CN107608218A - Household electrical appliance intelligent power control method - Google Patents
Household electrical appliance intelligent power control method Download PDFInfo
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- CN107608218A CN107608218A CN201710796719.4A CN201710796719A CN107608218A CN 107608218 A CN107608218 A CN 107608218A CN 201710796719 A CN201710796719 A CN 201710796719A CN 107608218 A CN107608218 A CN 107608218A
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Abstract
The present invention provides a kind of household electrical appliance intelligent power control method, including：Intelligent electric meter sends the charged data of collection to household energy management system；Household energy management system obtains charged data and comfort level setting value and calculated；The running status that household energy management system passes through wireless network control household electrical appliance according to result of calculation.A system being made up of household electrical appliance, intelligent electric meter, the small-scale photovoltaic generating system of family and household energy management system is constructed on hardware view, household energy management system passes through the start-stop of wireless network control household electrical appliance, more intellectuality；Take into account user's comfortableness and electric cost simultaneously so that family's electric cost expenditure is minimum；Wired home electricity system power-balance is ensure that, and eliminates household electricity structure to adverse effect caused by bulk power grid.
Description
Technical field
The invention belongs to Power System Intelligent control technology field, more particularly to a kind of household electrical appliance intelligent power controlling party
Method.
Background technology
Household electric appliance intelligent control is by carrying out information exchange, effective intelligent control household electrical appliance to household electrical appliance
Running status, realize optimization family electricity structure, and the comfortableness of user's life staying idle at home can be lifted.Existing household electrical appliance intelligence
It is the binary switch and energy management scheme by intelligent appliance to change control, is completed between operator and the equipment of smart machine
Two-way communication between instruction and data flow, realizes household electrical appliance spatial load forecasting, is required according to loadtype and the different of region
Using different spatial load forecasting schemes, different algorithm and models has been used.But current control program is not in hardware view
Build intelligent appliance control system, it is impossible to while take into account user's comfortableness and electric cost problem.
The content of the invention
In order to solve the above technical problems, the present invention provides a kind of household electrical appliance intelligent power control method.In order to disclosing
The some aspects of embodiment have a basic understanding, shown below is simple summary.The summarized section is not generally to comment
State, nor to determine key/critical component or describe the protection domain of these embodiments.Its sole purpose is with simple
Form some concepts are presented, in this, as the preamble of following detailed description.
The present invention adopts the following technical scheme that：
In some optional embodiments, there is provided a kind of household electrical appliance intelligent power control method, including：Intelligent electric meter is adopted
Collect the state-of-charge of household electrical appliance load, and the generated energy of small-scale photovoltaic generating system, to bulk power grid sale of electricity and power purchase
Electricity, and the charged data of collection are sent to household energy management system；Household energy management system obtains the charged number
According to and comfort level setting value and calculated；The household energy management system passes through wireless network control man according to result of calculation
The running status of electrical appliance.
In some optional embodiments, the household electrical appliance include：Controllable household electrical appliance and uncontrollable household electrical appliance, institute
Stating controllable household electrical appliance includes：The controllable household electrical appliance of non-constant temperature and the controllable household electrical appliance of constant temperature；The uncontrollable household electrical appliance bag
Include：Electric light, computer and refrigerator；The controllable household electrical appliance of non-constant temperature include：Dry cleaner, washing machine and be electric automobile；Institute
Stating the controllable household electrical appliance of constant temperature includes：Air-conditioning and electric heater.
In some optional embodiments, the household energy management system obtains charged data and the comfort level setting
The process for being worth and being calculated includes：Set initial velocity and the position of population；According to the small-scale photovoltaic generating system
Generated energy setting particulate initial solution, calculate the fitness of each particle；Calculate the electricity charge of each period and total electricity under original state
Take, obtain 24 fitness values, choose wherein minimum local optimum fitness value and global optimal adaptation angle value initial value；More
New day part particle rapidity and position.
In some optional embodiments, the household energy management system obtains charged data and the comfort level setting
The process for being worth and being calculated also includes：Judge whether generated energy meets workload demand, judge if workload demand is met comfortable
Whether degree is out-of-limit, otherwise examines the state of household electrical appliance successively according to the comfort level setting value, and according to priority by as little as
High orderly close-down household electrical appliance, until generated energy meets workload demand；Judge whether comfort level is out-of-limit, if comfort level is out-of-limit,
Then assignment carries out calculating each moment optimal operation mode combination of acquisition again；The electricity charge and the total electricity bill of each period is calculated, is obtained
24 fitness values, choose wherein minimum local optimum fitness value；Compare local optimum fitness value and the history overall situation most
Good fitness value, update global optimal adaptation angle value；Update inertia weight；Judge whether to reach iterations, if reaching iteration
Number, then finishing control flow, otherwise updates day part particle rapidity and position.
