Investigation of energy, water, and electromobility through the
development of a hybrid renewable energy system on the island of Kos
IASONAS NIKAS-NASIOULIS, MARIA MARGARITA BERTSIOU, EVANGELOS BALTAS
Department of Water Resources and Environmental Engineering, School of Civil Engineering,
National Technical University of Athens
5 Iroon Polytechniou, 157 80, Athens
GREECE
Abstract: The lack of fresh water and energy independence in remote islands leads to the investigation of
Hybrid Systems (HS). In this paper, the implementation of wind energy for meeting energy, water, and
electromobility demands on a Greek island is examined. The stochastic nature of wind potential leads to the
introduction of energy storage units. Energy storage can be achieved through the HS, which utilizes the rich
wind potential of the island of Kos, stores excess energy through pumping to an upper reservoir, and produces
hydropower in order to cover the energy deficit. The HS in this study consists of a wind farm with a total
capacity of 9.4 MW, which is composed of 4 wind turbines of 2.35 MW, two desalination units with a total
capacity of 2275 m3/day a 10 kW power pump for pumping the desalinated water to the drinking water
reservoir with a capacity of 180000 m3. It also consists of a hydro turbine of 5 m3/s and an upper reservoir with
a capacity of 400000 m3 at a height of 176 m above the hydroelectric station. The first operated scenario aims
to meet the energy and water needs of Pyli (3500 inhabitants). The second scenario aims to cover the
electromobility and water needs of 20000 inhabitants, which is equivalent to the entire city of Kos. The
simulation models operate with hourly meteorological and demand data for the period 2016-2020, results about
CO2 emissions, before and after the integration of the HS are presented, and a cost-benefit analysis is performed
for the first scenario.
Key-Words: Hybrid system, Wind power, Electricity, Water management, Desalination, Electromobility, Kos
island
Received: April 29, 2021. Revised: March 23, 2022. Accepted: April 26, 2022. Published: May 23, 2022.
1 Introduction
For many years, the majority of power generation
systems around the world have relied on non-
environmentally friendly thermal power plants. In
modern societies, the use of environmentally
friendly energy sources and the awareness of the
environmental impact of polluting fossil fuels is
getting attractive. Today the focus is both on the
adequacy of energy supply and on the
environmental impact of specific sources. In this
context, the European Union (EU) has launched a
series of actions and support measures for the
further expansion of Renewable Energy Sources
(RES).
In Greece, there is a special interest in the
development of RES, especially in its island sector,
as most of the islands are not connected to the
energy network of the mainland [1]. Also, during
the summer months, there are high energy
requirements due to the tourist traffic. The
electricity needs of these islands are usually met
either by autonomous power plants based on fossil
fuels or through their interconnection with the
mainland, which leads to energy dependence and
poor quality of electricity [2,3]. With the
development of RES units, an island becomes more
autonomous, the dependence on fossil fuels is
reduced and the fares to the EU are reduced [4].
Greek islands in general are suitable for the
installation and operation of wind farms, due to their
very high wind potential. Today, more and more
studies serve the energy supply for islands in the
world [5-9].
In the same direction as RES units, the
replacement of vehicles with electric vehicles is in
progress. In the next years, the number of electric
vehicles will increase significantly, both
internationally and nationally [10,11] Also, with the
horizon of green growth, an additional goal is the
supply of recharging infrastructure, to come
exclusively from electricity production through RES
[12,13]. Already, with the development of tax
incentives, it is becoming more attractive to install
recharging infrastructures that operate with energy
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
543
Volume 18, 2022
from alternative sources, thus making charging
100% green. In recent years, the share of CO2
emissions from the transport sector has risen in the
EU from 32% in 1990 to 45% in 2015. Furthermore,
road transport accounts for 92% of CO2 emissions
from the transport sector, and between 1990 and
2015 CO2 emissions from cars accounted for half of
the road transport emissions. This means that
transportation is a key sector for the goal of
minimizing CO2 emissions [14].
At the same time, the lack of water resources
worldwide is worrying. This problem affects also
Greece, where most of the islands have limited
water resources. Many Greek islands face water
scarcity problems. Current practices to ensure water
supply in small dry islands in Greece are not
sustainable and environmentally friendly, especially
during the tourist period, where water needs
increase significantly [15]. Meeting the water needs
of the islands takes place in two ways, either by
transporting drinking water by tankers, a process
that is quite expensive, or by dams (where possible),
or by costly energy-intensive drilling from
underground water. In the case of the Greek islands,
which are surrounded by the sea, the development
of seawater desalination systems is a solution for the
water needs [15,16]. Restrictions of groundwater
pumping will reduce the problem of salinization of
the aquifers and will increase the groundwater table.
