KR-20260063518-A - Apparatus and Method for Development of Energy Storage Technology Performance and Cost Analysis Platform

KR20260063518AKR 20260063518 AKR20260063518 AKR 20260063518AKR-20260063518-A

Abstract

The various embodiments of this post relate to a method for configuring a platform for analyzing energy storage technology characteristics and cost data, comprising a data collection unit for collecting technology characteristics and cost data of a plurality of energy storage technologies, a data reconstruction unit for reconstructing data collected by the data collection unit, and a data visualization unit for displaying energy storage technologies and costs on an output screen in various ways based on the data reconstructed by the data reconstruction unit, wherein the data visualization unit displays energy storage technologies and costs on the output screen through a cloud-based web environment.

Inventors

이지현

Assignees

한국전력공사

Dates

Publication Date: 20260507
Application Date: 20241030

Claims (20)

A data collection unit that collects technical characteristics and cost data of multiple energy storage technologies; A data reconstruction unit that reconstructs data collected by the above data collection unit; and The above data reconstruction unit includes a data visualization unit that displays energy storage technology and costs on an output screen in various ways based on the reconstructed data. The above data visualization unit displays energy storage technology and costs on the output screen through a cloud-based web environment, Energy storage technology and cost data analysis platform.
In paragraph 1, The above data collection unit collects technical characteristics and cost data of energy storage technology based on literature data presented by specialized institutions, Energy storage technology and cost data analysis platform.
In paragraph 1, The above-mentioned data collection unit collects information on all energy storage technologies and collects technology characteristic and cost data by considering the characteristics of energy storage technologies according to the technology field, Energy storage technology and cost data analysis platform.
In paragraph 1, The above data reconstruction unit identifies the format and technical field of the data collected by the data collection unit according to the source institution, identifies common data items among the data collected by the data collection unit, and creates a new data structure by setting categories according to each variable or attribute within the dataset. Energy storage technology and cost data analysis platform.
In paragraph 1, The above data visualization unit classifies the data to be displayed on the output screen into dimensions and measures to derive data characteristics and calculation formulas, and creates and visualizes the data source using a web data connector. Energy storage technology and cost data analysis platform.
In paragraph 1, The above data visualization unit represents one or more pieces of information among the prediction of medium-to-long-term costs by energy storage technology, medium-to-long-term performance prediction by energy storage technology, comparison of actual project results and predicted data, and investment costs of energy storage technology by facility capacity. Energy storage technology and cost data analysis platform.
In paragraph 6, The above data visualization unit sets one or more parameters for predicting medium-to-long-term costs by energy storage technology, among energy storage technology, forecasting agency, forecast value range, forecast time period, and end time period. Energy storage technology and cost data analysis platform.
In paragraph 6, The above data visualization unit sets parameters for predicting mid-to-long-term performance by energy storage technology as energy storage technology and technology performance characteristics, Energy storage technology and cost data analysis platform.
In paragraph 6, The above data visualization unit sets parameters for comparing the actual project results and predicted data as the range of energy storage technology and technology performance characteristics, Energy storage technology and cost data analysis platform.
In paragraph 6, The above data visualization unit sets the parameters for predicting the investment cost of energy storage technology by facility capacity as the prediction timing of the energy storage technology, characteristics of the technology, discharge duration, and the capacity of the energy storage plant, Energy storage technology and cost data analysis platform.
In the analysis method of an energy storage technology and cost data analysis platform, A step of collecting technical characteristics and cost data of multiple energy storage technologies; A step of reconstructing the collected data for visualization; and A step comprising expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the reconstructed data above, Analysis method.
In Article 11, The step of collecting technical characteristics and cost data of the plurality of energy storage technologies mentioned above is, A step including collecting technical characteristics and cost data of energy storage technology based on literature data presented by specialized institutions, Analysis method.
In Paragraph 11, The step of collecting technical characteristics and cost data of the plurality of energy storage technologies mentioned above is, A step comprising collecting information on all energy storage technologies and collecting technology characteristic and cost data by considering the characteristics of energy storage technologies according to the technology field, Analysis method.
In Paragraph 11, The step of reconstructing the collected data for visualization is, A method comprising the step of identifying the format and technical field of the source institution of the above data, identifying common data items among the above data, and creating a new data structure by setting categories according to each variable or attribute within the dataset. Analysis method.
In Paragraph 11, The step of expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the above-reconstructed data is, The method includes the step of classifying the data to be displayed on the output screen into dimensions and measures to derive data characteristics and formulas, and creating and visualizing the data source using Tableau. Analysis method.
In Paragraph 11, The step of expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the above-reconstructed data is, A step comprising expressing one or more pieces of information, such as forecasting of medium-to-long-term costs by energy storage technology, forecasting of medium-to-long-term performance by energy storage technology, comparison of actual project results with forecast data, and investment costs of energy storage technology by facility capacity. Analysis method.
In Paragraph 16, The step of expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the above-reconstructed data is, The method further includes the step of setting parameters for predicting medium-to-long-term costs by the above energy storage technology, one or more of the following: energy storage technology, forecasting agency, range of predicted values, time of prediction, and end date. Analysis method.
In Paragraph 16, The step of expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the above-reconstructed data is, A method further comprising the step of setting parameters for mid-to-long-term performance prediction for each of the above energy storage technologies as energy storage technologies and technology performance characteristics. Analysis method.
In Paragraph 16, The step of expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the above-reconstructed data is, A method further comprising the step of setting parameters for comparing the actual project results and predicted data as a range of energy storage technology and technical performance characteristics. Analysis method.
In Paragraph 16, The step of expressing energy storage technology and costs on an output screen in various ways through a cloud-based web environment based on the above-reconstructed data is, The method further includes the step of setting parameters for predicting investment costs of energy storage technology by facility capacity as the prediction timing of the energy storage technology, characteristics of the technology, discharge duration, and capacity of the energy storage plant. Analysis method.

