Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect

Abstract

Solar energy is the greatest source of energy for earth system. Solar based energy harvesting models are already developed but unavailability of sunlight most the time is the major drive behind the quest of finding new and modern sources of energy. Alternatively, wind energy is of great importance since it is always in motion. Wind dependent energy harvesting from trees and grass movement is a new milestone in this quest as they are in abundance in almost every environment. The idea was to use the piezoelectric effect i.e. the production of electric charge/polarity by the application of mechanical stresses in non-conducting crystals. The useable magnitude of harvested energy was studied through an efficient energy harvesting model for an area and its feasibility was prepared for large scale application using geographic information system (GIS). The developed model addressed the concern of cost, efficiency and the scale of extracted energy available for use. A mathematical model was developed to predict dynamic responses of trees to wind determining translational sway of tree components. Trees were considered as 1D slender structures with one degree of freedom in response to direct dynamic wind load. For tree model, the mechanical stresses produced during tree sways due to induced vibrations, e.g. wind or seismic vibrations, by means of a piezoelectric transducer, was used to harvest energy. For grass model, piezoelectric material was used instead of piezoelectric transducer which was combined with grass that acted like an artificially modeled grass. It was studied that how much energy could be transferred to piezoelectric transducer or material from the movement of tree and grass and extracted later on for various purposes. Applications of harvested scale of energy have also been proposed for practical use purposes.

Keywords: Mathematical modeling; structural & fluid dynamics; wind energy; slender structures; mechanical vibrations; sensor networks; geographic information system (GIS)

Full text

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 1
ABSTRACT
Solar energy is the greatest source of energy for earth system. Solar based energy harvesting models
are already developed but unavailability of sunlight most the time is the major drive behind the quest
of finding new and modern sources of energy. Alternatively, wind energy is of great importance
since it is always in motion. Wind dependent energy harvesting from trees and grass movement is a
new milestone in this quest as they are in abundance in almost every environment. The idea was to
use the piezoelectric effect i.e. the production of electric charge/polarity by the application of
mechanical stresses in non-conducting crystals. The useable magnitude of harvested energy was
studied through an efficient energy harvesting model for an area and its feasibility was prepared for
large scale application using geographic information system (GIS). The developed model addressed
the concern of cost, efficiency and the scale of extracted energy available for use. A mathematical
model was developed to predict dynamic responses of trees to wind determining translational sway
of tree components. Trees were considered as 1D slender structures with one degree of freedom in
response to direct dynamic wind load. For tree model, the mechanical stresses produced during tree
sways due to induced vibrations, e.g. wind or seismic vibrations, by means of a piezoelectric
transducer, was used to harvest energy. For grass model, piezoelectric material was used instead of
piezoelectric transducer which was combined with grass that acted like an artificially modeled grass.
It was studied that how much energy could be transferred to piezoelectric transducer or material
from the movement of tree and grass and extracted later on for various purposes. Applications of
harvested scale of energy have also been proposed for practical use purposes.
Keywords: Mathematical modeling; structural & fluid dynamics; wind energy; slender structures;
mechanical vibrations; sensor networks; geographic information system (GIS)
1. INTRODUCTION
The greatest energy source for mankind is the hot
burning sun itself undergoing nuclear fission and
fusion reactions all the time but worldly
limitations are pushing humans to find new and
modern sources of energy. Unavailability of
sunlight all the time due to earth’s rotation,
inclination angle or different topographic
conditions at different places is the major drive
behind the quest of new and modern sources of
energy. The scale and rapidness of depletion of
fossil energy resources including oil, coal and
natural gas in addition to depletion of non-
renewable energy resources further aggravates
the problem of limited energy. Pursuing the
trending research in energy harvesting from
various physical systems, an energy harvesting
model is prepared consuming tree and grass
movement using piezoelectric effect. The sway of
trees and grass is predicted through a
mathematical model that acts as one part of the
input domain of energy harvesting model.
Lumped mass approach with a single degree of
freedom was used to predict the inertially coupled
system dynamics of trees. Due to difference of
many physical properties between trees and grass
the sway prediction model was simplified for
grass. Euler-Bernoulli beam theory was
incorporated to the system for the sway prediction
model of grass considering it analogous to elastic
cantilever beam with dominant dynamic wind
load.
Piezoelectric energy harvesting model for trees is
proposed with simplified input parameters like
wind speed, diameter and height of tree that
generates the magnitude of harvestable energy
from that tree. Piezoelectric transducer links the
input and output domains of the system. For grass
the model is altered in a way that piezoelectric
transducer is abstractly replaced with
piezoelectric material integrated with proper
circuitry. The artificially modelled piezoelectric
grass would be responsible for the energy
generation from applied mechanical strains.

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 2
1.1 LITERATURE REVIEW
Ongoing research on plant biomechanics is an
academic venture between mathematicians,
physicists and engineers. The work of Galileo
Galilei in studying resistance of bending stresses
and the proposition of Hooke’s law by Robert
Hooke can be accounted as one of the earliest
discoveries in the subject. The logical
arrangement of plant biomechanical research
topics ranges from the internal cellular structure
and material properties of plant to the responses
developed due to interaction of tree with the
external environment [1].
Schwendener (1874-1887) linked correctly the
cross sectional variation of tensile and
compressive stresses with the ecological habitat
experienced by each plant [2]. Oltmanns in 1923
[3] and Rasdorsky in 1930 [4] drew attention that
plants are flexible as well as rigid enough to
withstand dynamically imposed fluid induced
drag forces along with their own weight which is
static in nature. Both argued convincingly that the
growth, architectural anatomy and morphology of
plants are adaptively responsive to dynamic and
static forces.
To understand the dynamic responsiveness and
mechanical stability of trees James in 2006
proposed a model that included the effect of the
damping of a small swaying mass of various tree
components which were inertially coupled to a
larger swaying mass in such a manner that large
sway amplitudes were constrained [5]. In another
study, he concluded that this mass damping effect
in combination with the drag forces curtails the
sway energies making the tree able to survive
large wind forces. He also suggested the failure
mechanism of trees as one or both of the two: (a)
wind throw i.e. failure of the root plate and (b)
limb failure i.e. failure due to localized stresses
on the material [6].
To predict the natural frequencies and modes of
oscillations of trees, a model was developed by
Gardiner et al. in 1998 comprising of coupled
second order differential equations which
resulted in a transfer function. He negated the idea
to assume branches as masses lumped together.
Rather, he proposed that the branches need to be
treated as coupled cantilevers attached to the stem
[7].
Researchers across the globe have developed
many vibration based piezoelectric energy
harvesting models with applications to many real
time physical systems. Energy harvesting models
from tree movement have also been developed in
last decade. Tree based piezoelectric energy
harvesting model by Hobbs et al. in 2011 is a
good example of such models. They designed and
tested micro watt energy harvesters stimulated by
the trunks of trees swaying in the wind and
measured the harvested energy as a function of
trunk spacing, wind speed, and relative positions
of the tree trunks within the array [8]. In the same
year McGarry et al. studied the potential for
energy harvesting from tree motion. They
investigated the extent of energy and power
available from the movement of a tree, horizontal
acceleration of free movement and the angular
deflection of the tree movement to determine the
magnitude of energy and power offered to
different types of energy harvesting devices [9].
Similar study has been done by Hobeck et al. in
2012 resulting in a model developed for grass
[10]. He is one of the first researchers to propose
and experimentally validate his idea of artificial
piezoelectric grass for energy harvesting from
turbulence induced vibration and, eventually,
achieve highest productivity using this method.
1.2 WIND ENERGY
Wind energy is an important source of energy as
the wind is always in motion. The kinetic energy
possessed by the wind can be scavenged through
standard procedures to be used for advantageous
applications. Wind-structure interaction is a
complex phenomenon to study and predict
completely. The pressure difference on windward
and leeward side separates the flow which form
shear layers and wake region. Dynamic nature of
wind also adds varying impact force to the
system. These impact, shear and torsional
response components form vortices which are
amplified due to inertial coupling of the structure.
The consequence of this dynamic excitation is
normally known as vortex induced vibrations.

