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General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library,  Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2013 Vol.1(1): 89-93 ISSN:2301-3559
DOI: 10.7763/LNSE.2013.V1.20

Location-Based Intelligent Power Generation and Management Algorithms for Physically Challenging Rural Areas

Onabajo Olawale Olusegun and Chong Eng Tan

Abstract—Climatic change is one of the driving forces behind a new wave of energy management systems being practiced in different parts of the world today. Power generation and Management in disconnected rural villages is challenging. The situation is even more challenging when landscape structures in such environment are irregular. This paper describes the implementation of two algorithms used in power generation and management of rural energy supplies: Location-based Solar Energy Potential Prediction Algorithm (LOSEPPA) and Intelligent Fuzzy-controlled Power Generation and Management Algorithm (IFPGMA). LOSEPPA takes as input, the geographic latitude of the location to compute the solar irradiance factor. IFPGMA intelligently manages the utilization of the generated solar energy. Geographic latitude plays an important role in the availability of sufficient solar radiation as well as the state of the atmosphere. Therefore, the value of solar irradiance factor serves as a guide to the state of the atmosphere in terms of degree of cloud cover, temperature, humidity and landscape structure; which determines the feasibility of the solar energy implementation. With the solar irradiance factor, solar panel can be mounted along specific angle of inclination to the sun. The implemented design is based on solar PV modules arranged in array, integrated with rechargeable batteries and converter models to drive solar energy generation for powering networking equipments. The proposed system was simulated using Homer energy software, C++ and MATLAB-Simulink.
Result show that the more irregular the landscape is, the lower the solar irradiance factor. Solar irradiance factor value of 400 and above predicts well enough sunshine for solar PV implementation. Set point values for battery charging/discharging and the charge controller, maintains circuit voltage supplies at 130V maximum and 2KWh/day at $0.735/KWh with an initial investment cost of $3,090 for the solar implementation.

Index Terms—Geographic latitude, battery charger, PV panel, voltage regulation.

Onabajo Olawale Olusegun is with the Faculty of Computer Science and Information Technology, (UNIMAS), Nigeria. (e-mail: victorious_gem@yahoo.com).
Tan Chong Eng is with the Department of Computer Systems and Communication Technology, UNIMAS, Kota Samarahan, Malaysia. (email: cetan@ieee.org).


Cite: Onabajo Olawale Olusegun and Chong Eng Tan, "Location-Based Intelligent Power Generation and Management Algorithms for Physically Challenging Rural Areas," Lecture Notes on Software Engineering  vol. 1, no. 1, pp. 89-93, 2013.

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