In order to meet the energy and water demands
of the islands and to deal with the stochastic nature
of wind energy, it is necessary to introduce energy
storage units [17,18] in autonomous island systems
[19]. Today, numerous researchers studied a
solution that includes energy storage [21-26].
Energy storage can be achieved through a HS,
which utilizes the rich wind potential of an island
and uses excess energy to pump seawater to the
upper reservoir [27,28]. Respectively, when there is
an energy deficit, the hydroelectric station is
activated and energy is produced. This is achieved
by converting the gravitational potential or kinetic
energy of the stored water for energy production
[29]. Α significant number of previous research
works have already studied the introduction of HS
on non-interconnected islands. Groppi et al. [5]
present solutions that address the stochasticity of
RES through the improvement of network capacity,
such as energy storage technologies. In addition,
Alves et al. [6] investigate the interconnection
between islands, in order to reach 100% renewable
energy systems in isolated islands. Petrakopoulou et
al. Al [18] estimate the cost of HS on a Greek island
and compare it to the cost of a local fossil fuel
power station. Icaza-alvarez et al. [21] present,
regarding 2050 targets, a zero-emission system
coupling with RES for the fragile ecosystem of the
Galapagos Islands of Ecuador. Segurado et al. [24]
promote a methodology for optimizing the size and
operation of a desalination unit powered by wind
and hydroelectric energy. Jurasz et al. [25] develop
a new mathematical model for planning the
operation of the HS 25 to 48 hours ahead, according
to meteorological forecasts. Liu et al. [30] study an
optimal capacity planning method for an HS with a
desalination unit using linear programming. Tsai et
al. [31] use a Philippine offshore island to optimize
the capacity planning of an HS using the Hybrid
Optimization Models for Energy Resources
(HOMER) software. Hamanah et al. [32] investigate
the sizing of an HS using the annual cost as an
objective function. Finally, Abdul-Wahab et al. [33]
investigate solutions for supplying electricity to
consumers in an off-grid remote area using the
HOMER software.
The object of the present research is the
simulation of an HS to meet the desalinated water,
energy, and electromobility needs on the island of
Kos. The project includes four wind turbines, a
hydroelectric station, a desalination unit, a pumping
station, a seawater reservoir, and finally, a drinking
water reservoir. Two scenarios are implemented
based on different priorities for on-demand
coverage. Also, results about CO2 emissions are
presented, and a cost-benefit analysis is performed
for the first scenario. The paper’s contribution is
summarized in the methodology for the assessment
of an HS for the water and energy demands
fulfillment and, also, the estimation of CO2
emissions before and after the application of HS on
the island of Kos, which is used as a case study. The
savings from the reduction of the CO2 emission
costs are then calculated, based on European
Union's taxes. Extensive historical data is used for
the water and energy needs of the island. In
addition, the contribution of each energy source to
the island's energy mix per month and the monthly
coverage of energy needs by the HS is presented.
Moreover, the penetration of electromobility on the
island and its connection to the HS is investigated.
The estimation of the number of vehicles and their
hourly demands per day, in line with the national
target of Greece [34] for a green transition in the
transport sector, is examined. Finally, a cost-benefit
analysis is conducted for the economic feasibility of
the proposed system and the profitability of the
investment.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
544
Volume 18, 2022
2 Problem Formulation
2.1 General Description of the Study Area
Kos is a Greek island, part of the Dodecanese island
chain group in the southeastern Aegean Sea. It is the
third-largest island of the Dodecanese after Rhodes
and Karpathos. The surface of the island is 295.3 sq.
km. with a coastline of 112 km. The capital of the
island is Kos, which is the main port of the island. It
is 200 nautical miles from the port of Piraeus. The
island also has an airport which is located 27 km
southwest of the city of Kos, near the village of
Antimacheia. The population of the island according
to the 2011 census amounts to 33388 permanent
residents. The island has tourist traffic during the
whole year. The population, especially during the
summer months, is double. The climate of Κοs is
the Mediterranean, characterized by mild winters,
with plenty of rain, strong winds, and periods of
relatively high sunshine. The dry or hot season lasts
from the end of April until mid-September. In terms
of temperature, according to Kos’ meteorological
station of the National Meteorological Service
(NMS), the lowest average minimum appears in
February (8.32 οC) with an average absolute
minimum temperature of 2.75 οC, while the highest
average maximum temperature appears in July
(30.67 οC) with an average absolute maximum
temperature of 35.75 οC. As for the precipitation, it
should be noted that the average rainfall is 559.54
mm with December appearing with the highest
average monthly rainfall of 121.96 mm. January is
the month with the highest maximum daily rainfall
(134.90 mm). In terms of winds, the prevailing
winds are North with an average annual number of
days that show an intensity above 8 Beaufort at 18,
most of them appear from December to March.
