Designing an intelligent decision support system for human-centered utility management automation part 1: structures, problem formulation, solution methodology

Authors:
Alireza Fereidunian;Caro Lucas;Hamid Lesani;Mansooreh Zangiabadi
Affiliations:
Islamic Azad University, Tehran, Iran and Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran;Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran and Intelligent Systems Group, Essential Sciences Research Center, IPM, Tehran, Iran;Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran;Electrical and Computer Engineering Department, Faculty of Engineering, University of Tehran, Tehran, Iran
Venue:
ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation
Year:
2005

Citing 8
Cited 0

Computational intelligence for decision support

Computational intelligence for decision support
The Science of Decision Making: A Problem-based Approach Using Excel

The Science of Decision Making: A Problem-based Approach Using Excel
Model-Based Systems Engineering

Model-Based Systems Engineering
Modern Control Engineering

Modern Control Engineering
The New Science of Management Decision

The New Science of Management Decision
Designing human-centered automation: trade-offs in collision avoidance system design

IEEE Transactions on Intelligent Transportation Systems
A model for types and levels of human interaction with automation

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Model-based human-centered task automation: a case study in ACC system design

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a Decision Support System (DSS) to aid the electric utility management automation system. A brief history of DSS application in power systems is presented. The importance and role of DSS and decision making in utility management automation are discussed. A power distribution system automation problem is stated, and a solution methodology, using problem decomposition, is formulated. Several training sets are derived mathematically from two numerical test sets, for DSS learning procedure. The paper includes discussions, structures, illustrations, numerical examples, and a complete reference citation for further reading.