In some optional embodiments, the small-scale photovoltaic generating system includes：Photovoltaic array, controller
And inverter.
Beneficial effect caused by the present invention：One is constructed on hardware view by household electrical appliance, intelligent electric meter, family
The system that small-scale photovoltaic generating system and household energy management system are formed, household energy management system pass through wireless network control
The start-stop of household electrical appliance processed, it is more intelligent；Structure household electrical appliance model is accustomed to and with method for electrically according to user power utilization, and then
More real control mode is constructed, user's comfortableness and electric cost can be taken into account simultaneously so that family's electric cost expenditure is minimum；
Wired home electricity system power-balance is ensure that, and eliminates household electricity structure to adverse effect caused by bulk power grid.
For above-mentioned and related purpose, one or more embodiments include will be explained in below and in claim
In the feature that particularly points out.Following explanation and accompanying drawing describe some illustrative aspects in detail, and its instruction is only
Some modes in the utilizable various modes of principle of each embodiment.Other benefits and novel features will be under
The detailed description in face is considered in conjunction with the accompanying and becomes obvious, the disclosed embodiments be will include all these aspects and they
Be equal.
Brief description of the drawings
Fig. 1 is the schematic diagram of present inventor's electrical appliance model；
Fig. 2 is the schematic flow sheet of present invention kind household electrical appliance intelligent power control method；
Fig. 3 is that household energy management system of the present invention obtains charged data and comfort level setting value and the flow calculated
Schematic diagram.
Embodiment
The following description and drawings fully show specific embodiments of the present invention, to enable those skilled in the art to
Put into practice them.Other embodiments can include structure, logic, it is electric, process and other change.Embodiment
Only represent possible change.Unless explicitly requested, otherwise single components and functionality is optional, and the order operated can be with
Change.The part of some embodiments and feature can be included in or replace part and the feature of other embodiments.This hair
The scope of bright embodiment includes the gamut of claims, and claims is all obtainable equivalent
Thing.
As shown in Figures 1 to 3, in some illustrative embodiments, the present invention construct by environmental protection and energy saving electric automobile,
The home intelligent power load such as air-conditioning, electric heater, electric light, television set, refrigerator, washing machine, and small-scale photovoltaic generation
The family expenses that system, intelligent electric meter, household energy management system (HEMS, Home Energy Management System) are formed
Appliance model, by analyzing intelligent appliance information, intelligent control is carried out to the running status of each electrical equipment.
In household electrical appliance model, the state-of-charge of household electrical appliance load is delivered in intelligent electric meter, small-scale photovoltaic generation
System generated energy, gathered by intelligent electric meter to bulk power grid sale of electricity and power purchase.Intelligent electric meter is by power consumption in household electrical appliance model
Deliver in HEMS, the comfort level setting value and the charged situation of each load that HEMS is inputted by user, using intellectualized algorithm, pass through
Family wireless network controls the running status of load, both causes system stable operation, causes that family's electric cost expenditure is minimum again.
Household electrical appliance include：Controllable household electrical appliance and uncontrollable household electrical appliance, uncontrollable household electrical appliance running situation can lead to
Cross historical data to be predicted, uncontrollable household electrical appliance include：Electric light, computer and refrigerator.The controllable household electrical appliance include：
The controllable household electrical appliance of non-constant temperature and the controllable household electrical appliance of constant temperature.The non-controllable household electrical appliance of constant temperature include：Dry cleaner, washing machine and it is
Electric automobile, start-stop control is directly carried out according to household electricity situation.The controllable household electrical appliance of constant temperature include：Air-conditioning and electric hot water
Device, there is energy-storage function, the scheduling of load must account for the dynamic process of heating or refrigeration, the randomness of load, and disappear
The electricity consumption comfort level demand of the person of expense.