2.2 Electricity and Water Needs in Kos
The energy needs of the island are served by an
autonomous power station of 138.74 MW located in
the area of Mastichari, west of the island. It supplies
electricity to the island of Kos, Kalymnos, Tenedos,
Leros, Lipsi, Gyali, Nisyros, Tilos, and Pserimos.
The main source of energy is the thermal power
plant that is installed on the island.
The water needs of the island are covered mainly by
groundwater and natural springs. The available
water covers completely the water supply needs.
The tourism sector consumes very high quantities,
as a result of which it operates in competition with
the agricultural sector. However, there are water
supply projects aimed at meeting both irrigation and
household water needs. The monthly variations of
water and electricity needs are shown in Fig.1 and
Fig. 2.
According to the national target of Greece [34],
electric vehicles will be 82422 by 2030 and will
correspond to 1.39% of the total amount. The
estimated total fleet of 12518 vehicles corresponds
to 174 electric vehicles on Kos. According to
published papers [35,36], about 68% of vehicles are
expected to be charged during the night hours (8 pm
to 8 am) when vehicle owners have returned home,
and 27.5% are expected to charge during the day
(from 10 am to 5 pm) at other charging points, such
as publicly accessible points located on the road, or
in workplaces. Based on the above, the hourly load
distribution by the fleet of electric vehicles is shown
in Fig.3
Fig. 1: Mean monthly demand for water supply
Fig. 2: Mean monthly energy demand
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
545
Volume 18, 2022
Fig. 3: Hourly load distribution by the fleet of
electric vehicles
2.3 Technical Description
The HS in this study consists of a wind farm with a
total capacity of 9.4 MW, which is composed of 4
wind turbines Enercon E-92 of 2.35 MW. Τhe wind
farm is located at an altitude of 303 m. In addition,
the HS consists of two desalination units with a total
capacity of 2275 m3/d and a capacity of 6.5 kW/m3,
in order to produce drinking water. The desalination
unit is accompanied by a 10 kW power pump to
pump the produced desalinated water to the drinking
water reservoir with a capacity of 180000 m3. The
drinking water reservoir is located next to the
desalination unit. The HS also consists of a hydro
turbine of 5 m3/s, in order to produce hydroelectric
energy. The seawater reservoir with a capacity of
400000 m3 is located at a height of 176 m above the
hydroelectric station. The existing local power
station meets the demand when the required energy
is not produced by the HS. The schematic
representation of the HS is shown in Figure 4.
Fig. 4: Schematic representation of the HS
3 Problem Solution
3.1 Methodology
In order to calculate the estimated wind energy
production, wind speed measurements are collected
from the local meteorological station of the National
Observatory of Athens Automatic Network
(NOANN) [37]. The time series processing is
carried out using the free software application
Hydrognomon [38]. Τhe wind speeds measured at
the meteorological station are converted according
to the height at which the wind turbines are
installed. Using the altitude of the meteorological
station, which is 42 m, and the height of the wind
turbine rotor, which is 303 m, the conversion of the
time series of the wind data is made. As mentioned
above, the Enercon E-92 wind turbine model is
selected. Based on the power curve, provided by the
manufacturer, the generated wind energy is
calculated. Fig. 5 shows the average hourly wind
energy produced per month. If the produced wind
energy does not adequately cover the needs, the
water of the seawater reservoir supplies the
hydroelectric power station, which covers the
energy deficit. If the electricity demand cannot be
met by the produced hydro energy, then the deficit
is covered by the local power station. Two operating
scenarios are simulated for the management of the
produced energy. In Scenario 1 the priority is to
meet the electricity load and in Scenario 2 the
priority is to meet the electromobility and
desalination energy needs. Τhe developed
methodology can be adapted by other islands,
interconnected or not, by importing the respective
data, thus, leading to the energy and water
independence, the increase of the penetration of
RES, and the reduction of CO2 emissions.
