Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm

This paper proposes an improved binary bat algorithm (IBBA) for solving static and dynamic transmission network expansion planning (TNEP) problems for standard and realistic networks considering different objective functions (OFs). The proposed IBBA has two modifications to enhance the solution qual...

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Autores principales:	Mohamed T. Mouwafi, Adel A. Abou El-Ela, Ragab A. El-Sehiemy, Waleed K. Al-Zahar
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2022
Materias:	Transmission network expansion planning Improved binary bat algorithm Adaptive neuro-fuzzy inference system Long-term load forecasting Reactive power compensation Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/47e2f94dc6bd4751be7bebf33a6443c5
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id	oai:doaj.org-article:47e2f94dc6bd4751be7bebf33a6443c5
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spelling	oai:doaj.org-article:47e2f94dc6bd4751be7bebf33a6443c52021-11-18T04:45:03ZTechno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm1110-016810.1016/j.aej.2021.06.021https://doaj.org/article/47e2f94dc6bd4751be7bebf33a6443c52022-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1110016821003732https://doaj.org/toc/1110-0168This paper proposes an improved binary bat algorithm (IBBA) for solving static and dynamic transmission network expansion planning (TNEP) problems for standard and realistic networks considering different objective functions (OFs). The proposed IBBA has two modifications to enhance the solution quality based on multi V-shaped transfer function and adaptive search space (ASS). The IBBA is applied to solve the static TNEP problem. A two-stage procedure is employed to solve the dynamic TNEP problem. In stage-1, the adaptive neuro-fuzzy inference system (ANFIS) is utilized to find the long-term load forecasting (LTLF) up to 2039. In stage-2, the IBBA is used to solve the dynamic TNEP problem. Two OFs are considered for solving TNEP problems. The first OF achieves the investment cost reduction. The second OF aims to minimize the total costs, which include the investment cost and the total costs of energy losses and reactive power compensation (RPC). The proposed procedure is applied to Garver’s 6-bus system and the West Delta Network (WDN) as a part of the Unified Egyptian Transmission Network (UETN) to solve TNEP problems. The obtained results are compared with other methods to show the robustness of the proposed procedure for solving TNEP problems.Mohamed T. MouwafiAdel A. Abou El-ElaRagab A. El-SehiemyWaleed K. Al-ZaharElsevierarticleTransmission network expansion planningImproved binary bat algorithmAdaptive neuro-fuzzy inference systemLong-term load forecastingReactive power compensationEngineering (General). Civil engineering (General)TA1-2040ENAlexandria Engineering Journal, Vol 61, Iss 2, Pp 1383-1401 (2022)
institution	DOAJ
collection	DOAJ
language	EN
topic	Transmission network expansion planning Improved binary bat algorithm Adaptive neuro-fuzzy inference system Long-term load forecasting Reactive power compensation Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Transmission network expansion planning Improved binary bat algorithm Adaptive neuro-fuzzy inference system Long-term load forecasting Reactive power compensation Engineering (General). Civil engineering (General) TA1-2040 Mohamed T. Mouwafi Adel A. Abou El-Ela Ragab A. El-Sehiemy Waleed K. Al-Zahar Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
description	This paper proposes an improved binary bat algorithm (IBBA) for solving static and dynamic transmission network expansion planning (TNEP) problems for standard and realistic networks considering different objective functions (OFs). The proposed IBBA has two modifications to enhance the solution quality based on multi V-shaped transfer function and adaptive search space (ASS). The IBBA is applied to solve the static TNEP problem. A two-stage procedure is employed to solve the dynamic TNEP problem. In stage-1, the adaptive neuro-fuzzy inference system (ANFIS) is utilized to find the long-term load forecasting (LTLF) up to 2039. In stage-2, the IBBA is used to solve the dynamic TNEP problem. Two OFs are considered for solving TNEP problems. The first OF achieves the investment cost reduction. The second OF aims to minimize the total costs, which include the investment cost and the total costs of energy losses and reactive power compensation (RPC). The proposed procedure is applied to Garver’s 6-bus system and the West Delta Network (WDN) as a part of the Unified Egyptian Transmission Network (UETN) to solve TNEP problems. The obtained results are compared with other methods to show the robustness of the proposed procedure for solving TNEP problems.
format	article
author	Mohamed T. Mouwafi Adel A. Abou El-Ela Ragab A. El-Sehiemy Waleed K. Al-Zahar
author_facet	Mohamed T. Mouwafi Adel A. Abou El-Ela Ragab A. El-Sehiemy Waleed K. Al-Zahar
author_sort	Mohamed T. Mouwafi
title	Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
title_short	Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
title_full	Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
title_fullStr	Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
title_full_unstemmed	Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
title_sort	techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm
publisher	Elsevier
publishDate	2022
url	https://doaj.org/article/47e2f94dc6bd4751be7bebf33a6443c5
work_keys_str_mv	AT mohamedtmouwafi technoeconomicbasedstaticanddynamictransmissionnetworkexpansionplanningusingimprovedbinarybatalgorithm AT adelaabouelela technoeconomicbasedstaticanddynamictransmissionnetworkexpansionplanningusingimprovedbinarybatalgorithm AT ragabaelsehiemy technoeconomicbasedstaticanddynamictransmissionnetworkexpansionplanningusingimprovedbinarybatalgorithm AT waleedkalzahar technoeconomicbasedstaticanddynamictransmissionnetworkexpansionplanningusingimprovedbinarybatalgorithm
_version_	1718425037177880576

Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm

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