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 3
The complexity arises because of the
asymmetrical edifice of trees and varying nature
of wind. The time and space dependent variation
of magnitude and direction of wind introduces
non linearity which makes the problem complex.
Therefore studies have been done with
simplifications and abstractions done to the real
world systems. In that regard, the incidental wind,
comprising of drag and lift forces, was assumed
to be applying harmonic drag force only. Lift
forces were ignored because the enough stiffness
of the tree to overcome vertical strain. Nominal
amount of vertical strain concludes insignificant
contribution to the harvestable energy from the
system.
The local conditions also play an important role
in determining the scale of energy that can be
scavenged. It is not feasible to allow the use of
photovoltaic or wind energy harvesters in
obstructions and thick forests due to large
difference of sway amplitude on top and bottom
of tree, lesser wind velocities at base and
unavailability of sunlight under forest canopies.
1.3 PIEZOELECTRICITY
Physical world is governed by three basic
conservation laws i.e. (a) Mass balance (b) Force
balance from Newton’s second law of motion and
(c) Energy balance. The underlying physics of
piezoelectric effect is based on these conservation
laws that allows the production of electric charge
by the application of mechanical stresses and vice
versa in non-conducting crystals. Asymmetrical
composition of crystals point to the Nano scale
study of these crystals that leads us to the concept
of polarization. Polarization is the dipole density
that results from difference of charge across two
points. The applied stresses tend to change the
molecular geometry of the crystals forcing the
particles to rearrange themselves in such a way
that polarity is relatively unidirectional. On the
other hand, if a piezoelectric material is placed in
an electric field, material deformation would be
observed in relation to the relative polarity of the
crystals and applied electric field. This
rearrangement results in generation of electric
charge from applied mechanical strain and
material deformation from applied electric field
which is a form of conservation.
Piezoelectric materials are of many kinds
depending upon the nature, composition and
behavior of its constituting crystals. These are
available in many forms including (a) single
crystal (e.g. quartz), (b) piezoceramic (e.g. lead
zirconate titanate or PZT), (c) thin film (e.g.
sputtered zinc oxide), (d) screen printable thick-
films based upon piezoceramic powders and (e)
polymeric materials such as
polyvinylidenefluoride (PVDF). [11]
1.4 ENERGY HARVESTING IN
MODERN WORLD
Energy harvesting is a trending research topic
observed in the last decade. Energy harvesting
simply means the mechanism to obtain, derive
and store energy from one source and harnessing
it with a system to be exploited in the form of
another. The scarcity of energy i.e. not being able
to meet demands from available resources, is due
to depletion of fossils and dependence on non-
renewable energy resources. To counter that we
need to consider sustainable plans for energy
production, distribution and composition. Energy
scavenging is one of the potential solution to the
problem of limited energy. Fluid driven wind
mills and water wheels are the earliest yet
efficient examples of energy harvesting
techniques. The use of thermal energy for
electrical power generation through pyroelectric
effect is also used for energy harvesting models.
Piezoelectric effect converts applied mechanical
strain to electrical charge is also an advancement
in the subject. Natural and transmitted radiations
also act as a wireless energy source using
photovoltaic effect. Models created on bio-
energy, geothermal and tidal waves are also seen
in working condition lately. Technological
advancement has led to the development of
Micro-Electro-Mechanical Systems (MEMS) to
power small autonomous sensors networks.
Electrostatic, magnetic and thermoelectric based
energy harvesting devices have also been
established. The topic nowadays is combining
researchers from fields having mechanics, energy
and smart materials background.

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 4
2. MATERIALS AND METHODS
2.1 TREES
Morphological complexity of trees with nonlinear
wind dynamics is a challenge to researchers
pursuing to understand true dynamic response of
trees. The functional anatomy of trees comprising
of connection of trunk to branches, branches to
stems and stem to leaves makes it a complex
network.
Trees have adaptive growth which makes them
smartly optimized structures. The roughly
circular shape of the trunk explains the equal
distribution of stress due to uniform moment of
inertia about both horizontal axes. The variation
in thickness and thinness of the growth rings
shows stress history which can be used to predict
the patterns of wind velocity and direction. The
stiffness of trees is adaptively adjusted to the
scale of wind loads such that the response
deflections can be accounted in elastic range. This
ambient elasticity allows trees to produce sways
without undergoing plastic deformations or
failure eventually.
2.1.1 Sway Prediction Model of Trees
Slender structures are the ones having one longer
dimension as compared to the other two other
dimensions. The diameter (D) is a two
dimensional quantity and the height (H) being one
dimensional quantity. Since the diameter to
height ratio (D/H) of tree is very low, generally,
therefore dynamic analysis of tree was considered
analogous to slender structures.
The varying magnitude and direction of wind in
three convective and one temporal dimension is a
complex phenomenon to solve analytically. The
abstractions to be done to the real runtime
behavior of trees to counter simultaneous
convection-diffusion process, nonlinearities and
wind vortices are hard to predict. The
characterization of one-dimensional continuous
structural models is done by their spatially and
temporally dependent displacements and
velocities along the system. These models are
governed by a set of partial differential equations.
One degree of freedom simplifies the analysis if
time step is in an acceptable small scale range.
To predict tree sway using mechanical dynamics
of slender structures for one degree of freedom
Mass-Spring-Dashpot system by lumped mass
approach can be expressed mathematically as:



where; x is the time dependent translation
displacement, m is the lumped mass of the tree,
F(t) is externally coupled force in the system, c is
the damping coefficient and k is the stiffness
coefficient.
Determining the damping coefficient is a tough
call to make, since, as proposed by Milne in 1991
[12] and refined by James in 2003 [6], the total
damping of sway was found to be consisting of
three fundamental components:
 Mass damping: Interference of branches
with those of neighbors dependent on the
distance to neighbors and relative sizes of
the chosen tree and its neighbors
 Hydraulic damping: Aerodynamic drag
on foliage i.e. larger for larger trees and
energy loss pattern are similar to the loss
using drag coefficients of wind tunnel
 Viscoelastic damping: Damping in the
stem i.e. linearly related to the stem
diameter
Ground Level
Total
Height
(H)
Sway (x)
DBH ~
1.35m
Wind/Drag
Force Direction
Figure 1: Schematic Representation of Tree Sway in
Dynamic Wind Load

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 5
The scaled importance of these three damping
components to overall damping was established
in the ratio 5:4:1 for the median sized trees.
The magnitude of dynamic excitation of trees in
response to wind can be predicted from the
following equation:


where; x is the translation displacement, m is the
lumped mass of the tree, F(t) is externally
coupled force in the system, c is the damping
coefficient and k is the stiffness coefficient. The
externally applied force as a function of time is
taken as:  
where; w is natural frequency, t is time period, φ
is phase shift and FD is drag force which is given
by:


in which, ρ is density of air (1.225 kg/m3), v is
wind velocity, Cd is drag coefficient an A is the
projected frontal area. Combining all equations
final ready-to-be-modeled equation is as follows:




This equation was modeled afterwards using a
computational software shown and explained in
the subsequent section.
2.1.2 Energy Harvesting Model from Tree
Sway
A number of methods have been considered to
achieve an efficient energy harvesting model,
including “tethered” and “inertial” energy
harvesting approaches, of which only the former
approach was considered feasible [9]. The model
proposed in this study is also based on the
“tethered” approach in which an optimized string
with minimal weight inclined at a suitable angle
is fastened to the different points in tree which is
attached to a piezoelectric transducer. Different
transducers are patented with all details provided
that can be purchased or constructed for academic
purposes with due permissions. The potential
energy imparted on tree by kinetic energy of wind
is converted in transducer and stored in capacitors
to be supplied later on for various purposes.
Piezoelectric material shows different vibrational
modes at different frequencies depending upon its
shape therefore area vibrational mode due to
combined effect of flexure, torsion and shear is
considered in this model. Piezoelectric energy
harvesting models operate efficiently at
frequencies as low as 100 Hz and as high as 1
GHz but the frequency of mechanical vibrations
of trees is relatively low. In order to overcome
this limitation the combination of vibrational
modes is proposed. However, vortex induced
vibrations of flexural nature due to applied lift
and drag forces on trees were considered
dominant after scaling analysis of the dynamic
system.
The process flow diagram of energy harvesting
model is a form of feedback loop shown
hereunder:
Figure 2: Process Flow Diagram of Developed Energy
Harvesting Model
Stepping forward, in addition of the sway
prediction equation, the work done on the tree due
to drag force can be expressed as:

where; FD is the drag force in the direction of the
displacement x(t) predicted earlier.
In order to determine the drag force value of ρ i.e.
density of air was taken as 1.225 kg/m3, value of
v i.e. wind velocity was assumed to be 5 m/s,