The emphasis of the present invention is that controllable household electrical appliance load is modeled, although controllable its working machine of household electrical appliance load
Reason is different, but household electrical appliances electricity cost is all influenceed by factors such as Spot Price, running status, power, thus controllable household electrical appliance this
Type load electricity cost Optimized model can be collectively expressed as：
Wherein, constraints is：
Zn+1=f (Zn,Pα,……) (1a)
Zmin≤Zn≤Zmax (1b)
The purpose of formula 1 be in order to reduce electric cost expenditure to greatest extent in following a period of time, wherein,For n when
Electricity price, βnFor the household electrical appliances running status in n, PαFor the rated power of household electrical appliance load, Δ T represents time interval；ZnRepresent
In tnWhen family's electric load current intelligence, Zmin、ZmaxThe respectively lower and upper limit of comfort level scope, according to historical data and
User is accustomed to obtaining the model of controllable household electrical appliance.
For whole home intelligent power system, target is by being controlled to controllable type household electrical appliance load come really
Determine least cost and optimized operation, (2) formula can be used to represent：
Here, Pt gridPower network power output is represented, is the β in formula 1 in each electric modeln·PαSum, Pt PV,soldTable
Showing that photovoltaic generation is sold to the power of power network, Δ T represents time interval [h],Represent that electric energy buys in electricity price from power network,Generation
Table electric energy is sold back to the electricity price of power network.
Household electrical appliance model running constraints with small-scale photovoltaic generating system and household electrical appliance is：
In family, the power balance equation at each moment can be described as formula 2a：
Wherein, Pt gridRepresent power network power output, Pt PV,usedRepresent that photovoltaic generation is used for the power of family, LtTo be non-controllable
Household electrical appliance load, Pt EVCharging electric vehicle power is represented,Represent controllable household electric appliance power, Pt EWHRepresent electric hot water
Device power, Pt ACRepresent air-conditioning power.
Wherein, Pt PV,PRORepresent photovoltaic generation power, ut gridIf representing power network power output, for 1, otherwise work(is absorbed
Rate is then 0, Pt PV,soldRepresent that photovoltaic generation is sold to the power of power network；Parameter N1And N2For to sucking or being injected back into grid power
It is any limitation as, user can set a reasonable value according to home background.
Optimization aim is under the conditions of users'comfort is met, the electric cost expenditure for making family total is minimum.Particle Swarm Optimization
Method is that solve the more applicable method of stochastic optimization problems.The speed and location updating formula of particle is：
In above formula：Inertia weight w describes influence of the inertia to speed of particle, and w values influence whether particle cluster algorithm
Global and local search capability, w is more big, and then ability of searching optimum is stronger.c1、c2For Studying factors, usually constant, r1, r2It is 0
Random number between to 1.Guided by adjustment of the Q learning methods to inertia weight w, to improve response speed, and avoid falling into
Enter local optimum.W more new formula is as follows：
Wherein, α learning rates ∈ [0,1], γ discount factors ∈ [0,1], A be all alternative actions set, r
(s, it is a) reward function value, wk(s ', a ') is the functional value of any behavior a ' of Systematic selection in next state s.
The present invention provides a kind of household electrical appliance intelligent power control method, including：
11：The state-of-charge of intelligent electric meter collection household electrical appliance load, and the generated energy of small-scale photovoltaic generating system,
Sent to bulk power grid sale of electricity and the electricity of power purchase, and by the charged data of collection to household energy management system.
12：Household energy management system obtains charged data and comfort level setting value and calculated, comfort level setting value
It is configured by user.
13：The running status that household energy management system passes through wireless network control household electrical appliance according to result of calculation.Adopt
With intellectualized algorithm, the running status of load is controlled by family wireless network, both causes system stable operation, causes family again
Electric cost expenditure is minimum.
The household electrical appliance intelligent power control method of the present invention is calculated using particle swarm optimization algorithm, and population is calculated
Method is a kind of optimized algorithm for solving stochastic problem based on colony intelligence.
Wherein, household energy management system obtains the charged data and comfort level setting value and the process bag calculated
Include：
1201：Initialization, setting comfort of air conditioner scope, the washing machine start completion time, the charging electric vehicle time, can
Control the priority of household electrical appliance.
1202：Population scale is set, sets initial velocity and the position of population, is specially：Randomly generate one
The two-dimensional array of (popsize, dimension), the two-dimensional array of one (288,24) is produced herein.Speed is initialized to set
To be decremented to 0.4 linear, accelerator coefficient c from 0.91And c22 are arranged to, maximum cycle is set to 5000, and population has 24
Individual position.
