Method, device and terminal for power load forecasting

Abstract

The present invention is applicable to the field of electric power technology, and provides a method, device and terminal for power load prediction, the method comprising: dividing the electric equipment into continuous type appliances and intermittent type appliances according to the power consumption characteristics of the electric equipment; obtaining the first average energy consumption curve of the continuous type appliances, the second average energy consumption curve of the intermittent type appliances and the start-up time period of the intermittent type appliances; determining the probability distribution of the start-up time of the continuous type appliances based on the first average energy consumption curve, and determining the first load curve based on the probability distribution, and determining the second load curve based on the second average energy consumption curve and the start-up time period of the intermittent type appliances; determining the target power load curve based on the first load curve and the second load curve. The invention completes the prediction of the power load curve based on the power consumption characteristics and start-up time of different types of appliances, improves the prediction accuracy, and thus improves the accuracy of power dispatching.

Description

Technical Field

[0001] The present invention belongs to the field of electric power technology, and in particular relates to a method, a device and a terminal for predicting electric load. Background Art

[0002] At present, detailed residential power consumption load curves are crucial for small-scale distributed generation and local demand-side management in local areas. They are based on the analysis and research of historical data of the power system to make advance estimates and inferences on the power consumption level. They are the basic work for improving power system planning, power consumption and scheduling. Compared with traditional load forecasting problems, residential load forecasting is more challenging. The load scale of substations or nodes is large and generally stable. The power load of industrial and commercial users is affected by production laws and can often be divided into several typical power consumption patterns with strong regularity. However, residential loads are closely related to users' power consumption behavior. Traditional load forecasting methods only use the load data of household total electricity meters, resulting in the dispatching scheme that is too rough in describing the power load, making power dispatching inaccurate. Summary of the invention

[0003] In view of this, the present invention provides a method, device and terminal for power load forecasting, which can improve the accuracy of power load forecasting to accurately perform power dispatching.

[0004] The setting aspect of an embodiment of the present invention provides a method for power load forecasting, including:

[0005] According to the electricity consumption characteristics of electrical equipment, electrical equipment is divided into continuous electrical equipment and intermittent electrical equipment;

[0006] Acquire a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance;

[0007] Determine the probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve, determine a first load curve based on the probability distribution, and determine a second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance;

[0008] A target power load curve is determined based on the first load curve and the second load curve.

[0009] A second aspect of an embodiment of the present invention provides a device for power load forecasting, comprising:

[0010] A classification module, used to classify electrical appliances into continuous electrical appliances and intermittent electrical appliances according to the electrical consumption characteristics of the electrical appliances;

[0011] An acquisition module, used to acquire a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance;

[0012] a first determination module, configured to determine a probability distribution of a start-up time of the continuous electrical appliance based on the first average energy consumption curve, determine a first load curve based on the probability distribution, and determine a second load curve based on the second average energy consumption curve and a start-up time period of the intermittent electrical appliance;

[0013] The second determination module is used to determine a target power load curve based on the first load curve and the second load curve.

[0014] A third aspect of an embodiment of the present invention provides a terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any method for electricity load forecasting as described in any one of the items when executing the computer program.

[0015] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any method for electricity load forecasting are implemented.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The present invention divides electrical equipment into continuous electrical appliances and intermittent electrical appliances according to their power consumption characteristics, obtains the first average energy consumption curve of the continuous electrical appliances, the second average energy consumption curve of the intermittent electrical appliances, and the start-up time period of the intermittent electrical appliances, performs cluster analysis based on the power consumption characteristics, determines the probability distribution of the start-up time of the continuous electrical appliances based on the first average energy consumption curve, determines the first load curve based on the probability distribution, determines the second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliances, determines the target power load curve based on the first load curve and the second load curve, and performs analysis based on the probability distribution and the start-up time period on the basis of the cluster analysis. The present invention completes the prediction of the power load curve based on the power consumption characteristics and start-up time of different types of electrical appliances, improves the prediction accuracy, and thus improves the accuracy of power dispatching. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, 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 labor.

