Novel power distribution system typical equipment price prediction model system and method

Abstract

The invention provides a novel power distribution system typical equipment price prediction model system and method, and relates to the technical field of novel power distribution system typical equipment price prediction. The method comprises the steps of system feature analysis, comparative analysis, framework formation, equipment price analysis and price prediction, and the system feature analysis is to analyze each composition feature of the novel power distribution system, so that subsequent comparison is facilitated; the contrastive analysis is to compare and analyze differences between the novel power distribution system equipment and the traditional power distribution system equipment; the formation of the architecture is to construct a more efficient analysis architecture from analysis commodities. By providing a novel power distribution system typical equipment price prediction method, power distribution network equipment price prediction can be carried out by using the result, and the result is issued by a company regularly, so that a price basis is provided for construction cost file compilation such as power distribution network estimation, budget and the like, and the power distribution network project price listing accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of price prediction of typical equipment in a new power distribution system, and in particular to a model system and method for price prediction of typical equipment in a new power distribution system. Background Art

[0002] The core of the construction of a new energy system is to promote the leapfrog development of new energy and build a new power system with new energy as the main body and flexible resources as the support. With the acceleration of the construction of the new power system, a high proportion of distributed new energy will achieve large-scale access, accelerated electricity substitution, enhanced interaction among multiple types of loads, the rise of AC / DC hybrid distribution networks, and the rapid development of power electronic equipment, which will fundamentally change the components, network topology, and operation and production modes of the distribution system, and promote the transformation of the traditional distribution network from one-way supply of source and load to "source-load interaction", and a new distribution system will come into being. The new distribution system will be composed of a variety of "source-grid-load-storage" resources such as distributed energy, new loads, and distributed energy storage, integrating new equipment and advanced sensing technology, information and communication technology, etc., to form a regional energy optimization and coordination platform, a resource interaction platform, and a clean energy consumption platform, effectively promoting the coordinated interaction of "source-grid-load-storage".

[0003] In today's era, the complex interweaving of various factors such as economic globalization and business diversification has exacerbated the uncertainty of electricity supply and demand and raw material price fluctuations, posing challenges to the security and stability of the power supply chain. The agreement inventory model adopted by the traditional distribution network engineering material supply management has problems such as the difficulty in accurately predicting the scale of material procurement and the quantity of reserves, the difficulty in matching material procurement with engineering construction needs, and the lack of equipment price basis. In the face of increasing risks in the security and supply of the power supply chain and the differentiated characteristics of the construction needs of new distribution systems, it is urgent to optimize the pre-purchase, pre-storage and dynamic allocation mechanism of traditional distribution projects, strengthen the accurate prediction of the necessary demand and reasonable reserve of various distribution materials, optimize the procurement and reserve strategy of new distribution systems, and promote cost reduction and efficiency improvement and construction efficiency improvement of new distribution systems.

[0004] The prices of equipment and materials for the existing new distribution network rely on inquiries from the compiling units. Subjective factors have a great influence on the prices. The prices of equipment and materials listed in the project budget stage deviate greatly from the actual winning bid prices. There is a lack of supporting basis for compiling the highest bid price limit in the bidding stage, which increases the difficulty of cost control and reduces the investment benefits of the project. The price data of equipment and materials continues to increase. Under the circumstances of changes in market supply and demand and fluctuations in raw material prices, the analysis of the reasons for fluctuations in some price data is more complicated and needs to be comprehensively analyzed in combination with the actual bidding situation of the project. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the shortcomings of the prior art, the present invention provides a price prediction model system and method for typical equipment of a new power distribution system, which solves the problems of defining the research scope of typical equipment of a new power distribution system, clarifying the composition of raw materials of the equipment of a new power distribution system, analyzing the price formation mechanism of the equipment of a new power distribution system based on factor input, and constructing a price prediction model for typical equipment of a new power distribution system.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a price prediction model system and method for typical equipment of a new power distribution system, including analyzing system characteristics, comparative analysis, forming an architecture, equipment price analysis and price prediction, characterized in that: the analysis of system characteristics is to analyze the characteristics of each component of the new power distribution system, so as to facilitate subsequent comparison; the comparative analysis is to compare and analyze the differences between the new power distribution system equipment and the traditional power distribution system equipment; the formation of the architecture is to construct a more efficient analysis architecture from the analysis of commodities; the equipment price analysis is to establish a reasonable price formation mechanism through the price analysis of raw materials; the price prediction is to analyze and predict the equipment prices of the new power distribution system by visually modeling through programming.

