ELECTRIFICATION STRATEGY FOR SUSTAINABLE RURAL AGRICULTURE: A LEAST COST ANALYSIS APPROACH

Dominic Ugwudike; Arthur Ekwue; Boniface Anyaka; Theophilus Madueme; Emenike Ejiogu

doi:10.4314/njt.v44i2.17

Authors

D. Ugwudike Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria
A. Ekwue Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria
B. Anyaka Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria
T. C. Madueme Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria
E. Ejiogu Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria

DOI:

https://doi.org/10.4314/njt.v44i2.17

Keywords:

Energy systems, Load demand forecast, Cost analysis, Rice farm operation

Abstract

Electric energy is one of the most widely used form of energy around the globe and as such has the most dynamic means of impacting positively on economic development of any nation in the world. Therefore, to further grow the economy through increased agricultural productivity and rural development, there is an urgent need to address the issue of poor and ineffective rural electrification strategy for sustainable farm operations. Consequently, this paper presents a framework that uses intelligent load forecast, geospatial and cost-effective metric for the analysis of the economic optimality of grid extension, diesel and hybrid photovoltaic (PV)/diesel renewable power generation systems for rural farm operations. The historic national load demand data for 20 years obtained from the national bureau of statistics and central bank was used for the training and validation of the forecast model. The historic electric load data for the case study farm cluster (Adani Enugu Nigeria) was taken to be the electric energy equivalent of the contribution of Adani Enugu to the gross domestic product (GDP) of Enugu state. Input parameters to the neuro-genetic forecast model are the contribution of rice production to the national GDP, contribution of Adani Enugu farm cluster to the national GDP, electric energy consumption (EEC) per ton of rice produced at Adani Enugu and the annual population growth rate. From the simulations carried out, the economic viabilities of the generation options were assessed in terms of capital expenditure (CAPEX) and operational expenditure (OPEX). However, with a 93.84% decrease in CAPEX per kWh if massive investment and expansion of rice processing capacity were made over the forecast horizon, grid extension was found to have the lowest CAPEX. The OPEX for this generation option remained relatively steady for the mentioned condition. However, the approach presented in this paper can be integrated as core components in any generation analysis tool for driving support in optimal generation planning.

Author Biographies

A. Ekwue, Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria

Professor of Power Systems, Electrical Engineering Department, University of Nigeria Nsukka
B. Anyaka, Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria

Associate Professor of Power Systems, Electrical Engineering Department, University of Nigeria Nsukka.
T. C. Madueme, Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria

Professor of Power Systems, Electrical Engineering Department, University of Nigeria Nsukka.
E. Ejiogu, Department of Electrical Engineering, University of Nigeria, Nsukka, Enugu State, Nigeria

Professor of Power Electronics, Electrical Engineering Department, University of Nigeria, Nsukka.

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