Abstract
Exceeding intermitence and the stochastic character associated with most renewable energy sources in order to maintain the balance between generation and consumption require the most efficient energy storage methods. This balance is important to maintain the quality of the power supply by adjusting the frequency and voltage of the grid. Storage is the capture of the energy produced at a given time for later use. It is known that electricity cannot be stored directly unless it is stored in condenser batteries or in superconducting coils. Other methods of electricity storage presuppose the conversion of these into other forms of energy: mechanical storage, electrochemical storage. The optimization of RES operation and, implicitly, of the energy system implies the choice of a suitable conversion / storage system that must take into account a number of factors, such as: capacity and minimum storage time, loading and unloading conditions, minimum number of cycles download loading, power supply required by the storage system, system lifetime. It is not to be neglected the space required for the installation of the storage systems and their impact on the environment during their exploitation as well as during the post-use and recycling period. There are RES that contain natural storage systems (hydro-electric power plants and biomass and biogas generators). The article proposes an analysis of how to store electricity by approach a Pelton water-water-turbine hybrid system. The heat pump consumes electrical energy for action, producing a thermal effect. By integrating a system with Pelton water storage tank and turbine on the heat pump outlet circuit, the lost hydraulic energy can be recovered. The experimental hybrid system was made to develop HRES optimization models. Hybrid systems may exceed the limits of individual generators in terms of efficiency, economy, reliability and flexibility. An energy storage system can alleviate the problems associated with uncertainties and fluctuations from renewable sources. The large number of random variables and parameters in a hybrid energy system requires optimization to increase the efficiency of hybrid system components to achieve economic and technical benefits.
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