Smart fusion terminal-based household intelligent power utilization management method and system

Abstract

The present application relates to the field of household electricity management, and particularly relates to a household intelligent electricity management method and system based on an intelligent fusion terminal, comprising: obtaining a plurality of device sets of a root node, taking any device set as a target set, taking the product of electricity fees required for starting all devices in the target set and preference differences as branch weights, taking the root node plus 1 as a target subnode, traversing to obtain a subnode corresponding to each device set, for each subnode, in response to the subnode being less than a preset end time, taking the subnode as a parent node, iterating the process of obtaining the subnode according to the root node until the subnode is equal to the preset end time, and stopping iteration; traversing a device management tree, taking a target path corresponding to a minimum comprehensive value as an optimal path; and generating an electricity management scheme of the device according to the optimal path. The electricity management method can save household electricity fees while taking into account the usage habit requirements of users.

Description

Technical Field

[0001] This invention relates to the field of household electricity management. More specifically, this invention relates to a method and system for smart household electricity management based on an intelligent converged terminal. Background Technology

[0002] The main focus of household electricity management is the rational planning of electricity consumption. Rational planning can effectively reduce electricity bills, thereby lowering the cost of living for households. Current household electricity management primarily relies on time-of-use (TOU) pricing mechanisms. TOU pricing divides the day into peak, off-peak, and flat periods with different pricing (peak hours have significantly higher prices than off-peak hours). This encourages users to concentrate their electricity consumption during off-peak periods to reduce costs. However, simply pursuing low electricity prices may overlook user habits, such as running washing machines during off-peak hours (late at night). Therefore, existing household electricity management methods have shortcomings. Summary of the Invention

[0003] The main objective of this application is to propose a smart home electricity management method and system based on a smart fusion terminal, which aims to save household electricity costs while taking into account users' usage habits and needs.

[0004] To achieve the above objectives, an embodiment of the first aspect of this application proposes a home smart electricity management method based on a smart converged terminal. The method includes: constructing a device management tree with a preset start time as the root node, wherein the construction process is as follows: obtaining several device sets of the root node; taking any one of the device sets as a target set; taking the product of the electricity cost required to start all devices in the target set and the preference difference as the branch weight; adding 1 to the root node as the target child node; traversing to obtain the child nodes corresponding to each device set; for each child node, in response to the child node being less than a preset end time, taking the child node as the parent node; iterating the above process of obtaining child nodes based on the root node until the child node is equal to the preset end time, stopping the iteration, obtaining the target path; traversing to obtain the target path corresponding to each device set to construct the device management tree; traversing the device management tree, calculating the comprehensive value of the branch weights in each target path, and taking the target path corresponding to the smallest comprehensive value as the optimal path; generating an electricity management scheme for the devices based on the optimal path.

[0005] In some embodiments, obtaining a plurality of device sets for the root node includes: obtaining the start flag and start interval of all devices in the home, wherein the start flag is 0 to indicate that the device has never been started, and the start flag is 1 to indicate that the device has been started; for each device, in response to the start flag being 0 and the root node being within the start interval, each device is included as a started device in a preliminary set, and in response to the start flag being 1 or the root node being not within the start interval, each device is excluded from the preliminary set as a non-started device; and the preliminary set is enumerated to obtain a plurality of device sets.

[0006] In some embodiments, obtaining the startup interval includes: for each device in the home, obtaining the earliest startup time and the latest startup time of each device; constructing a closed interval with the earliest startup time as the lower limit and the latest startup time as the upper limit, and using the closed interval as the startup interval of each device.

[0007] In some embodiments, the calculation process for the required electricity cost is as follows: obtain the rated power of each device in the target set, and multiply the sum of all the rated power by the current electricity price as the electricity cost increment; obtain the accumulated electricity cost of the root node; use the sum of the accumulated electricity cost and a preset first parameter as a first reference value; and use the ratio of the electricity cost increment to the first reference value and the sum of a preset second parameter as the required electricity cost.