[0019] Figure 1 is a flow chart of an implementation method for power load forecasting provided by an embodiment of the present invention;

[0020] Figure 2 is a flow chart of a method for predicting power load provided by another embodiment of the present invention;

[0021] Figure 3 is a structural schematic diagram of a device for power load prediction provided by an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0024] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0025] The load curve contains three aspects of information: the time when the equipment starts to consume energy, the power demand of the equipment operation, and the time when the equipment stops. The average load curve combines all this information from different residences. The electricity consumption information contained in these load curves is very limited and cannot reveal the specific electricity consumption behavior in each residence and the power consumption characteristics of different equipment. Therefore, it is necessary to generate a more detailed minute-level load curve based on hourly load modeling in an average sense.

[0026] Figure 1 The present invention provides a method for predicting power load according to an embodiment of the present invention, which includes the following steps:

[0027] S101, classifying electrical appliances into continuous electrical appliances and intermittent electrical appliances according to the electrical consumption characteristics of the electrical appliances.

[0028] Optionally, household appliances are divided into two types: Type 1 is household appliances that are started once and need to run for a period of time before stopping, that is, continuous appliances, such as electric water heaters and dryers. Type 2 is household appliances that can be started at any time of the day, that is, intermittent appliances, such as lighting equipment. These two types of appliances consume most of the electrical energy in the house.

[0029] S102, obtaining a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance.

[0030] The average power consumption of each device contains information about the probability of when the user uses the device. This information includes not only the proportion of devices in use, but also the probability of starting the device at any time of the day. When the constant power and time requirements are determined, the average load curves of different devices can be regarded as only related to the start-up time. For continuous appliances such as electric water heaters and dryers, the constant power consumption time represents the average usage time. For intermittent appliances such as lighting equipment, whether the user turns on the device at this moment has no effect on the next moment, so each moment can be regarded as the start-up moment of the lighting device.

[0031] In view of the above situation, the device behavior can be described as follows: Type 1 includes electric water heaters and dryers whose load curves are generated based on their startup time. The startup time determines different load curves, and the startup time can be generated by its probability distribution, which is based on the average device-level load curve and device usage characteristics. The load curve of lighting equipment included in Type 2 can be obtained by calculating the basic load curve of a single household.

[0032] Among them, optionally, the first average energy consumption curve is calculated based on the average rated power of different types of continuous electrical appliances, or is calculated based on the average power consumption of multiple residential houses obtained during the first set time period (for example, during the time period when the residents are away from home). Optionally, the second average energy consumption curve is calculated based on the average rated power of different types of intermittent electrical appliances, or is calculated based on the power consumption of multiple residential houses obtained during the second set time period and the power consumption of multiple residential houses obtained during the first set time period (for example, during the time period when the residents are away from home).

[0033] S103, determining a probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve, determining a first load curve based on the probability distribution, and determining a second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance.

[0034] S104: Determine a target power load curve based on the first load curve and the second load curve.

[0035] In this embodiment, electrical equipment is divided into continuous electrical appliances and intermittent electrical appliances according to their power consumption characteristics, the first average energy consumption curve of the continuous electrical appliances, the second average energy consumption curve of the intermittent electrical appliances, and the start-up time period of the intermittent electrical appliances are obtained, cluster analysis is performed based on the power consumption characteristics, and the probability distribution of the start-up time of the continuous electrical appliances is determined based on the first average energy consumption curve, and the first load curve is determined based on the probability distribution, the second load curve is determined based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliances, the target power load curve is determined based on the first load curve and the second load curve, and analysis is performed based on the probability distribution and the start-up time period on the basis of the cluster analysis. This embodiment completes the prediction of the power load curve based on the power consumption characteristics and start-up time of different types of electrical appliances, improves the prediction accuracy, and thus improves the accuracy of power dispatching.

[0036] In some embodiments, in step S104, determining a target power load curve based on the first load curve and the second load curve includes:

[0037] Determine a device-level power load curve based on the power-consuming device type, the first load curve, and the second load curve; and / or,

[0038] A residential level electrical load profile is determined based on the first load profile and the second load profile.

[0039] The first load curves of the same electrical equipment or all continuous electrical appliances can be added to obtain the equipment-level load curve, and the second load curves of lighting equipment or all intermittent electrical appliances can be added to obtain the equipment-level load curve. The residential load curves composed of different equipment can also be added to obtain the total load curve of multiple residences, that is, a certain area.

