Variable-Speed Microhydropower Plant Using Adaptive MPPT

ISSN 2319 – 1953 International Journal of Scientific Research in Computer Science Applications and Management Studies
IJSRCSAMS Volume 3, Issue 5 (September 2014) www.ijsrcsams.com
Variable-Speed Microhydropower Plant Using
Adaptive MPPT Soma Sekhar
Abstract—Hydropower systems use the energy in flowing water to
produce electricity or mechanical energy. Although there are
several ways to harness the moving water to produce energy, run-
of-the-river systems, which do not require large storage
reservoirs, are often used for microhydropower systems. For
Variable speed microhydropower energy systems the maximum
power point tracking (MPPT) is a very important requirement in
order to maximize the efficiency. And these have recently received
significant attention in the renewable energy field, because of its
overall efficiency and great potential available worldwide. In this
paper, a variable-speed microhydropower plant based on a semi-
Kaplan turbine is employed and a novel adaptive high-
performance MPPT technique is proposed. This allows high
tracking quality due to superior dynamic response and high
output power quality due to steady-state oscillations cancellation.
This approach has been simulated by using
MATLAB/SIMULINK.
point tracking (MPPT), permanent magnet synchronous
generator (PMSG), variable-speed operation.
ORC Optimal regimes characteristic.
SMC Sliding mode controller.
THD Total harmonic distortion. PI Proportional-integral controller.
TT , PT , Turbine torque and turbine power.
Ω, Tem Generator rotational speed and electromechanical
torque.
Te,K, δ, kup, kdown Adaptive MPPT algorithm parameters.
UDC, IDC DC-link voltage and current injected in the
dc link.
filter in grid mode.
ia, ib, ic, isa, isb, isc Generator and grid three-phased currents.
η Hydraulic turbine efficiency. Ph, PT Hydraulic and mechanical powers.
uG, uL Generator-side and grid-side converters’ duty
cycles
a dramatic technical progress because of their major
importance to the sustainable development. These power systems such as wind, tidal, or even microhydro need to
improve their operation in terms of efficiency and integration
to the power grid both from technical and economical
viewpoints. Hydroelectricity is the term referring to electricity
generated by hydropower. It is the most widely used form of
renewable energy, accounting for >16 percent of global
electricity generation – 3,427 terawatt-hours of electricity
production in 2010 and is expected to increase about 3.1%
each year for the next 25 years. Countries such as Brazil, the
U.S., and Norway produce significant amounts of electricity
from very large hydroelectric facilities. However, there are also many regions of the world (e.g., China) that have a significant
number of small hydro power plants in operation. There is no
universally accepted definition of the term microhydro
which, depending on local definitions, can vary from a few
kilowatts up to 100 kW.
The microhydropower has a huge potential throughout the
world, which would allow significant contribution to future
energy needs [1], [2]. In the new context of electricity
merchandizing and regulations, this technology represents a
good solution in terms of cost and environmental impact. As
the primary resource is continuous and predictable, these
systems can constitute the basis of future microgrids especially in the insulated sites. The variable-speed generation
technology, which is well established in WECS and available
at a reasonable cost, has recently generated a significant
interest in microhydro applications by offering the possibility
of avoiding adjustable turbine blades and wicket gates [3], [4].
The variable-speed capability allows for the improvement of
the operation efficiency of microturbines in numerous aspects
[5]. First, the energy efficiency or power regulation may be
achieved. Also, the cavitation effect [6] can be mitigated and
the drive trains can be simplified by eliminating the gearbox
and eventual flywheels. Water hammer disturbances and governing problems are considerably simplified, resulting in
saving space, equipment, and low cost maintenance [1]. The
power grid ancillary services can be insured as well by creating
spinning reserves. The variable speed is an efficient way to
optimize the transients in pumped-storage plants [7].
Fig. 1. Diagram representing the MHPP under study.