Fig. 5: Average hourly wind energy produced per
month
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
546
Volume 18, 2022
3.2 Scenario 1: Energy Coverage as a
Priority
The operating scenario aims to meet the energy and
water needs of Pyli (3500 inhabitants) on the island
of Kos. Τhe priority is to cover the energy needs and
then the water needs. From the produced energy
from the wind turbines, 30% is distributed directly
to the grid, while the remaining 70% goes is used
firstly to the pumping station for pumping seawater
and secondly to the desalination unit for drinking
water production. The wind energy is primarily
allocated to the pumping station for pumping water
to the upper reservoir, in order to be stored and
released to the hydro turbine when there is an
energy deficit. The energy that cannot be
implemented by the pumps, due to their capacity, is
used for the desalination of seawater. The pumping
of seawater in the upper tank in case of excess
energy and the operation of the hydroelectric power
station in case of deficit smooths out the sharp
fluctuation of the produced energy. Thus, with the
presence of the HS instead of an individual wind
farm, much higher percentages of reliability in
meeting the needs for energy and water supply are
achieved. Τhe system is simulated for 5 years with
an hourly step. Fig. 6 shows the management of the
total wind energy for each month. The strong
fluctuation of the wind is reflected in the generated
wind energy per month. Fig. 7 shows the monthly
coverage of energy needs by the HS and the
coverage ranges from 58% in August to 81% in
July. Fig. 8 and 9 show the energy production per
month and how energy needs are met. It is observed
that the maximum monthly energy production
occurs in July and exceeds 3000 MWh, due to high
wind energy production. Demand in August is high,
due to tourism, but due to lower wind energy
production, the LPS operates more than in other
months.
Fig. 6: Wind energy management
Fig.7: Monthly coverage of energy requirements by
the HS
Fig. 8: Energy production per month
Fig. 9: Covering energy needs
Drinking water production per month is shown in
Fig. 10. The volume of desalinated water produced
is stored in a reservoir and is used to meet water
supply needs.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
547
Volume 18, 2022
Fig. 10: Production of desalinated water per month
For the population of 3500 inhabitants, the
percentage of coverage of energy demand by the
desalination unit is 95% from the HS, as shown in
Fig. 11. At a rate of 5% that the HS is unable to
meet demand, water is supplied by the natural
springs of Kos.
Fig. 11: Covering water needs
3.3 Scenario 2: Coverage of Energy
Requirements for Electro-Mobility and
Desalination as a Priority
In Scenario 2 the priority is to cover the energy
requirements of the electric vehicles and then the
energy requirements of the desalination unit. Like in
Scenario 1, 30% of the energy produced by the wind
farm is given directly to the grid. The remaining
70% is distributed at a rate of 75% to cover the
needs of the electric vehicles in priority, and then
the energy requirements of the desalination unit.
The remaining 25% is used to pump water to the
upper reservoir for energy storage. The priority in
this scenario is coverage of water and
electromobility demands of the city of Kos, with a
population of 20000 inhabitants, and secondly the
coverage of the energy requirements of the
households. In Fig. 12 it is shown that the energy for
the electrification of the vehicles of the island is
consistently much smaller than the generated wind
energy, so the percentage of reliability of its
coverage with "green energy" from the HS reaches
100%. This fact is quite encouraging and even if the
forecasts for the penetration of electric propulsion
are exceeded, the HS will still be able to respond.
Furthermore, the fact that electric vehicles do not
consume much energy is encouraging, as, in the
societies of the future, electric vehicles will have to
be charged with energy from RES and not from
fossil fuels. In addition, it can be seen that in July,
the month with the highest wind potential, the
highest production of drinking water takes place and
the largest monthly volume of water is pumped.
Fig. 12: Wind energy management
Fig. 13 shows the monthly coverage of energy
requirements by the HS. Τhe percentages are
reduced, compared to Scenario 1, which has energy
coverage as a priority. Nevertheless, they are still
satisfying, as they range from 46% in May to 70%
in November.
Fig. 13: Monthly coverage of energy requirements
by the HS
Fig. 14 and 15 show the percentage of energy
demand coverage as well as the average monthly
energy production from each of the respective
energy sources. The percentages of hydroelectric
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
548
Volume 18, 2022
energy are reduced, compared to Scenario 1,
because smaller amounts of energy are available for
energy storage in the upper reservoir.
