Method for realizing household energy management based on household intelligent router

Abstract

The invention discloses a method for realizing household energy management based on a household intelligent router, relates to the technical field of household energy management, and solves the problems that in the prior art, the purpose of saving household energy is achieved only by analyzing the energy consumption condition of a smart home and adjusting the working state of the smart home, the considered factor is relatively single, and the efficiency is relatively high. And comprehensive and efficient household energy management cannot be realized. The method comprises the following steps: analyzing unit time energy consumption and daily average operation duration of electric equipment, and classifying the electric equipment; the power utilization habit of the user is analyzed; establishing a target function with the minimum total energy consumption per unit time of the household electric equipment, and solving an optimal solution of the target function; based on the optimal solution, the intelligent router controls and adjusts the running state of the electric equipment in use; according to the invention, a'power grid-user-electric appliance 'linked resident household energy management system is established, intelligent power utilization control is realized, and the maximization of the energy-saving effect is ensured.

Description

Technical Field

[0001] The present invention belongs to the field of home energy management, and in particular is a method for realizing home energy management based on a household intelligent router. Background Art

[0002] With the popularization of smart homes, more and more electrical appliances are used in homes, and energy consumption is also increasing.

[0003] The invention patent application with publication number CN110032077A discloses a home energy management system, which is provided with a smart home interconnection system. Each smart home in the home is interconnected with at least an energy master product, and adjusts the working mode according to the output instruction of the energy master product to save electricity; the energy master product collects the power consumption data of each smart home, and outputs automatic adjustment working mode instructions to the smart home with high power consumption to save electricity. The home energy management system of the present invention can automatically obtain the consumption of the smart home, adjust the working mode of the smart home in time, and meet the requirements of low power loss.

[0004] The above-mentioned prior art only analyzes the energy consumption of smart homes and adjusts the working status of smart homes to achieve the purpose of saving household energy. However, in reality, household energy management is interfered by many factors, such as user behavior, power grid operation status, etc. Therefore, the factors considered in the prior art are indeed relatively single, and it is impossible to achieve comprehensive and efficient household energy management; therefore, the present invention provides a method for realizing household energy management based on a household smart router. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a method for realizing home energy management based on a household smart router, which is used to solve the technical problem that the prior art only analyzes the energy consumption of smart homes and adjusts the working status of smart homes to achieve the purpose of saving home energy, and the factors considered are indeed relatively single, and it is impossible to realize comprehensive and efficient home energy management.

[0006] To achieve the above object, a first aspect of the present invention provides a method for implementing home energy management based on a household intelligent router, comprising the following steps:

[0007] Step 1: Collecting the operating data of the electrical equipment; wherein the intelligent router is connected to the electrical equipment and collects the operating data of the electrical equipment; the operating data includes current, voltage and operating time;

[0008] Step 2: extracting the operation data of the electrical equipment for several days from the historical data, analyzing the energy consumption per unit time and the average daily operation time of the electrical equipment; classifying the electrical equipment based on the energy consumption per unit time and the average daily operation time of the electrical equipment; and,

[0009] Extract several household electricity consumption data in different seasons from historical electricity consumption data to analyze users' electricity consumption habits;

[0010] Step 3: Establish an objective function to minimize the total energy consumption per unit time of household electrical appliances, and find the optimal solution of the objective function; based on the optimal solution, the intelligent router controls and adjusts the operating status of the electrical appliances in use.

[0011] Preferably, analyzing the energy consumption per unit time of electrical equipment includes:

[0012] Extract the operating data of the power equipment for several days from the historical data, and use the formula Ei = Σ j [Pij / (tij×N)] calculates the energy consumption per unit time Ei of the electrical equipment; where i is the type of electrical equipment; j is the date of several days; Pij is the average power of the electrical equipment, Pij=Vij×Iij, Vij is the average voltage on date j, Iij is the average current on date j; tij is the operating time of the electrical equipment; N is the number of historical days collected; Σ sums up j.

[0013] The present invention calculates the energy consumption level per unit time of electrical equipment by comprehensively considering factors such as voltage, current and operating time, which is of great significance for evaluating the energy efficiency of equipment, formulating energy-saving measures and conducting cost budgeting. Energy consumption analysis based on historical data can reveal the operating laws and energy consumption characteristics of different equipment, provide data support for formulating scientific energy-saving measures, and lay the foundation for the subsequent attribute classification of electrical equipment.

