Title of article :
Numerical simulation analysis of the impact of photovoltaic systems and energy storage technologies on centralised generation: a case study for Australia
Author/Authors :
Yaici, Wahiba CanmetENERGY Research Centre - Natural Resources Canada - Ottawa, Canada , Brenna, Morris Department of Energy - Politecnico di Milano - Via La Masa 34 - 20156 Milan, Italy , Corradi, Alessandro Department of Energy - Politecnico di Milano - Via La Masa 34 - 20156 Milan, Italy , Foiadelli, Federica Department of Energy - Politecnico di Milano - Via La Masa 34 - 20156 Milan, Italy , Longo, Michela Department of Energy - Politecnico di Milano - Via La Masa 34 - 20156 Milan, Italy
Abstract :
In response to climate change concerns, most of the industrialised countries have committed in recent years to increase their
share of Renewable Energy Sources to reduce Greenhouse Gas emissions. Therefore, the rapid deployment of small-scale
photovoltaic (PV) systems, mainly in residential applications, is starting to represent a considerable portion of the available
electrical power generation and, for this reason, the stochastic and intermittent nature of these systems are affecting the operation
of centralised generation (CG) resources. Network operators are constantly changing their approach to both short-term
and long-term forecasting activities due to the higher complexity of the scenario in which more and more stakeholders have
active roles in the network. An increasing number of customers must be treated as prosumers and no longer only as consumers.
In this context, storage technologies are considered the suitable solution. These can be necessary in order to solve and fill
the problems of the renewable distributed sources are introducing in the management of the network infrastructure. The aim
of this work was to create a model in order to evaluate the impact of power generation considering PV systems in Australia
along with a model to simulate Battery Energy Storage Systems (BESSs) and Electric Vehicles future contributions using
MATLAB. The methodology used to develop these models was based on statistical assumptions concerning the available
details about PV systems installed and current storage technologies. It has been shown that in all the scenarios analysed, the
future adoption of rooftop PV panels and impact on the CG is incredibly higher than the uptake of energy storage systems.
Hence, the influence on the demand will be driven by the behaviour of the PV systems. Only in the hypothetical scenario
in which the installations of BESSs will assume comparable levels of the PV systems, it will be possible to better manage
the centralised resources.
Keywords :
Electric vehicles (EVs) , Photovoltaic system (PV) , Battery energy storage system (BESS) , Distributed generation (DG) , Centralised generation (CG)
Journal title :
International Journal of Energy and Environmental Engineering (IJEEE)