[0008] In some embodiments, the accumulated electricity cost is 0.

[0009] In some embodiments, the calculation process of the preference difference is as follows: obtain the startup frequency of each device in the target set, take the difference between 1 and the startup frequency as the difference loss of each device, and take the sum of all the difference losses as the difference increment; obtain the cumulative loss of the root node; take the sum of the cumulative loss and a preset first parameter as a second reference value; take the sum of the ratio of the difference increment to the second reference value and the preset second parameter as the preference difference.

[0010] In some embodiments, obtaining the startup frequency of each device in the target set includes: taking any device in the target set as the target device, obtaining the total number of times the target device runs and the number of times the target device is started at the root node; taking the ratio of the number of starts to the total number of runs as the startup frequency of the target device; and traversing to obtain the startup frequency of each device in the target set.

[0011] In some embodiments, the cumulative loss is 0.

[0012] In some embodiments, the process of constructing the preset first parameter and the preset second parameter is as follows: Calculate the historical accumulated electricity cost and the historical accumulated loss at each moment from the preset start time to the preset end time, and use the minimum non-zero value among all the historical accumulated electricity costs and all the historical accumulated losses as a first reference value; calculate the preset first parameter based on the first reference value; take any moment from the preset start time to the preset end time as a target moment, and take the next moment of the target moment as a reference moment; calculate the historical electricity cost increment and the historical difference increment between the target moment and the reference moment; use the ratio of the historical electricity cost increment to the historical accumulated electricity cost at the target moment as the historical electricity cost growth rate at the target moment; use the ratio of the historical difference increment to the historical accumulated loss at the target moment as the historical preference growth rate at the target moment; iterate through and obtain the historical electricity cost growth rate and the historical preference growth rate at each moment; use the minimum non-zero value among all the historical electricity cost growth rates and all the historical preference growth rates as a second reference value; calculate the preset second parameter based on the second reference value.

[0013] The second aspect of this application proposes a smart home electricity management system based on a smart converged terminal. The system includes a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the above-described smart home electricity management method based on a smart converged terminal is implemented.

[0014] The beneficial effects of this invention are:

[0015] This invention uses a preset start time as the root node, and starts all devices in each device set of the root node. Each device set represents a start option. The product of the electricity cost and preference difference required to start each device set is calculated, and the product is used as the branch weight of each device set. The root node is incremented by 1 to become a child node. At this time, each device set corresponds to a branch weight and a child node. For each child node, if the child node is less than the preset end time, it is used as the parent node. The process of obtaining child nodes from the root node is iterated until the child node is equal to the preset end time. The iteration stops and a path is obtained to construct a device management tree. The device management tree contains multiple start options within a specified time period (from the preset start time to the preset end time) and the branch weight corresponding to each start option. The branch weight can represent the comprehensive cost of electricity cost and preference brought by the start option. This invention takes the path corresponding to the smallest comprehensive value as the optimal path, that is, selects the path with the smallest comprehensive cost. Therefore, the power management scheme of generating devices based on the optimal path can save household electricity costs while taking into account the user's usage habits. Attached Figure Description

[0016] Figure 1 This is a flowchart of steps S1-S3 in the home smart electricity management method based on a smart fusion terminal according to an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0018] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0019] Reference Figure 1 The smart home electricity management method based on intelligent converged terminals includes steps S1-S3, as follows:

[0020] Step S1: Construct a device management tree with a preset start time as the root node. The construction process is as follows: Obtain several device sets from the root node, take any device set as the target set, use the product of the electricity cost and preference differences required to start all devices in the target set as the branch weight, increment the root node by 1 to become the target child node, traverse to obtain the child nodes corresponding to each device set, for each child node, in response to the child node being less than the preset end time, take the child node as the parent node, iterate the above process of obtaining child nodes from the root node until the child node is equal to the preset end time, stop the iteration, obtain the target path, traverse to obtain the target path corresponding to each device set to construct the device management tree.

