Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources

Transmission Expansion Planning (TEP) involves determining if and how transmission lines should be added to the power grid so that the operational and investment costs are minimized. TEP is a major issue in smart grid development, where demand response resources affect short- and long-term power sys...

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Main Authors: Amir Sadegh Zakeri, Hossein Askarian Abyaneh
Format: Article
Language:English
Published: MDPI AG 2017-09-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/10/9/1376
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author Amir Sadegh Zakeri
Hossein Askarian Abyaneh
author_facet Amir Sadegh Zakeri
Hossein Askarian Abyaneh
author_sort Amir Sadegh Zakeri
collection DOAJ
description Transmission Expansion Planning (TEP) involves determining if and how transmission lines should be added to the power grid so that the operational and investment costs are minimized. TEP is a major issue in smart grid development, where demand response resources affect short- and long-term power system decisions, and these in turn, affect TEP. First, this paper discusses the effects of demand response programs on reducing the final costs of a system in TEP. Then, the TEP problem is solved using a Teaching Learning Based Optimization (TLBO) algorithm taking into consideration power generation costs, power loss, and line construction costs. Simulation results show the optimal effect of demand response programs on postponing the additional cost of investments for supplying peak load.
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spelling doaj.art-b70c250189194128bc51c8a8e38fc12c2022-12-22T01:56:54ZengMDPI AGEnergies1996-10732017-09-01109137610.3390/en10091376en10091376Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response ResourcesAmir Sadegh Zakeri0Hossein Askarian Abyaneh1Tehran Polytechnic, Amirkabir University of Technology, 424 Hafez Ave, 159163-4311 Tehran, IranTehran Polytechnic, Amirkabir University of Technology, 424 Hafez Ave, 159163-4311 Tehran, IranTransmission Expansion Planning (TEP) involves determining if and how transmission lines should be added to the power grid so that the operational and investment costs are minimized. TEP is a major issue in smart grid development, where demand response resources affect short- and long-term power system decisions, and these in turn, affect TEP. First, this paper discusses the effects of demand response programs on reducing the final costs of a system in TEP. Then, the TEP problem is solved using a Teaching Learning Based Optimization (TLBO) algorithm taking into consideration power generation costs, power loss, and line construction costs. Simulation results show the optimal effect of demand response programs on postponing the additional cost of investments for supplying peak load.https://www.mdpi.com/1996-1073/10/9/1376transmission expansion planningdemand response programTLBOelasticity
spellingShingle Amir Sadegh Zakeri
Hossein Askarian Abyaneh
Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources
Energies
transmission expansion planning
demand response program
TLBO
elasticity
title Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources
title_full Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources
title_fullStr Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources
title_full_unstemmed Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources
title_short Transmission Expansion Planning Using TLBO Algorithm in the Presence of Demand Response Resources
title_sort transmission expansion planning using tlbo algorithm in the presence of demand response resources
topic transmission expansion planning
demand response program
TLBO
elasticity
url https://www.mdpi.com/1996-1073/10/9/1376
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