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 6
value of projected frontal area of sphere with
average diameter of 5 meters was taken as 19.63
m2 and the value of CD i.e. drag coefficient for
ellipsoid was taken as 0.2 in turbulent range of
Reynolds’s numbers from the table developed by
White [13]:
L/d
Laminar
Turbulent
0.75
0.5
0.2
1
0.47
0.2
2
0.27
0.13
4
0.25
0.1
8
0.2
0.08
Table 1: Drag Coefficients for Ellipsoid
To determine the harvestable energy, from the
work done, the energy can be simple calculated as
a function of rate of change of work done,
expressed as:
 

where; WD is the work done in a specific time
interval t. It has also been studied in the past that
the magnitude of this harvestable energy is
reduced as a function of the overall spring
constant. This energy magnitude could be used to
generate power according to its scale and
magnitude.
To practically convert this mechanical energy
into electrical energy, there are three major kinds
of transducers adopted by researchers in energy
harvesting models namely, electromagnetic,
piezoelectric and electrostatic transducers of
which piezoelectric energy harvesters have
ambient power density and simpler structure to be
used in MEMS technology.
2.2 GRASS
Grass is a natural material having similar origin
as of trees in terms of internal material
organization but it differs in terms of external
responses to loading. Moore et al. in 2004
conducted experiments on 602 trees of eight
different species. They found that the natural
sway frequency of almost all species was strongly
and linearly proportioned to the ratio of diameter
at breast height (DBH) to total tree height (H)
squared (i.e., DBH/H2). They also established the
fact that the difference between natural
frequencies of unbranched trees and branched
trees increased with an increasing ratio of
DBH/H2 and the natural sway frequencies of
unbranched trees were significantly higher than
those of the same trees with branches [14].
Considering this finding, we revised the model
and ignored the lumped mass approach to predict
sways for grass.
2.2.1 Sway Prediction Model of Grass
Mechanically speaking, grass is different from
trees in a many ways, as:
 It shows highly elastic behavior in
response to dynamic wind load as
compared to trees.
 It is always engulfed by local obstructions
in the form of closely packed grass around
itself.
 It has relatively reduced surface area to
withstand wind drag and lift forces.
 No coupled mass is attached to grass
while tree trunks have branches, twigs and
leaves attached to it.
Therefore, in spite of lumped mass modeling
approach, keeping in view the material properties,
general in-situ conditions and local variability of
the physical model, Euler–Bernoulli beam theory
was used to predict the sway of grass. Grass has
been considered a beam for Euler–Bernoulli
beam theory because of the following two key
assumptions:
 Cross sections of the grass are assumed
rigid which do not deform considerably
under the application of transverse or
axial loads.
 There is no rotation of the cross section
around transverse axis of the grass.
Euler–Bernoulli beam equation can be stated as:
 


where, w is the distributed load intensity, y is the
out-of-plane displacement, E is the elastic
modulus of grass and that I is the second moment
of area of the grass's cross-section.

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 7
Figure 3: Schematic Representation of Grass Sway in
Dynamic Wind Load
2.2.2 Energy Harvesting Model from Grass
Sway
A single leaf stalk type piezoelectric energy
harvester was examined in smooth and aspects of
replicated Atmospheric Boundary Layer (ABL)
turbulence at differing wind velocities that
concluded some noteworthy outcomes. They
verified through experimentation that the
harvester performance degrades as the impact
angle of wind is increased and for parallel flow,
performance is again decreased in turbulence as
compared to smooth flow. However, for off-axis
flow at higher wind speeds the harvester
performance is enhanced in turbulence compared
to smooth flow [15]. Using their findings the
assumptions for the model proposed in this paper
are prepared accordingly. Direct dynamic load at
right angle in smooth flows is considered for
maximum parallel flow performance of the
harvester.
It is to be made sure that the artificially modeled
grass is properly held at the base to act as rigid
beam taking load at right angle producing enough
bending strains to give ambient harvestable
energy.
The energy harvesting model for grass is same as
that of tree’s model. The only difference is that
here the piezoelectric transducer is replaced by
the piezoelectric material itself. This material of
optimized piezoelectric grass harvester prototype
was placed in such a way that it acts as a
cantilever to wind loading. The variations of drag
force imparted on tree and resulting
displacements are shown in the graphs attached
hereunder. The displacement magnitude is further
multiplied with the imparted drag force to express
the work done by the drag force in the direction
of the sway displacement. This variation has also
been generated and shown hereunder:
Figure 4: Drag Force Variation with Time
Figure 5: Dynamic Sway Variation with Time
Figure 6: Work Done Variation with Time
Total Height
(H)
Sway (x)
Wind/Drag Force
Direction