Fig. 14: Energy production per month
Fig. 15: Covering energy needs
Fig. 16 shows the average monthly production of
desalinated water. It is obvious that in Scenario 2
much larger amounts of water are desalinated since
the water supply is a priority. The production of
drinking water in Scenario 2 can cover the water
needs of the entire city of Kos, at a rate of 92%, as it
is shown in Fig. 17. The use of HS for drinking
water supply will improve groundwater quality and
quantity. In particular, the level of the aquifer will
rise and the risk of salinization of groundwater will
be minimized.
Fig. 16: Production of desalinated water per month
Fig. 17: Covering water needs
3.4 Comparison of CO2 Emissions before and
after the Integration of the Hybrid System
This subchapter presents data depicting the total
CO2 emissions from the operation of the LPS and
the number of conventional vehicles on the island.
The purpose is to compare the pollutants emitted
before and after the integration of HS and electric
vehicles. For the calculations, it is assumed that the
CO2 emissions for conventional vehicles are 120
g/km [39,40]. The CO2 emissions of the LPS are
considered about 0.92 kg CO2/kWh [41]. Emission
reductions are estimated to be 9720 tons of CO2 per
year in Scenario 1 and 6290 tons of CO2 in Scenario
2. It is considered that the price is 60 € per ton for
the first 10 years of operation [42]. In Fig. 18 the
annual cost of the LPS before and after the inclusion
of HS for each operating scenario is shown.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
549
Volume 18, 2022
Fig. 18: Αnnual cost per case of operation
3.5 Cost-Benefit Analysis
The cost-benefit analysis [43,44] is based on the
results of Scenario 1. The total amount of the
investment amounts to 11333600 €, based on prices
presented in [45]. The following financing scheme
is provided for this investment: grant, bank loan,
and own capital investment. The grant is given by
an operational program for the promotion of RES in
the islands and is set at 40% of the total cost [45],
which is 4533440 €. The bank loan is taken for 40%
of the investment, namely 4533440 € and finally,
the same participation amounts to 20%, which
corresponds to 2266720 €. Based on the
assumptions mentioned above, the Net Present
Value (NPV) of the investment is zeroing for a sale
price of desalinated water at 2.18 €/m3 and a fixed
sale price of energy of 0,0875 €/kWh [46]. For this
price, the Internal Rate of Return (IRR) is equal to
the discount rate and the investment is marginally
profitable [47]. Fig. 19 shows the efficiency of the
project depending on the selling price of water
through the NPV and IRR diagram for different
water prices. Likewise, Fig. 20 shows the efficiency
of the project depending on the selling price of
energy through the NPV and IRR diagram for
different energy prices. It is observed that for an
extremely small increase in the selling price of
either water or energy, NPV is increasing
significantly because annual cash inflows are
increasing. Specifically, an increase of NPV by
approximately 400000 € corresponds to an increase
in energy of just 0,00345 €/kWh discounts.
Similarly, for the same increase in NPV, an increase
in a water price of at least 0,07 €/m3 is required. In
addition, it is worth noting that compared to the
selling price of water; small changes in the selling
price of energy have a greater effect on the NPV.
Fig. 19: NPV and IRR for different selling prices of
desalinated water
Fig. 20: NPV and IRR for different selling prices of
energy
4 Discussion
This research work presents the assessment of an
HS on the Greek island of Kos, to promote its
contribution to local sustainability and energy
independence. Data about the island’s population
and data on water and electricity consumption are
collected, as well as data from the meteorological
station of the island. In addition, based on the
national plan of Greece, an estimation is made for
the number of electric vehicles on the island of Kos
and their energy requirements. Then, based on the
processed data, two different operating scenarios are
evaluated. The first scenario aims to meet the
energy and water needs of Pyli (3500 inhabitants).
The second scenario aims to cover the
electromobility and water needs of 20000
inhabitants, which is equivalent to the entire city of
Kos. The simulation uses hourly meteorological and
demand data for the period 2016-2020. Also, results
about CO2 emissions, before and after the
integration of the HS are presented and a cost-
benefit analysis is performed for the first scenario.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
550
Volume 18, 2022
Monthly energy production is maximized during the
tourist months of July and August and minimized
during March and April. In Scenario 1, in which
energy demand is a priority, the requirements are
covered by 60% by the HS on average. Specifically,
28% of the demands are covered by wind turbines
and 32% by the hydroelectric station. This
participation significantly reduces the emitted
pollutants, as a result, the Greek state spares an
estimated 600000 € per year, due to the reduction of
the cost of CO2 emission allowances. The HS's
monthly coverage of energy requirements ranges
from 58% in August to 82% in July. Also, the water
demands of 3500 inhabitants are covered by 96%
with drinking water from the desalination unit.