[0040] In some embodiments, in step S103, determining the probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve includes:

[0041] Analyze the first average energy consumption curve to determine the average power of the constant power usage rate and the average operation time of the equipment;

[0042] The probability distribution is determined based on the average power at a constant power usage rate and the average operating time of the equipment.

[0043] Continuous electrical appliances need to run for a period of time after starting once before stopping. The probability distribution determined based on the average power of constant energy usage and the average running time of the equipment can be used to explain the operation process of electric water heaters and dryers.

[0044] In some embodiments, the relationship between the average power of the constant power usage rate, the average operation time of the device and the probability distribution is as follows:

[0045]

[0046] Among them, p d is the probability of continuous electrical appliances being used every day; P a Indicates the average power at constant power usage rate; T a is the average operating time of continuous appliances; N is the total number of residences; TS represents the total time period; t is the time index; P(t) is the average power consumption of continuous appliances at time t.

[0047] Among them, the average operating time of continuous electrical appliances is obtained based on the thermodynamic model of equivalent thermal parameters.

[0048] Take an electric water heater as an example to illustrate the process of determining the average operating time of an electric water heater:

[0049] The thermodynamic model based on equivalent thermal parameters can be used to represent the power consumption process of electric water heaters. This physical model reflects the energy exchange between the injected cold water and the environment. The increase and decrease of water temperature are caused by the input electrical energy and energy loss respectively.

[0050] The calculation formula for the water temperature inside the water heater is as follows:

[0051]

[0052] Among them, t 0 is the initial time; T am and T in is the temperature of the external environment and the cold water injected into the water inlet; T(t) is the water temperature inside the water heater at time t; Q is related to the rated power P of the water heater R Proportional to input power efficiency; C w is the specific heat capacity of water in the tank; 1 and λ 2 They represent the heat exchange factors of the environment and cold water affecting the water temperature in the water tank respectively.

[0053] When there is no cold water injected into the water tank, there is no hot water consumption, and the water heater is only caused by heat loss to cause the water heater to circulate, then the λ in the above formula 2 =0, the calculation formula of the water temperature inside the water heater is as follows:

[0054]

[0055] Among them, t 0 is the initial time; T am and T in is the temperature of the external environment and the cold water injected into the water inlet; T(t) is the water temperature inside the water heater at time t; Q is related to the rated power P of the water heater R Proportional to input power efficiency; C w is the specific heat capacity of water in the tank; 1 and λ2 They represent the heat exchange factors of the environment and cold water affecting the water temperature in the water tank respectively.

[0056] Electric water heaters provide hot water to residents in three main areas, including showering, hot water for the kitchen, and the washbasin. The hot water required for showering far exceeds the other two areas, which means that residents' showering behavior causes the most electricity consumption for residential water heaters. When the water heater is turned on, the electricity is consumed at a constant rate. Therefore, considering that the amount of water required for a shower is constant and the water flow rate is constant, the required electricity is also a constant. When water is first used, the electric water heater does not need to consume electricity until the water temperature drops to the lower limit, and then the water heater starts to use electricity for heating. The time required to use electricity is the time from the start of heating until the heating reaches the upper limit.

[0057] For dryers and lighting, electricity consumption starts when users turn on the devices, but there are still differences between their behaviors. The dryer is used at a constant power for a period of time, which is set by the resident when turning on the dryer. Therefore, the resident cannot use the dryer again before completing a task. In this regard, the use of the dryer has a certain similarity with the operation mode of the electric water heater. They both have a certain length of operation time, and the next use must be after the previous use ends. As for lighting equipment, whether the resident turns on the lighting equipment at this moment will not affect the use of the equipment at the next moment, so the resident can decide to turn the lighting equipment on and off at any time. Here, the start time is defined as the moment when the equipment starts to consume electricity. The dryer and lighting both start consuming electricity when the equipment is turned on, while the electric water heater may start consuming electricity when the resident is using it.

[0058] In some embodiments, in step S103, determining the first load curve based on the probability distribution includes:

[0059] Determine the number of electrical devices consuming electrical energy at a first set time and the number of electrical devices consuming electrical energy starting from a second set time based on the probability distribution;

[0060] The first load curve is determined based on the number of electric devices consuming electric energy at the first set time and the number of electric devices consuming electric energy starting from the second set time.