[0009] The analysis system characteristics are analyzed and refined from the aspects of power supply structure, load characteristics, grid form, operation characteristics, etc. through literature review, field investigation and daily work experience. The composition characteristics of the new distribution system are analyzed and refined.

[0010] The comparative analysis is based on the characteristics of the new distribution system, such as clean, low-carbon, safe and controllable. It compares the differences between the new distribution equipment and the traditional distribution system equipment, further selects typical equipment from different perspectives such as equipment usage frequency and functional attributes, and defines the research scope of typical equipment of the new distribution system from many equipment types.

[0011] The framework is formed based on theoretical methods such as the labor theory of value and the equilibrium price theory to form a general commodity price analysis framework for subsequent rapid analysis.

[0012] The equipment price analysis is to clarify the specific contents of the raw material composition of the new distribution system equipment and the human, financial and material investment in research and development, combine the main characteristics of the typical equipment of the new distribution system, analyze the specific process and mechanism of the price formation of the new distribution system equipment, and form a scientific and reasonable price formation mechanism.

[0013] The price forecast is to combine the price formation mechanism of different typical equipment, consider the price fluctuation characteristics under the change of market factors, conduct price characteristic analysis, use Python programming for visual analysis, and use time series, neural network, deep learning and other forecasting methods to model the price forecast of typical equipment in new power distribution system. Combined with the price characteristics of different equipment, the forecasting method is selected in a targeted manner to improve the applicability and accuracy of the forecasting model.

[0014] A price prediction method proposed based on a new price prediction model system for typical equipment in a power distribution system includes the following steps:

[0015] Step 1: Through literature review, field investigation and daily work experience, starting from the power supply structure, load characteristics, grid form, operation characteristics and other aspects, analyze and refine the composition characteristics of the new distribution system, and then compare the differences between the new distribution equipment and the traditional distribution system equipment. Further select typical equipment from different perspectives such as equipment usage frequency and functional attributes, and define the research scope of typical equipment of the new distribution system from many equipment types.

[0016] Step 2: Based on the labor value theory and equilibrium price theory, a general commodity price analysis framework is formed, and then the specific contents of the raw material composition and R&D human, financial and material input of the new distribution system equipment are clarified. Combined with the main characteristics of typical equipment of the new distribution system, the specific process and mechanism of price formation of the new distribution system equipment is analyzed to form a scientific and reasonable price formation mechanism.

[0017] Step 3: Combine the price formation mechanism of different typical equipment, consider the price fluctuation characteristics under the change of market factors, conduct price characteristic analysis, use Python programming for visual analysis, and use time series, neural networks and deep learning prediction methods to carry out price prediction modeling of typical equipment in new distribution systems. Then, combine the price characteristics of different equipment to select prediction methods in a targeted manner to improve the applicability and accuracy of the prediction model.

[0018] (III) Beneficial effects

[0019] The present invention provides a new type of power distribution system typical equipment price prediction model system and method. It has the following beneficial effects:

[0020] 1. By proposing a price prediction method for typical equipment of the new distribution system, the results can be used to carry out price prediction of distribution network equipment, which will be published regularly by the company to provide a price basis for the preparation of cost documents such as distribution network estimation, budget estimates, and budgets, thereby improving the accuracy of price calculation of distribution network projects.

[0021] 2. The existing equipment and material price data are constantly increasing. Under the circumstances of changes in market supply and demand and fluctuations in raw material prices, the analysis of the causes of fluctuations in some price data is more complicated. The efficiency of the analysis of the causes of price data fluctuations is improved through the new distribution system typical equipment price forecasting method. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of a flow chart of a novel price prediction model system and method for typical equipment in a power distribution system proposed by the present invention; DETAILED DESCRIPTION

[0023] 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.