1203：Generated energy according to the small-scale photovoltaic generating system sets particulate initial solution, calculates the suitable of each particle
Response.By formula 2, constraints is formula 2a, formula 2b, formula 2c and formula 2d, with controllable household electrical appliance it is minimum into
The fitness of sheet and optimized operation as each particulate.
1204：The electricity charge of each period and total electricity bill under original state are calculated, obtains 24 fitness values, is chosen wherein most
Small local optimum fitness value and global optimal adaptation angle value initial value；Select preferable 24 of performance micro- from each population
Grain is used as initial solution, in current 24 particulates, will select the best conduct overall situation optimal adaptation angle value of fitness.
1205：By formula 3, day part particle rapidity and position are updated.
1206：Judge whether generated energy meets workload demand, if meeting workload demand, carry out step 1207, otherwise enter
Row step 1213.
1207：Judge whether comfort level is out-of-limit, if comfort level is out-of-limit, carry out step 1208, otherwise carry out step 1209.
1208：According to formula 1, formula 1a, formula 1b, formula 2, formula 2a, formula 2b, formula 2c, formula 2d, formula 3,
Again assignment carries out calculating each moment optimal operation mode combination of acquisition formula 4.
1209：The electricity charge and the total electricity bill of each period is calculated, obtains 24 fitness values, chooses wherein minimum part most
Good fitness value.
1210：After the completion of the calculating of a new round, compare local optimum fitness value and history overall situation optimal adaptation angle value, more
New global optimal adaptation angle value.If this time local optimum fitness value is better than global optimal adaptation angle value, by this part
Optimal adaptation angle value is updated to global optimal adaptation angle value, otherwise maintains former global optimal adaptation angle value.
1211：Inertia weight is updated according to formula 4.
1212：Judge whether to reach iterations, if reaching iterations, finishing control flow, otherwise carry out step
1205, iterations 5000.
1213：Examine the state of household electrical appliance successively according to the comfort level setting value, and according to priority from low to high
Orderly close-down household electrical appliance, until generated energy meets workload demand.With electric automobile, washing machine, air-conditioning, electric heater in figure
Order, be shown exemplified by the order of priority from low to high, examine the state of household electrical appliance successively, close a household electric
Examine total load whether out-of-limit after device, if out-of-limit, detect next household electrical appliance in order.
If total power consumption limits less than demand, i.e., generated energy meets workload demand, and out-of-limit without comfort level occurs, then not
Take any operation.
If being unsatisfactory for comfort level requirement, i.e. generation comfort level is out-of-limit, and household energy management system will force selected family
Electrical appliance is opened to meet comfort level.
If total power consumption limits higher than demand, i.e., generated energy is unsatisfactory for workload demand, and household energy management system will close
The minimum load of priority, the priority set according to user, first since the minimum electric automobile of priority, followed by wash
Clothing machine and air-conditioning, it is finally electric heater, to keep total power consumption to be limited less than demand.
When the total power consumption that household electrical appliance occur is more than, demand is limited and comfort level is more prescribed a time limit, and considers whether to meet first
Overall energy balance demand, under the conditions of meet demand, then meet comfort level as much as possible.Required that controllable family can be set according to user
The running priority level of electrical appliance, when the total power consumption that household electrical appliance occur is more than demand limitation and has the comfort level of a household electrical appliance
Surmount, then household energy management system bears the priority of household electrical appliance in more all operations from lowest priority
Lotus begins to shut off the electrical equipment until highest priority, until the equilibrium of supply and demand.Pass through the Particle Swarm Optimization based on Q learning methods again
Method, carried out according to formula 1, formula 1a, formula 1b, formula 2, formula 2a, formula 2b, formula 2c, formula 2d, formula 3, formula 4
Again assignment calculates, and to seek optimal solution, that is, obtains each moment optimal operation mode combination.If household electrical appliance priority is higher than
During other household electrical appliance opened, household energy management system will close the load of lower priority, be set until total power consumption is less than
Fixed demand limitation.
The small-scale photovoltaic generating system includes：Photovoltaic array, controller and inverter
The present invention provides New Century Planned Textbook for China's electric power in space and seasonal supply and demand anxiety problem, promotes the hair of technology
Exhibition, solve it is grid-connected after power network will appear from load peak-valley difference increase, the quality of power supply be deteriorated, operation stability reduce etc. ask
Topic so that electrical equipment economical operation, using automatic control mode, it is not necessary to which user is manually operated, it is therefore prevented that user is missed
Operation, it is no more than 0.2S once breaking down and cutting fault time.
