21-05-2012, 04:03 PM
MPPT Operation for PV Grid-connected System using RBFNN and Fuzzy Classification
[attachment=22604]
INTRODUCTION
THE Kyoto agreement on global reduction of greenhouse
gas emission has prompted interest on renewable energy
systems worldwide. Nowadays photovoltaic energy is one of
the most popular renewable sources since it is clean,
inexhaustible and requires little maintenance. However, it still
presents a lake of competition comparing to conventional
energy resources due to its high cost and low efficiency during
energy conversion. Regarding to this, it is necessary to optimize
the performance of PV systems through the operation of
conversion systems to increase the output efficiency of the
overall system. This approach is commonly named as MPPT,
several methods are referred in the bibliography: the P&O
method is the most commonly used in practice due to its
simplicity and ease of implementation, however, this algorithm
can fail or oscillate around the Maximum Power Point (MPP)
under sudden sunlight changes [1, 2].
OVERVIEW OF THE SIMULATION SYSTEM
the overall of the studied system, composed of a
20 kW photovoltaic generator connected to the main electric
grid via two power electronics stages. The first stage consists of
a DC-DC converter that insures impedance adaptation between
the generator and the load by tracking the reference voltage
estimated by the neuro-fuzzy network. While the second stage
is composed of a DC bus and a PQ inverter that injects the
power generated by the PV generator into the main grid, where
the inverter is acting as power controller ensuring a high power
factor. In the following subsections, all the components of the
grid connected PV system are described in details.
DC-DC boost converter
The operating point of a PV generator connected to a load is
the intersection of the load curve and the PV current-voltage
characteristics. In case of resistive load, the load characteristic
is a straight line with slop
[attachment=22604]
INTRODUCTION
THE Kyoto agreement on global reduction of greenhouse
gas emission has prompted interest on renewable energy
systems worldwide. Nowadays photovoltaic energy is one of
the most popular renewable sources since it is clean,
inexhaustible and requires little maintenance. However, it still
presents a lake of competition comparing to conventional
energy resources due to its high cost and low efficiency during
energy conversion. Regarding to this, it is necessary to optimize
the performance of PV systems through the operation of
conversion systems to increase the output efficiency of the
overall system. This approach is commonly named as MPPT,
several methods are referred in the bibliography: the P&O
method is the most commonly used in practice due to its
simplicity and ease of implementation, however, this algorithm
can fail or oscillate around the Maximum Power Point (MPP)
under sudden sunlight changes [1, 2].
OVERVIEW OF THE SIMULATION SYSTEM
the overall of the studied system, composed of a
20 kW photovoltaic generator connected to the main electric
grid via two power electronics stages. The first stage consists of
a DC-DC converter that insures impedance adaptation between
the generator and the load by tracking the reference voltage
estimated by the neuro-fuzzy network. While the second stage
is composed of a DC bus and a PQ inverter that injects the
power generated by the PV generator into the main grid, where
the inverter is acting as power controller ensuring a high power
factor. In the following subsections, all the components of the
grid connected PV system are described in details.
DC-DC boost converter
The operating point of a PV generator connected to a load is
the intersection of the load curve and the PV current-voltage
characteristics. In case of resistive load, the load characteristic
is a straight line with slop