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Energy Procedia 36 (2013) 546 – 557
TerraGreen 13 International Conference 2013 - Advancements in Renewable Energy
and Clean Environment
A computer program development for sizing stand-alone
Photovoltaic-Wind hybrid systems
a
H. Belmilia, M. F. Almia, B.Bendiba, S. Boloumaa,*
Group of research: Photovoltaic system, Unit of Development of Solar Equipments (UDES)/EPSTT CDER
Route Nationale N°: 11 Bou-Ismaïl
LP 365, Tipaza 42415, Algeria,
Abstract
The exhaustion and all the drawbacks of fossil fuels are the main elements that led to the development and use of new
alternativesfor power generation based on renewable energy,amongthem: photovoltaic energy systems, windenergy
systems and their combination in a hybrid photovoltaic-wind system.
In this paper we proposed a sizing approach of stand-alone Photovoltaic-Wind systems which is evaluated by the
development of a computer applicationbased essentially on Loss of Power Supply Probability (LPSP) algorithmto
provide an optimal technical-economic configuration. An example of a PV-Wind plant sizing is presented and
discussed.
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Authors.
Published by Elsevier
Ltd. Ltd.
© 2013
2013The
The
Authors.Published
by Elsevier
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peer-review
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Academy Academy.
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Keywords: Software, Sizing, Photovoltaic, Wind, LPSP Algorithms, Hybrid System;
1. Introduction
In a general context, Hybrid Energy Systems (HES) combine two or more complementary renewable
sources like wind turbines and photovoltaic generators and/or
d
one or more conventional sources like
diesel generators [1]. Naturally, renewable sources are not constant, so their combination with
conventional ones allowsan uninterrupted power generation. Most hybrid systems have an energy storage
system [2].There are many systems for storage; electrochemical batteries, inertial storage and hydrogen.
* Corresponding author. Tel.: +213-24-41-02-00; fax: +213-24-41-01-33.
E mail address:belmilih@yahoo.fr.
E-
1876-6102 © 2013 The Authors. Published by Elsevier Ltd.
Selection and/or peer-review under responsibility of the TerraGreen Academy
doi:10.1016/j.egypro.2013.07.063
H. Belmili et al. / Energy Procedia 36 (2013) 546 – 557
The latter is limited in storage capacity and has a high cost. In general there are three main aspects to
consider for a hybrid system [3]:
x The hybrid system configuration with respect to the available resources and constraints utilization.
x The optimization of the available renewable resources exploitation.
x The optimization of the output power quality.
There are many configurations of hybrid systems. The most popular are: DC-bus configuration and
DC/AC mixed bus configuration. In what follows we present a brief description of these architectures.
1.1 DC bus architecture
In this case the power provided by each source is centralized on a DC-bus, figure.1. The matching
between the DC bus and the AC loads is possible by using DC-AC inverter, the advantage of this
architecture is that the control system is relatively simple [4].
Fig.1. DC Bus architecture
1.2 Mixed-bus AC / DC Architecture
This architecture is more efficient compared to the DC bus architecture. Indeed in this case the wind
generator output power can be directly feed the AC load which increases the system performance. Where
there is a surplus of energy, the batteries will start charging, figure.2. For the converters, it can be a single
bi-directional between the two buses DC and AC replaces the other two converters unidirectional [2, 4].
Fig.2. DC - AC Bus Architecture
1.3
operating strategy
It is an algorithm that manages the flow of energy in the different system components. Depending on the
load profile and the characteristics of system, as well as the requirements on power quality [2, 3].
The operation of a hybrid system depends on the following parameters:
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x The load profile, diurnal variations, seasonal variations, peak dips…etc.
x Renewable resources: the mean, standard deviation, frequencies of events, extreme values, diurnal
variations, seasonal variations
x The system configuration: number and types of components
x Standards of power quality.
