Power grid equipment material price prediction and dynamic adjustment method

Abstract

The invention relates to the technical field of power grid equipment planning, and discloses a power grid equipment material price prediction and dynamic adjustment method, which comprises the following steps: presetting a fluctuation period, dividing the preset fluctuation period into a plurality of time nodes, and obtaining a power grid equipment material price corresponding to each time node; screening the power grid equipment material price corresponding to each time node to obtain a power grid equipment material effective price group; based on the power grid equipment material effective price group, establishing a plane-coordinate system with time as an X axis and power grid equipment material price as a Y axis in a preset fluctuation period, and constructing an equipment material price curve with the power grid equipment material effective price group; on-line identification of the fluctuation state of the power grid equipment material price in the preset period is completed according to the equipment material price curve; and the price of the power grid equipment material price in the next fluctuation period is predicted and adjusted based on the fluctuation state of the power grid equipment material price in the preset period, so that the accuracy is high.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid equipment planning, and in particular to a method for predicting and dynamically adjusting the price of power grid equipment materials. Background Art

[0002] As the proportion of engineering equipment and material purchase costs in project investment continues to increase, the impact of equipment and material prices on power grid project investment and the company's overall operating conditions has become increasingly significant. The marketization level of material procurement continues to improve, and new equipment and new materials are being updated more frequently, resulting in increasingly complex factors causing equipment and material price fluctuations. The models of equipment and materials are more diverse, and the difficulty of price preparation and forecasting has increased significantly.

[0003] The price forecasting and dynamic adjustment method of power grid equipment and materials is of great significance to improving the efficiency and quality of power grid construction projects and ensuring the safe and stable operation of power grids. It is an effective means for enterprises to cope with market changes and enhance their competitiveness, and it is also an important support for promoting the sustainable development of the power industry. Summary of the invention

[0004] The purpose of the present invention is to provide a method for predicting and dynamically adjusting the prices of power grid equipment and materials, constructing an equipment and material price curve with an effective price group of power grid equipment and materials within a preset fluctuation period, completing online identification of the fluctuation state of the power grid equipment and material prices within the preset period according to the equipment and material price curve, and predicting and adjusting the prices of the power grid equipment and materials within the next fluctuation period based on the fluctuation state of the power grid equipment and material prices within the preset period, thereby realizing effective evaluation of power grid equipment and materials within the period.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for predicting and dynamically adjusting the price of power grid equipment materials comprises the following steps:

[0007] Preset a fluctuation period, divide the preset fluctuation period into several time nodes, and obtain the price of power grid equipment and materials corresponding to each time node;

[0008] Screen and process the prices of power grid equipment and materials corresponding to each time node to obtain a valid price group of power grid equipment and materials;

[0009] Based on the effective price group of power grid equipment and materials, a plane coordinate system is established with time as the X-axis and the price of power grid equipment and materials as the Y-axis within a preset fluctuation period, and an equipment and material price curve is constructed with the effective price group of power grid equipment and materials;

[0010] Complete online identification of the fluctuation status of power grid equipment and material prices within a preset period based on the equipment and material price curve;

[0011] Based on the fluctuation status of the prices of power grid equipment and materials within the preset period, the price forecast of the prices of power grid equipment and materials within the next fluctuation period is adjusted.

[0012] As a further solution of the present invention: the price of the power grid equipment material corresponding to each time node is recorded as Vi, i is the number of time nodes, i=1, 2, ..., n;

[0013] Obtain the price groups V1, V2, V3, ..., Vi of power grid equipment materials at all time nodes within the preset fluctuation period;

[0014] According to the formula The standard deviation value Va of the power grid equipment material price group is calculated, where Vp is the average value of the power grid equipment material price group V1, V2, V3, ..., Vn.

[0015] As a further solution of the present invention: a standard deviation threshold of the power grid equipment material price group is preset as Vy;

[0016] If the standard deviation value Va of the power grid equipment and material price group is greater than or equal to the standard deviation threshold value Vy of the power grid equipment and material price group, the maximum value and / or minimum value in the power grid equipment and material price group data is deleted, and the standard deviation value Va of the power grid equipment and material price group data is calculated again until Va is less than the standard deviation threshold value Vy of the power grid equipment and material price group, and the remaining power grid equipment and material prices in the power grid equipment and material price group are marked and sorted to obtain a valid power grid equipment and material price group.

