By Cliff Ortmeyer, Global Head of Solutions Development, Newark element14
Energy Harvesting and
Storage Drive Expansion
of IoT Applications
An Io T application can only go as far as its edge devices can take it.
Acritical constraint for edge devices is power availability—as the name implies, an edge device can
exist or move among any number of far-flung locations,
where a power supply is not available. Consider, for
example, a tracker application in which a device is
dropped into a parcel consigned for shipment; the user
can track the parcel during its journey and check its
progress or condition. Clearly, no tethered connections
are possible, so the device must communicate wirelessly
while relying on an internal power source.
In other scenarios, edge devices may be located in
remote areas, and possibly in large quantities. Not only
are power mains unavailable, but maintenance visits to
replace batteries are also time-consuming and expensive.
Edge sensor designers can respond by using rechargeable
batteries or supercapacitors together with an energy
harvesting strategy to recharge them in the field. Energy
harvesting is attractive, as it taps into an inexhaustible
supply of ambient energy. It is also challenging, and may
not meet power needs of the node without a deliberate
approach to low-power design.
Low-Power Design to Make Energy Harvesting Practical
Edge sensor power consumption is driven by the need
to digitize, package, and transmit measured data to a
gateway. These functions require at least the sensor,
a microprocessor complete with crystal oscillator,
memory array, and possibly A/D converter, plus the
communications interface hardware.
There are a number of design techniques to minimizing
power demand in an edge sensor:
• Sleep mode: choose a processor that can
be efficiently driven into sleep mode when
measurements aren’t necessary, and draws minimal
leakage current while asleep.
• The choice of local network protocol: some
protocols may have more data bandwidth than
required, while drawing excessive power to
• Component choice and programming: overall,
a designer needs to select a processor, memory
subsystem, oscillator, and A/D converter for
minimum power consumption, as well as coding the
system to maximize energy efficiency.
By minimizing edge sensor power requirements,
energy harvesting solutions may be sufficient to deliver
the power required when ambient energy is available
in adequate quantities. There are four main ambient
energy sources available in the environment: mechanical,
thermal, radiant, and biochemical. These energy sources
are characterized by different power densities, the most
popular being radiant and mechanical.
Capturing Radiant Energy with Solar PV Cells
Solar cells can harvest radiant light energy, converting
it directly into a flow of electrons due to a photovoltaic
(PV) effect. Solar cell technologies have evolved over
• First generation types are mainly based on silicon
wafers and typically perform at about 15–20 percent
efficiency. They offer good performance, but are rigid,
and their production is energy-intensive.
• Second generation cells are based on amorphous
(non-crystalline) silicon, so they cost less than first
generation. They deliver typically 10–15 percent
efficiency, and have some flexibility. Production is still
energy intensive, and the use of scarce elements limits
• Third generation solar cells use organic materials
such as small molecules or polymers. Therefore,
they offer great potential for advantageous pricing,
efficiency, and are now being commercialized. Today,
their performance and stability is currently limited
compared to first- and second-generation products.
Solar energy has the potential to power Io T devices
indefinitely, but there are application challenges. Many
solar cells are too bulky, rigid, or inefficient for use in
small and remote Io T devices.