Browsing by Author "Bachari, Nour El Islam"

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Creating an artificial neural network time series model for the prediction of daily solar radiation in oran
(Desalination Publ, 2022-04-01) Soukeur, El Hussein Iz El Islam; Chaabane, Djamal; Amarouche, Khalid; Bachari, Nour El Islam; AMAROUCHE, KHALID; Khalid Amarouche; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği Bölümü.; 0000-0001-7983-4611; AFR-7886-2022
Water and clean energies are currently a major scientific and political concern. The use of numerical prediction is often recommended in these areas, for optimal exploitation of renewable energy resources, mainly for seawater desalination and other energy and food security activities. In this study, we present an application of artificial neural networks (ANN), developed for daily solar energy forecasting. The ANN model developed is based on the multi-layer perceptron, the most widely used ANN type in renewable energy and time series forecasting. The developed model has two main properties: I. The ANN training is based on long-term reanalysis data, allowing the model to be trained even in areas where no radiation measurements are available, as is the case for marine areas and in the new desalination plants. II. The model allows automatic selection of the optimal ANN model architecture based on the training data. A thirty-nine-year time series of reanalysis data between 1980 and 2018 was used for training and model implementation. Thus, the model accuracy was evaluated based on one-year data (2019). The obtained error analysis results show that the developed model has a good performance in line with previous studies. The developed ANN models are characterized by reasonable daily prediction accuracy, with a root mean square error of 3.248 MJ/(m2 d) for solar radiation prediction. This verifies the accuracy and ability of the model to predict solar radiation to ensure optimal management of solar energy farms.
Evaluation of a high-resolution wave hindcast model SWAN for the West Mediterranean basin
(Elsevier Science, 2019-01-18) Amarouche, Khalid; Bachari, Nour El Islam; Houma, Fouzia; Akpınar, Adem; Çakmak, Recep Emre; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği Bölümü.; 0000-0002-9042-6851; 0000-0003-0700-8622; AAC-6763-2019; AAG-8624-2021; 23026855400; 57675048100
This study aims to present an evaluation and implementation of a high-resolution SWAN wind wave hindcast model forced by the CFSR wind fields in the west Mediterranean basin, taking into account the recent developments in wave modelling as the new source terms package ST6. For this purpose, the SWAN model was calibrated based on one-year wave observations of Azeffoune buoy (Algerian coast) and validated against eleven wave buoys measurements through the West Mediterranean basin. For the calibration process, we focused on the whitecapping dissipation coefficient C-ds and on the exponential wind wave growth and whitecapping dissipation source terms. The statistical error analysis of the calibration results led to conclude that the SWAN model calibration corrected the underestimation of the significant wave height hindcasts in the default mode and improved its accuracy in the West Mediterranean basin. The exponential wind wave growth of Komen et al (1984) and the whitecapping dissipation source terms of Janssen (1991) with C-ds = 1.0 have been thus recommended for the western Mediterranean basin. The comparison of the simulation results obtained using this calibrated parameters against eleven measurement buoys showed a high performance of the calibrated SWAN model with an average scatter index of 30% for the significant wave heights and 19% for the mean wave period. This calibrated SWAN model will constitute a practical wave hindcast model with high spatial resolution ((similar to)3 km) and high accuracy in the Algerian basin, which will allow us to proceed to a finer mesh size using the SWAN nested grid system in this area.
Wave energy resource assessment along the Algerian coast based on 39-year wave hindcast
(Pergamon-Elsevier Science, 2020-02-11) Amarouche, Khalid; Houma, Fouzia; Bachari, Nour El Islam; Akpınar, Adem; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/İnşaat Mühendisliği.; 0000-0002-9042-6851; ABE-8817-2020; 23026855400
This study investigates a long-term assessment of the wave energy resource propagated along the Algerian basin, based on a 39-year wave hindcast. The wave energy hindcast dataset was developed using the Simulating WAve Nearshore (SWAN) model, calibrated and validated [1] against wave measurements performed on the Algerian coast. A detailed spatial and local analysis was performed following the hindcast results. We have determined several parameters including; hourly, monthly, seasonal and annual variations of wave energy resources, the probability of occurrence distribution for different wave power ranges with different directions, the probability of calm sea states, the wave energy development index (WEDI) and the total annual wave energy and their distribution as a function of significant wave height and energy period. All these results enabled a very important benchmark for decision making regarding the future implementation and design of wave energy converters (WECs) and other offshore structures in the Algerian basin. Our findings have shown that the Algerian coasts are characterized by a considerable wave energy potential with a large hotspot area in the eastern coasts. Thus, we have recorded a significant variability in the wave energy characteristics available in each zone along the Algerian coast. The western zone was characterized by an average energy of ∼7.5 kW/m with a low monthly and seasonal variation (<1.2), the central zone was characterized by a significant total annual wave energy of 63 MWh/m/year and a considerable WEDI of 0.019, and the eastern Algerian coast was characterized by one of the highest energy potential in the Mediterranean basin with a total annual energy exceeding 100 MWh/m for less than 15 km from the coast and a calm sea state probability lower than 18%. Thus, it has been concluded that since 1995, wave energy resources have tended to increase further.