Description

Apparatus and Method for Development of Energy Storage Technology Performance and Cost Analysis Platform The various embodiments of this post relate to methods for configuring a platform for analyzing energy storage technology characteristics and cost data. As the global market size for energy storage technology has recently grown rapidly, there is a need to establish a platform for analyzing the characteristics and cost data of various energy storage technologies to forecast mid-to-long-term energy market trends and predict costs. The importance of the platform for analyzing the characteristics and cost data of energy storage technologies is emphasized, as it can be utilized in various fields, such as establishing national power grid investment plans for renewable energy-energy storage integration, presenting energy storage technology specifications to companies, and improving the performance of existing technologies. FIG. 1 is a block diagram briefly illustrating the components of an energy storage technology and cost data analysis platform according to one embodiment of the present invention. FIG. 2 is a diagram illustrating the structure of energy storage technology and cost data collected by a data collection unit according to one embodiment. Figure 3 is a flowchart illustrating the process of processing data in the data reconstruction unit. Figure 4 is a diagram showing the process of visualizing data in the data visualization unit. The advantages and features of this post, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, this post is not limited to the embodiments described below but may be implemented in various different forms; these embodiments are provided merely to make this post complete and to fully inform those skilled in the art of the scope of this post, and this post is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components. When one component is referred to as being "connected to" or "coupled to" another component, it includes cases where it is directly connected or coupled to the other component, or cases where another component is interposed. Conversely, when one component is referred to as being "directly connected to" or "directly coupled to" another component, it indicates that no other component is interposed. "And/or" includes each of the mentioned items and all combinations of one or more of them. The terms used herein are for describing the embodiments and are not intended to limit this post. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used herein, "comprises" and/or "comprising" do not exclude the presence or addition of one or more other components, steps, actions, and/or elements to the mentioned components, steps, actions, and/or elements. Although terms such as "first," "second," etc., are used to describe various components, it goes without saying that these components are not limited by these terms. These terms are used merely to distinguish one component from another. Therefore, it is obvious that the first component mentioned below may be the second component within the technical scope of this post. Unless otherwise defined, all terms used in this specification (including technical and scientific terms) may be used in a meaning that is commonly understood by those skilled in the art to which this post belongs. Furthermore, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise. The terms 'part' or 'module' as used in this embodiment refer to software or hardware components such as FPGAs or ASICs, and the 'part' or 'module' performs certain roles. However, the meaning of 'part' or 'module' is not limited to software or hardware. The 'part' or 'module' may be configured to reside in an addressable storage medium or configured to run one or more processors. Thus, as an example, the 'part' or 'module' may include components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The components and functions provided within the 'part' or 'module' may be combined into a smaller number of components and 'part' or 'module', or further separated into additional components and 'part' or 'module'. Steps of the method or algorithm described in connection with some embodiments of this post may be directly implemented in hardware, software modules, or a combination of both, executed by a processor. Software modules may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory,