Cover Image

Investment Planning Problem in Power System Using Artificial Neural Network

Link to publisher's homepage at http://amci.unimap.edu.my

Saved in:
Bibliographic Details
Main Authors: Shamshul Bahar, Yaakob, Siti Hajar, Mohd Tahar, Amran, Ahmed
Other Authors: amranahmed@unimap.edu.my
Format: Article
Language:English
Published: Institute of Engineering Mathematics, Universiti Malaysia Perlis 2018
Subjects:
Mean-variance Analysis
Hopfield Network
Boltzmann Machine
Distribution Expansion Planning
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/54393
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-54393
record_format dspace
spelling my.unimap-543932018-07-24T01:47:27Z Investment Planning Problem in Power System Using Artificial Neural Network Shamshul Bahar, Yaakob Siti Hajar, Mohd Tahar Amran, Ahmed amranahmed@unimap.edu.my Mean-variance Analysis Hopfield Network Boltzmann Machine Distribution Expansion Planning Link to publisher's homepage at http://amci.unimap.edu.my This paper presents a model to solve Distribution Expansion Planning (DEP) problem. An effective method is proposed to determine an optimal solution for strategic investment planning in distribution system. The proposed method will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer quadratic programming problem. Its target is to minimize the risk and maximize the expected return. The proposed method consists of two layers neural networks combining Hopfield network at the upper layer and Boltzmann machine in the lower layer resulting the fast computational time. The originality of the proposed model is it will delete the unit of the lower layer, which is not selected in upper layer in its execution. Then, the lower layer is restructured using the selected units. Due to this feature, the proposed model will improve times and the accuracy of obtained solution. The significance of output from this project is the improvement of computational time and the accurate solution will be obtained. This model might help the decision makers to choose the optimal solution with variety options provided from this proposed method. Therefore, the performance of strategic investment planning in solving DEP problem certainly enhanced 2018-07-19T03:48:36Z 2018-07-19T03:48:36Z 2018 Article Applied Mathematics and Computational Intelligence (AMCI), vol.7(1), 2018, pages 13-22 2289-1323 (online) 2289-1315 (print) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/54393 en Institute of Engineering Mathematics, Universiti Malaysia Perlis
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Mean-variance Analysis
Hopfield Network
Boltzmann Machine
Distribution Expansion Planning
spellingShingle Mean-variance Analysis
Hopfield Network
Boltzmann Machine
Distribution Expansion Planning
Shamshul Bahar, Yaakob
Siti Hajar, Mohd Tahar
Amran, Ahmed
Investment Planning Problem in Power System Using Artificial Neural Network
description Link to publisher's homepage at http://amci.unimap.edu.my
author2 amranahmed@unimap.edu.my
author_facet amranahmed@unimap.edu.my
Shamshul Bahar, Yaakob
Siti Hajar, Mohd Tahar
Amran, Ahmed
format Article
author Shamshul Bahar, Yaakob
Siti Hajar, Mohd Tahar
Amran, Ahmed
author_sort Shamshul Bahar, Yaakob
title Investment Planning Problem in Power System Using Artificial Neural Network
title_short Investment Planning Problem in Power System Using Artificial Neural Network
title_full Investment Planning Problem in Power System Using Artificial Neural Network
title_fullStr Investment Planning Problem in Power System Using Artificial Neural Network
title_full_unstemmed Investment Planning Problem in Power System Using Artificial Neural Network
title_sort investment planning problem in power system using artificial neural network
publisher Institute of Engineering Mathematics, Universiti Malaysia Perlis
publishDate 2018
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/54393
_version_ 1643804317996548096
score 13.211869

Similar Items