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 8
2.3 LARGE SCALE APPLICATION
MODEL
The model can be used as an integral part of the
process of development of sustainable energy
systems. Urban buildings aiming at sustainability
and eco-friendly environment can integrate small
devices capable to harvest energy from the
proposed model and artificially designed
piezoelectric grass fields. These fields are capable
of acting as source to low power technologies
such as surveillance cameras, sensor nodes, LED
lightings and many more.
The Area of Interest (AOI) was taken on Canal
Bank Road in Lahore, Pakistan comprising of
densely residential area along with open grounds
and parks. This combination is nearly present in
all urban dwellings. The imagery was taken from
Google Earth™ and further processing including
Geo Referencing and digitization was done in
ArcGIS 9.3 software.
The first input parameter for large scale
application for grass model was the energy
produced per unit area to be calculated from the
model proposed in previous section. The other
input parameter was the area of grassy field to be
calculated from ArcGIS digitization in projected
coordinate system. The product of both
parameters resulted in the total amount of
harvested energy from an area comprising of
grassy fields. For large scale application of tree
model, the input parameters are the harvestable
amount of energy from one tree and the number
of trees in an AOI resulting in total amount of
harvested energy in that AOI.
Area of Interest (AOI) - Lahore Canal Bank Road, Lahore, Pakistan
Figur 7: Geo Referenced AOI
Figure 8: Digitized output of AOI
Figure 9: Digitized AOI for Grassy Fields
Figure 10: Digitized AOI for Number of Trees

National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 9
3. CONCLUSION
3.1 FUTURE PROSPECTS
Prototype development should be considered of
miniature size and optimized power output
capable to power small autonomous devices like
wrist watches, mobile phones, LED etc. A sensor
network of accelerometers should be used in all
three dimensions to verify the translational
displacements of trees predicted from the
mathematical model. Experimental study should
be carried out to identify how much energy could
be transferred to piezoelectric material from
movement of grass and extracted later on.
3.2 DISCUSSION
This study provided an overview of the related
studies done in past for developing models for
energy harvesting from tree and grass movement.
The novelty introduced in this study was to link
the dynamically predicted sways and
piezoelectric energy harvesting models. The sway
prediction model acted as one part of the input
domain of the energy harvesting model.
Piezoelectric transducers and material was used
to harvest energy from tree and grass movement
based piezoelectric energy harvesting model. The
developed model had an environmental
supremacy as ecological complications like
chemical waste production, depletion of fossil
and nonrenewable energy resources and bringing
about large scale pollution would be reduced if
this model is implemented properly. This model
replaces batteries and endorses tree plantation
instead of promotion of bio degradation for
energy production. The proposed large scale
model has the potential for monetary gains by
reducing maintenance costs and is one of the
distinguished sustainable solutions for energy
production locally and globally.
4. ACKNOWLEDGMENT
The work was done under the supervision of Dr.
Shahid Ali without whose help and motivation the
work would not have been possible. The author
also acknowledges the supportive and research
orientated environment provided at Department
of Civil Engineering of National University of
Computer and Emerging Sciences (NUCES)
which is a part of Foundation for Advancement of
Science and Technology (FAST).
5. REFERENCES
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National Multidisciplinary Engineering Conference (NMEC 15), November 2015, Lahore, Pakistan.
Pakistan Academy of Sciences (PAS) & Pakistan Engineering Council (PEC), Islamabad, Pakistan.
Energy Harvesting Model From Tree And Grass Movement Using Piezoelectric Effect (NMEC ENE 28)
Muhammad Hassan Khan Niazi1 & Dr. Shahid Ali
1Contact: hassaniazi@gmail.com / +92 324 452 1015 Page | 10
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