[0021] It should be noted that this invention can operate on a 24-hour management cycle. The node of time is used This indicates that the preset start time is 0:00, the preset end time is 24:00, and the root node is... leaf nodes are If a child node equals the preset end time, then that child node is a leaf node and will not have any branches.

[0022] Understandably, obtaining several device sets for the root node includes: obtaining the start flag and start interval of all devices in the household, where a start flag of 0 indicates that the device has never been started, and a start flag of 1 indicates that the device has been started; for each device, in response to a start flag of 0 and the root node being within the start interval, each device is included in the pre-set as a started device, and in response to a start flag of 1 or the root node not being within the start interval, each device is excluded from the pre-set as a non-start device; enumerating the pre-set yields several device sets.

[0023] It should be noted that household appliances include non-real-time devices such as washing machines, dishwashers, electric vehicle charging stations, and water heaters. (Activation indicator used...) This indicates that the startup flag is 1 as long as the device has been started. , The total number of devices in the household. For the first in the family One device For example, at the current time; Indicates the first The device is The timeline has already been activated. Indicates the first The device is It has never been started yet.

[0024] It is understandable that obtaining the startup interval includes: for each device in the home, obtaining the earliest startup time and the latest startup time of each device; constructing a closed interval with the earliest startup time as the lower limit and the latest startup time as the upper limit, and using the closed interval as the startup interval for each device.

[0025] It should be noted that the starting range is used It means that, among them, For the first The earliest startup time of each device For the first The latest task completion time for each device. For the first The task duration of each device is its runtime. For the first The latest startup time of the device, the first Only by activating the device within the activation range can the task be completed in a timely manner.

[0026] It should be noted that the preparatory set The preparatory set is represented in A set of devices that can be started at any time, and each device in the set is prepared. exist Always ready to start, ensuring timely task completion; equipment aggregation express, Preparing the set. For example, nodes... Preparatory set This indicates that the device can be started at 9 o'clock. and equipment Enumerating this pre-set yields four device sets, namely... , , and , This indicates that the set of devices is an empty set, i.e., the set of devices is empty. and equipment It doesn't start at 9 o'clock. Indicates equipment Start at 9 o'clock. Indicates equipment Start at 9 o'clock. Indicates equipment and equipment All devices will start at 9:00 AM. The four device sets represent four different startup schemes, and each device will be started according to one of these schemes. and equipment This results in four branches, each corresponding to a child node. .by Taking this branch as an example, at node , , , So at the node Since only the device was started , , , .

[0027] Understandably, the calculation process for the required electricity cost is as follows: obtain the rated power of each device in the target set, and multiply the sum of all rated power by the current electricity price as the electricity cost increment; obtain the accumulated electricity cost of the root node, and use the sum of the accumulated electricity cost and a preset first parameter as the first reference value; use the ratio of the electricity cost increment to the first reference value and the sum of the preset second parameter as the required electricity cost.

[0028] Understandably, the calculation process for preference difference is as follows: obtain the startup frequency of each device in the target set, take the difference between 1 and the startup frequency as the difference loss of each device, and take the sum of all difference losses as the difference increment; obtain the cumulative loss of the root node, take the sum of the cumulative loss and the preset first parameter as the second control value; take the sum of the ratio of the difference increment to the second control value and the preset second parameter as the preference difference.

[0029] It is understandable that obtaining the startup frequency of each device in the target set includes: taking any device in the target set as the target device, obtaining the total number of times the target device runs and the number of times the target device is started at the root node; taking the ratio of the number of starts to the total number of runs as the startup frequency of the target device; and traversing to obtain the startup frequency of each device in the target set.

[0030] For example, node and nodes The formula for calculating the branch weights is as follows:

[0031]

[0032]

[0033]

[0034] In the formula middle, For nodes and nodes Branch weights between For the node The required electricity cost, For the node The difference in preferences. Both the required electricity cost and the difference in preferences are positively correlated with the branch weight.

