This paper proposes a method for evaluating the optimal configuration of a hybrid system (biomass power plant and photovoltaic plant), which is connected to the electrical grid, to achieve minimum energy costs. The study is applied to a small rural municipality in the Valencian Community, Spain, as an energy community. The approach takes into account the daily energy demand variation and price curves for energy that are either imported or exported to the grid. The optimal configuration is determined by the highest internal rate of return (IRR) over a 12-year period while providing a 20% discount in electricity prices for the energy community. The approach is extrapolated to an annual period using the statistical data of sunny and cloudy days, considering 23.8% of the year as cloudy. The methodology provides a general procedure for hybridising both plants and the grid to meet the energy needs of a small rural population. In the analysed case, an optimal combination of 140 kW of rated power from the biogas generator was found, which is lower than the maximum demand of 366 kW and 80 kW installed power in the photovoltaic plant, resulting in an IRR of 6.13% over 12 years. Sensitivity studies for data variations are also provided.
Climate change is a global problem, which is being mitigated over the last decades. To this end, several regulations are being developed to make an energy transition towards renewable resources. In this framework, more and more energy communities are being created in Europe, with the aim of reducing energy consumption based on fossil fuels and promoting the use of renewable energies. This work proposes the design and management of renewable resources to introduce them into the energy matrix. This energy matrix based on renewable energies aims to cover the energy demand of a small rural municipality in the Valencian Community (Spain), for which the annual consumption is known. The results show the possibility of achieving a high percentage of self-consumption in rural municipalities, minimising dependence on the general electricity grid.
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