynamic prioritization as claimed in claim 1, wherein: in the first step, the household appliance comprises a water heater, a warm water dispenser, an air conditioner, an air humidifier and an electric automobile, the control process is discretized into a plurality of time slots t, each time slot is a control period, and an intelligent household appliance control model is constructed as follows:
the on-off state of the water heater at time t can be expressed as:
wherein DeltaT EWH Setting a range for the temperature of the water heater; s is S EWH,t-1 The water heater is in a switching state at the time t-1; t (T) EWH,s Temperature value set for user, T EWH,t The temperature of the water heater at the moment t;
the on-off state of the warm water dispenser at the time t can be expressed as:
wherein DeltaT DF Setting a range for the temperature of the warm water dispenser; s is S DF,t-1 The water dispenser is in the on-off state at the time t-1; t (T) DF,s Temperature value set for user, T DF,t The temperature at the moment t of the water dispenser;
assuming that the air conditioner operates in a cooling mode, the on-off state of the air conditioner at time t can be expressed as:
wherein DeltaT AC Setting a range for the temperature of the air conditioner; s is S AC,t-1 The air conditioner is in a switching state at the time t-1; t (T) AC,s Temperature value set for user, T AC,t The temperature at the time t of the air conditioner;
the on-off state of the air humidifier at time t can be expressed as:
wherein DeltaH AH Setting a range for the humidity of the humidifier; s is S AH,t-1 The switching state of the humidifier at the moment t-1; h AH,s Humidity value H set for user AH,t The humidity at the moment t of the humidifier;
the switching state of the electric automobile at the time t can be expressed as:
wherein SOC is t For the charge quantity of the electric automobile in the time interval t, SOC max Showing the maximum value of the state of charge of the battery.
3. The intelligent home appliance control method based on dynamic prioritization as claimed in claim 1, wherein: the second step specifically comprises:
the control quantity in the time slot t is determined through real-time analysis, so that the control type in the time slot is determined, and the method can be expressed as follows:
P total (t)＝P base (t)+P target (t)
ΔP(t)＝P total (t)-P real (t)
wherein P is total (t) is the total target power within time interval t; p (P) base (t) is a load baseline of the household appliance within the time interval t; p (P) target (t) is the target consumption of the appliance in the time interval t; p (P) real (t) is the actual work of operation in the time interval tA rate; Δp (t) is the control amount in time interval t;
if Δp (t) >0, the household should increase the load during time interval t; Δp (t) <0, the household should reduce the load during time interval t.
4. The intelligent home appliance control method based on dynamic prioritization as claimed in claim 1, wherein: the fourth step specifically comprises:
according to the order of the priority of the household appliances from high to low, if the load should be increased in the time interval t, gradually starting the load; if load should be reduced in the time interval t, gradually closing the household appliances, selecting k household appliances from n household appliances capable of participating in DR according to priority order to participate in regulation, and re-opening or closing the household appliances, wherein the power respectively meets the following formula:
wherein DeltaP (t) is the regulation and control quantity in the time interval t, P APPi And (t) restarting or closing the household appliance power for the time interval t, executing the household appliance control decision, and then entering the next time period to repeat the steps until the demand response is finished.
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