It should also be appreciated by one skilled in the art that the various illustrative boxes described with reference to the embodiments herein, mould
Block, circuit and algorithm steps can be implemented as electronic hardware, computer software or its combination.In order to clearly demonstrate hardware and
Interchangeability between software, various illustrative part, frame, module, circuit and steps are carried out around its function above
It is generally described.Hardware is implemented as this function and is also implemented as software, depending on specific application and to whole
The design constraint that system is applied.Those skilled in the art can be directed to each application-specific, be realized in a manner of flexible
Described function, it is still, this to realize that decision-making should not be construed as the protection domain away from the disclosure.
Claims (5)
1. household electrical appliance intelligent power control method, it is characterised in that including：
Intelligent electric meter gathers the state-of-charge of household electrical appliance load, and generated energy, the Xiang great electricity of small-scale photovoltaic generating system
Net sale of electricity and the electricity of power purchase, and the charged data of collection are sent to household energy management system；
Household energy management system obtains the charged data and comfort level setting value and calculated；
The running status that the household energy management system passes through wireless network control household electrical appliance according to result of calculation.
2. household electrical appliance intelligent power control method according to claim 1, it is characterised in that the household electrical appliance bag
Include：Controllable household electrical appliance and uncontrollable household electrical appliance, the controllable household electrical appliance include：The controllable household electrical appliance of non-constant temperature and constant temperature
Controllable household electrical appliance；
The uncontrollable household electrical appliance include：Electric light, computer and refrigerator；
The controllable household electrical appliance of non-constant temperature include：Dry cleaner, washing machine and be electric automobile；
The controllable household electrical appliance of constant temperature include：Air-conditioning and electric heater.
3. household electrical appliance intelligent power control method according to claim 2, it is characterised in that the home energy management
The process that system obtains the charged data and comfort level setting value and calculated includes：
Set initial velocity and the position of population；
Generated energy according to the small-scale photovoltaic generating system sets particulate initial solution, calculates the fitness of each particle；
The electricity charge of each period and total electricity bill under original state are calculated, obtains 24 fitness values, chooses wherein minimum part
Optimal adaptation angle value and global optimal adaptation angle value initial value；
Update day part particle rapidity and position.
4. household electrical appliance intelligent power control method according to claim 3, it is characterised in that the home energy management
The process that system obtains the charged data and comfort level setting value and calculated also includes：
Judge whether generated energy meets workload demand, judge whether comfort level is out-of-limit if workload demand is met, otherwise according to institute
The state that comfort level setting value examines household electrical appliance successively, and the orderly close-down household electrical appliance according to priority from low to high are stated,
Until generated energy meets workload demand；
Judge whether comfort level is out-of-limit, if comfort level is out-of-limit, assignment, which calculate, again obtains each moment optimal operation mode
Combination；
The electricity charge and the total electricity bill of each period is calculated, obtains 24 fitness values, chooses wherein minimum local optimum fitness
Value；
Compare local optimum fitness value and history overall situation optimal adaptation angle value, update global optimal adaptation angle value；
Update inertia weight；
Judge whether to reach iterations, if reaching iterations, finishing control flow, otherwise update day part particle rapidity
And position.