1.4 Storage Management
x The storage strategy in the short-term "Shaving pecker Strategy", allows you to filter out fluctuations
in renewable energy and/or load.
x The long-term strategy "Cycle Charge Strategy" is used to supply the load for a long period of time; it
also improves energy balance [4].
1.5 Load management
It can be seen as short-term or long-term expenses that are connected or disconnected according to
their priority:
Fig.3. Load management
2. The studied hybrid system
Figure 4 presents the hybrid system. This system is based on a photovoltaic and an asynchronous
machine wind turbine. The storage part is connected to DC-bus through a shopper. DC loads are supplied
directly from DC-bus by using DC/DC chopper and AC loads are fed using DC/AC inverter.
The photovoltaic generator is connected to the DC-bus through a DC/DC chopper controlled by an
MPPT controller; however the wind generator is connected to both the DC and AC buses.
We denote the energy produced for a period of a typical day Ep, where Ep = EPV + EW, and on the
other side the energy consumption: Ec. the flow of energy is shown in the Fig.5.
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DC BUS
Fig.4.Configuration of the standalone studied PV-Wind hybrid system.
Fig.5. Energy flow diagram
ip
ic
Assuming the bus voltage is still constant, it can resonate in current such as:
Ep
24h.U c
(1)
Ec
24h.U
(2)
We can establish the nodes equation: i p ic ib , where ib is the equivalent battery current. If there is
an imbalance between production and consumption, this difference will vary the DC-bus voltage for a
period of time ΔT, the timewhen the battery is working: either to charge or to discharge, we can write:
'T . I p I c
§ 'U ·
(3)
C¨
¸ I p Ic Ÿ C
'U
© 'T ¹
In this way we can estimate a priori the value of the battery capacity.
ic
The following diagram gives a synopsis of the developed software
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H. Belmili et al. / Energy Procedia 36 (2013) 546 – 557
Fig.6. synopsis of the developed software
3. Explanation of the developed interface:
In this section we have developed a software code for sizing PV-Wind hybrid system which is based on
the loss of power supply probability (LPSP) method [5,9]. The design of a facility window for LPSP
sizing appears with five buttons in order to carry the different tasks in the sizing procedure, figure 7.
Fig.7. LPSP based window
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When a button is clicked, a new window appears, allowing the user to define the various quantities and
constants that characterize his system size. These windows are discussed below.
3.1 Sites Sittings: Selecting this button will lead us to the next window:
In this window the user can choose the location where he will implement his installation: a database
provided by NASA gives us the different values necessary for our design: temperature, sunlight, pressure,
wind speed...etc. Once the location is well chosen it is validated by clicking the OK button: the icon that
was red turns green to confirm this validation. We reduce the window and we move to the second button.
Fig.8. Sitecharacterizations.
3.2 Load characteristics
This step is crucial, the user must specify the load profile [6, 12]; this can be done in two ways:
x
x
Daily average load: where the user should provide the load values during 24 hours within a
typical day in each month.
Monthly average load: where the user is prompted to enter the daily average load value of his
load.
For the daily average load whenever the user entered a value, he must increment time by clicking the
increment button.
At the end user must provide the rated values: number of days of autonomy, to be able to operate the
system using the storage and the probability of dissatisfaction LPSP in the load [7, 13]. The validation is
done by a click on the submit button, the icon red becomes green for the confirmation of validation.
H. Belmili et al. / Energy Procedia 36 (2013) 546 – 557
Fig.9. Load profile window
Fig.10. monthly Average consumption
3.3 Technical parameters
When clicking the technical parameters button, a new window appears, which bring together all the
parameters characterizing the system, it is unscrewed in four fields:
x Adjustment of the range of system production: the user must specify the maximum power, the power
and the minimum increment step for each PV system and wind, figure11.
Fig.11. Variation interval of production sources
Parameters of the photovoltaic generators: to calculate the power of PV generator, the user is prompted for this field: the
performance of the panel, NOTC temperature, reference temperature (usually it is equal to 25°C), the temperature coefficient β
(generally between 0.004 and 0.006) [8], figure.12.