[0035] In the formula middle, For nodes and nodes The increase in electricity costs between them For nodes The accumulated electricity bill, The first parameter is preset. As the first control value, This is the preset second parameter.

[0036] In the formula middle, For nodes and nodes The difference increment between them For nodes The cumulative losses The first parameter is preset. This is the second control value. This is the preset second parameter.

[0037] For the above formula It should be added that, ,in, For the target set, For the target set The rated power of each device The sum of all rated power in the target set. In order to be in Electricity price at any given time. Rated power is an inherent attribute of the equipment, and electricity prices may vary in different regions and at different times. Both rated power and electricity price are collected by the intelligent fusion terminal.

[0038] For the above formula It should be added that, , From time 0 (preset initial time) to time... At any time between, Adjacent nodes and nodes The increase in electricity costs between them From arrive The sum of the electricity cost increments between all adjacent nodes on the path, i.e., the cumulative electricity cost consumed when starting the equipment. The smaller the value, the more likely it is to be from arrive The lower the electricity cost resulting from the equipment scheduling scheme along the path, the better. It's understandable that the accumulated electricity cost of the root node is 0.

[0039] For the above formula It should be added that, ,in, For the target set, For the target set The device is Startup frequency at any time For the target set The device is Time difference loss, To concentrate all devices in the target The sum of the difference loss at any given time is the difference increment.

[0040] For the above formula It should be added that the first target in the target set Each device at the node The number of times it is started, i.e., the first The device is The number of times the target is started at any given moment. The total number of times each device is run is the number of times within a management cycle. The total number of times a device is started, and both can be obtained from the device's operation logs. Startup frequency can quantify user habits and reflect the user's comfort level when starting the device at a particular moment. The device is The higher the startup frequency at any given moment, the more... The device is The smaller the time difference loss, It quantifies the impact of devices at different startup times on user habits. The habitual impact on the corresponding branch of the target set was measured. For example, if the washing machine starts at 20:00 with a frequency of 0.7, it means that 70% of the user's historical laundry tasks are started at this time. If the washing machine is scheduled to run at 20:00, the difference loss is 0.3, which means the degree of impact on user habits is 0.3.

[0041] For the above formula It should be added that, , From time 0 (preset initial time) to time... At any time between, Adjacent nodes and nodes The difference increment between them From arrive The sum of the incremental differences between all adjacent nodes on the path represents the cumulative habitual influence of the starting device. Understandably, the cumulative loss at the root node is 0.

[0042] For the above formula and It should be added that, and For a fixed small value, make sure or When it is 0 It can still perform calculations normally. make sure and When one side is 0, the other side's value can still be taken into account. The impact. For example .

[0043] It should be added that, compared to traditional technologies that directly enumerate all startup combinations of devices, (scale) This invention introduces a start flag. This can effectively reduce the computational tasks of intelligent converged terminals.

[0044] In some embodiments, the process of constructing the preset first parameter and the preset second parameter is as follows: calculate the historical accumulated electricity cost and the historical accumulated loss at each moment from the preset start time to the preset end time, and use the minimum non-zero value among all historical accumulated electricity costs and all historical accumulated losses as the first reference value; calculate the preset first parameter based on the first reference value; take any moment from the preset start time to the preset end time as the target time, take the next moment of the target time as the reference time, calculate the historical electricity cost increment and historical difference increment between the target time and the reference time, use the ratio of the historical electricity cost increment to the historical accumulated electricity cost at the target time as the historical electricity cost growth rate at the target time, use the ratio of the historical difference increment to the historical accumulated loss at the target time as the historical preference growth rate at the target time, iterate to obtain the historical electricity cost growth rate and the historical preference growth rate at each moment, use the minimum non-zero value of all historical electricity cost growth rates and all historical preference growth rates as the second reference value, and calculate the preset second parameter based on the second reference value.