5. household electrical appliance intelligent power control method according to claim 1, it is characterised in that the small-scale photovoltaic hair
Electric system includes：Photovoltaic array, controller and inverter.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110109367A (en) * | 2019-05-13 | 2019-08-09 | 北京科创智汇科技有限责任公司 | Safety control system |
| CN110173835A (en) * | 2019-05-10 | 2019-08-27 | 广东美的制冷设备有限公司 | Control method, device and the air conditioner of air conditioner |
| CN110837857A (en) * | 2019-10-31 | 2020-02-25 | 杭州中恒云能源互联网技术有限公司 | Industrial electricity load prediction method, system and storage medium thereof |
| CN111817302A (en) * | 2020-07-31 | 2020-10-23 | 三峡大学 | Load operation optimization method considering flexibility potential |
| CN112366708A (en) * | 2020-11-30 | 2021-02-12 | 深圳市汇拓新邦科技有限公司 | Charging management method, device, equipment and storage medium |
| CN114598564A (en) * | 2022-02-23 | 2022-06-07 | 杭州博联智能科技股份有限公司 | Equipment control method, system, electronic equipment and storage medium |
| CN116449723A (en) * | 2023-05-29 | 2023-07-18 | 固强科技（深圳）有限公司 | Intelligent household appliance control system |
| CN117331320A (en) * | 2023-12-01 | 2024-01-02 | 佳源科技股份有限公司 | Household appliance control method and system based on electric energy meter data analysis |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100891513B1 (en) * | 2008-08-18 | 2009-04-06 | 주식회사 케이디파워 | Grid-connected hybrid generation system using solar photovoltaic generation system and battery system and generation method using thereof |
| CN104008432A (en) * | 2014-06-03 | 2014-08-27 | 华北电力大学 | Micro-grid short-term load forecasting method based on EMD-KELM-EKF |
| CN104182809A (en) * | 2014-08-29 | 2014-12-03 | 国家电网公司 | Optimization method of intelligent household power system |
| CN104778507A (en) * | 2015-04-02 | 2015-07-15 | 南京邮电大学 | Intelligent building power utilization strategy acquiring method based on self-adaptive particle swarm algorithm |
| CN106602557A (en) * | 2017-02-24 | 2017-04-26 | 三峡大学 | Multi-period optimization reconstruction method of active power distribution network comprising electric automobiles |
-
2017
- 2017-09-06 CN CN201710796719.4A patent/CN107608218A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100891513B1 (en) * | 2008-08-18 | 2009-04-06 | 주식회사 케이디파워 | Grid-connected hybrid generation system using solar photovoltaic generation system and battery system and generation method using thereof |
| CN104008432A (en) * | 2014-06-03 | 2014-08-27 | 华北电力大学 | Micro-grid short-term load forecasting method based on EMD-KELM-EKF |
| CN104182809A (en) * | 2014-08-29 | 2014-12-03 | 国家电网公司 | Optimization method of intelligent household power system |
| CN104778507A (en) * | 2015-04-02 | 2015-07-15 | 南京邮电大学 | Intelligent building power utilization strategy acquiring method based on self-adaptive particle swarm algorithm |
| CN106602557A (en) * | 2017-02-24 | 2017-04-26 | 三峡大学 | Multi-period optimization reconstruction method of active power distribution network comprising electric automobiles |
Non-Patent Citations (1)
| Title |
|---|
| 姜杰: "家用电器智能用电的模型与方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110173835A (en) * | 2019-05-10 | 2019-08-27 | 广东美的制冷设备有限公司 | Control method, device and the air conditioner of air conditioner |
| CN110173835B (en) * | 2019-05-10 | 2021-07-20 | 广东美的制冷设备有限公司 | Control method and device of air conditioner and air conditioner |
| CN110109367A (en) * | 2019-05-13 | 2019-08-09 | 北京科创智汇科技有限责任公司 | Safety control system |
| CN110109367B (en) * | 2019-05-13 | 2022-02-18 | 北京科创智汇科技有限责任公司 | Safety protection control system |
| CN110837857A (en) * | 2019-10-31 | 2020-02-25 | 杭州中恒云能源互联网技术有限公司 | Industrial electricity load prediction method, system and storage medium thereof |
| CN111817302A (en) * | 2020-07-31 | 2020-10-23 | 三峡大学 | Load operation optimization method considering flexibility potential |
| CN112366708A (en) * | 2020-11-30 | 2021-02-12 | 深圳市汇拓新邦科技有限公司 | Charging management method, device, equipment and storage medium |
| CN114598564A (en) * | 2022-02-23 | 2022-06-07 | 杭州博联智能科技股份有限公司 | Equipment control method, system, electronic equipment and storage medium |
| CN114598564B (en) * | 2022-02-23 | 2023-07-04 | 杭州博联智能科技股份有限公司 | Equipment control method, system, electronic equipment and storage medium |
| CN116449723A (en) * | 2023-05-29 | 2023-07-18 | 固强科技（深圳）有限公司 | Intelligent household appliance control system |
| CN117331320A (en) * | 2023-12-01 | 2024-01-02 | 佳源科技股份有限公司 | Household appliance control method and system based on electric energy meter data analysis |
| CN117331320B (en) * | 2023-12-01 | 2024-01-30 | 佳源科技股份有限公司 | Household appliance control method and system based on electric energy meter data analysis |
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