[0061] In some embodiments, the relationship between the number of electrical devices consuming electrical energy at the first set time, the number of electrical devices consuming electrical energy starting from the second set time, and the first load curve is as follows:

[0062]

[0063] Among them, p s (t) is the probability of the device starting at time t; k u(t) represents the number of devices in use at time t, that is, the number of electrical devices consuming electrical energy at the first set time; k u (t-1) is the number of devices in use at time t-1; k s (tT a ) is tT a The number of devices turned on at any time, that is, the number of electrical devices that consume electrical energy starting from the second set time; N is the total number of residences.

[0064] In the embodiment of the present invention, T a is the average running time of the device. Some devices will automatically shut down after running for a period of time. When calculating the number of devices turned on at time t, the above calculation process not only uses the number of devices in use at time t k u (t) minus the number of devices in use at time t-1 k u (t-1), and also considering the number of devices that are turned off when reaching time t, k s (tT a ), that is, the distance from time t to time t T a The number of devices that are turned on at the time of the duration.

[0065] The specific example is used for explanation. If at tT a At any time, a device is turned on. After T a After a certain time, the device is turned off at time t. If there are 4 devices working at time t and 2 devices working at time t-1, the number of devices turned on at time t is not 4-2=2, that is, the number of devices turned on at time t is not 2, but should be considered to be continuously running T. a Duration, and the device that is turned off at time t is working at time t-1, the number of devices turned on at time t is: 4-2+1=3, that is, 3 devices are turned on at time t.

[0066] The above formula is used to determine the probability of the device starting at each moment. The result obtained by the above formula can be used to generate countless start-up moments of electric water heaters and dryers, and then countless load curves for different devices or different houses can be constructed.

[0067] In some embodiments, determining the second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance includes:

[0068] Analyze the second average energy consumption curve to determine the average power of the intermittent electrical appliance's energy usage rate;

[0069] The second load curve is determined according to the average power of the electric energy usage rate and the startup time period of the intermittent electrical appliance.

[0070] Intermittent appliances such as lighting equipment can be turned on at any time of the day. For such equipment, the basic load curve of a single residence can be obtained from the average energy consumption curve. Assuming that the lighting demand of each residence is determined by the basic lighting and the number of residents returning home at any time, the formula for the lighting load curve is as follows:

[0071]

[0072] Where P(t) is the lighting demand of each residence at time t; NP l (t) refers to the lighting demand of N households; k u (t)P l (t) represents the power consumption of the lighting equipment turned on at time t.

[0073] With the base load curve, the load curve for any residence can be constructed using the start-up time periods, where the start-up time periods are determined based on the arrival and departure times.

[0074] In the embodiment of the present invention, P l (t) is an average indicator. When residents return home, they think they have lighting needs and consume P l (t) of electric charge, k u (t) here represents the number of lighting devices in use at time t, k u (t)P l (t) represents the power consumption of the lighting equipment turned on at time t, that is, at time t, someone comes home and generates new lighting demand. l (t) refers to the lighting demand of N households, which can be considered as the power consumption of lighting equipment turned on by people who are already at home before time t. Then NP l (t)+k u (t)P l (t) represents the total power consumption of all people at home in N households at time t. Based on the total power consumption divided by N, the power consumption P(t) of each household at time t is obtained.

[0075] Figure 2 FIG. 1 is a flowchart of a method for predicting power load provided by another embodiment of the present invention, comprising the following steps:

[0076] S201, divide into continuous electrical appliances and intermittent electrical appliances.

[0077] Among them, electrical equipment is divided into continuous electrical appliances and intermittent electrical appliances according to their power consumption characteristics.

[0078] Optionally, household appliances are divided into two types: Type 1 is household appliances that need to run for a period of time before stopping after being started, i.e., continuous appliances, such as electric water heaters and dryers. Type 2 is household appliances that can be started at any time of the day, i.e., intermittent appliances, such as lighting equipment. These two types of appliances consume most of the electrical energy in the house. In step S201, continuous appliances and intermittent appliances are divided, and steps S202 and S207 are executed.

