Sizing and Optimization of a Hybrid Green Energy System for Radio Sites of Mobile Telecommunications Networks

In the telecommunications field, the ability of algorithms to transform a sector is no longer in doubt. They could well have major consequences on the way they produce and consume energy, optimize a traffic propagation etc. Between reducing the energy balance of network installations and better use of renewable energies, operators are undertaking major projects. And each time, algorithms are at the heart of these changes. This article seeks to optimize a hybrid system composed of renewable energy (photovoltaic panels, wind turbines) and batteries to power telecommunications base stations (BTS) sites. It proceeds with modeling and optimization based on the non-dominated sorting genetic algorithm (NSGA-II). A multi-objective formulation is proposed to minimize the power loss probability (LPSP) and the levelized cost of energy (LCOE). Input data including ambient temperature, solar irradiation, wind speed and the load profile of the BTS site are considered for simulation in Matlab software. The results obtained are very encouraging for the integration of green energy into modern telecommunications systems. The optimization resulted in a hybrid system composed of 48 photovoltaic modules, each with a capacity of 540 peak watts (Wp), 17 wind turbines, each with a nominal power of one kilowatt, and a storage system with a capacity of 1500 ampere-hours (Ah). The adoption of this system would cost 0.13 euros per kilowatt-hour in our context in Benin with a reliability of 99.2%, providing reliable energy at a lower cost while contributing to achieving the seventh Sustainable Development Goal (SDG).

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Published
2024-12-20
DOI
https://doi.org/10.1109/acai63924.2024.10899642
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
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article

Sizing and Optimization of a Hybrid Green Energy System for Radio Sites of Mobile Telecommunications Networks

Christian Akowanou, Régis Donald Hontinfinde, Sylvain M. Tchike, Géraud Azehoun-Pazou et al.
Energy Harvesting in Wireless Networks
article

Sizing and Optimization of a Hybrid Green Energy System for Radio Sites of Mobile Telecommunications Networks

Christian Akowanou, Régis Donald Hontinfinde, Sylvain M. Tchike, Géraud Azehoun-Pazou, Audace Kosoko B. Didavi, Giro Arnaud M. Hounsou
article en

Abstract

In the telecommunications field, the ability of algorithms to transform a sector is no longer in doubt. They could well have major consequences on the way they produce and consume energy, optimize a traffic propagation etc. Between reducing the energy balance of network installations and better use of renewable energies, operators are undertaking major projects. And each time, algorithms are at the heart of these changes. This article seeks to optimize a hybrid system composed of renewable energy (photovoltaic panels, wind turbines) and batteries to power telecommunications base stations (BTS) sites. It proceeds with modeling and optimization based on the non-dominated sorting genetic algorithm (NSGA-II). A multi-objective formulation is proposed to minimize the power loss probability (LPSP) and the levelized cost of energy (LCOE). Input data including ambient temperature, solar irradiation, wind speed and the load profile of the BTS site are considered for simulation in Matlab software. The results obtained are very encouraging for the integration of green energy into modern telecommunications systems. The optimization resulted in a hybrid system composed of 48 photovoltaic modules, each with a capacity of 540 peak watts (Wp), 17 wind turbines, each with a nominal power of one kilowatt, and a storage system with a capacity of 1500 ampere-hours (Ah). The adoption of this system would cost 0.13 euros per kilowatt-hour in our context in Benin with a reliability of 99.2%, providing reliable energy at a lower cost while contributing to achieving the seventh Sustainable Development Goal (SDG).

Université d'Abomey-Calavi (BJ), National University of Sciences, Technologies, Engineering and Mathematics (BJ)
Affordable and clean energy
Openalex Percentile: Top 74%
Energy Harvesting in Wireless Networks
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