Enhancing energy access in rural areas: Intelligent microgrid management for universal telecommunications and electricity

• Microgrid for enhanced universal access to telecommunications and electrical energy. • Microgrid was designed with solar panels, generator and batteries. • Particle Swarm optimization of electricity cost and power supply shortage probability. • The proposed microgrid reduces greenhouse gas emissions and operating costs. In rural areas lacking an electricity grid, cell phone operators use generators to power their facilities. At the same time, however, the local population is finding it difficult to use the cell phones and other electronic devices for which these operators are deploying their efforts. This situation, due to the problem of access to energy, hinders universal access to telecommunications. The present study aims to solve this problem using microgrid techniques. A microgrid consisting of photovoltaic panels, a genset and storage batteries has been designed to meet the needs of cell phone operators' sites in Bapure, a rural locality in Togo. The focus is on managing energy flows between the various sources of the microgrid, and between the needs of the cell phone operators' site and those of the local population. To resolve the lack of solar irradiation data at Bapure, hourly solar irradiation was predicted using the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm to obtain a realistic result. Optimization studies were then carried out using the Particle Swarm Optimization (PSO) algorithm to determine the optimum system configuration to ensure continuity of service at the operator's site. The simulation results show that the proposed system has a surplus of energy production at all times, which can be used to supply electricity to the population at a cost equal to 0.0185 USD, with a solar energy utilization rate of 98,95 % and a generator that only needs to operate at 0.15 % throughout the year. The results obtained indicate that a renewable energy system can provide a more efficient solution for electrifying the rural mobile operator's sites and the local population, and can improve the quality of service for the telecommunications industries.

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Publication Details

Journal
Cleaner Energy Systems
Published
2024-08-16
DOI
https://doi.org/10.1016/j.cles.2024.100136
Citations
6
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
1.97
Controls
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article

Enhancing energy access in rural areas: Intelligent microgrid management for universal telecommunications and electricity

Kanlou Zandjina Dadjiogou, Yao Bokovi, Ayité Sénah Akoda Ajavon
6 citations
Cleaner Energy Systems
Microgrid Control and Optimization
1.97
article

Enhancing energy access in rural areas: Intelligent microgrid management for universal telecommunications and electricity

Kanlou Zandjina Dadjiogou, Yao Bokovi, Ayité Sénah Akoda Ajavon
article en
6 citations

Abstract

• Microgrid for enhanced universal access to telecommunications and electrical energy. • Microgrid was designed with solar panels, generator and batteries. • Particle Swarm optimization of electricity cost and power supply shortage probability. • The proposed microgrid reduces greenhouse gas emissions and operating costs. In rural areas lacking an electricity grid, cell phone operators use generators to power their facilities. At the same time, however, the local population is finding it difficult to use the cell phones and other electronic devices for which these operators are deploying their efforts. This situation, due to the problem of access to energy, hinders universal access to telecommunications. The present study aims to solve this problem using microgrid techniques. A microgrid consisting of photovoltaic panels, a genset and storage batteries has been designed to meet the needs of cell phone operators' sites in Bapure, a rural locality in Togo. The focus is on managing energy flows between the various sources of the microgrid, and between the needs of the cell phone operators' site and those of the local population. To resolve the lack of solar irradiation data at Bapure, hourly solar irradiation was predicted using the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm to obtain a realistic result. Optimization studies were then carried out using the Particle Swarm Optimization (PSO) algorithm to determine the optimum system configuration to ensure continuity of service at the operator's site. The simulation results show that the proposed system has a surplus of energy production at all times, which can be used to supply electricity to the population at a cost equal to 0.0185 USD, with a solar energy utilization rate of 98,95 % and a generator that only needs to operate at 0.15 % throughout the year. The results obtained indicate that a renewable energy system can provide a more efficient solution for electrifying the rural mobile operator's sites and the local population, and can improve the quality of service for the telecommunications industries.

Cleaner Energy SystemsVol. 9
University of Lomé (TG)
Affordable and clean energy
Openalex Percentile: Top 14%
Microgrid Control and Optimization
1.97
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