In Scenario 2, in which energy demand is a priority,
the priority is to cover the energy needs of
desalination and electromobility. The requirements
are covered by 37% by the HS on average.
Specifically, 27% of the demands are covered by
wind turbines and 10% by the hydroelectric station.
This participation significantly reduces the emitted
pollutants, as a result, the Greek state spares an
estimated 380000 € per year, due to the reduction of
the cost of emission allowances. The HS's monthly
coverage of energy requirements ranges from 46%
in August to 71% in November. Also, the water
demands of 20000 inhabitants are covered by 96%
from the desalination unit. In addition, Scenario 2
covers 100% of the projected penetration of
electromobility on the island of Kos until 2030 from
the ΗS. In particular, the need for 174 electric cars,
which are part of the national target, is adequately
met. Even if the progress of the electric vehicles is
made at a faster pace, the HS will be able to meet
with 100% adequacy the needs of all vehicles, due
to the energy storage that takes place.
5 Conclusions
Scenario 1 is more cost-effective and more
environmentally friendly. However, in the future,
when more electric vehicles will be used, increased
amounts of energy will be required and Scenario 2
will be preferred for covering the required needs.
The system seems to meet to a large extent the
energy and water demands of the island of Kos. At
the same time, the emitted pollutants are minimized
and the groundwater table is increased. Thus, the
problem of groundwater salinization will be
addressed. In addition, the island becomes
autonomous and self-sufficient, by producing
drinking water and energy for all its annual needs.
Τhe area of the reservoir can be a place of recreation
and green spaces can be developed around it.
Electromobility will reduce pollution in the busy,
tourist city of Kos, and noise pollution will be
minimized since electric vehicles do not emit
pollutants and are noiseless. Thus, the HS will make
a significant contribution to the development of the
area and improvement of the quality of life. Τhe
application of this methodology is suggested in
other islands of Greece, interconnected and not,
contributing to the local independence from the
electrical network, increasing the contribution of
RES, and reducing CO2 emissions.
Based on this research work and its results, further
research is proposed on the optimization of the HS.
Also, the production of stochastic time series for the
prediction of the future response of the HS would
provide an overall picture for the optimization of the
system. Finally, a multi-criteria analysis for the
installation of each subsystem could enhance the
minimization of the environmental impact of the
HS.
References:
[1] Bertsiou, M., Feloni, E., Karpouzos, D., &
Baltas, E., Water management and electricity
output of a hybrid renewable energy system
(HRES) in Fournoi island in Aegean Sea.
Renewable energy, 118, 2018, pp. 790-798.
[2] Skroufouta, S., & Baltas, E., Investigation of
hybrid renewable energy system (HRES) for
covering energy and water needs on the Island
of Karpathos in Aegean Sea. Renewable
Energy, 173, 2021, pp. 141-150.
[3] Ma, T., Yang, H., & Lu, L., A feasibility study
of a stand-alone hybrid solar–wind–battery
system for a remote island. Applied Energy,
121, 2014, pp. 149-158.
[4] Sarris, D., Bertsiou, M. M., & Baltas, E.,
Evaluation of a Hybrid Renewable Energy
System (HRES) in Patmos Island.
International Journal of Renewable Energy
Sources, 4, 2019.
[5] Groppi, D., Pfeifer, A., Garcia, D. A., Krajačić,
G., & Duić, N., A review on energy storage
and demand side management solutions in
smart energy islands. Renewable and
Sustainable Energy Reviews, 135, 2021,
110183.
[6] Alves, M., Segurado, R., & Costa, M., On the
road to 100% renewable energy systems in
isolated islands. Energy, 198, 117321, 2020.
[7] Skjølsvold, T. M., Ryghaug, M., & Throndsen,
W., European island imaginaries: Examining
the actors, innovations, and renewable energy
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
551
Volume 18, 2022
transitions of 8 islands. Energy Research &
Social Science, 65, 101491, 2020.
[8] Dallavalle, E., Cipolletta, M., Moreno, V. C.,
Cozzani, V., & Zanuttigh, B., Towards green
transition of touristic islands through hybrid
renewable energy systems. A case study in
Tenerife, Canary Islands. Renewable Energy,
174, 2021, pp. 426-443.