The large majority of small and microhydro plants are run
of river, which implies that they have low heads with high
water flow rates. This makes the Kaplan and the semi-Kaplan
(propeller) turbines most attractive prime movers for such
applications [2], [8]. The associated electrical configuration
including the power interface depends on the chosen generator
and on the power grid itself [9]. The associated control system
has a classical structure that separately handles two subsystems
decoupled by the power electronics interface itself. In this
context, the generator-side control loop deals with turbine
operation and the grid-side control loop which ensures the
transfer of the generated power to the utility grid [10], [11]. There are two important topics related to these control
structures that have been approached in this paper. First, the
energy optimization of the turbine in the previous presented
context (i.e., cost-effectiveness of the installation and low cost
maintenance) by means of an MPPT algorithm has been taken
into account [12]. This operation may have adverse influence
on the output power quality; this aspect is analyzed and
handled in the second topic of this paper. Concerning the
MPPT algorithms, these have been extensively developed
within renewable energy system controls such as wind turbines
or photovoltaic systems [9], [13]. However, in this paper, a novel adaptive P&O algorithm that ensures a fast maximum
power point (MPP) tracking without supplementary
information is employed (in terms of water flow
measurements, system parameters identification, etc.). This
algorithm also significantly mitigates the shaft rotational speed
oscillations in steady state and increases the output power
quality [14].
This paper is organized as follows: the next section is
dedicated to the presentation and analysis of the studied
system. In Section III, the control strategy of the studied
MHPP is presented. The proposed adaptive MPPT algorithm is detailed in Section IV. In Section V, the simulation results are
briefly presented and some conclusions are drawn in section
VI.
The MHPP under study is globally represented by the setup
depicted in Fig. 1. It consists of an axial flow hydraulic (semi-
Kaplan) turbine with fixed blades and fixed-position wicket
gates. The turbine is fed by a penstock linked to a fore bay
which is supplied by an upstream canal (see Fig. 1). This
configuration can be found near permanent creeks and rivers
that never dry up, and these are the most suitable for low-head
microhydro power production [1]. In order to decrease the
installation operating and maintenance costs, the inbound water
flow is not controlled and no water flow sensor is employed. In
this context, the turbine is completely exposed to the falling
water gravitational energy, i.e., to its inherent variations.
Similarly to the wind turbines case, the operating range, determined by the extreme water flow values, is defined by a
technical study of the implantation site. The plant must be
protected against floods or dangerously high water flows by an
upstream protective device.
The electrical machine is a PMSG of few kilowatts, rigidly
coupled to the hydraulic turbine. The generator is interfaced to
the utility by means of a power electronics converter consisting
in a back-to-back two-level voltage-source inverter (VSI) [10].
The grid-side converter is connected to the utility via an ac
power transformer. The turbine converts the falling water
gravitational energy to mechanical power. The expression of
the available (potential) hydraulic power depends on the water head and water flow
rate
(discharge)
expression:
where PT is the mechanical power produced at the turbine
shaft (Watts), η is the hydraulic turbine efficiency, ρ is the
volume density of water (kg/m3 ), g is the acceleration due to
gravity (m/s2 ), Qw is the water flow rate passing through the turbine (m3 /s), and H is the effective head of water across the
turbine (meter).
The model of hydraulic turbines commonly used in the fixed
speed operation is the one that gives a linear falling mechanical
torque versus rotational speed characteristic [3], [8]. This
simple modeling behavior gives good performances for an a
priori designed head and water flow rate operating point but is
not suitable for variable-speed operation. In this case, advanced
models that accurately reflect the real system conditions are
needed because the efficiency of the hydraulic turbine depends
strongly on the operation conditions such as head, water flow
rate, and shaft speed [3], [4]. In this paper, the modeling approach of the considered
hydraulic turbine is based on the efficiency versus rotational
speed characteristic drawn as to correspond to semi-Kaplan
axial flow micro hydraulic turbine with non pitchable blades
and fixed position wicket gates. This is often used for low head
and high flow rates; however, in the recent literature, some
advanced models for the axial-flow hydraulic turbines
efficiency have been published [4]. These models are either
deduced from the so-called efficiency hill curves, which are
given by manufacturers or by experimental tests on reduced-
scale prototypes in laboratory conditions and the results are
extrapolated to large scale using the similarity
Fig. 2. Performance of a semi-Kaplan hydraulic turbine: projection on the
plan water flow—rotational speed.
laws in hydraulic machines [15]. These 3-D characteristics
may be projected on the plan water flow—rotational speed for
various power efficiency values, as shown in Fig. 2.
