• Energy Research

Purpose This paper aims to propose an approach based on physical model integration for surface and cloud albedo computation using an approximate form of the atmospheric radiative transfer equation and sun-pixel-satellite. Design/methodology/approach The data used in this study are global irradiance collected from for various sites in Algeria, and data were obtained from the processing of the high-resolution visible images taken by the Meteosat Second Generation satellite in 2010. Findings The results suggest that the standard deviation obtained with this method is similar to that obtained with current estimation methods. The hourly and daily correlation coefficients range between 0.95 and 0.97 and between 0.97 and 0.99, respectively. The hourly and daily mean bias errors range between −0.2 and +1.2 per cent and between −0.2 and +1.4 per cent, respectively. The hourly and daily root mean square errors range between 10 and 17 per cent and between 4 and 8 per cent, respectively. Originality/value This paper developed a new estimating method that derives the hourly global horizontal solar irradiation at a ground level from geostationary satellite data under local climate conditions.

Purpose This paper aims to propose an approach based on physical model integration for surface and cloud albedo computation using an approximate form of the atmospheric radiative transfer equation and sun-pixel-satellite. Design/methodology/approach The data used in this study are global irradiance collected from for various sites in Algeria, and data were obtained from the processing of the high-resolution visible images taken by the Meteosat Second Generation satellite in 2010. Findings The results suggest that the standard deviation obtained with this method is similar to that obtained with current estimation methods. The hourly and daily correlation coefficients range between 0.95 and 0.97 and between 0.97 and 0.99, respectively. The hourly and daily mean bias errors range between −0.2 and +1.2 per cent and between −0.2 and +1.4 per cent, respectively. The hourly and daily root mean square errors range between 10 and 17 per cent and between 4 and 8 per cent, respectively. Originality/value This paper developed a new estimating method that derives the hourly global horizontal solar irradiation at a ground level from geostationary satellite data under local climate conditions.

Abstract Accurate predictions of the solar resource are essential tools for the design, performance analysis, and economic evaluation of various solar energy projects. This paper is proposed in an attempt to overcome the lack of solar radiation data and predicting models in Algeria. New and readjusted models have been developed to estimate the daily and monthly mean daily global solar irradiations over Algerian Big South, based on measured ground data of air temperature and sunshine hours, as well as the day/month number. After a careful evaluation of the models’ performances using the standard K-fold cross-validation method, it was found that only the sunshine-based models can offer excellent estimations in the daily time scale, with validation RMSEs in the range of 1.470–2.425 MJ/m2 day. Meanwhile, all types of models have superior estimations of the monthly mean global irradiation (RRMSE less than 10% in most cases). The merits of using the K-fold cross-validation method in optimizing the error estimates, stabilizing the performances, as well as selecting the appropriate models, have been demonstrated.

Abstract Accurate predictions of the solar resource are essential tools for the design, performance analysis, and economic evaluation of various solar energy projects. This paper is proposed in an attempt to overcome the lack of solar radiation data and predicting models in Algeria. New and readjusted models have been developed to estimate the daily and monthly mean daily global solar irradiations over Algerian Big South, based on measured ground data of air temperature and sunshine hours, as well as the day/month number. After a careful evaluation of the models’ performances using the standard K-fold cross-validation method, it was found that only the sunshine-based models can offer excellent estimations in the daily time scale, with validation RMSEs in the range of 1.470–2.425 MJ/m2 day. Meanwhile, all types of models have superior estimations of the monthly mean global irradiation (RRMSE less than 10% in most cases). The merits of using the K-fold cross-validation method in optimizing the error estimates, stabilizing the performances, as well as selecting the appropriate models, have been demonstrated.

Abstract The effectiveness and accuracy of the methods used in modeling photovoltaic (PV) cells are necessary for predicting the performance of PV systems. This article presents and analyses four methods used to estimate the unknown parameters of photovoltaic devices for one- (four and five parameters) and two-diode (seven parameters) models. The study has three main objectives: (i) extract the unknown parameters by the four methods for the 28 modules of different PV technologies (mono-crystalline, multi-crystalline, HIT, and amorphous) and manufacturers under standard test conditions, (ii) verify the effectiveness and the accuracy of the methods, at each current-voltage curve data point (category 1), and the error relative at each short-circuit current (Isc), open circuit voltage (Voc) and peak power (Pp) points (category 2) and (iii) study the accuracy and reliability of the four methods for the energy measurement of a PV plant of 1.75 kW over three days installed in desert environment. The results show that the most accurate method is obtained by the four parameters one-diode model. It was shown that there is a good agreement with all important points of the I–V curves; especially at Isc, Voc and Pp points, and with the energy delivered by the PV system in the three days.