[0014] Preferably, analyzing the average daily operating time of electrical equipment includes:

[0015] The operation data of the electrical equipment for several days are extracted from the historical data, and the total operation time of each electrical equipment for several days is counted and marked as Ti; the average daily operation time Eti is calculated by the formula ETi=Ti / N.

[0016] The present invention extracts the operating data of electrical equipment for several days from historical data, analyzes the average daily operating time of the electrical equipment, provides an intuitive and quantitative indicator for equipment efficiency evaluation, and lays the foundation for the subsequent attribute classification of electrical equipment; and the method ensures the comprehensiveness and accuracy of the data. By collecting data covering multiple time points, it can more comprehensively reflect the actual operating conditions of the equipment and avoid the deviation that may be caused by data at a single time point.

[0017] Preferably, the classification of electrical equipment according to energy consumption per unit time and average daily operating time includes:

[0018] The energy consumption per unit time and the average daily operation time are compared with the corresponding thresholds, and the power-consuming devices are marked as high-energy-consuming devices, low-energy-consuming devices, long-operating devices, and short-operating devices; and,

[0019] Through cluster analysis, the electrical equipment is classified to obtain the category attributes of the electrical equipment.

[0020] The present invention compares the energy consumption per unit time and the average daily operating time with preset thresholds to identify high-energy consumption equipment and low-energy consumption equipment, as well as long-operating equipment and short-operating equipment; the cluster analysis rule provides a more in-depth and detailed classification method. By considering data in multiple dimensions (such as energy consumption, operating time, power, etc.), cluster analysis can reveal the inherent connections and differences between devices, and classify devices with similar characteristics into the same category. By collecting and processing data through automated and digital means, and combining intelligent algorithms for analysis and classification, it helps to achieve the goal of energy conservation and emission reduction.

[0021] Preferably, the analyzing the user's electricity usage habits includes:

[0022] Extracting several household electricity consumption data in different seasons from the historical electricity consumption data; dividing several household electricity consumption data by season, and dividing each day into several fixed time periods;

[0023] Based on the seasonal division, the number of times the electrical equipment is used in each fixed time period is counted, marked as Sr; where r is the fixed time period number;

[0024] The frequency Pir of the user using the electrical device i in a fixed time period r is calculated by the formula Pir=Σ(Sir) / N, and Σ is summed over r.

[0025] The present invention divides household electricity consumption data by season and refines it into different time periods of the day. This method can accurately capture the impact of seasonal changes on household electricity consumption behavior. Factors such as climate conditions and living habits in different seasons will lead to significant differences in electricity consumption patterns. This refined division helps to more accurately understand the seasonal characteristics of household electricity consumption. In addition, by counting the number of times electrical equipment is used in each fixed time period and calculating the frequency of use, the usage preferences of the equipment in different time periods are revealed; by understanding the frequency of use of electrical equipment by households in different seasons and time periods, it helps to achieve personalized electricity management.

[0026] Preferably, the step of establishing an objective function for minimizing the total energy consumption per unit time of household electrical appliances and solving the optimal solution of the objective function includes:

[0027] Establish the objective function of minimizing the total energy consumption per unit time of household electrical equipment, marked as Min(NL):

[0028] Min(NL)=ΣEi;

[0029] Among them, NL is the total energy consumption per unit time of household electrical equipment; Ei is the energy consumption per unit time of each household electrical equipment; Σ is the sum of i;

[0030] Constraints: The running time of the electrical equipment is less than the time threshold, and the usage frequency of the electrical equipment in the current season and time period is greater than the preset frequency;

[0031] According to the category attributes of the electrical equipment currently in use, with the goal of minimizing the total energy consumption per unit time of household electrical equipment and stabilizing the voltage of the power grid, a genetic algorithm is used to solve the optimal solution of the objective function Min(NL).

[0032] The present invention directly targets the core demand of household energy conservation by clarifying the objective function, namely minimizing the total energy consumption per unit time of household electrical appliances. The setting of this goal makes the optimization process have clear directionality and pertinence, which is helpful to realize the effective utilization and conservation of household energy. Secondly, the introduced constraints fully consider the diversity and complexity of actual electricity consumption. The operating time of the electrical equipment is less than the time threshold, which ensures that the equipment operates within a reasonable range and avoids damage or safety hazards caused by excessive use. The frequency of use of the electrical equipment in the current season and the current time period is greater than the preset frequency, which reflects the user's usage habits and needs, ensuring the practicality and feasibility of the optimization scheme. The voltage stability of the power grid is also considered as one of the optimization goals. While optimizing the energy consumption of household electrical appliances, the voltage stability of the power grid is ensured, which is of great significance for ensuring the safety and reliability of household electricity use.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. The present invention uses existing smart routers to achieve home energy management, without the need to install additional hardware equipment, thus reducing costs; the smart router collects the operating data of electrical equipment and analyzes the minimum power consumption required by the family in different time periods; according to the operating time of the electrical equipment and the user's behavior habits, the operating state of the household electrical equipment is adjusted with the minimum energy consumption and grid stability as the goal, thereby minimizing the energy consumption of the household electrical equipment, ensuring the safe operation of the electrical equipment and the voltage stability of the grid, and providing a scientific, personalized and effective solution for household energy saving and energy management;