[0079] S202, obtaining an average energy consumption curve of the continuous electrical appliance, that is, obtaining a first average energy consumption curve.

[0080] S203, using formula (1) to calculate and determine the daily usage probability of the continuous type electrical appliance.

[0081] S204, obtaining the probability distribution of the start time.

[0082] S205, determining the start time, wherein the start time is the time when the continuous electrical appliance consumes electric energy every day.

[0083] S206, determining a load curve of the continuous type electrical appliance, that is, determining a first load curve. The load curve of the continuous type electrical appliance is determined based on the above formula (5).

[0084] S207, obtaining an average energy consumption curve of the intermittent electrical appliance, that is, obtaining a second average energy consumption curve.

[0085] S208, obtaining the time of leaving home and arriving home, that is, determining the start-up time period of the intermittent electrical appliance.

[0086] S209, calculated using formula (6).

[0087] S210, determining the load curve of the intermittent electrical appliance, that is, determining the second load curve. The load curve of the intermittent electrical appliance is directly determined based on the above formula (6).

[0088] S211, calculating a device-level load curve or a residential-level power load curve.

[0089] In this embodiment, electrical equipment is divided into continuous electrical appliances and intermittent electrical appliances according to their power consumption characteristics, the first average energy consumption curve of the continuous electrical appliances, the second average energy consumption curve of the intermittent electrical appliances, and the start-up time period of the intermittent electrical appliances are obtained, cluster analysis is performed based on the power consumption characteristics, and the probability distribution of the start-up time of the continuous electrical appliances is determined based on the first average energy consumption curve, and the first load curve is determined based on the probability distribution, the second load curve is determined based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliances, the target power load curve is determined based on the first load curve and the second load curve, and analysis is performed based on the probability distribution and the start-up time period on the basis of the cluster analysis. This embodiment completes the prediction of the power load curve based on the power consumption characteristics and start-up time of different types of electrical appliances, improves the prediction accuracy, and thus improves the accuracy of power dispatching.

[0090] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0091] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0092] Figure 3 The following is a schematic diagram of the structure of a device for power load prediction provided by an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown, which are described in detail as follows:

[0093] like Figure 3 As shown, the device for power load prediction includes: a division module 301 , an acquisition module 302 , a first determination module 303 and a second determination module 304 .

[0094] The classification module 301 is used to classify the electrical equipment into continuous electrical equipment and intermittent electrical equipment according to the electrical consumption characteristics of the electrical equipment.

[0095] The acquisition module 302 is used to acquire a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance.

[0096] The first determination module 303 is used to determine the probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve, determine the first load curve based on the probability distribution, and determine the second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance.

[0097] The second determination module 304 is configured to determine a target power load curve based on the first load curve and the second load curve.

[0098] In this embodiment, electrical equipment is divided into continuous electrical appliances and intermittent electrical appliances according to their power consumption characteristics, the first average energy consumption curve of the continuous electrical appliances, the second average energy consumption curve of the intermittent electrical appliances, and the start-up time period of the intermittent electrical appliances are obtained, cluster analysis is performed based on the power consumption characteristics, and the probability distribution of the start-up time of the continuous electrical appliances is determined based on the first average energy consumption curve, and the first load curve is determined based on the probability distribution, the second load curve is determined based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliances, the target power load curve is determined based on the first load curve and the second load curve, and analysis is performed based on the probability distribution and the start-up time period on the basis of the cluster analysis. This embodiment completes the prediction of the power load curve based on the power consumption characteristics and start-up time of different types of electrical appliances, improves the prediction accuracy, and thus improves the accuracy of power dispatching.

[0099] Figure 4 FIG. 1 is a schematic diagram of a terminal provided by an embodiment of the present invention. Figure 4 As shown, the terminal 4 of this embodiment includes: a processor 40, a memory 41, and a computer program 42 stored in the memory 41 and executable on the processor 40. When the processor 40 executes the computer program 42, the steps in the above-mentioned method embodiments for predicting power load are implemented, such as Figure 1 Alternatively, when the processor 40 executes the computer program 42, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 3 Functions of modules 301 to 304 are shown.

