A method for short-term power load forecasting of power grids based on environmental feedback

Abstract

This invention provides a short-term power load forecasting method based on environmental feedback, specifically as follows: Power grid information is acquired during user operation; a power grid analysis module receives the power grid information, analyzes it, and derives power operation parameters; a load information storage module stores the derived power operation parameters and transmits them to a load calculation module; the load calculation module calculates power operation reference data and transmits the calculated reference data to a load forecasting module; the load forecasting module performs power load forecasting based on the received reference data and derives forecast data; the forecast data is then transmitted to a power consumption control module for power consumption control. This invention sets multiple temperature ranges based on environmental information, statistically analyzes power grid operation information under different temperature ranges, and performs power forecasting based on the environment, thereby improving the accuracy of power forecasting.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power load prediction, in particular to a power grid short-term power load prediction method based on environmental feedback. BACKGROUND

[0002] Power load, also known as "electricity load". The total power taken by the power user's electrical equipment at a certain time is called electricity load. According to the different load characteristics of power users, power load can be divided into various industrial loads, agricultural loads, transportation industry loads and domestic electricity loads. The total load of the power system is the sum of the total power consumed by all electrical equipment in the system; the power consumed by industry, agriculture, post and telecommunications, transportation, municipal administration, business and urban and rural residents is added to obtain the comprehensive electricity load of the power system; the comprehensive electricity load plus the network loss power is the power that each power plant should supply, which is called the power supply load (power supply) of the power system; the power supply load plus the power consumed by each power plant itself (i.e. plant power) is the power that each generator should generate, which is called the power generation load (power generation) of the system.

[0003] In the prior art, the power grid usually predicts and analyzes the power load according to the power consumption in the process of power load prediction. The power load is not accurate due to the influence of the environment under different environments, which affects the prediction effect. Therefore, the present application provides a power grid short-term power load prediction method based on environmental feedback. SUMMARY

[0004] In view of the deficiencies in the prior art, the present application aims to provide a power grid short-term power load prediction method based on environmental feedback. The present application acquires power grid information of users in the use process, analyzes power operation information and environmental information according to the power grid information, sets multiple temperature intervals according to the environmental information, counts power grid operation information under different temperature intervals, and predicts power according to the environment to improve the accuracy of power prediction.

[0005] In order to achieve the above-mentioned purpose, the present application is realized by the following technical scheme: a power grid short-term power load prediction method based on environmental feedback, the power load prediction comprising the following steps:

[0006] Step S1: an information acquisition module acquires power grid information of users in the use process, and sends the power grid information to a power grid analysis module. The power grid analysis module receives the power grid information, analyzes based on the power grid information, and obtains power operation parameters;

[0007] Step S2: a load information storage module stores the power operation parameters obtained by analysis, and sends the power operation parameters stored in the T time period to an electric load calculation module;

[0008] Step S3: The power load calculation module receives the power operation parameters, calculates the power operation reference data, and sends the calculated power operation reference data to the load prediction module.

[0009] Step S4: The load forecasting module performs power load forecasting based on the received power operation reference data and obtains forecast data; the forecast data is then transmitted to the power consumption control module for power consumption control.

[0010] Furthermore, power grid information includes power operation information as well as environmental information;

[0011] The power grid analysis module receives and analyzes power operation information and environmental information. The specific analysis steps are as follows:

[0012] Step S11: Obtain power operation information within time period T; The data analysis module obtains the power usage time value, power value, and electricity user value from the power operation information within time period T, and obtains the temperature value from the environmental information.

[0013] Step S12: Set the electricity user value to YDHSz; calculate the electricity consumption based on the time and power values; set the number of years included in the time period T to n years, obtain the temperature values ​​in n years, obtain the minimum temperature value as WDSZmin; obtain the maximum temperature value as WDSZmax; obtain the difference between the maximum and minimum temperatures, and set the temperature difference value as WDCz; generate temperature ranges based on the obtained differences, and set the first temperature range, second temperature range, third temperature range, fourth temperature range, and fifth temperature range respectively.

[0014] Step S13: Count the number of days in the first temperature range, second temperature range, third temperature range, fourth temperature range and fifth temperature range in the first year respectively, and obtain the electricity consumption of the first electricity user in the first temperature range, the electricity consumption of the second electricity user in the first temperature range, the electricity consumption of the third electricity user in the first temperature range, ... the electricity consumption of the YDHSzth electricity user in the first temperature range.