[0045] It should be noted that the historical accumulated electricity charges refer to the accumulated electricity charges in the historical dispatch data; therefore, its calculation formula remains the same. ,in, This represents the increase in electricity costs. Similarly, the historical accumulated loss is the accumulated loss from historical scheduling data, and its calculation formula remains the same. ,in, This represents the difference increment.

[0046] It should be noted that historical dispatch data can include equipment startup records, electricity price information, and user preference frequency data within the past 30 days.

[0047] For a fixed small value, make sure , When the weight is 0, the branch weight It can still calculate correctly, but The settings must conform to the dimensions of the data, for example, all The values ​​are all below 0.1. If you set it at this time... Obviously for To be honest It is no longer a small value. Therefore, the first reference value (minimum value) mentioned above can be found. 1% of the first reference value can be used as the preset first parameter. The specific percentage setting is adjusted according to the preset error range.

[0048] Similarly, For a fixed small value, This ensures that even when one variable changes to 0, the change in the other variable can still be correctly considered. Find the aforementioned second reference value (minimum value), and use 1% of this second reference value as the preset second parameter. The specific percentage setting should be adjusted according to the preset error range.

[0049] By setting the first and second preset parameters as described above, the formula is guaranteed. and formula The calculation is universally applicable to all nodes while ensuring that the error is within a preset error range, which can be 5%.

[0050] The method for calculating the error is as follows: (Formula omitted) For example, in Under the premise of non-zero values, calculate respectively: , of and none , of , will two The relative difference is taken as the error.

[0051] Step S2: Traverse the device management tree, calculate the comprehensive value of the branch weights in each target path, and take the target path with the smallest comprehensive value as the optimal path.

[0052] It should be noted that the overall value of the target path... , With a preset end time, the device management tree is traversed layer by layer from top to bottom, visiting nodes in each layer from left to right. After traversal, multiple paths are obtained, the number of paths being the same as the number of leaf nodes. For each path, the sum of the weights of all branches is calculated. A smaller sum indicates a better balance between electricity costs and user preferences.

[0053] Step S3: Generate a power management plan for the equipment based on the optimal path.

[0054] It should be further explained that the process involves obtaining the device set between all adjacent nodes on the optimal path, and generating device scheduling (startup) instructions based on each device set, such as the nodes in the optimal path. Equipment collection The system generates an instruction to start device 1 at 9 o'clock. Based on this example, it obtains all device scheduling instructions and generates a device scheduling table. This device scheduling table is a power management scheme. The intelligent converged terminal determines which devices to start at what time based on the power management scheme, which can save electricity costs while taking into account users' usage habits.

[0055] This invention also provides a smart home electricity management system based on a smart converged terminal. The system includes a processor and a memory, the memory storing computer program instructions. When the processor executes the computer program instructions, it implements the smart home electricity management method based on a smart converged terminal according to the first aspect of this invention. The system also includes other components well-known to those skilled in the art, such as a communication bus and a communication interface; their configuration and functions are known in the art and will not be described further here.

[0056] It should be noted that the preferred embodiments of this application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of this application. For those skilled in the art, various modifications and improvements can be made without departing from the concept of the invention, and these all fall within the protection scope of the invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for smart home electricity management based on intelligent converged terminals, characterized in that: include: A device management tree is constructed with a preset start time as the root node. The construction process is as follows: several device sets are obtained from the root node. Any of the device sets is taken as the target set. The product of the electricity cost required to start all devices in the target set and the preference difference is taken as the branch weight. The root node is incremented by 1 as the target child node. The child nodes corresponding to each device set are obtained through traversal. For each child node, in response to the child node being less than the preset end time, the child node is taken as the parent node. The process of obtaining child nodes based on the root node is iterated until the child node is equal to the preset end time. The iteration is stopped to obtain the target path. The target path corresponding to each device set is obtained through traversal to construct the device management tree. Traverse the device management tree, calculate the comprehensive value of the branch weights in each target path, and take the target path with the smallest comprehensive value as the optimal path; A power management scheme for the equipment is generated based on the optimal path; The method for calculating the preference difference is as follows: The startup frequency of each device in the target set is obtained, and the difference between 1 and the startup frequency is taken as the difference loss of each device. The sum of all the difference losses is taken as the difference increment. The cumulative loss of the root node is obtained, and the sum of the cumulative loss and the preset first parameter is taken as the second control value. The sum of the ratio of the difference increment to the second control value and the preset second parameter is taken as the preference difference.