Abstract The effectiveness and accuracy of the methods used in modeling photovoltaic (PV) cells are necessary for predicting the performance of PV systems. This article presents and analyses four methods used to estimate the unknown parameters of photovoltaic devices for one- (four and five parameters) and two-diode (seven parameters) models. The study has three main objectives: (i) extract the unknown parameters by the four methods for the 28 modules of different PV technologies (mono-crystalline, multi-crystalline, HIT, and amorphous) and manufacturers under standard test conditions, (ii) verify the effectiveness and the accuracy of the methods, at each current-voltage curve data point (category 1), and the error relative at each short-circuit current (Isc), open circuit voltage (Voc) and peak power (Pp) points (category 2) and (iii) study the accuracy and reliability of the four methods for the energy measurement of a PV plant of 1.75 kW over three days installed in desert environment. The results show that the most accurate method is obtained by the four parameters one-diode model. It was shown that there is a good agreement with all important points of the I–V curves; especially at Isc, Voc and Pp points, and with the energy delivered by the PV system in the three days.

Exploiting natural sun and wind resources in remote and isolated areas is undoubtedly an excellent decision to generate electrical energy due to their availability and cleanliness. Various systems were used to generate this energy, such as photovoltaics (PV), wind turbine sand other energy systems. Moreover, for optimum energy use, some of these systems are combined either with each other or with other conventional systems, such as diesel generators with PV systems (i.e., hybrid systems). This work aims to present a technical-economic study of PV/diesel autonomous hybrid systems to supply electrical power for an isolated house located in a hot desert climate, Adrar. For optimizing the hybrid systems, hourly input data of solar radiation and load were used according to two configurations, where the annual load is 11.2 kWh/day. The findings showed that the diesel system had a high cost, with a cost for energy of $0.407/kWh and a fuel price of $0.140/l. Among the hybrid power systems but with significant pollution, the proposed hybrid system 2 kw photovoltaic and diesel generator with 2.3 kW has important economic feasibility, where the energy cost amounted to $0.172/kWh. In addition, CO2 emissions are reduced by approximately 5 tons every year compared to an independent diesel generator system.

Exploiting natural sun and wind resources in remote and isolated areas is undoubtedly an excellent decision to generate electrical energy due to their availability and cleanliness. Various systems were used to generate this energy, such as photovoltaics (PV), wind turbine sand other energy systems. Moreover, for optimum energy use, some of these systems are combined either with each other or with other conventional systems, such as diesel generators with PV systems (i.e., hybrid systems). This work aims to present a technical-economic study of PV/diesel autonomous hybrid systems to supply electrical power for an isolated house located in a hot desert climate, Adrar. For optimizing the hybrid systems, hourly input data of solar radiation and load were used according to two configurations, where the annual load is 11.2 kWh/day. The findings showed that the diesel system had a high cost, with a cost for energy of $0.407/kWh and a fuel price of $0.140/l. Among the hybrid power systems but with significant pollution, the proposed hybrid system 2 kw photovoltaic and diesel generator with 2.3 kW has important economic feasibility, where the energy cost amounted to $0.172/kWh. In addition, CO2 emissions are reduced by approximately 5 tons every year compared to an independent diesel generator system.

Abstract Accurate estimation of diffuse solar radiation (DSR) is among the critical concerns in successful solar energy projects. This paper presents a systematic approach for DSR estimation over the Algerian Sahara. The authors explore the available meteorological and radiometric data. These data include the sunshine hour fraction (ratio of sunshine duration to maximum possible sunshine hours), and the relative clearness index. The data cover a period of six years from 2010 to 2015 measured in the Adrar region. Through an elaborated statistical performance analysis, thirty-five models were tested for constructing the most accurate empirical model for estimating the monthly average daily DSR over the Saharian medium. The proposed correlation models were compared with 8 models available in the literature using the widely used statistical indicators i.e. MPE, RMSE, U95, R, TS and GPI. From this analysis, the quadratic equation model is selected as the most accurate model. The study concluded that the suggested correlation is applicable to estimate the monthly average daily diffuse radiation on a horizontal surface for any location over the Algerian Sahara region, which can serve as a resource for the design of photovoltaic systems.