[0015] Step S14: Calculate the average electricity consumption for each interval based on the electricity consumption; obtain the average electricity consumption for the first interval a1, the second interval a1, the third interval a1, the fourth interval a1, and the fifth interval a1.

[0016] Step S15: Thus, the electricity consumption in different temperature ranges in the second year, the third year...the nth year is calculated respectively.

[0017] Further, in step S12, the first temperature range threshold is [WDSZmin, WDSZmin+WDCz / 5]; the second temperature range threshold is (WDSZmin+WDCz / 5, 2×(WDSZmin+WDCz) / 5]; the third temperature range threshold is (2×(WDSZmin+WDCz) / 5, 3×(WDSZmin+WDCz) / 5]; the fourth temperature range threshold is (3×WDSZmin+WDCz / 5, 4×(WDSZmin+WDCz) / 5]; and the fifth temperature range threshold is (4×(WDSZmin+WDCz) / 5, WDSZmax).

[0018] Furthermore, in step S3, when the electrical load calculation module performs the calculation, the specific steps are as follows:

[0019] Step S31: The power load calculation module receives the average power consumption of each interval in the power operation parameters; it obtains the values ​​of the average power consumption of the first interval a1, the first interval a2, the first interval a3, ... the first interval an, and obtains the change value of power consumption in the first temperature interval in each year;

[0020] Step S32: Obtain the values ​​of the average electricity consumption in the second interval a1, the average electricity consumption in the second interval a2, the average electricity consumption in the second interval a3, ... the average electricity consumption in the second interval an, and obtain the change in electricity consumption in the second temperature interval in each year;

[0021] Step S33: Obtain the values ​​of the average electricity consumption in the third interval a1, the average electricity consumption in the third interval a2, the average electricity consumption in the third interval a3, ... the average electricity consumption in the third interval an, and obtain the change value of electricity consumption in the third temperature interval in each year.

[0022] Step S34: Obtain the values ​​of the average electricity consumption in the fourth interval a1, the average electricity consumption in the fourth interval a2, the average electricity consumption in the fourth interval a3, ... the average electricity consumption in the fourth interval an, and obtain the change in electricity consumption in the fourth temperature interval in each year;

[0023] Step S35: Obtain the values ​​of the average electricity consumption in the fifth interval a1, the average electricity consumption in the fifth interval a2, the average electricity consumption in the fifth interval a3, ... the average electricity consumption in the fifth interval an, and obtain the change in electricity consumption in the fifth temperature interval in each year;

[0024] Step S36: Define the acquired power change value as power operation reference data and transmit the power operation reference data to the load forecasting module.

[0025] Furthermore, in step S15, when calculating the electricity consumption in different temperature ranges for the second year, the third year...the nth year, the specific steps are as follows:

[0026] Find the average electricity consumption of the first interval a2, the average electricity consumption of the second interval a2, the average electricity consumption of the third interval a2, the average electricity consumption of the fourth interval a2, and the average electricity consumption of the fifth interval a2 in the second year.

[0027] ...

[0028] Find the average electricity consumption of the first interval an, the second interval an, the third interval an, the fourth interval an, and the fifth interval an in the nth year; define the obtained average electricity consumption of each interval as the power operation parameter.

[0029] Furthermore, the load forecasting module performs the following specific actions when forecasting power load:

[0030] The load forecasting module acquires the temperature change values ​​of the first interval, the second interval, the third interval, the fourth interval, and the fifth interval from the power operation reference data; and forecasts the power load for the next year based on the temperature change values.

[0031] The beneficial effects of this invention are:

[0032] 1. This invention is based on acquiring power grid information during user operation, analyzing power operation information and environmental information based on the power grid information, setting multiple temperature ranges based on the environmental information, statistically analyzing power grid operation information under different temperature ranges, and making power predictions based on the environment, thereby improving the accuracy of power predictions.

[0033] 2. This invention acquires power operation information over a certain period of time, analyzes and judges the changes in power operation information due to different environments, and then predicts the short-term power load of the power grid based on these environmental changes. Attached Figure Description

[0034] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0035] Figure 1 This is a flowchart illustrating the steps of a short-term power load forecasting method for power grids based on environmental feedback, as described in this invention.

