THE METHOD OF OPTIMIZATION OF THE DEVELOPMENT OF POWER SYSTEMS WITH THE USE OF MATHEMATICAL MODELS (O METODE OPTIMIZATSII RAZVITIYA ENERGETICHESKIKH SISTEM S ISPOLZOVANIEM MATEMATICHESKIKH MODELEI),

Abstract

The article describes a mathematical model for optimalizing the structure of a power system. The authors use the competition method, based on the principles of dynamic programming, and the relaxation method. The Siberian Power Institute has accumulated some experience in constructing and putting to use the so-called simplified linear and non-linear models of power systems; so far, this experience indicates that mathematical modeling is unquestionably superior to conventional manual computing methods, which imply that the system remains static. Even the use of simplified models offers great in choosing optimal developmental strategy, delineating the relative importance of various factors in the solution, and determining the relative economy of the various possible structures of a system; modeling also makes it possible to assess directly the 'weight' of individual power plants in the effectiveness of an entire system. However, the models developed so far leave out of account a number of important factors, such as order of construction, optimal capacity of newly built stations, structural parameters, and the like. The article includes a brief discussion of models, the description of an optimalization algorithm, and graphic material.

Document Details

Document Type
Technical Report
Publication Date
Jun 09, 1967
Accession Number
AD0669517

Entities

People

  • L. A. Melentev
  • Yu. P. Syrov

Organizations

  • National Air and Space Intelligence Center

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Competition
  • Computer Programming
  • Construction
  • Dynamic Programming
  • Evolutionary Algorithms
  • Heuristic Methods
  • Materials
  • Mathematical Models
  • Mathematics
  • Models
  • Optimization
  • Transport Ships

Readers

  • Computational Modeling and Simulation
  • Information Retrieval
  • Operations Research