A New Approach for Optimizing Management of a Real Time Solar Charger Using the Firebase Platform Under Android

With the continuous growth of energy consumption, the rationalization of energy has become a priority. The photovoltaic energy sector remains a major occupation for researchers in the field of production optimization or storage methods. The concept developed in this work is a mixed optimization approach for energy management during battery charging with a duty cycle. A selective collaborative algorithm intervenes to choose and use the appropriate results of the few techniques to optimize the charging time of a battery and estimate its state of charge by using the minimum possible tools. This is done using a collective database that is accessible in real time. It also effectively allows the synchronization of information between several customers. This approach is performed on a mobile application on android, through a Google Firebase platform that allows us to secure collaborative access between multiple customers and use the results of the calculations of some algorithms. It gives us the values obtained by the various sensors in real time to accelerate the charging speed of the battery. The validation of this approach led us to practice a few scenarios using an Arduino board to show that this approach has a better performance.

Rigorous Integrated Evolutionary Workflow for Optimal Exploitation of Unconventional Gas Assets

Applications of stochastic evolutionary algorithms in engineering are gaining more attention in practical applications in the oil and gas industry. An important factor to consider when implementing stochastic algorithms is its ability to find the global optimum efficiently. In this study the authors formulate, implement, and test a genetic algorithm with strong elitism to solve a critical problem in the upstream oil industry: how to develop economically an unconventional gas asset. This problem involves finding the optimal number of horizontal wells, the number of transverse hydraulic fracture stages along them, and stage half-length. The described problem is inherently discrete or mixed optimization problem for which the authors develop a conceptually new evolutionary integrated framework that addresses all production design questions. They outline the range of applicability of their workflow and provide ample test cases and results. Their rigorous formulation performs well for a given problem statement and finds the optimal solution that is consistent with the industry accepted optimum.