[0036] Figure 2 This is a block diagram illustrating the principle of a short-term power load forecasting method for power grids based on environmental feedback, according to the present invention. Detailed Implementation

[0037] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0038] In this invention, please refer to Figure 1 and Figure 2 A short-term power load forecasting method for power grids based on environmental feedback includes an information acquisition module, a power grid analysis module, an electrical load calculation module, a load forecasting module, an electricity consumption control module, a load information storage module, and a server; the information acquisition module, the power grid analysis module, the electrical load calculation module, the load forecasting module, the electricity consumption control module, and the load information storage module are respectively connected to the server for data.

[0039] The information acquisition module acquires power grid information during user operation and transmits the power grid information to the power grid analysis module. The power grid analysis module receives the power grid information, analyzes it based on the power grid information, and derives power operation parameters.

[0040] In this embodiment, the power grid information includes power operation information and environmental information;

[0041] The power grid analysis module receives and analyzes power operation information and environmental information, as detailed below:

[0042] Obtain power operation information within time period T;

[0043] The data analysis module acquires the power usage time, power, and user data within the power operation information for the time period T, and also acquires the temperature data from the environmental information.

[0044] The user's electricity consumption value is set as YDHSz; the electricity consumption is calculated based on the time and power values.

[0045] Let time period T encompass n years. We obtain the temperature values ​​for each of those n years: Minimum temperature value: WDSZmin; Maximum temperature value: WDSZmax.

[0046] Obtain the difference between the maximum and minimum temperatures, and set the temperature difference value as WDCz. Generate temperature ranges based on the obtained difference, setting the threshold values ​​for the first temperature range to [WDSZmin, WDSZmin+WDCz / 5]; the second temperature range to (WDSZmin+WDCz / 5, 2×(WDSZmin+WDCz) / 5]; the third temperature range to (2×(WDSZmin+WDCz) / 5, 3×(WDSZmin+WDCz) / 5]; the fourth temperature range to (3×WDSZmin+WDCz / 5, 4×(WDSZmin+WDCz) / 5]; and the fifth temperature range to (4×(WDSZmin+WDCz) / 5, WDSZmax].

[0047] The number of days in the first temperature range, second temperature range, third temperature range, fourth temperature range, and fifth temperature range in the first year are counted respectively to obtain the electricity consumption of the first electricity user in the first temperature range, the electricity consumption of the second electricity user in the first temperature range, the electricity consumption of the third electricity user in the first temperature range, ... the electricity consumption of the YDHSzth electricity user in the first temperature range.

[0048] Calculate the average electricity consumption for each interval based on the electricity consumption; thus, obtain the average electricity consumption for the first interval a1, the second interval a1, the third interval a1, the fourth interval a1, and the fifth interval a1.

[0049] Therefore, the electricity consumption in different temperature ranges in the second year, the third year... and the nth year can be analyzed respectively;

[0050] Find the average electricity consumption of the first interval a2, the average electricity consumption of the second interval a2, the average electricity consumption of the third interval a2, the average electricity consumption of the fourth interval a2, and the average electricity consumption of the fifth interval a2 in the second year.

[0051] ...

[0052] Find the average electricity consumption of the first interval an, the second interval an, the third interval an, the fourth interval an, and the fifth interval an in the nth year.

[0053] The average electricity consumption for each interval is defined as the power operation parameter;

[0054] It should be noted that: T represents a time unit, which can be 2 years, 3 years, or 5 years, etc.;

[0055] The load information storage module stores the power operation parameters obtained from the analysis and sends the power operation parameters stored in the time period T to the power load calculation module; the power load calculation module receives the power operation parameters, calculates the power operation reference data, and sends the calculated power operation reference data to the load prediction module.

[0056] The electrical load calculation module receives the average electricity consumption for each interval in the power operation parameters;

[0057] The values ​​of the average electricity consumption in the first interval a1, the first interval a2, the first interval a3, ... the first interval an are obtained, and the change in electricity consumption in the first temperature interval in each year is obtained.