[0035] 2. The present invention extracts the operation data of electrical equipment for several days from historical data, analyzes the energy consumption per unit time and the average daily operation time of the electrical equipment; classifies the electrical equipment based on the energy consumption per unit time and the average daily operation time of the electrical equipment; and analyzes the electricity consumption habits of users; establishes an objective function for minimizing the total energy consumption per unit time of household electrical equipment, and solves the optimal solution of the objective function; based on the optimal solution, the intelligent router controls and adjusts the operating status of the electrical equipment in use; establishes a residential energy management system that links "grid-user-electrical appliance" to realize intelligent electricity control and ensure maximum energy-saving effect. By comprehensively considering the energy consumption of household electrical equipment and the voltage stability of the grid, the method can achieve the dual goals of household energy management and optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 It is a schematic diagram of the process structure of the method of the present invention;

[0038] Figure 2 A flow chart of the method for analyzing the electricity usage habits of users of the present invention;

[0039] Figure 3 The figure is a schematic diagram of the overall architecture of residential household energy management based on household routers according to the present invention. DETAILED DESCRIPTION

[0040] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] See also Figure 1 The first embodiment of the present invention provides a method for implementing home energy management based on a household intelligent router, comprising the following steps:

[0042] Step 1: Collecting the operating data of the electrical equipment; wherein the intelligent router is connected to the electrical equipment and collects the operating data of the electrical equipment; the operating data includes current, voltage and operating time;

[0043] Step 2: Extract the operation data of the electrical equipment for several days from the historical data, analyze the energy consumption per unit time and the average daily operation time of the electrical equipment; classify the electrical equipment based on the energy consumption per unit time and the average daily operation time of the electrical equipment;

[0044] Specifically, the operating data of the electrical equipment for several days are extracted from the historical data, and the formula Ei = Σ j [Pij / (tij×N)] calculates the energy consumption per unit time Ei of the electrical equipment; where i is the type of electrical equipment; j is the date of several days; Pij is the average power of the electrical equipment, Pij=Vij×Iij, Vij is the average voltage on date j, Iij is the average current on date j; tij is the operating time of the electrical equipment; N is the number of historical days collected; Σ sums up j.

[0045] The present invention evaluates the energy consumption attributes of electrical equipment through energy consumption per unit time; the energy consumption attributes of electrical equipment are mainly closely related to the average power of the electrical equipment, the operating time and the historical number of days collected; if the historical number of days N is large, the average power of a certain electrical equipment within N days is large, and the operating time is short, it indicates that the electrical equipment consumes a large amount of energy per unit time, that is, it is a high-energy consumption equipment.

[0046] Among them, the energy consumption per unit time of electrical equipment is usually based on the energy consumed per hour.

[0047] The operation data of the electrical equipment for several days are extracted from the historical data, and the total operation time of each electrical equipment for several days is counted and marked as Ti; the average daily operation time Eti is calculated by the formula ETi=Ti / N.

[0048] The present invention evaluates the daily working hours of the electrical equipment by analyzing the average daily operating hours of the electrical equipment, thereby laying a foundation for subsequent classification of the electrical equipment.

[0049] The energy consumption per unit time and the average daily operation time are compared with the corresponding thresholds, and the power-consuming devices are marked as high-energy-consuming devices, low-energy-consuming devices, long-operating devices, and short-operating devices; and,

[0050] Through cluster analysis, the electrical equipment is classified to obtain the category attributes of the electrical equipment.