2. The home smart electricity management method based on a smart converged terminal according to claim 1, characterized in that, The set of devices used to obtain the root node includes: Obtain the start flag and start interval of all devices in the home, wherein a start flag of 0 indicates that the device has never been started, and a start flag of 1 indicates that the device has been started; For each device, in response to the start flag being 0 and the root node being within the start interval, each device is included in the pre-set as a start device; in response to the start flag being 1 or the root node being outside the start interval, each device is excluded from the pre-set as a non-start device. Enumerating the preparatory set yields several device sets.

3. The home smart electricity management method based on a smart fusion terminal according to claim 2, characterized in that, The startup range includes: For each device in the home, obtain the earliest start time and the latest start time of each device; A closed interval is constructed with the earliest start time as the lower limit and the latest start time as the upper limit, and the closed interval is used as the start interval of each device.

4. The home smart electricity management method based on a smart fusion terminal according to claim 1, characterized in that, The calculation process for the required electricity cost is as follows: Obtain the rated power of each device in the target set, and multiply the sum of all the rated powers by the current electricity price as the electricity bill increment; Obtain the accumulated electricity cost of the root node; The sum of the accumulated electricity cost and the preset first parameter is used as the first comparison value; The sum of the ratio of the electricity cost increment to the first reference value and the preset second parameter is used as the required electricity cost.

5. The home smart electricity management method based on a smart fusion terminal according to claim 4, characterized in that, The accumulated electricity cost is 0.

6. The home smart electricity management method based on a smart fusion terminal according to claim 1, characterized in that, Obtaining the startup frequency of each device in the target set includes: Take any device in the target set as the target device. Obtain the total number of times the target device runs and the number of times the target device is started at the root node; The ratio of the number of startups to the total number of runs is taken as the startup frequency of the target device; The startup frequency of each device in the target set is obtained by iterating through the set.

7. The home smart electricity management method based on a smart fusion terminal according to claim 1, characterized in that, The cumulative loss is 0.

8. The home smart electricity management method based on a smart fusion terminal according to claim 4, characterized in that, The process of constructing the preset first parameter and the preset second parameter is as follows: Calculate the historical accumulated electricity cost and the historical accumulated loss at each moment from the preset start time to the preset end time. The minimum non-zero value among all the historical accumulated electricity costs and all the historical accumulated losses is used as a first reference value. The preset first parameter is calculated based on the first reference value. The target time is any time from the preset start time to the preset end time, and the next time after the target time is the reference time. The historical electricity cost increment and historical difference increment between the target time and the reference time are calculated. The ratio of the historical electricity cost increment to the historical accumulated electricity cost at the target time is taken as the historical electricity cost growth rate at the target time. The ratio of the historical difference increment to the historical accumulated loss at the target time is taken as the historical preference growth rate at the target time. The historical electricity cost growth rate and the historical preference growth rate at each time are obtained iteratively. The minimum non-zero value of all the historical electricity cost growth rates and all the historical preference growth rates is taken as the second reference value. The preset second parameter is calculated based on the second reference value.

9. A home smart electricity management system based on an intelligent converged terminal, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, which, when executed by the processor, implement the home smart electricity management method based on a smart fusion terminal as described in any one of claims 1-8.

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