Supervision of a Hybrid Renewable Energy System by an Evolutionary Fuzzy System: Modeling and Implementation

In Hybrid Renewable Energy Systems (HRES), energy flow management is necessary to ensure a continuous power supply for the load demand and a reliable HRES. However, the dynamic interaction between renewable energy sources and the load demand generates serious problems of stability. Therefore, there is a need to control and supervise systems based on renewable energy in order to overcome the transient response in energy distribution network. To carry out an HRES supervision in this work, the modeling and experimental implementation of supervisory control is presented with an intelligent systems approach inspired by the paradigm of evolutionary and fuzzy computing, on an HRES composed of two renewable energy subsystems ( solar and wind) and a storage system. The methodology for the design of the supervisor is divided into several steps from the working specifications of the HRES to the experimental implementation of the supervisor in a simulation model.