[0058] The values ​​of the average electricity consumption in the second interval a1, the second interval a2, the second interval a3, ... the second interval an are obtained, and the changes in electricity consumption in the second temperature interval are obtained in each year.

[0059] The values ​​of the average electricity consumption in the third interval a1, the third interval a2, the third interval a3, ... the third interval an are obtained, and the changes in electricity consumption in the third temperature interval in each year are obtained.

[0060] The values ​​of the average electricity consumption in the fourth interval a1, the fourth interval a2, the fourth interval a3, ... the fourth interval an are obtained, and the changes in electricity consumption in the fourth temperature interval are obtained in each year.

[0061] The values ​​of the average electricity consumption in the fifth interval a1, the fifth interval a2, the fifth interval a3, ... the fifth interval an are obtained, and the changes in electricity consumption in the fifth temperature interval are obtained in each year.

[0062] The acquired power change value is defined as power operation reference data, and the power operation reference data is sent to the load forecasting module;

[0063] The load forecasting module performs power load forecasting based on the received power operation reference data and obtains forecast data;

[0064] The load forecasting module acquires the temperature change values ​​for the first, second, third, fourth, and fifth intervals of the power operation reference data; and forecasts the power load for the next year based on these temperature change values.

[0065] The predicted data is sent to the power control module for power control.

[0066] In this invention, a short-term power load forecasting method for power grids based on environmental feedback specifically includes the following steps when forecasting power load:

[0067] Step S1: The information acquisition module acquires the power grid information during the user's use and transmits the power grid information to the power grid analysis module. The power grid analysis module receives the power grid information, analyzes it based on the power grid information, and obtains the power operation parameters.

[0068] Power grid information includes power operation information and environmental information;

[0069] The power grid analysis module receives and analyzes power operation information and environmental information. The specific analysis steps are as follows:

[0070] Step S11: Obtain power operation information within time period T; The data analysis module obtains the power usage time value, power value, and electricity user value from the power operation information within time period T, and obtains the temperature value from the environmental information.

[0071] Step S12: Set the electricity user value to: YDHSz; calculate the electricity consumption based on the time value and power value; set the number of years included in the time period T to n years, obtain the temperature values ​​in n years, obtain the minimum temperature value to: WDSZmin; obtain the maximum temperature value to: WDSZmax; obtain the difference between the maximum temperature and the minimum temperature, and set the temperature difference value to: WDCz; generate a temperature range based on the obtained difference, and set the threshold of the first temperature range to [WDSZmin, WDSZmin+WDCz / 5]; The threshold for the second temperature range is (WDSZmin+WDCz / 5, 2×(WDSZmin+WDCz) / 5]; the threshold for the third temperature range is (2×(WDSZmin+WDCz) / 5, 3×(WDSZmin+WDCz) / 5]; the threshold for the fourth temperature range is (3×WDSZmin+WDCz / 5, 4×(WDSZmin+WDCz) / 5]; the threshold for the fifth temperature range is (4×(WDSZmin+WDCz) / 5, WDSZmax];

[0072] Step S13: Count the number of days in the first temperature range, second temperature range, third temperature range, fourth temperature range and fifth temperature range in the first year respectively, and obtain the electricity consumption of the first electricity user in the first temperature range, the electricity consumption of the second electricity user in the first temperature range, the electricity consumption of the third electricity user in the first temperature range, ... the electricity consumption of the YDHSzth electricity user in the first temperature range.

[0073] Step S14: Calculate the average electricity consumption for each interval based on the electricity consumption; obtain the average electricity consumption for the first interval a1, the second interval a1, the third interval a1, the fourth interval a1, and the fifth interval a1.

[0074] Step S15: Thus, the electricity consumption in different temperature ranges in the second year, the third year...then year is calculated respectively;

[0075] Find the average electricity consumption of the first interval a2, the average electricity consumption of the second interval a2, the average electricity consumption of the third interval a2, the average electricity consumption of the fourth interval a2, and the average electricity consumption of the fifth interval a2 in the second year.

[0076] ...

[0077] Find the average electricity consumption of the first interval an, the second interval an, the third interval an, the fourth interval an, and the fifth interval an in the nth year; define the average electricity consumption of each interval as the power operation parameter.