[0017] As a further solution of the present invention: based on the effective price group of power grid equipment and materials, the price of power grid equipment and materials corresponding to each time node of the effective price group of power grid equipment and materials within a preset fluctuation period is obtained, and an equipment and material price curve is constructed in a plane coordinate system;

[0018] Analyze the equipment and material price curve, the first equipment and material price boundary, and the second equipment and material price boundary;

[0019] The area where the equipment and material price curve is located above the first equipment and material price boundary is recorded as the upper floating area;

[0020] The area where the equipment and material price curve is below the second boundary line of the equipment and material price is recorded as the lower floating area;

[0021] The upper floating area and the lower floating area are recorded as floating areas;

[0022] The area where the equipment and material price curve is located between the first equipment and material price boundary line and the second equipment and material price boundary line is recorded as a non-floating area.

[0023] As a further solution of the present invention: the floating area and the non-floating area are processed to obtain the floating amplitude value, the floating time occupation value and the floating difference limit ratio;

[0024] The floating amplitude value is recorded as Ff;

[0025] The floating time occupied value is recorded as Ft;

[0026] The floating difference limit ratio is recorded as Fc;

[0027] By formula The price fluctuation behavior value Fi of power grid equipment materials within the preset fluctuation period is calculated, where a1 and a2 are both preset proportional coefficients.

[0028] As a further solution of the present invention: if the power grid equipment material price fluctuation behavior value is greater than or equal to the power grid equipment material price fluctuation behavior threshold, then a power grid equipment material price fluctuation abnormality signal is generated;

[0029] If the power grid equipment material price fluctuation behavior value is less than the power grid equipment material price fluctuation behavior threshold, a power grid equipment material price fluctuation normal signal is generated.

[0030] As a further solution of the present invention: obtaining area values ​​of the floating area and the non-floating area, the floating amplitude value is the ratio of the non-floating area value to the floating area value;

[0031] Get the time length value of the floating area and the time length value of the non-floating area;

[0032] The floating time duration value is the ratio of the time length value of the floating area to the time length value of the non-floating area.

[0033] As a further solution of the present invention: obtaining the maximum grid equipment material price in the upper floating area and the minimum grid equipment material price in the lower floating area, performing a difference calculation between the maximum grid equipment material price and the minimum grid equipment material price, and obtaining a floating difference limit value of the floating area;

[0034] The floating difference limit value of the floating area is calculated by ratio with the rated middle value of the power grid equipment material price to obtain the floating difference limit ratio of the floating area.

[0035] As a further solution of the present invention: based on the largest price of power grid equipment and materials in the upper floating area and the smallest price of power grid equipment and materials in the lower floating area, a forecast adjustment of the price of power grid equipment and materials in the next fluctuation cycle is completed;

[0036] The maximum price of grid equipment and materials in the upper floating area is recorded as Vmax;

[0037] Then in the next fluctuation cycle, the maximum price of power grid equipment materials is V1max=Vmax*1+Vqs), where Vqs is the price dynamic trend ratio;

[0038] The minimum price of power grid equipment and materials in the lower floating area is recorded as Vmin;

[0039] Then in the next fluctuation cycle, the lowest price of power grid equipment materials is V1min=Vmax*1-Vqs), where Vqs is the price dynamic trend ratio.

[0040] As a further solution of the present invention: obtaining an area value of the upper floating area and an area value of the lower floating area, performing a difference calculation between the area value of the upper floating area and the area value of the lower floating area, and obtaining a dynamic trend value of the floating area;

[0041] The dynamic trend value of the floating area is calculated by ratioing it with the non-floating area value to obtain the price dynamic trend ratio.

[0042] The beneficial effects of the present invention are as follows: the present invention screens and processes the power grid equipment and material prices corresponding to each time node within a preset fluctuation period to obtain an effective price group of power grid equipment and materials, constructs an equipment and material price curve based on the effective price group of power grid equipment and materials, completes online identification of the fluctuation state of the power grid equipment and material prices within the preset period according to the equipment and material price curve, and adjusts the price forecast of the power grid equipment and material prices in the next fluctuation period based on the fluctuation state of the power grid equipment and material prices within the preset period, thereby realizing effective evaluation of power grid equipment and materials within the period with high accuracy and strong reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] Figure 1 It is a flow chart of a method for predicting and dynamically adjusting the price of power grid equipment materials of the present invention;

[0045] Figure 2 The invention discloses a power grid equipment material price fluctuation identification diagram in a power grid equipment material price prediction and dynamic adjustment method. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Example 1

[0048] See also Figure 1-Figure 2 As shown, the present invention is a method for predicting and dynamically adjusting the price of power grid equipment materials, comprising the following steps:

