Potential of a Nonperennial Tributary Integrated with Solar Energy for Rural Electrification: A Case Study of Ikukwa Village in Tanzania

Author:

Mwakitalima Isaka J12ORCID,Rizwan Mohammad1,Kumar Narendra1

Affiliation:

1. Department of Electrical Engineering, Delhi Technological University, Delhi, India

2. Department of Electrical and Power Engineering, Mbeya University of Science and Technology, P.O. Box 131, Mbeya, Tanzania

Abstract

This study evaluates the hydropower potential in the design of a micro-hydro/solar photovoltaic hybrid system with battery energy storage for increasing the access to electricity in Ikukwa Village in Mbeya Region of Tanzania. Usually, hybridized hydropower schemes are designed from perennial streams for the provision of electricity. This study incorporates the run-of-the river (COE) power scheme, which originates from the untapped potential of nonperennial hydro-energy source and the use of traditional approach of data measurements for Ikata tributary to design hybrid system. The system is optimized by the minimization of the total net present cost (NPC) and cost of energy (COE) using the soft computing method of Hybrid Optimization of Multiple Energy Resources (HOMER) software and artificial intelligent (AI) techniques. AI optimization techniques such as particle swarm optimization (PSO), grey wolf optimization (GWO), and GWO-PSO hybrid (GWO-PSOHD) algorithms have been employed for further optimal results. The data for solar radiation and the tributary have been obtained from the National Aeronautics and Space Administration (NASA) and traditional methods of measurements, respectively. The estimated maximum water flow rate and head are 2.943 m3/s and 13 m, respectively. In the same period, the approximated theoretical power potential of the tributary is found to be 375 kW. Total NPCs obtained from HOMER, PSO, GWO, and GWO-PSOHD methods are $ 141, 397.76, $ 95 167.21, $ 92 472.82, and $ 91,854.10, respectively. Similarly, the optimal results of COE from HOMER, PSO, GWO, and GWO-PSOHD approaches are $ 0.1818/kWh, $ 0.1185/kWh, $ 0.1182/kWh, and $ 0.1181/kWh, respectively. Comparatively, PSO implementation has indicated the greatest energy cost, while the cost acquired by GWO-PSOHD is the lowest for all aforementioned AI optimization techniques. The tributary under study has a high potential of diversification of energy sources for rural electrification in the area of study and other parts of the world with comparable conditions.

Funder

Indian Council for Cultural Relations

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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