This figure shows that a change in the operation speed can improve the turbine efficiency which means that the harvested
power can be maximized for any operating point (in terms of
water flow rate, water head, and rotational speed). Note that it
is quite difficult to extract a useful model (from the control
viewpoint) from these curves. Instead of using these 3-D
models, one may prefer to consider the water head fixed and to
model the system accordingly. For obtaining an optimal
turbine operation, the control structure should be designed such
as to take into account the water head variations and to
mitigate their effect on the system output. To this purpose, a
tracking algorithm (MPPT) will be employed for searching the
maximum power available in the water flow by using available information like the output power and rotational speed. For a
fixed head, the steady-state power efficiency of the considered
hydraulic turbine has a unimodal shape as experimentally
described in [4]. The same work provides an analytical
expression for the power efficiency that has been identified via
interpolation, given in
with
λi = [1/(λ + 0.089) − 0.0035]−1 , and λ = RAΩ/Qw (4)
where R is the radius of the hydraulic turbine (meter), A is
the area swept by the rotor blades (m2 ), and Ω is the rotational
speed (rad/s).
The family of curves of power efficiency as described by (3)
for various values of the water flow rate are presented in
Fig. 3. The maxima of these curves are forming a geometric locus named ORC (see Fig. 3). Note that these shapes are
significantly sharper than in the case of full Kaplan turbines
that usually operate at fixed speed [1]. This means that the
semi-Kaplan turbine efficiency is very sensitive to water flow
And rotational speed variations. That is why the variable-
speed operation has a great potential in ensuring the maximum
turbine efficiency in a large range of operating points (in both
water flow rates and rotational speeds).
For a fixed water head, the turbine hydrodynamic torque
depends only on the water flow rate and on the rotational speed
and is given by TT (Qw , Ω) = PT /Ω. (5)
Neglecting the mechanical friction effects, the turbine motion
equation is given by
TT (Qw , Ω) − Tem = JdΩ/dt (6)
where J is the total inertia of the turbine–generator coupling
and Tem is the generator (electromagnetic) torque. As will be
detailed in the next section, Tem can be imposed with a
sufficiently high dynamic in order to conveniently drive the turbine at variable rotational speed [16].
Fig. 3. Semi-Kaplan (or propeller) steady-state characteristics: efficiency
versus rotational speed.
Among the possible variable-speed MHPP architectures, the
electrical power chain presented in Fig. 4 shows a great
potential as it has been successfully tested in other application
fields such as WECS and tidal generation systems [5], [9],
[10]. The semi-Kaplan turbine is directly coupled to the PMSG
which is increasingly favored in developing new designs because of its high efficiency and high power density [5]. A
back-to back three-phased (PWM) power electronics converter
implements the interface between the generator and the utility
grid and splits the generating system into two separate plants.
The control structure has three layers (levels), as shown in Fig.
4. The innermost one consists of the control of both inverters
current control. The intermediate layer deals with the rotational
speed control through the generator-side converter and the
control of the dc-bus voltage; finally, the outermost control
loop performs various functions such as operation
optimization, supervision, protection, and eventual ancillary
services.
The control strategy in grid-connected mode determines the
tasks that must be performed by each of the two converters. In
fact, searching for the MPP, solicitation of the machine to its
unity power factor and reducing THD are the tasks assigned to
the generator-side converter. Besides all these, the grid-side
converter maintains the dc-bus voltage at a constant value in
order to evacuate the generated electrical power to the utility grid.