[9] Curto, D., Franzitta, V., Viola, A., Cirrincione,
M., Mohammadi, A., & Kumar, A., A
renewable energy mix to supply small islands.
A comparative study applied to Balearic
Islands and Fiji. Journal of Cleaner
Production, 241, 2019, 118356.
[10] Sun, X., Li, Z., Wang, X., & Li, C.,
Technology development of electric vehicles:
A review. Energies, 13(1), 90, 2019.
[11] Deng, J., Bae, C., Denlinger, A., & Miller, T.,
Electric vehicles batteries: requirements and
challenges. Joule, 4(3), 2020, pp. 511-515.
[12] Colmenar-Santos, A., Muñoz-Gómez, A. M.,
Rosales-Asensio, E., & López-Rey, Á.,
Electric vehicle charging strategy to support
renewable energy sources in Europe 2050
low-carbon scenario. Energy, 183, 2019, pp.
61-74.
[13] Geronikolos, I., & Potoglou, D., An exploration
of electric-car mobility in Greece: A
stakeholders’ perspective, Case Studies on
Transport Policy, 9, 2, 2021, pp. 906-912.
[14] González, R. M., Marrero, G. A., Rodríguez-
López, J., & Marrero, Á. S., Analyzing CO2
emissions from passenger cars in Europe: A
dynamic panel data approach. Energy Policy,
129, 2019, pp. 1271-1281.
[15] Kourtis, I. M., Kotsifakis, K. G., Feloni, E. G.,
& Baltas, E., A Sustainable water resources
management in small Greek islands under
changing climate. Water, 11(8), 1694, 2019.
[16] Peñate, B., & García-Rodríguez, L., Current
trends and future prospects in the design of
seawater reverse osmosis desalination
technology. Desalination, 284, 2012, pp. 1-8.
[17] Bhattacharjee, S., & Nayak, P. K., PV-pumped
energy storage option for convalescing
performance of hydroelectric station under
declining precipitation trend. Renewable
energy, 135, 2019, pp. 288-302.
[18] Petrakopoulou, F., Robinson, A., & Loizidou,
M., Simulation and analysis of a stand-alone
solar-wind and pumped-storage hydropower
plant. Energy, 96, 2016, pp. 676-683.
[19] Kaldellis, J. K., Koroneos, C., Triantafyllou, P.,
Kaldellis, A., & Kollas, P., Clean energy
solution for remote islands. The case of
Nisyros island, International Journal of
Sustainable Energy, 2022, pp. 1-25.
[20] Makkiabadi, M., Hoseinzadeh, S., Nezhad, M.
M., Sohani, A., & Groppi, D., Techno-
Economic Study of a New Hybrid Solar
Desalination System for Producing Fresh
Water in a Hot–Arid Climate. Sustainability,
13(22), 12676, 2021.
[21] Icaza-Alvarez, D., Jurado, F., Tostado-Véliz,
M., & Arevalo, P., Decarbonization of the
Galapagos Islands. Proposal to transform the
energy system into 100% renewable by 2050.
Renewable Energy, 189, 2022, pp. 199-220.
[22] Ammari, C., Belatrache, D., Touhami, B., &
Makhloufi, S., Sizing, optimization, control
and energy management of hybrid renewable
energy system—A review, Energy and Built
Environment, 2021.
[23] Pacaldo, J. C., Abundo, M. L. S., Bellotindos,
L. M., & Baco Jr, C. S., Performance Analysis
of a Hybrid Diesel–Renewable Energy (RE)
Electrical System in Cuyo Island, Palawan,
Philippines. International Journal of
Advanced Research in Engineering
Innovation, 4(1), 2022, pp. 1-15.
[24] R. Segurado, J.F.A. Madeira, M. Costa, N.
Duić, M.G. Carvalho, Optimization of a wind
powered desalination and pumped hydro
storage system, Appl. Energy, 177, 2016, pp.
487-499.
[25] J. Jurasz, A. Kies. A day-ahead probabilistic
model for scheduling the operation of a wind
pumped-storage hybrid power station:
overcoming forecasting errors to ensure the
reliability of supply to the grid, Sustainability,
10, 2019, pp. 1989.
[26] Mehrjerdi, H., Modeling, integration, and
optimal selection of the turbine technology in
the hybrid wind-photovoltaic renewable
energy system design. Energy Conversion and
Management, 205, 2020, 112350.