[0078] Step S2: The load information storage module stores the power operation parameters obtained from the analysis and transmits the power operation parameters stored in the time period T to the power load calculation module;

[0079] Step S3: The power load calculation module receives the power operation parameters, calculates the power operation reference data, and sends the calculated power operation reference data to the load prediction module.

[0080] The specific steps for the electrical load calculation module are as follows:

[0081] Step S31: The power load calculation module receives the average power consumption of each interval in the power operation parameters; it obtains the values ​​of the average power consumption of the first interval a1, the first interval a2, the first interval a3, ... the first interval an, and obtains the change value of power consumption in the first temperature interval in each year;

[0082] Step S32: Obtain the values ​​of the average electricity consumption in the second interval a1, the average electricity consumption in the second interval a2, the average electricity consumption in the second interval a3, ... the average electricity consumption in the second interval an, and obtain the change in electricity consumption in the second temperature interval in each year;

[0083] Step S33: Obtain the values ​​of the average electricity consumption in the third interval a1, the average electricity consumption in the third interval a2, the average electricity consumption in the third interval a3, ... the average electricity consumption in the third interval an, and obtain the change value of electricity consumption in the third temperature interval in each year.

[0084] Step S34: Obtain the values ​​of the average electricity consumption in the fourth interval a1, the average electricity consumption in the fourth interval a2, the average electricity consumption in the fourth interval a3, ... the average electricity consumption in the fourth interval an, and obtain the change in electricity consumption in the fourth temperature interval in each year;

[0085] Step S35: Obtain the values ​​of the average electricity consumption in the fifth interval a1, the average electricity consumption in the fifth interval a2, the average electricity consumption in the fifth interval a3, ... the average electricity consumption in the fifth interval an, and obtain the change in electricity consumption in the fifth temperature interval in each year;

[0086] Step S36: Define the acquired power change value as power operation reference data, and transmit the power operation reference data to the load forecasting module;

[0087] Step S4: The load forecasting module performs power load forecasting based on the received power operation reference data and obtains forecast data; the forecast data is then transmitted to the power consumption control module for power consumption control.

[0088] When performing power load forecasting, the load forecasting module does the following:

[0089] The load forecasting module acquires the temperature change values ​​of the first interval, the second interval, the third interval, the fourth interval, and the fifth interval from the power operation reference data; and forecasts the power load for the next year based on the temperature change values.

[0090] The above formulas are all dimensionless calculations. The formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. For example, there are weighting coefficients and proportional coefficients. The values ​​set are to quantify each parameter to obtain a specific value, which is convenient for subsequent comparison. The values ​​of the weighting coefficients and proportional coefficients are only required to not affect the proportional relationship between the parameters and the quantified values.

[0091] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0092] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media containing computer-usable program code.

[0093] The above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and are not intended to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the scope of the technology disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of protection of the claims.

Claims

1. A method for short-term power load forecasting of power grid based on environmental feedback, characterized in that, The power load prediction comprises the following steps: Step S1: The information acquisition module acquires power grid information in the use process of the user, and delivers the power grid information to a power grid analysis module; the power grid analysis module receives the power grid information, analyzes based on the power grid information, and obtains power operation parameters; Step S2: The load information storage module stores the power operation parameters obtained by analysis, and delivers the power operation parameters stored in the T time period to an electric load calculation module; Step S3: The electric load calculation module receives the power operation parameters to calculate power operation reference data, and delivers the calculated power operation reference data to a load prediction module; In step S3, when the electric load calculation module calculates, the specific steps are as follows: Step S31: The electric load calculation module receives the average power consumption value of each interval in the power operation parameters; the numerical value of the first interval a1 average power consumption value, the first interval a2 average power consumption value, the first interval a3 average power consumption value,..., the first interval an average power consumption value is acquired, and the power consumption change value of the first temperature interval in each year is acquired; Step S32: The numerical value of the second interval a1 average power consumption value, the second interval a2 average power consumption value, the second interval a3 average power consumption value,..., the second interval an average power consumption value is acquired, and the power consumption change value of the second temperature interval in each year is acquired; Step S33: The numerical value of the third interval a1 average power consumption value, the third interval a2 average power consumption value, the third interval a3 average power consumption value,..., the third interval an average power consumption value is acquired, and the power consumption change value of the third temperature interval in each year is acquired; Step S34: The numerical value of the fourth interval a1 average power consumption value, the fourth interval a2 average power consumption value, the fourth interval a3 average power consumption value,..., the fourth interval an average power consumption value is acquired, and the power consumption change value of the fourth temperature interval in each year is acquired; Step S35: The numerical value of the fifth interval a1 average power consumption value, the fifth interval a2 average power consumption value, the fifth interval a3 average power consumption value,..., the fifth interval an average power consumption value is acquired, and the power consumption change value of the fifth temperature interval in each year is acquired; Step S36: The acquired power change value is defined as power operation reference data, and the power operation reference data is delivered to the load prediction module; Step S4: The load prediction module performs power load prediction according to the received power operation reference data, and obtains prediction data; the prediction data obtained by prediction is delivered to a power consumption control module for power consumption control; When the load prediction module performs power load prediction, the specific steps are as follows: The load prediction module acquires the temperature change value of the first interval, the temperature change value of the second interval, the temperature change value of the third interval, the temperature change value of the fourth interval, and the temperature change value of the fifth interval in the power operation reference data; based on the temperature change value, the power load of the next year is predicted.