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Fig.12. PV Generator parameters
x Parameters of wind generators: in this field the user must specify the ranges of variation of the used
wind turbines. There are three tracks to complete, and every power range of wind turbines must enter
their speed characteristics: Release, Nominal, and Maximal (that according to Power (speed) turbines
gives by manufacturers) [9].
Fig.13. Wind generator parameters
3.4 Technical parameters
When clicking the technical parameters button, a new window appears, which bring together all the
parameters characterizing the system, it is unscrewed in four fields:
Adjustment of the range of system production: the user must specify the maximum power, the power and
the minimum increment step for each PV system and wind, figure11.
3.5 Storage Settings
To define the storage capacity of the overall system, the user must enter the storage capacity in [Ah]of
a single battery, the performance of charging and discharging, the depth of discharge and voltage rating
[10] (it depends on the continuous bus used in the system), figure 14.
At the end make sure to fill the box that defines the performance of the inverter use, typically it is
around 90-98% [11], and once the user finishes entering All parameters specified must be validated by a
click on the red icon and the green confirms validation.
3.4 Economic Parameters
The economic parameters are in a direct relationship with the overall cost of the installation, select ing
this button will lead us to a new window where the user is prompted for each component: the photovoltaic
panel, the wind, batteries, inverter and its initial price, and maintenance price in $/W and its life time [12,
13], figure 15.
H. Belmili et al. / Energy Procedia 36 (2013) 546 – 557
Fig.14. Storage system and inverter parameters
Fig.15. Economic parameters window
3.4
System sizing
On reaching this stage, the user had finished entering all parameters and constants characterizing the
hybrid system, it should be emphasized that, before the design, the user is strongly advised to check the
validation of the values recorded after each step, verifying that the red icon before the OK button is set to
green each time. Clicking this button will lead us to a new summary window across the sizing; it appears
as shown in the figure below:
4
5
6
7
8
9
The user will find this window in the optimal configuration of the hybrid system design:
The optimal power of the wind turbine to be used;
optimal power photovoltaic panels;
The number of batteries;
The number of autonomy days;
The overall cost of the facility;
LPSP.
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Fig.16. Screen of simulation results
Other configurations that satisfy the condition specified in the value of the IPPL are classified in a table,
to fill the calculated results from the user presses the button "Add Results". Graphs are provided by
clicking different buttons:
10 "Draw the graph of PV power"
11 "Draw the graph of wind power"
12 "Draw the graph of the number of battery"
13 "Draw the graph of the overall cost"
3. Conclusion :
In this work we have implemented the LPSP method for the sizing of a standalone PV-Wind system.
This method is based in principle on a technical-economic strategy that’s depending on the cost study
taking into account the different equipment’s, the load profile and the meteorological characteristics of
H. Belmili et al. / Energy Procedia 36 (2013) 546 – 557
each installation site. This method allows to define several configurations results that satisfy the profile
load. The economical study is then performed to determine the optimal configuration. The following
step of this work is the design and the realization of the software which can support this analysis study. A
presentation of this software is established carefully to explain the LPSP sizing technique of PV-Wind
hybrid system. Our software has become practical, interactive and easy to use. This elaborated simulation
program allows as to determine the optimum size of battery bank and PV array for an autonomous PVwind hybrid energy system for a given load and a desired loss of power supply probability based on the
minimum cost of the system. The total cost also depends on investment cost, operation and maintenance
costs, depreciation period and energy produced in one year, in addition to external trends such as the cost
of batteries (subject to legislation affecting the cost of new materials and the cost of disposal), the
potential downward trend of equipment costs with rising volumes etc. The competitiveness of a hybrid
system also depends on the relative cost of fossil fuels and the demand for renewable energy from the
market. The competitiveness of a hybrid system also depends on the relative cost of fossil fuels and the
demand for renewable energy from the market.
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