[0024] like Figure 1 As shown, an embodiment of the present invention provides a price prediction model system and method for typical equipment of a new power distribution system, including analyzing system characteristics, comparative analysis, forming an architecture, equipment price analysis and price prediction. Analyzing system characteristics is to analyze the characteristics of each component of the new power distribution system to facilitate subsequent comparison; comparative analysis is to compare and analyze the differences between the new power distribution system equipment and the traditional power distribution system equipment; forming an architecture is to construct a more efficient analysis architecture from the analysis of commodities; equipment price analysis is to establish a reasonable price formation mechanism through price analysis of raw materials; price prediction is to analyze and predict the equipment prices of the new power distribution system by visually modeling them through programming.

[0025] The system characteristics are analyzed by literature review, field investigation and daily work experience, starting from the power supply structure, load characteristics, grid form, operation characteristics and other aspects, to analyze and refine the composition characteristics of the new distribution system.

[0026] The comparative analysis is based on the characteristics of the new distribution system, such as clean, low-carbon, safe and controllable. It compares the differences between the new distribution equipment and the traditional distribution system equipment, and further selects typical equipment from different perspectives such as equipment usage frequency and functional attributes. From the many equipment types, the research scope of typical equipment of the new distribution system is defined.

[0027] The framework is formed based on theoretical methods such as the labor theory of value and the equilibrium price theory, forming a general commodity price analysis framework to facilitate subsequent rapid analysis.

[0028] Equipment price analysis is to clarify the specific contents such as the raw material composition of new distribution system equipment and the investment of human, financial and material resources in research and development, combine the main characteristics of typical equipment of new distribution system, analyze the specific process and mechanism of price formation of new distribution system equipment, and form a scientific and reasonable price formation mechanism.

[0029] Price forecasting is to combine the price formation mechanism of different typical equipment, consider the price fluctuation characteristics under the change of market factors, conduct price characteristic analysis, use Python programming for visual analysis, and use time series, neural network, deep learning and other forecasting methods to model the price forecast of typical equipment in new power distribution systems. Combined with the price characteristics of different equipment, the forecasting method is selected in a targeted manner to improve the applicability and accuracy of the forecasting model.

[0030] A price prediction method proposed based on a new price prediction model system for typical equipment in a power distribution system includes the following steps:

[0031] Step 1: Through literature review, field investigation and daily work experience, starting from the power supply structure, load characteristics, grid form, operation characteristics and other aspects, analyze and refine the composition characteristics of the new distribution system, and then compare the differences between the new distribution equipment and the traditional distribution system equipment. Further select typical equipment from different perspectives such as equipment usage frequency and functional attributes, and define the research scope of typical equipment of the new distribution system from many equipment types.

[0032] Step 2: Based on the labor value theory and equilibrium price theory, a general commodity price analysis framework is formed, and then the specific contents of the raw material composition and R&D human, financial and material input of the new distribution system equipment are clarified. Combined with the main characteristics of typical equipment of the new distribution system, the specific process and mechanism of price formation of the new distribution system equipment is analyzed to form a scientific and reasonable price formation mechanism.

[0033] Step 3: Combine the price formation mechanism of different typical equipment, consider the price fluctuation characteristics under the change of market factors, conduct price characteristic analysis, use Python programming for visual analysis, and use time series, neural networks and deep learning prediction methods to carry out price prediction modeling of typical equipment in new distribution systems. Then, combine the price characteristics of different equipment to select prediction methods in a targeted manner to improve the applicability and accuracy of the prediction model.

[0034] Summarize the characteristics of new distribution systems, comprehensively consider key points such as equipment applicability and functional requirements, and define the research scope of typical equipment of new distribution systems; form a price formation mechanism for typical equipment based on factors such as raw material price changes, human, financial and material inputs in equipment manufacturing, market supply and demand, and equilibrium prices; combine different equipment types and technical characteristics, and construct a targeted price prediction model for typical equipment of new distribution systems based on the price formation mechanism.