2. The method for short-term power load forecasting of power grid based on environmental feedback according to claim 1, characterized in that, The power grid information comprises power operation information and environmental information; The power grid analysis module receives the power operation information and the environmental information for analysis, and the specific analysis steps are as follows: Step S11: Obtain power operation information in a T time period; the data analysis module obtains power operation information in the T time period, obtains power use time values, power values, and power user values in the power operation information, and obtains temperature values in the environmental information; Step S12: Set the power user value as YDHSz; According to the time values and the power values, obtain the power consumption; set the number of years included in the T time period as n years, obtain the temperature values in the n years, obtain the minimum temperature value as WDSZmin, obtain the maximum temperature value as WDSZmax, obtain the difference between the maximum temperature and the minimum temperature, set the temperature difference as WDCz, generate temperature intervals according to the obtained difference, and set the first temperature interval, the second temperature interval, the third temperature interval, the fourth temperature interval, and the fifth temperature interval respectively; Step S13: Count the number of days in the first temperature interval, the second temperature interval, the third temperature interval, the fourth temperature interval, and the fifth temperature interval in the first year respectively, obtain the power consumption of the first power user in the first temperature interval, the power consumption of the second power user in the first temperature interval, the power consumption of the third power user in the first temperature interval, and the power consumption of the YDHSz power user in the first temperature interval; Step S14: According to the power consumption, obtain the average power consumption of each interval; obtain the first interval a1 average power consumption, the second interval a1 average power consumption, the third interval a1 average power consumption, the fourth interval a1 average power consumption, and the fifth interval a1 average power consumption; Step S15: Thus, the power consumption in different temperature intervals in the second year, the third year,..., and the n-th year is obtained.

3. The method for short-term power load forecasting of power grid based on environmental feedback according to claim 2, characterized in that, In the step S12, the first temperature interval threshold is in [WDSZmin, WDSZmin+WDCz / 5]; the second temperature interval threshold is in (WDSZmin+WDCz / 5, 2×(WDSZmin+WDCz) / 5]; the third temperature interval threshold is in (2×(WDSZmin+WDCz) / 5, 3×(WDSZmin+WDCz) / 5]; the fourth temperature interval threshold is in (3×WDSZmin+WDCz / 5, 4×(WDSZmin+WDCz) / 5]; and the fifth temperature interval threshold is in (4×(WDSZmin+WDCz) / 5, WDSZmax].

4. The method for short-term power load forecasting of power grid based on environmental feedback according to claim 2, characterized in that, In the step S15, when the power consumption in different temperature intervals in the second year, the third year,..., and the n-th year is obtained, the following is specifically performed: In the second year, the first interval a2 average power consumption, the second interval a2 average power consumption, the third interval a2 average power consumption, the fourth interval a2 average power consumption, and the fifth interval a2 average power consumption are obtained; …… In the n-th year, the first interval an average power consumption, the second interval an average power consumption, the third interval an average power consumption, the fourth interval an average power consumption, and the fifth interval an average power consumption are obtained; and the obtained average power consumption of each interval is defined as a power operation parameter.

Images