[0100] Exemplarily, the computer program 42 may be divided into one or more modules / units, which are stored in the memory 41 and executed by the processor 40 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 42 in the terminal 4. For example, the computer program 42 may be divided into a division module, an acquisition module, a first determination module, and a second determination module, and the specific functions of each module are as follows:

[0101] A classification module, used to classify electrical appliances into continuous electrical appliances and intermittent electrical appliances according to the electrical consumption characteristics of the electrical appliances;

[0102] An acquisition module, used to acquire a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance;

[0103] A first determination module is used to determine the probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve, determine the first load curve based on the probability distribution, and determine the second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance;

[0104] The second determination module is used to determine a target power load curve based on the first load curve and the second load curve.

[0105] The terminal 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will appreciate that Figure 4 It is only an example of terminal 4 and does not constitute a limitation on terminal 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0106] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0107] The memory 41 may be an internal storage unit of the terminal 4, such as a hard disk or memory of the terminal 4. The memory 41 may also be an external storage device of the terminal 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the terminal 4. The memory 41 is used to store the computer program and other programs and data required by the terminal. The memory 41 may also be used to temporarily store data that has been output or is to be output.

[0108] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0109] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0110] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0111] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0112] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0113] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0114] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0115] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for predicting power load, It is characterized in that include: According to the electricity consumption characteristics of electrical equipment, electrical equipment is divided into continuous electrical equipment and intermittent electrical equipment; Acquire a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance; Determine the probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve, determine a first load curve based on the probability distribution, and determine a second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance; determining a target power load curve based on the first load curve and the second load curve; Wherein, the determining the probability distribution of the start-up time of the continuous electrical appliance based on the first average energy consumption curve includes: Analyzing the first average energy consumption curve to determine the average power at a constant power usage rate and the average operating time of the device; The probability distribution is determined according to the average power of the constant power usage rate and the average operation time of the device: in, is the probability of using the continuous appliance every day; Indicates the average power at a constant power usage rate; is the average operating time of the continuous appliance; is the total number of dwellings; Indicates the total time period; The continuous electrical appliance Average power consumption at any time; The determining a first load curve based on the probability distribution comprises: Determine the number of electrical devices consuming electrical energy at a first set time and the number of electrical devices consuming electrical energy starting from a second set time based on the probability distribution; determining a first load curve based on the number of electrical devices consuming electrical energy at the first set time and the number of electrical devices consuming electrical energy starting from the second set time; in, for The probability of the device starting at the moment; express The number of electrical devices consuming power at any given moment; ; for The number of devices currently in use; For The number of devices that are turned on at any given time.

2. The method according to claim 1, It is characterized in that The determining a target power load curve based on the first load curve and the second load curve includes: Determine a device-level power load curve based on the type of power-consuming equipment, the first load curve, and the second load curve; and / or, A residential level electrical load profile is determined based on the first load profile and the second load profile.

3. The method according to claim 1, It is characterized in that The determining of the second load curve based on the second average energy consumption curve and the start-up time period of the intermittent electrical appliance comprises: Analyzing the second average energy consumption curve to determine the average power of the electric energy usage rate of the intermittent electrical appliance; The second load curve is determined according to the average power of the electric energy usage rate of the intermittent electrical appliance and the startup time period.

4. A device for executing the method for electricity load forecasting according to any one of claims 1 to 3, It is characterized in that include: A classification module, used to classify electrical appliances into continuous electrical appliances and intermittent electrical appliances according to the electrical consumption characteristics of the electrical appliances; An acquisition module, used to acquire a first average energy consumption curve of the continuous electrical appliance, a second average energy consumption curve of the intermittent electrical appliance, and a start-up time period of the intermittent electrical appliance; a first determination module, configured to determine a probability distribution of a start-up time of the continuous electrical appliance based on the first average energy consumption curve, determine a first load curve based on the probability distribution, and determine a second load curve based on the second average energy consumption curve and a start-up time period of the intermittent electrical appliance; The second determination module is used to determine a target power load curve based on the first load curve and the second load curve.

5. A terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the steps of the method for electricity load forecasting as described in any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium storing a computer program, It is characterized in that When the computer program is executed by a processor, the steps of the method for electricity load forecasting as described in any one of claims 1 to 3 are implemented.

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