Hybrid Predictive Models for Accurate Forecasting in PV Systems

Hybrid Predictive Models for Accurate Forecasting in PV Systems

The accurate forecasting of energy production from renewable sources represents an important topic also looking at different national authorities that are starting to stimulate a greater responsibility towards plants using non-programmable renewables. In this paper the authors use advanced hybrid evolutionary techniques of computational intelligence applied to photovoltaic systems forecasting, ...

Hybrid Neural Models for Time-series Forecasting

Three new hybrid neural models which are based upon the basic neural model put forth by McCulloch and Pitts (Haykin, 1999) and the compensatory neural models by Sinha et al. (2000), (2001) are proposed in this paper. The basic neural and the compensatory neural models are modified to take into account any linear dependence of the outputs on the inputs. This makes the hybrid models suitable for ...

Model Predictive Control of Three Phase Inverter for PV Systems

This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize the TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of a boost converter (BC), maximum power point tracking (MPPT) co...

Rural Electrification with PV Hybrid Systems

Accurate Event Detection for Simulating Hybrid Systems

It has been observed that there are a variety of situations in which the most popular hybrid simulation methods can fail to properly detect the occurrence of discrete events. In this paper, we present a method for detecting discrete which, using techniques borrowed from control theory, selects integration step sizes in such a way that the simulation slows down as the state approaches a set whic...