A. Generator-Side Subsystem
In the grid-connected mode (or PQ mode [10]), the variable
speed operation is used for maximizing the turbine output
power which consequently will minimize the effect of
cavitations that presents nwanted consequences such as flow
instabilities, excessive vibrations, and damage to turbine blades
[6]. The generator-side subsystem is composed of hydraulic
turbine, a PMSG, an ac/dc converter, and an absolute position
encoder (see Fig. 4). Its associated control structure is based
upon the PMSG Park model (dq frame) and the generator is
field-oriented controlled [17]. The electromagnetic torque is therefore imposed separately by means of the quadrature
current component iqG, while the field orientation is achieved
by regulating the direct current component, idG to zero
(armature flux position imposed at π/2). This two control loops
are build using second-order SMCs [18], and the interaction
between the channels d and q has been suppressed by
using a decoupling structure [19].
The d-current control loop has not been figured in Fig. 4 for
sake of simplicity. The PMSG speed control relies on
employing an outer loop over the q-channel control loop (see
Fig. 4). The speed PI controller employed in the outer loop is designed by using the symmetrical optimum criterion, thus
allowing an optimally sized closed-loop ramp response [16].
This controller outputs the electromagnetic torque reference,
and hence, the i∗ qG value. One must note that in the real
application, this structure is more complex, as it includes the
Park transformations (d, q) ↔ (a, b, c) computed using the
rotor absolute position [20], pulse width modulators, and other
circuit elements.
The grid-side subsystem is composed of a dc-link bus, a
dc/ac converter (VSI), filter, and the power grid (see Fig. 4). In order to transfer the available electrical active power, the three-
phased currents are fed into the mains, while controlling the
dc-link voltage at an imposed constant value Udc. The MHPP
should also be able to supply reactive power to the grid and to
provide supplementary means for ac voltage control. The
control structure is based upon three current control loops for
the grid current components, and an outer voltage control loop,
which regulates the dc-link voltage Udc at an imposed value.
The current loops include effective resonant PI controllers
(generalized integrators) [10], [11].
The dc-link voltage controller provides the amplitude of the
output currents. A phase lag between the current references and the grid voltages can also be used if reactive power is to be
supplied to the grid. To this end, a software three-phased
phase-locked loop is employed [21]. The third control level
(see Fig. 4) changes the turbine operating point in order to
maintain the optimal operating regime in a variable and quasi-
unknown environment. Actually, as a simplified model has
been used, the real power coefficient curves are unknown due
to the absence of information regarding water flow and water
head values. This determines the use of a robust P&O
searching algorithm that tracks for the actual MPP. This
algorithm will be detailed in the next section.
Fig. 4. MHPP-based generation system: subsystems and the associated control for grid-connected mode.
IV. SIMULATION RESULTS
Fig 5. Simulink model of hydropower plant
Fig 6. (a)grid voltage (b)grid current, (c)VSC voltage (d)dc link voltage
(e)modulation index
Fig 8. Active Power and Reactive Power
Fig 9. Generator current and Speed
V. CONCLUSION
configurations are based on the variable-speed pitch control
and the fixed-speed stall-control concepts. A systematic
analysis of the adaptive technique for MPPT to variable speed MHPP has been given in this research paper.
The proposed adaptive technique is universal, does not
require any preset constants unlike the classical techniques that
suffer from steady-state oscillations and that are context
dependent, moreover the proposed technique can be easily
adapted to wind, tidal, and photovoltaic systems. Using the
proposed technique the achievement of the high-performance
dynamical operation with no oscillations around the MPP has
been demonstrated.
The overall performances of these systems can be improved
by the variable-speed operation for the MHPPs which is an emergent technology, in terms of cost-effectiveness, operating
efficiency, reliability, captured power, etc. When operating in
free water flows the variable-speed operation capability
combined with P&O techniques is a very powerful way of
ensuring high energy efficiency.
With respect to the classical P&O, the quality of the output
current injected to the power grid has been greatly improved in
this context. It needs a minimum number of sensors and
depends on a relatively simple digital algorithm in order to
conclude the effectiveness of the proposed technique. It can be
easily implemented in Matlab/Simulink. The future works should focus on the proposed adaptive MPPT performance
when feeding power in a significantly perturbed grid (voltage
sags, etc.). An optimal adaptation of the MPPT gain should
also be anticipated. Finally, the proposed method can also be
applied to wind turbines operating in turbulent winds or in
photovoltaic systems.
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Variable-Speed Microhydropower Plant Using Adaptive MPPT

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