Artificial Neural Network Approach for the Integration of Renewable Energy in Telecommunication Systems

Dotche, K. A.; Salami, Adekunlé Akim; Kodjo, Mawugno Koffi; Sekyere, François; Bedja, Koffi-Sa

doi:10.1109/powerafrica.2019.8928774

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…There are several types of ANNs. The MLP type ANNs are the most widely used, especially in nonlinear regression problems [31][32]. An MLP network consists of one or more hidden sigmoid layers as an activation function and an output layer.…”

Section: Mlp Approachesmentioning

confidence: 99%

Wind energy potential estimation using neural network and SVR approaches

et al. 2022

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The distribution of wind speed and the optimal assessment of wind energy potential are very important factors when selecting a suitable site for a wind power plant. In wind farm design projects for the supply of electrical energy, designers use the Weibull distribution law to analyse the characteristics and variations of wind speed in order to evaluate the wind potential. In our study we used two approaches, namely, the Multilayer Perceptron (MLP) approach and the Support Vector Machine (SVR) approach to determine a distribution law of wind speeds and to optimally evaluate the wind potential. These two approaches were compared to two well-known numerical methods which are the Justus Empirical Method (EMJ) and the Maximum Likelihood Method (MLM). The results show that the neural network approach produces a better fit of the distribution curve with an Root Mean Square Error (RMSE) of 0.00005016 at Lomé, 0.000040289 at Cotonou site and a more interesting estimate of the wind potential. After that SVR show a better result too with an RMSE of 0.0095618 at the Lomé site and 0.0053549 at the Cotonou site.

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Section: Mlp Approachesmentioning

confidence: 99%

Wind energy potential estimation using neural network and SVR approaches

et al. 2022

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“…Biogas production or anaerobic digestion is technical, ecological and social innovation, which recovers organic waste by producing renewable energy and fertilizer, while preserving environment by reducing polluting gases rejection [12], [13]. The advantage of this hybrid system is that it solves variable and unsecured power problem of photovoltaic solar, by biogas complementarity and increases water pumping time, compared to solar only use [14]. In addition, it minimizes generators usage time, also reducing maintenance costs.…”

Section: Introductionmentioning

confidence: 99%

Endogenous Renewable Energies Conversion Into Electricity for Optimal Pumping of Aquifers Groundwater in the Sahelian Area: Case Study in Burkina Faso

2020

IJESRT

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The water lack is a major obstacle to socio-economic development in the Sahel of southern countries. Water resources access being one of necessary conditions for the Sahelian space development, only water control is a lasting solution to Sahel development problem. Surface water being very ephemeral in the Sahel area, groundwater exploitation is essential for satisfying daily water needs, especially in rural areas. However, dewatering at optimal cost of groundwater faces the access to electricity problem, which is essential for pumping water. This work presents the optimization of a pumping system for groundwater stored in aquifers, to increase the offer of water resources access in Sahelian area, at a lower cost per cubic meter. The required electrical energy for pumping is produced from a hybrid electrical system, composed of photovoltaic solar and generator sets running on biogas, produced from animal droppings. The technical and economic optimization is done by Homer software. The simulation is carried out with four sites characteristics, located in the Sahel region of Burkina Faso, in West Africa. Simulation results gave water costs at the four sites: 0.152 $/m3 for Oudalan site, 0.184 $/m3 for Seno site, 0.151 $/m3 for Soum site and 0.152 $/m3 for Yagha site. This pumping system integrates environmental consecrations by calculating equivalent CO2 before and after conversion of biogas into electricity. CO2 quantity avoided is 134,244,818 tons per year. Biogas use in addition to solar photovoltaic as sources of energy for hybrid electric system has made it possible to lessen pumped water m3 cost and reduce significantly polluting and greenhouse gas emissions.

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Key Role of Cold-Start Circuits in Low-Power Energy Harvesting Systems: A Research Review

Shi,

Cai,

Jiang

2024

JLPEA

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The primary functions of an energy harvesting system include the harvesting, transformation, management, and storage of energy. Until now, various types of energy, with different power levels, have been harvested and stored by the energy harvesting system. In low-power scenarios, such as microwaves, sound, friction, and pressure, a specific low-power energy harvesting system is required. Due to the absence of an external power supply in such systems, cold-start circuits play a crucial role in igniting the low-power energy harvesting system, ensuring a reliable start-up from the initial state. This paper reviews the categorization and characteristics of energy harvesting systems, with a focus on the design and performance parameters of cold-start circuits. A tabular comparison of existing cold-start strategies is presented herein. The study demonstrates that resonance-based integrated cold-start methods offer significant advantages in terms of conversion efficiency and dynamic range, while ring oscillator-based integrated cold-start methods achieve the lowest start-up voltage. Additionally, the paper discusses the challenges of self-starting and future research directions, highlighting the potential role of emerging technologies, such as artificial intelligence (AI) and neural networks, in optimizing the design of energy harvesting systems.

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Artificial Neural Network Approach for the Integration of Renewable Energy in Telecommunication Systems

Cited by 3 publications

References 5 publications

Wind energy potential estimation using neural network and SVR approaches

Wind energy potential estimation using neural network and SVR approaches

Endogenous Renewable Energies Conversion Into Electricity for Optimal Pumping of Aquifers Groundwater in the Sahelian Area: Case Study in Burkina Faso

Key Role of Cold-Start Circuits in Low-Power Energy Harvesting Systems: A Research Review

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