The exploitation of renewable energies despite their availability in domestic scale remains very insufficient. This is mainly due to three reasons. The first one is about the problem of intermittent power generation by solar and wind energy. The second problem is the high cost of traditional solar and wind installations. In addition, the third problem is the large space occupied by these systems. To help solve these problems and optimize the production of electricity and the space occupied, we proposed a compact system with flexible photovoltaic (PV) solar panels that automatically takes the shape of wind turbine blades named Savonius. This coupling ensures two modes of ecological production of green energy namely PV mode and wind turbine mode where these two technologies compensate to partially overcome the problem of intermittent and also save space. This is a new idea in the literature, unlike conventional hybrid systems which include wind turbines and PV solar panels separately. The proposed system is based on a management algorithm developed in MATLAB/Simulink and modeled with "Stateflow" which allows changing between the solar wind modes according of meteorological values.
To lower the production of greenhouse gases while covering energy needs, it is necessary to exploit renewable energies in the urban environment and manage energy production and consumption as well. In this work, we interested in the study of a house using renewable energy sources such as photovoltaic (PV) panels, thermal panels and wind turbines (WT). The energy consumption happens through electrical charges like the refrigerator, the heat pump, the lighting... The main objective of this work is to change the operating time of secondary loads and to propose an energy management algorithm. Firstly, we will model the consumption of electrical charges and move the operation of secondary charges to moderate the consumed energy. Finally, we suggested an algorithm to manage and optimize energy production and consumption. The results show that the displacement of secondary loads reduces over 8.5% of the energy bill and the suggested algorithm optimizes the operation of the energy production equipment while covering the energy needs of the inhabitants.
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