[0035] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A new type of typical equipment price prediction model system for power distribution system, including analyzing system characteristics, comparative analysis, forming architecture, equipment price analysis and price prediction, characterized by: The analysis system features are to analyze the characteristics of each component of the new distribution system to facilitate subsequent comparison; the comparative analysis is to compare and analyze the differences between the new distribution system equipment and the traditional distribution system equipment; the formation architecture is to build a more efficient analysis architecture from the analysis of commodities; the equipment price analysis is to establish a reasonable price formation mechanism through price analysis of raw materials; the price prediction is to analyze and predict the equipment price of the new distribution system by visually modeling it through programming.

2. According to claim 1, a new type of typical equipment price prediction model system for power distribution system is characterized by: The analysis system characteristics are analyzed and refined from the aspects of power supply structure, load characteristics, grid form, operation characteristics, etc. through literature review, field investigation and daily work experience. The composition characteristics of the new distribution system are analyzed and refined.

3. According to claim 1, a new type of typical equipment price prediction model system for power distribution system is characterized by: The comparative analysis is based on the characteristics of the new distribution system, such as clean, low-carbon, safe and controllable. It compares the differences between the new distribution equipment and the traditional distribution system equipment, further selects typical equipment from different perspectives such as equipment usage frequency and functional attributes, and defines the research scope of typical equipment of the new distribution system from many equipment types.

4. The price prediction model system for typical equipment in a new type of power distribution system according to claim 1 is characterized by: The framework is formed based on theoretical methods such as the labor theory of value and the equilibrium price theory to form a general commodity price analysis framework for subsequent rapid analysis.

5. The price prediction model system for typical equipment in a new type of power distribution system according to claim 1 is characterized by: The equipment price analysis is to clarify the specific contents of the raw material composition of the new distribution system equipment and the human, financial and material investment in research and development, combine the main characteristics of the typical equipment of the new distribution system, analyze the specific process and mechanism of the price formation of the new distribution system equipment, and form a scientific and reasonable price formation mechanism.

6. A new type of typical equipment price prediction model system for power distribution system according to claim 1, characterized in that: The price forecast is to combine the price formation mechanism of different typical equipment, consider the price fluctuation characteristics under the change of market factors, conduct price characteristic analysis, use Python programming for visual analysis, and use time series, neural network, deep learning and other forecasting methods to model the price forecast of typical equipment in new power distribution system. Combined with the price characteristics of different equipment, the forecasting method is selected in a targeted manner to improve the applicability and accuracy of the forecasting model.

7. A price prediction method proposed by a new type of typical equipment price prediction model system for power distribution system according to any one of claims 1 to 6, characterized in that: The following steps are involved: Step 1: Through literature review, field investigation and daily work experience, starting from the power supply structure, load characteristics, grid form, operation characteristics and other aspects, analyze and refine the composition characteristics of the new distribution system, and then compare the differences between the new distribution equipment and the traditional distribution system equipment. Further select typical equipment from different perspectives such as equipment usage frequency and functional attributes, and define the research scope of typical equipment of the new distribution system from many equipment types. Step 2: Based on the labor value theory and equilibrium price theory, a general commodity price analysis framework is formed, and then the specific contents of the raw material composition and R&D human, financial and material input of the new distribution system equipment are clarified. Combined with the main characteristics of typical equipment of the new distribution system, the specific process and mechanism of price formation of the new distribution system equipment is analyzed to form a scientific and reasonable price formation mechanism. Step 3: Combine the price formation mechanism of different typical equipment, consider the price fluctuation characteristics under the change of market factors, conduct price characteristic analysis, use Python programming for visual analysis, and use time series, neural networks and deep learning prediction methods to carry out price prediction modeling of typical equipment in new distribution systems. Then, combine the price characteristics of different equipment to select prediction methods in a targeted manner to improve the applicability and accuracy of the prediction model.

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