KR-20260067074-A - METHOD FOR SYSTEMATIC ANALYSIS AND OPTIMIZATION OF NON-LINEAR PROGRAMMING BASED ON PARALLEL PROCESSING

KR20260067074AKR 20260067074 AKR20260067074 AKR 20260067074AKR-20260067074-A

Abstract

An apparatus for system analysis and optimization of a parallel processing-based nonlinear programming method according to one embodiment includes: an optimal solution calculation unit that calculates an optimal solution using parallel processing; and a control management unit that controls or manages a power-related system based on the optimal solution, wherein the optimal solution calculation unit can calculate an optimal solution based on at least a part of a convex optimization algorithm, a KKT (Karush-Kuhn-Tucker) algorithm, a linear optimization algorithm, or a simplex method.

Inventors

홍상범
김준호
고상원
최준호

Assignees

한전케이디엔주식회사
전남대학교산학협력단

Dates

Publication Date: 20260512
Application Date: 20241105

Claims (14)

In an apparatus for system analysis and optimization of parallel processing-based nonlinear programming, Optimum solution calculation unit that calculates an optimal solution using parallel processing; and A control management unit that controls or manages power-related systems based on the above optimal solution. Includes, The above optimal solution calculation unit is, Calculating the optimal solution based on at least a part of the convex optimization algorithm, the KKT (Karush-Kuhn-Tucker) algorithm, the linear optimization algorithm, or the simplex method device.
In paragraph 1, The above optimal solution calculation unit is, Calculate an unconstrained optimal solution based on parallel processing with convex optimization applied, The power system generation cost function is calculated based on a quadratic function of generator output. device.
In paragraph 2, The above optimal solution calculation unit is, The objective function is the “problem of minimizing the output cost of all generators,” and the equality constraint is defined as “the sum of the outputs of all generators is equal to the load.” device.
In paragraph 1, The above optimal solution calculation unit is, Calculate a constrained optimal solution based on parallel processing with convex optimization applied, Redefining the optimization problem by excluding the constrained generator device.
In paragraph 4, The above optimal solution calculation unit is, Generators that fall outside the range regarding the minimum or maximum limit are excluded from the optimization problem by setting constraint values. device.
In paragraph 1, The above optimal solution calculation unit is, Calculate the optimal solution for inequality constraints based on parallel processing applying convex optimization and the simplex method, Redefining the optimization problem by including inequality constraints on some generator groups device.
In paragraph 6, The above optimal solution calculation unit is, Calculating the optimal solution based on the Lagrangian function and differentiation device.
In a method for system analysis and optimization of parallel processing-based nonlinear programming, A step of calculating the optimal solution using parallel processing; and A step of controlling or managing a power-related system based on the above optimal solution. Includes, The above calculation step is, Calculating the optimal solution based on at least a part of the convex optimization algorithm, the KKT (Karush-Kuhn-Tucker) algorithm, the linear optimization algorithm, or the simplex method method.
In paragraph 8, The above calculation step is, Step of calculating an unconstrained optimal solution based on parallel processing with convex optimization applied Including more, The power system generation cost function is calculated based on a quadratic function of generator output. method.
In Paragraph 9, The step of calculating the above-mentioned unconstrained optimal solution is, Step where the objective function becomes the “problem of minimizing the output costs of all generators” and the equality constraint is defined as “the sum of the outputs of all generators is equal to the load”. A method that includes more.
In paragraph 8, The above calculation step is, Step of calculating a constrained optimal solution based on parallel processing with convex optimization applied Including more, Redefining the optimization problem by excluding the constrained generator method.
In Paragraph 11, The step of calculating the above-mentioned constraint optimal solution is, A step of setting constraints on generators outside the range regarding the minimum or maximum limits and excluding them from the optimization problem. A method that includes more.
In paragraph 8, The above calculation step is, Step of calculating the optimal solution for inequality-constrained parallel processing using convex optimization and the simplex method Including more, Redefining the optimization problem by including inequality constraints on some generator groups method.
In Paragraph 13, The step of calculating the optimal solution for the above inequality constraints is, Calculating the optimal solution based on the Lagrangian function and differentiation method.

Description

Method for Systemic Analysis and Optimization of Non-Linear Programming Based on Parallel Processing One embodiment of the present invention relates to a method and apparatus for system analysis and optimization of parallel processing-based nonlinear programming, and specifically, to a system analysis and optimization of parallel processing-based nonlinear programming and a method thereof. Currently operating power system operation systems (EMS) and SCADA systems do not utilize resources efficiently because most applications are not parallelized. In particular, there are issues with low performance because flow calculations and optimization algorithms in system analysis, which require a significant amount of CPU time, are not parallelized. To address these issues, we propose a system and method for system analysis and optimization of parallel processing-based nonlinear programming. Figure 1 is a flowchart of a method for systematic analysis and optimization of a parallel processing-based nonlinear programming method according to one embodiment. FIG. 2 is a diagram showing a method for system analysis and optimization of a parallel processing-based nonlinear programming method according to one embodiment. FIG. 3 is a block diagram of an apparatus for system analysis and optimization of a parallel processing-based nonlinear programming method according to one embodiment. Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings. However, the technical concept of the present invention is not limited to some of the described embodiments but can be implemented in various different forms, and within the scope of the technical concept of the present invention, one or more of the components among the embodiments may be selectively combined or substituted. In addition, terms used in the embodiments of the present invention (including technical and scientific terms) may be interpreted in a sense that is generally understood by those skilled in the art to which the present invention belongs, unless explicitly and specifically defined otherwise. Terms that are commonly used, such as terms defined in advance, may be interpreted in consideration of their meaning in the context of the relevant technology. Furthermore, the terms used in the embodiments of the present invention are for the purpose of describing the embodiments and are not intended to limit the present invention. In this specification, the singular form may include the plural form unless specifically stated otherwise in the text, and when described as “at least one of A and B, C (or more than one of them),” it may include one or more of all combinations that can be formed from A, B, and C. In addition, terms such as first, second, A, B, (a), (b), etc. may be used when describing the components of the embodiments of the present invention. These terms are intended merely to distinguish a component from other components and are not limited by the nature, order, sequence, etc., of the said component. And, where it is stated that a component is 'connected', 'combined', or 'joined' to another component, this may include not only cases where the component is directly connected, combined, or joined to the other component, but also cases where it is 'connected', 'combined', or 'joined' due to another component located between the component and the other component. Furthermore, when described as being formed or placed on the “top or bottom” of each component, “top or bottom” includes not only cases where two components are in direct contact with each other, but also cases where one or more other components are formed or placed between the two components. Additionally, when expressed as “top or bottom,” it may include the meaning of a downward direction as well as an upward direction relative to a single component. Hereinafter, embodiments will be described in detail with reference to the attached drawings, provided that identical or corresponding components are given the same reference number regardless of the drawing symbols, and redundant descriptions thereof will be omitted. FIG. 1 is a flowchart of a method for systematic analysis and optimization of a parallel processing-based nonlinear programming method according to one embodiment. A method for system analysis and optimization of a parallel processing-based nonlinear programming method according to one embodiment can be performed by at least some of the components of a device for system analysis and optimization of a parallel processing-based nonlinear programming method described below. The components of a device for system analysis and optimization of parallel processing-based nonlinear programming may be configured to include at least a part of a machine, circuit, semiconductor, computing device, memory, processor, data transceiver, etc., and at least a part of each component may be mechanically/physically/communicationally/electrically co