Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms

M. H. Albadi; A. S. Al-Hinai; N. N. Al-Abri; Y. H. Al-Busafi; R. S. Al-Sadairi

doi:10.1109/APPEEC.2012.6307161

Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms

M. H. Albadi^*, A. S. Al-Hinai, N. N. Al-Abri, Y. H. Al-Busafi, R. S. Al-Sadairi

^*المؤلف المقابل لهذا العمل

Electrical and Computer Engineering

نتاج البحث: Conference contribution

8 اقتباسات (Scopus)

ملخص

This paper presents a case study about the optimal allocation of renewable-based DG resources in rural areas using genetic algorithms. After building the power flow model based on the available data, the system performance in terms of power losses are studied for different scenarios. Based on loss minimization as an objective function, the optimal location and size of DG is found. In addition, the fuel saving, loss reduction and environmental benefits of the proposed DG size at the optimum location are quantified.

اللغة الأصلية	English
عنوان منشور المضيف	APPEEC 2012 - 2012 Asia-Pacific Power and Energy Engineering Conference, Proceedings
المعرِّفات الرقمية للأشياء	https://doi.org/10.1109/APPEEC.2012.6307161
حالة النشر	Published - 2012
الحدث	2012 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2012 - Shanghai, China المدة: مارس ٢٧ ٢٠١٢ → مارس ٢٩ ٢٠١٢

سلسلة المنشورات

الاسم	Asia-Pacific Power and Energy Engineering Conference, APPEEC
رقم المعيار الدولي للدوريات (المطبوع)	2157-4839
رقم المعيار الدولي للدوريات (الإلكتروني)	2157-4847

Other

Other	2012 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2012
الدولة/الإقليم	China
المدينة	Shanghai
المدة	٣/٢٧/١٢ → ٣/٢٩/١٢

ASJC Scopus subject areas

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أهداف الأمم المتحدة للتنمية المستدامة

يساهم هذا المخرج في تحقيق أهداف الأمم المتحدة للتنمية المستدامة التالية (SDGs)

الوصول إلى المستند

10.1109/APPEEC.2012.6307161

الملفات والروابط الأخرى

قم بذكر هذا

Albadi, M. H., Al-Hinai, A. S., Al-Abri, N. N., Al-Busafi, Y. H., & Al-Sadairi, R. S. (2012). Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms. في APPEEC 2012 - 2012 Asia-Pacific Power and Energy Engineering Conference, Proceedings المقال 6307161 (Asia-Pacific Power and Energy Engineering Conference, APPEEC). https://doi.org/10.1109/APPEEC.2012.6307161

Albadi, MH , Al-Hinai, AS, Al-Abri, NN, Al-Busafi, YH & Al-Sadairi, RS 2012, Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms. في APPEEC 2012 - 2012 Asia-Pacific Power and Energy Engineering Conference, Proceedings., 6307161, Asia-Pacific Power and Energy Engineering Conference, APPEEC, 2012 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2012, Shanghai, China, ٣/٢٧/١٢. https://doi.org/10.1109/APPEEC.2012.6307161

@inproceedings{ebf5efaab30c4a778a1276d02bebe9fd,

title = "Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms",

abstract = "This paper presents a case study about the optimal allocation of renewable-based DG resources in rural areas using genetic algorithms. After building the power flow model based on the available data, the system performance in terms of power losses are studied for different scenarios. Based on loss minimization as an objective function, the optimal location and size of DG is found. In addition, the fuel saving, loss reduction and environmental benefits of the proposed DG size at the optimum location are quantified.",

keywords = "Distributed Generation, Genetic Algorithms, Loss minimization",

author = "Albadi, {M. H.} and Al-Hinai, {A. S.} and Al-Abri, {N. N.} and Al-Busafi, {Y. H.} and Al-Sadairi, {R. S.}",

year = "2012",

doi = "10.1109/APPEEC.2012.6307161",

language = "English",

isbn = "9781457705472",

series = "Asia-Pacific Power and Energy Engineering Conference, APPEEC",

booktitle = "APPEEC 2012 - 2012 Asia-Pacific Power and Energy Engineering Conference, Proceedings",

note = "2012 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2012 ; Conference date: 27-03-2012 Through 29-03-2012",

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TY - GEN

T1 - Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms

AU - Albadi, M. H.

AU - Al-Hinai, A. S.

AU - Al-Abri, N. N.

AU - Al-Busafi, Y. H.

AU - Al-Sadairi, R. S.

PY - 2012

Y1 - 2012

N2 - This paper presents a case study about the optimal allocation of renewable-based DG resources in rural areas using genetic algorithms. After building the power flow model based on the available data, the system performance in terms of power losses are studied for different scenarios. Based on loss minimization as an objective function, the optimal location and size of DG is found. In addition, the fuel saving, loss reduction and environmental benefits of the proposed DG size at the optimum location are quantified.

AB - This paper presents a case study about the optimal allocation of renewable-based DG resources in rural areas using genetic algorithms. After building the power flow model based on the available data, the system performance in terms of power losses are studied for different scenarios. Based on loss minimization as an objective function, the optimal location and size of DG is found. In addition, the fuel saving, loss reduction and environmental benefits of the proposed DG size at the optimum location are quantified.

KW - Distributed Generation

KW - Genetic Algorithms

KW - Loss minimization

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UR - http://www.scopus.com/inward/citedby.url?scp=84870555458&partnerID=8YFLogxK

U2 - 10.1109/APPEEC.2012.6307161

DO - 10.1109/APPEEC.2012.6307161

M3 - Conference contribution

AN - SCOPUS:84870555458

SN - 9781457705472

T3 - Asia-Pacific Power and Energy Engineering Conference, APPEEC

BT - APPEEC 2012 - 2012 Asia-Pacific Power and Energy Engineering Conference, Proceedings

T2 - 2012 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2012

Y2 - 27 March 2012 through 29 March 2012

ER -

Optimal allocation of renewable-based DG resources in rural areas using genetic algorithms

ملخص

سلسلة المنشورات

Other

ASJC Scopus subject areas

أهداف الأمم المتحدة للتنمية المستدامة

الوصول إلى المستند

الملفات والروابط الأخرى

بصمة

قم بذكر هذا