[0049] Preset a fluctuation period, divide the preset fluctuation period into several time nodes, and obtain the price of power grid equipment and materials corresponding to each time node;

[0050] Screen and process the prices of power grid equipment and materials corresponding to each time node to obtain a valid price group of power grid equipment and materials;

[0051] Based on the effective price group of power grid equipment and materials, a plane coordinate system is established with time as the X-axis and the price of power grid equipment and materials as the Y-axis within a preset fluctuation period, and an equipment and material price curve is constructed based on the effective price group of power grid equipment and materials;

[0052] Complete online identification of the fluctuation status of power grid equipment and material prices within a preset period based on the equipment and material price curve;

[0053] Based on the fluctuation status of the prices of power grid equipment and materials within the preset period, the price forecast of the prices of power grid equipment and materials within the next fluctuation period is adjusted.

[0054] Example 2

[0055] The preset fluctuation period is set by the staff based on experience, including but not limited to 1 month, 3 months or 6 months;

[0056] Power grid equipment materials include but are not limited to copper, aluminum, steel core aluminum stranded wire and cable materials;

[0057] The price of power grid equipment materials corresponding to each time node is recorded as Vi, i is the number of time nodes, i = 1, 2, ..., n;

[0058] Mark and sort the prices of power grid equipment and materials corresponding to all time nodes within the preset fluctuation period to obtain power grid equipment and material price groups V1, V2, V3, ..., Vi of all time nodes within the preset fluctuation period;

[0059] Process the prices within the price group of power grid equipment and materials;

[0060] According to the formula The standard deviation value Va of the power grid equipment material price group is calculated, wherein Vp is the average value of the power grid equipment material price group V1, V2, V3, ...., Vn;

[0061] Identify the standard deviation Va of the power grid equipment material price group, specifically:

[0062] The standard deviation threshold of the power grid equipment material price group is preset to be Vy;

[0063] If the standard deviation value Va of the power grid equipment and material price group is greater than or equal to the standard deviation threshold value Vy of the power grid equipment and material price group, the maximum value and / or minimum value in the power grid equipment and material price group data is deleted, and the standard deviation value Va of the power grid equipment and material price group data is calculated again until Va is less than the standard deviation threshold value Vy of the power grid equipment and material price group, and the remaining power grid equipment and material prices in the power grid equipment and material price group are marked and sorted to obtain a valid power grid equipment and material price group.

[0064] Based on the effective price group of power grid equipment and materials, the power grid equipment and material prices corresponding to the effective price group of power grid equipment and materials are matched one by one with the time nodes within the preset fluctuation period;

[0065] And within the preset fluctuation period, the effective price group of power grid equipment and materials is processed. The specific process is as follows:

[0066] A plane coordinate system is established with time as the X-axis and the price of power grid equipment materials as the Y-axis;

[0067] The price of power grid equipment and materials corresponding to each time node of the effective price group of power grid equipment and materials within the preset fluctuation period is obtained, and an equipment and material price curve is constructed in the plane coordinate system;

[0068] Obtain the rated range value of the price of power grid equipment and materials, and record the rated upper limit value of the price of power grid equipment and materials as the upper limit value of the price of equipment and materials;

[0069] The rated lower limit of the price of power grid equipment and materials is recorded as the lower limit of the price of equipment and materials;

[0070] Draw a horizontal line parallel to the X-axis in the plane coordinate system at the upper limit of the equipment and material price, and record it as the first limit of the equipment and material price;

[0071] Draw a horizontal line parallel to the X-axis in the plane coordinate system at the lower limit of the equipment and material prices, and record it as the second limit of the equipment and material prices;

[0072] Analyze the equipment and material price curve, the first equipment and material price boundary, and the second equipment and material price boundary;

[0073] The area where the equipment and material price curve is located above the first equipment and material price boundary is recorded as the upper floating area;

[0074] The area where the equipment and material price curve is below the second boundary line of the equipment and material price is recorded as the lower floating area;

[0075] The upper floating area and the lower floating area are recorded as floating areas;

[0076] The area of ​​the equipment and material price curve between the first equipment and material price boundary and the second equipment and material price boundary is recorded as a non-floating area;

[0077] Process the floating area and the non-floating area to obtain the area values ​​of the floating area and the non-floating area;

[0078] The area value of the floating area is recorded as the floating area value;

[0079] The area value of the non-floating area is recorded as the non-floating area value;

[0080] Calculate the ratio of the non-floating area value to the floating area value to obtain the floating amplitude value;

