Hybrid Electric Power Generation System Wind-Photovoltaic with REF Control Applied to the Desalination Process
Hybrid Generation, Electromagnetic Frequency Regulator and Optimization, Desalinators
This work proposes the analysis of the technical and economic feasibility of a Water System.
Wind-photovoltaic (E-PV) Electric Power Generation (SHGEE), applied to a desalination system, with a focus on the sustainable service of isolated communities. It also aims to reduce dependence on fossil fuels and increase the
energy reliability in regions of the semi-arid Northeast.
In addition, the recent technological innovations of integration of different sources
encouraged research. In this sense, the advantages added to the Electromagnetic Frequency Regulator (REF) are adopted. This equipment is capable of
maintain the frequency of electrical energy from sources of intermittent speed,
converting it into a constant frequency. Among many applications, it is useful for the
activation of sensitive loads, such as desalination systems, especially in
scenarios of disconnection from the conventional power grid; that is, off-grid.
The evaluation of the feasibility of the system is conducted through an optimization process based on energy service as a priority and, as a subsequence, the
economic sustainability as a function of Net Present Value (NPV). The objective function used in this work is a continuous and nonlinear function, defined in three variables
decision: maximum number of users, and installed potentials of the sources of
tions. This nonlinearity stems from the physical modeling of wind and photovoltaic generation,
the hourly energy balance, the behavior of the storage system and the
economic structure of the NPV. Thus, investment costs, revenues and
and penalties associated with the technical and operational constraints of the system.
The optimization surface is of the multimodal type, as there are multiple optimal locations,
Typical condition of hybrid power generation systems subject to technical variables
and economic. Given this complexity, a meta-heuristic method in an algorithm
(AG) is implemented in the MATLAB environment. Finally, based on studies
previous and in the results obtained, the feasibility of the proposal presented is verified.