[0051] For example: assuming that high-energy consumption equipment: energy consumption per unit time> 400 watts / hour; low-energy consumption equipment: energy consumption per unit time ≤ 400 watts / hour; long-running equipment: average daily operating time> 5 hours / day; short-running equipment: average daily operating time ≤ 5 hours / day;

[0052] Assume that the energy consumption per unit time and the average daily operating time of air conditioners, refrigerators and washing machines are as shown in the following table:

[0053] Device Type Ei (watt / hour) ETi(hours / day) air conditioner 350 4.43 refrigerator 230 24 washing machine 440 1

[0054] The clustering results are as follows:

[0055] Category A: Low energy consumption, long-running equipment (such as refrigerators);

[0056] Category B: high energy consumption, short-time operation equipment (such as washing machines);

[0057] Category C: Low energy consumption, short-time operation equipment (such as air conditioners).

[0058] See also Figure 2 ,As well as, extracting several household electricity consumption data in different seasons from historical electricity consumption data, ,and analyzing the electricity consumption habits of users;

[0059] Extracting several household electricity consumption data in different seasons from the historical electricity consumption data; dividing several household electricity consumption data by season, and dividing each day into several fixed time periods;

[0060] It should be noted that the seasons are divided into spring, summer, autumn and winter; a day can be divided into multiple time periods, which can be divided according to peak and off-peak electricity consumption, such as: 5:00-10:00; 10:00-13:00; 13:00-17:00; 17:00-23:00; 23:00-5:00.

[0061] Based on the seasonal division, the number of times the electrical equipment is used in each fixed time period is counted and marked as Sir; where r is the fixed time period number;

[0062] The frequency Pir of the user using the electrical device i in a fixed time period r is calculated by the formula Pir=Σ(Sir) / N, and Σ is summed over r.

[0063] Step 3: Establish an objective function to minimize the total energy consumption per unit time of household electrical equipment and find the optimal solution of the objective function, including:

[0064] Establish the objective function of minimizing the total energy consumption per unit time of household electrical equipment, marked as Min(NL):

[0065] Min(NL)=ΣEi;

[0066] Among them, NL is the total energy consumption per unit time of household electrical equipment; Ei is the energy consumption per unit time of each household electrical equipment; Σ is the sum of i;

[0067] Constraints: The running time of the electrical equipment is less than the time threshold, and the usage frequency of the electrical equipment in the current season and time period is greater than the preset frequency;

[0068] According to the category attributes of the electrical equipment currently in use, with the goal of minimizing the total energy consumption per unit time of household electrical equipment and stabilizing the voltage of the power grid, a genetic algorithm is used to solve the optimal solution of the objective function Min(NL).

[0069] Establish an objective function to minimize the total energy consumption per unit time of household electrical equipment and find the optimal solution of the objective function, including:

[0070] Establish the objective function of minimizing the total energy consumption per unit time of household electrical equipment, marked as Min(NL):

[0071] Min(NL)=ΣEi;

[0072] Among them, NL is the total energy consumption per unit time of household electrical equipment; Ei is the energy consumption per unit time of each household electrical equipment; Σ is the sum of i;

[0073] Constraints: The running time of the electrical equipment is less than the time threshold, and the usage frequency of the electrical equipment in the current season and time period is greater than the preset frequency;

[0074] According to the category attributes of the electrical equipment currently in use, with the goal of minimizing the total energy consumption per unit time of household electrical equipment and stabilizing the voltage of the power grid, a genetic algorithm is used to solve the optimal solution of the objective function Min(NL);

[0075] Based on the optimal solution, the intelligent router controls and adjusts the operating status of the electrical equipment in use.

[0076] The present invention adjusts the operating state of the current household electrical appliances by solving the optimal solution of the objective function, so that the electrical appliances in the current period can meet the user's usage needs and the total energy consumption per unit time of the electrical appliances used is minimized; to ensure the maximum energy saving effect and assist the peak load regulation of the power grid.

[0077] The optimal solution is obtained by the smart router issuing control instructions through the downlink communication management module, sending corresponding adjustment commands to the electrical equipment, and automatically adjusting the operating status of the household appliances; such as turning on / off high-energy-consuming equipment; adjusting the power of equipment (such as air conditioners, washing machines, etc.); switching working modes (such as night mode, energy-saving mode, etc.).

[0078] The present invention will fully consider the current operation status of the power grid, including factors such as power grid load, power supply stability and electricity price fluctuations, during the process of strategy generation and execution.

[0079] When the grid load is high, priority is given to adjusting the use of high-energy-consuming equipment and implementing demand response strategies to help the grid balance the load and improve the intelligence and flexibility of electricity use.