[0081] Get the time length value of the floating area, and record it as the time length value of the floating area;

[0082] Get the time length value of the non-floating area, and record it as the time length value of the non-floating area;

[0083] The floating time value is obtained by calculating the ratio of the time length value of the floating area to the time length value of the non-floating area;

[0084] Obtain the maximum price of power grid equipment and materials in the upper floating area and the minimum price of power grid equipment and materials in the lower floating area, calculate the difference between the maximum price of power grid equipment and materials and the minimum price of power grid equipment and materials, and obtain the floating difference limit value of the floating area;

[0085] The floating difference limit value of the floating area is calculated by ratio with the rated middle value of the price of the power grid equipment and materials, so as to obtain the floating difference limit ratio of the floating area;

[0086] Among them, the rated median value of the power grid equipment and material price is the median value of the rated range of equipment and material prices;

[0087] The floating amplitude value is recorded as Ff;

[0088] The floating time occupied value is recorded as Ft;

[0089] The floating difference limit ratio is recorded as Fc;

[0090] By formula The price fluctuation behavior value Fi of power grid equipment materials within the preset fluctuation period is calculated, wherein a1 and a2 are both preset proportional coefficients, and a1>0, a2>0.

[0091] comparing the power grid equipment material price fluctuation behavior value with the power grid equipment material price fluctuation behavior threshold;

[0092] If the power grid equipment and material price fluctuation behavior value is greater than or equal to the power grid equipment and material price fluctuation behavior threshold, it means that within the preset fluctuation period, the power grid equipment and material price is not within the rated range of the power grid equipment and material price for a long time and exceeds the range by a large amount, and a power grid equipment and material price fluctuation abnormal signal is generated;

[0093] If the power grid equipment and material price fluctuation behavior value is less than the power grid equipment and material price fluctuation behavior threshold, it means that within the preset fluctuation period, the power grid equipment and material price is in the power grid equipment and material price range for a short time and exceeds the range for a small time, thereby generating a normal power grid equipment and material price fluctuation signal.

[0094] Obtain the area value of the upper floating area and the area value of the lower floating area, perform difference calculation on the area value of the upper floating area and the area value of the lower floating area, and obtain the dynamic trend value of the floating area;

[0095] Calculate the ratio of the dynamic trend value of the floating area to the non-floating area value to obtain the price dynamic trend ratio;

[0096] Based on the largest price of power grid equipment and materials in the upper floating area and the smallest price of power grid equipment and materials in the lower floating area, complete the forecast adjustment of power grid equipment and material prices in the next fluctuation cycle;

[0097] The maximum price of grid equipment and materials in the upper floating area is recorded as Vmax;

[0098] Then in the next fluctuation cycle, the maximum price of power grid equipment materials is V1max=Vmax*1+Vqs), where Vqs is the price dynamic trend ratio;

[0099] The minimum price of power grid equipment and materials in the lower floating area is recorded as Vmin;

[0100] Then in the next fluctuation cycle, the lowest price of power grid equipment materials is V1min=Vmax*1-Vqs), where Vqs is the price dynamic trend ratio.

[0101] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for predicting and dynamically adjusting the price of power grid equipment materials, characterized in that: The following steps are involved: Preset a fluctuation period, divide the preset fluctuation period into several time nodes, and obtain the price of power grid equipment and materials corresponding to each time node; Screen and process the prices of power grid equipment and materials corresponding to each time node to obtain a valid price group of power grid equipment and materials; Based on the effective price group of power grid equipment and materials, a plane coordinate system is established with time as the X-axis and the price of power grid equipment and materials as the Y-axis within a preset fluctuation period, and an equipment and material price curve is constructed based on the effective price group of power grid equipment and materials; Complete online identification of the fluctuation status of power grid equipment and material prices within a preset period based on the equipment and material price curve; And based on the fluctuation status of power grid equipment and material prices within a preset period, the price forecast of power grid equipment and material prices in the next fluctuation period is adjusted.

2. A method for predicting and dynamically adjusting power grid equipment material prices according to claim 1, characterized in that: The price of power grid equipment materials corresponding to each time node is recorded as Vi, i is the number of time nodes, i = 1, 2, ..., n; Obtain the price groups V1, V2, V3, ..., Vi of power grid equipment materials at all time nodes within the preset fluctuation period; According to the formula The standard deviation value Va of the power grid equipment material price group is calculated, where Vp is the average value of the power grid equipment material price group V1, V2, V3, ..., Vn.

