Johansen model for photovoltaic a very short term prediction to electrical power grids in the Island of Mauritius

Sudden variability in solar photovoltaic (PV) power output to electrical grid can not only cause grid instability but can also affect power and frequency quality. Therefore, to study the balance of electrical grid or micro-grid power generated by PV systems in an upstream direction, predicting models can help. The power output conversion is directly proportional to the solar irradiance. Unlike time horizons predictions, many technics of irradiance forecasting have been proposed, long, medium and short term forecasting. For the Island of Mauritius in the Indian Ocean, and regards to key policy decisions, the government has outlined its intention to promote the PV technologies through the local electricity supplier but oversee the technical requirements of PV power output predicts for 1 hour to 15-minutes ahead. So, this paper is illustrating results of the Johansen vector error correction model (VECM) cointegration approach, from the author original and previous studies, but for a very short term prediction of 15-minutes to PV power output in Mauritius. The novelty of this study, is the long run equilibrium relationship of the Johansen model, that was initially determined in previous research works and from dataset in Reunion Island, is then applied to the PV plant in the Island of Mauritius. The proposed prediction model is trained for an hourly and 15-minutes period from year 2019 to year 2022 for a random month and a random day. The experimental results show that the performance metric R2 values are more than 93% signifying that Johansen model is positively and strongly correlated to onsite measurements. This proposed model is a powerful predicting tool and more accuracy should be attained when associated to a machine learning method that can learn from datasets

Instrumentation de mesures d’une cellule lithium-ion: Caractérisation électrique et influence de l’état de charge

International audienceLi-Ion cells are increasingly used in automotive area due to its high capacity. Predict the behavior is necessary: no manufacturer takes the risk to let the user without the knowledge of the remainder energy available and the used of cell without management can cause drastic performance loss. Therefore, prediction is effective only if we know and understand the cell behavior. To know this one, electrical measurements have to be made under thermal constraints. A fast low-cost test bench is developed. Various tests procedures are explained in the interest of extracting all required parameters.Les cellules Li-Ion sont de plus en plus présentes dans le domaine de la mobilité automobile car elles possèdent de fortes capacités électriques. Prédire le comportement d’une cellule est primordiale : aucun constructeur ne prend le risque de laisser un usager sans connaissance du reste d’énergie encore disponible, et l’utilisation d’une batterie sans une gestion efficace amoindrie ses performances de plus de la moitié. La prédiction est donc effective qu’à partir de la connaissance du comportement d’une cellule Li-Ion obtenue par différentes mesures électriques sous contraintes thermiques. Un banc de mesures rapides à faible coût est développé. Diverses procédures de mesures sont détaillées afin d’extraire les paramètres caractéristiques importants d’une cellule Li-Ion

Effect of aligned and misaligned ventilation opening affecting energy demand and air quality in buildings

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Computational Simulation of Entropy Generation in a Combustion Chamber Using a Single Burner

In this study, we examine the behavior of a propane diffusion flame with air in a burner; the computational investigations are achieved for each case employing the Fluent package. The graphs generated illustrate the influence of flow parameters, the effects of the oxygen percentage in the air, and the effects of the equivalence ratio φ on the entropy generation, the temperature gradients, and the Bejan number. The obtained results show that incorporation of hydrogen with propane reduced both temperature and carbon monoxide emission

Accurate determination of parameters relationship for photovoltaic power output by augmented dickey fuller test and engle granger method

Power output from photovoltaic (PV) systems in outdoor conditions is substantially influenced by climatic parameters such as solar irradiance and temperature. PV manufacturers always provide technical specifications in laboratory conditions but reliable relationship for the power output must be determined for accurate prediction under real operating conditions. For the present study, solar irradiance G, temperature T and electrical power output P data under real conditions are methodically and regularly inscribed in dataloggers. Hence, in this paper, we investigate rigorous and robust statistical methods for small sample such as Augmented Dickey-Fuller and Engle Granger for stationary series to determine the estimate regression between variables P, G & T. A first regression of power output P time series variable on solar irradiance G time series has shown spurious results and thus spurious regression. The first differences of such time series are stationary and a regression is proposed whereas temperature variable is identified as not significant and where autocorrelation of residuals is suspected. Finally, the novelty of this paper is the Engle & Granger method that is used to provide a relationship between variables P and G in a difference level. A final relationship without suspicious heteroscedasticity has been determined. Our model is formulated on the basis of PV real conditions statistical approach and is more realistic than steady approach models

Thermo-Fluid Simulation for Indoor Air Quality and Buildings Thermal Comfort

Air conditioning systems are seen as a crucial part of any structure because they are directly related to the comfort of the occupants. Finding a conditioning system that exhibits not only a high level of comfort, but also a decrease in energy consumption and cost of the system is now very much preferable, especially with the ever-increasing cost of energy. Mixed convection for different boundary conditions and different configuration is carried out. In addition, a flow is injected through a window and extracted through an opposite window. In this work we examine the influence of the value of the Rayleigh number on the flow structure. The numerical analysis was carried out using the ‘Fluent’ software. To deal with turbulence the RNG k-ε model was adopted in this study. The study of ventilation efficiency has shown that the intensity of the recirculation flow increases near the adiabatic wall with the increase of Rayleigh number

Thermo-Fluid Simulation for Indoor Air Quality and Buildings Thermal Comfort

Air conditioning systems are seen as a crucial part of any structure because they are directly related to the comfort of the occupants. Finding a conditioning system that exhibits not only a high level of comfort, but also a decrease in energy consumption and cost of the system is now very much preferable, especially with the ever-increasing cost of energy. Mixed convection for different boundary conditions and different configuration is carried out. In addition, a flow is injected through a window and extracted through an opposite window. In this work we examine the influence of the value of the Rayleigh number on the flow structure. The numerical analysis was carried out using the ‘Fluent’ software. To deal with turbulence the RNG k-ε model was adopted in this study. The study of ventilation efficiency has shown that the intensity of the recirculation flow increases near the adiabatic wall with the increase of Rayleigh number

Comparative Weibull distribution methods for reliable global solar irradiance assessment in France areas

International audienceThis paper investigates the Weibull distribution analysis for an accuracy global solar irradiance assessment considering period measurements based on several and grouping years. The problem study in this paper is to find a global solar irradiance model in order to provide accurate estimation of PV energy output allowing better sizing of PV installation. The aim is to select the best Weibull fit procedure for obtaining reliable global solar irradiance from sun that incident in a place during time periods to estimate its yearly energy generation from PV plant. Comparisons are carried out between Graphic, Moments and Maximum Likelihood methods with two different databases (real data on-site measurements and SODA website database). These comparisons are made on global solar irradiance frequency distributions and annual solar irradiance assessment for different French locations. The originality of the paper is that the obtained results prove that the Maximum Likelihood method fits better with the global solar irradiance distribution while the Moment method provides an annual solar irradiance prediction. Thereby, we exploit the obtained results from the Moment method to achieve a more accurate solar energy forecasting model. This resulting model can be implemented for providing one solar energy estimation tool for PV plant sites