[0080] like Figure 3As shown, the second aspect of the present invention proposes an overall architecture of household energy management based on household smart routers. The smart router is a complete set of hardware and software systems based on household smart routers and household energy management system software, mainly composed of an uplink communication management module, a downlink communication management module and an autonomous control system module. The uplink communication management module establishes a network connection with the grid-side platform by using the home broadband / 4G modem of the communication operator, and receives various instructions issued by the grid-side platform at the same time; the downlink communication management module establishes a network connection with smart home appliances by using a wireless WiFi local area network, collects the power load information and real-time power of smart home appliances, and issues flexible adjustment instructions at the same time; the autonomous control system module is the intelligent center of the smart router, actively analyzes various instructions from the grid-side platform or senses the power data of smart home appliances to actively generate adjustment instructions, and controls smart home appliances online in real time according to the flexible load control strategy.

[0081] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0082] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for implementing home energy management based on household intelligent router, characterized in that: The following steps are involved: Step 1: Collecting the operating data of the electrical equipment; wherein the intelligent router is connected to the electrical equipment and collects the operating data of the electrical equipment; the operating data includes current, voltage and operating time; Step 2: extracting the operation data of the electrical equipment for several days from the historical data, analyzing the energy consumption per unit time and the average daily operation time of the electrical equipment; classifying the electrical equipment based on the energy consumption per unit time and the average daily operation time of the electrical equipment; and, Extract several household electricity consumption data in different seasons from historical electricity consumption data to analyze users' electricity consumption habits; Step 3: Establish an objective function to minimize the total energy consumption per unit time of household electrical appliances, and find the optimal solution of the objective function; based on the optimal solution, the intelligent router controls and adjusts the operating status of the electrical appliances in use.

2. A method for implementing home energy management based on household intelligent router according to claim 1, characterized in that: Analyze the energy consumption per unit time of electrical equipment, including: Extract the operating data of the power equipment for several days from the historical data, and use the formula Ei = Σ j [Pij / (tij×N)] calculates the energy consumption per unit time Ei of the electrical equipment; where i is the type of electrical equipment; j is the date of several days; Pij is the average power of the electrical equipment, Pij=Vij×Iij, Vij is the average voltage on date j, Iij is the average current on date j; tij is the operating time of the electrical equipment; N is the number of historical days collected; Σ sums up j.

3. A method for implementing home energy management based on household intelligent router according to claim 1, characterized in that: Analyze the average daily operating time of electrical equipment, including: The operation data of the electrical equipment for several days are extracted from the historical data, and the total operation time of each electrical equipment for several days is counted and marked as Ti; the average daily operation time Eti is calculated by the formula ETi=Ti / N.

4. A method for implementing home energy management based on household intelligent router according to claim 1, characterized in that: According to the energy consumption per unit time and the average daily operating time, the electrical equipment is classified, including: The energy consumption per unit time and the average daily operation time are compared with the corresponding thresholds, and the power-consuming devices are marked as high-energy-consuming devices, low-energy-consuming devices, long-operating devices, and short-operating devices; and, Through cluster analysis, the electrical equipment is classified to obtain the category attributes of the electrical equipment.

5. A method for implementing home energy management based on household intelligent router according to claim 1, characterized in that: The analyzing of the user's electricity usage habits includes: Extracting several household electricity consumption data in different seasons from the historical electricity consumption data; dividing several household electricity consumption data by season, and dividing each day into several fixed time periods; Based on the seasonal division, the number of times the electrical equipment is used in each fixed time period is counted, marked as Sr; where r is the fixed time period number; The frequency Pir of the user using the electrical device i in a fixed time period r is calculated by the formula Pir=Σ(Sir) / N, and Σ is summed over r.

6. A method for implementing home energy management based on household intelligent router according to claim 1, characterized in that: The step of establishing an objective function for minimizing the total energy consumption per unit time of household electrical appliances and solving the optimal solution of the objective function includes: Establish the objective function of minimizing the total energy consumption per unit time of household electrical equipment, marked as Min(NL): Min(NL)=ΣEi; Among them, NL is the total energy consumption per unit time of household electrical appliances; Ei is the energy consumption per unit time of each household electrical appliance; Σ is the sum of i; Constraints: The running time of the electrical equipment is less than the time threshold, and the usage frequency of the electrical equipment in the current season and time period is greater than the preset frequency; According to the category attributes of the electrical equipment currently in use, with the goal of minimizing the total energy consumption per unit time of household electrical equipment and stabilizing the voltage of the power grid, a genetic algorithm is used to solve the optimal solution of the objective function Min(NL).

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