Abstract: The use of hydroelectric pump-storage system at large
scale, MW-size systems, is already widespread around the world.
Designed for large scale applications, pump-storage station can be
scaled-down for small, remote residential applications. Given the cost
and complexity associated with installing a substation further than
100 miles from the main transmission lines, a remote, independent
and self-sufficient system is by far the most feasible solution. This
article is aiming at the design of wind and solar power generating
system, by means of pumped-storage to replace the wind and /or solar
power systems with a battery bank energy storage. Wind and solar
pumped-storage power generating system can reduce the cost of
power generation system, according to the user's electricity load and
resource condition and also can ensure system reliability of power
supply. Wind and solar pumped-storage power generation system is
well suited for remote residential applications with intermittent wind
and/or solar energy. This type of power systems, installed in these
locations, could be a very good alternative, with economic benefits
and positive social effects. The advantage of pumped storage power
system, where wind power regulation is calculated, shows that a
significant smoothing of the produced power is obtained, resulting in
a power-on-demand system’s capability, concomitant to extra
economic benefits.
Abstract: To explore how the brain may recognise objects in its
general,accurate and energy-efficient manner, this paper proposes the
use of a neuromorphic hardware system formed from a Dynamic
Video Sensor (DVS) silicon retina in concert with the SpiNNaker
real-time Spiking Neural Network (SNN) simulator. As a first step
in the exploration on this platform a recognition system for dynamic
hand postures is developed, enabling the study of the methods used
in the visual pathways of the brain. Inspired by the behaviours of
the primary visual cortex, Convolutional Neural Networks (CNNs)
are modelled using both linear perceptrons and spiking Leaky
Integrate-and-Fire (LIF) neurons.
In this study’s largest configuration using these approaches, a
network of 74,210 neurons and 15,216,512 synapses is created and
operated in real-time using 290 SpiNNaker processor cores in parallel
and with 93.0% accuracy. A smaller network using only 1/10th of the
resources is also created, again operating in real-time, and it is able
to recognise the postures with an accuracy of around 86.4% - only
6.6% lower than the much larger system. The recognition rate of the
smaller network developed on this neuromorphic system is sufficient
for a successful hand posture recognition system, and demonstrates
a much improved cost to performance trade-off in its approach.
Abstract: A compound parabolic concentrator (CPC) is a wellknown
non-imaging concentrator that will concentrate the solar
radiation onto receiver (PV cell). One of disadvantage of CPC is has
tall and narrow height compared to its diameter entry aperture area.
Therefore, for economic reason, a truncation had been done by
removed from the top of the full height CPC. This also will lead to
the decreases of concentration ratio but it will be negligible. In this
paper, the flux distribution of untruncated and truncated 2-D hollow
compound parabolic trough concentrator (hCPTC) design is
presented. The untruncated design has initial height H=193.4mm
with concentration ratio C_(2-D)=4. This paper presents the optical
simulation of compound parabolic trough concentrator using raytracing
software TracePro. Results showed that, after the truncation,
the height of CPC reduced 45% from initial height with the
geometrical concentration ratio only decrease 10%. Thus, the cost of
reflector and material dielectric usage can be saved especially at
manufacturing site.