3. A method for predicting and dynamically adjusting the price of power grid equipment materials according to claim 2, characterized in that: The standard deviation threshold of the power grid equipment material price group is preset to Vy; If the standard deviation value Va of the power grid equipment and material price group is greater than or equal to the standard deviation threshold value Vy of the power grid equipment and material price group, the maximum value and / or minimum value in the power grid equipment and material price group data is deleted, and the standard deviation value Va of the power grid equipment and material price group data is calculated again until Va is less than the standard deviation threshold value Vy of the power grid equipment and material price group, and the remaining power grid equipment and material prices in the power grid equipment and material price group are marked and sorted to obtain a valid power grid equipment and material price group.

4. A method for predicting and dynamically adjusting power grid equipment material prices according to claim 1, characterized in that: Based on the effective price group of power grid equipment and materials, the price of power grid equipment and materials corresponding to each time node of the effective price group of power grid equipment and materials within the preset fluctuation period is obtained, and an equipment and material price curve is constructed in the plane coordinate system; Analyze the equipment and material price curve, the first equipment and material price boundary, and the second equipment and material price boundary; The area where the equipment and material price curve is located above the first equipment and material price boundary is recorded as the upper floating area; The area where the equipment and material price curve is below the second boundary line of the equipment and material price is recorded as the lower floating area; The upper floating area and the lower floating area are recorded as floating areas; The area where the equipment and material price curve is located between the first equipment and material price boundary line and the second equipment and material price boundary line is recorded as a non-floating area.

5. A method for predicting and dynamically adjusting the price of power grid equipment materials according to claim 4, characterized in that: Process the floating area and the non-floating area to obtain the floating amplitude value, floating time value and floating difference limit ratio; The floating amplitude value is recorded as Ff; The floating time occupied value is recorded as Ft; The floating difference limit ratio is recorded as Fc; By formula The price fluctuation behavior value Fi of power grid equipment materials within the preset fluctuation period is calculated, where a1 and a2 are both preset proportional coefficients.

6. A method for predicting and dynamically adjusting power grid equipment material prices according to claim 5, characterized in that: If the power grid equipment material price fluctuation behavior value is greater than or equal to the power grid equipment material price fluctuation behavior threshold, a power grid equipment material price fluctuation abnormal signal is generated; If the power grid equipment material price fluctuation behavior value is less than the power grid equipment material price fluctuation behavior threshold, a power grid equipment material price fluctuation normal signal is generated.

7. A method for predicting and dynamically adjusting the price of power grid equipment materials according to claim 5, characterized in that: Get the area values ​​of the floating area and the non-floating area. The floating amplitude value is the ratio of the non-floating area value to the floating area value. Get the time length value of the floating area and the time length value of the non-floating area; The floating time duration value is the ratio of the time length value of the floating area to the time length value of the non-floating area.

8. A method for predicting and dynamically adjusting power grid equipment material prices according to claim 5, characterized in that: Obtain the maximum price of power grid equipment and materials in the upper floating area and the minimum price of power grid equipment and materials in the lower floating area, calculate the difference between the maximum price of power grid equipment and materials and the minimum price of power grid equipment and materials, and obtain the floating difference limit value of the floating area; The floating difference limit value of the floating area is calculated by ratio with the rated middle value of the power grid equipment material price to obtain the floating difference limit ratio of the floating area.

9. A method for predicting and dynamically adjusting the price of power grid equipment materials according to claim 4, characterized in that: Based on the largest price of power grid equipment and materials in the upper floating area and the smallest price of power grid equipment and materials in the lower floating area, complete the forecast adjustment of power grid equipment and material prices in the next fluctuation cycle; The maximum price of grid equipment and materials in the upper floating area is recorded as Vmax; Then in the next fluctuation cycle, the maximum price of power grid equipment materials is V1max=Vmax*1+Vqs), where Vqs is the price dynamic trend ratio; The minimum price of power grid equipment and materials in the lower floating area is recorded as Vmin; Then in the next fluctuation cycle, the lowest price of power grid equipment materials is V1min=Vmax*1-Vqs), where Vqs is the price dynamic trend ratio.

10. A method for predicting and dynamically adjusting power grid equipment material prices according to claim 9, characterized in that: Obtain the area value of the upper floating area and the area value of the lower floating area, perform difference calculation on the area value of the upper floating area and the area value of the lower floating area, and obtain the dynamic trend value of the floating area; The dynamic trend value of the floating area is calculated by ratioing it with the non-floating area value to obtain the price dynamic trend ratio.

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