Long-term operation optimization of integrated generation systems by fuzzy logic-based management

The aim of this paper is to implement a smart control strategy to improve the long-term energy performance of stand alone electric generation systems integrated by renewable energy systems (photovoltaic and wind energy conversion systems). The paper describes a fuzzy logic application to optimize the energy management (EM) of integrated generation systems (IGS) and shows its effectiveness in exploiting the qualitative information, on an optimal operation of diesel groups (DGs) and of renewable generating units (available from manufacturers) as well as on the operating experience of IGSs supplied by highly variable and sitespecific renewable energy sources and coupled with different load demand patterns. As a case study, a rule-based operation planning strategy has been implemented to a small size experimental IGS prototype in order to minimize both fuel consumption and load energy not supplied. The simulation results prove that a fuzzy-based EM, taking into account the fuzziness of predicted wind and solar resources as well as user load demand, assures better energy performance on long-term operations than conventional approaches.