[27] Wang, Y., Wang, Y., Huang, Y., Li, F., Zeng,
M., Li, J., Wang, X., & Zhang, F., Planning
and operation method of the regional
integrated energy system considering
economy and environment. Energy, 171,
2019, pp. 731-750.
[28] Ming, B., Liu, P., & Cheng, L., An integrated
framework for optimizing large hydro–
photovoltaic hybrid energy systems: Capacity
planning and operations management. Journal
of Cleaner Production, 306, 2021, 127253.
[29] Yang, J., Han, J., Wu, T., Zhang, H., & Shang,
L., Sizing and optimization of on-grid hybrid
renewable energy systems considering
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
552
Volume 18, 2022
hydroelectric energy storage, Journal of
Intelligent & Fuzzy Systems, 40, 1, 2021, pp.
1521-1536.
[30] Liu, B., Zhou, B., Yang, D., Yang, Z., & Cui,
M., Optimal capacity planning of combined
renewable energy source-pumped storage and
seawater desalination systems. Global Energy
Interconnection, 2(4), 2019, pp. 310-317.
[31] Tsai, C. T., Beza, T. M., Wu, W. B., & Kuo, C.
C., Optimal configuration with capacity
analysis of a hybrid renewable energy and
storage system for an island application.
Energies, 13(1), 8, 2019.
[32] Hamanah, W. M., Abido, M. A., & Alhems, L.
M., Optimum sizing of hybrid pv, wind,
battery and diesel system using lightning
search algorithm. Arabian Journal for Science
and Engineering, 45(3), 2020, pp. 1871-1883.
[33] Abdul-Wahab, S., Mujezinovic, K., & Al-
Mahruqi, A. M., Optimal design and
evaluation of a hybrid energy system for off-
grid remote area. Energy Sources, Part A:
Recovery, Utilization, and Environmental
Effects, 2019, pp. 1-13.
[34] Zervas, E., Vatikiotis, L., Gareiou, Z., Manika,
S., & Herrero-Martin, R., Assessment of the
Greek National Plan of Energy and Climate
Change—Critical Remarks. Sustainability,
13(23), 2021, 13143.
[35] Moon, H., Park, S. Y., Jeong, C., & Lee, J.,
Forecasting electricity demand of electric
vehicles by analyzing consumers’ charging
patterns. Transportation Research Part D:
Transport and Environment, 62, 2018, pp. 64-
79
[36] Gerossier, A., Girard, R., & Kariniotakis, G.,
Modeling, and forecasting electric vehicle
consumption profiles. Energies, 12(7), 2019,
pp. 1341.
[37] Lagouvardos, K., Kotroni, V., Bezes, A.,
Koletsis, I., Kopania, T., Lykoudis, S.,
Mazarakis N., Papagiannaki N. &
Vougioukas, S., The automatic weather
stations NOANN network of the National
Observatory of Athens: Operation and
database. Geoscience Data Journal, 4,1, 2017,
pp. 4-16.
[38] S. Kozanis, A. Christofides, N. Mamassis, A.
Efstratiadis, and D. Koutsoyiannis,
Hydrognomon – open source software for the
analysis of hydrological data, European
Geosciences Union General Assembly 2010,
Geophysical Research Abstracts, 12, Vienna,
European Geosciences Union, 2010.
[39] Fontaras, G., Zacharof, N. G., & Ciuffo, B.,
Fuel consumption and CO2 emissions from
passenger cars in Europe–Laboratory versus
real-world emissions. Progress in energy and
combustion Science, 60, 2017, pp. 97-131.
[40] Mele, E., Natsis, A., Ktena, A., Manasis, C., &
Assimakis, N., Electromobility and Flexibility
Management on a Non-Interconnected Island.
Energies, 14, 5, 2021, pp. 1337.
[41] Hawkes, A. D., Estimating marginal CO2
emissions rates for national electricity
systems. Energy Policy, 38(10), 2010, pp.
5977-5987.
[42] Ciesielska-Maciągowska, D., Klimczak, D., &
Skrzek-Lubasińska, M., Central and eastern
European CO2 market—challenges of
emissions trading for energy companies.
Energies, 14, 4, 2021, pp. 1051.
[43] Katsivelakis, M. Bargiotas, D., Daskalopulu,
A., Panapaidis, I.P., Tsoukalas, L., Techno-
Economic Analysis of a Stand-Alone Hybrid
System: Application in Donoussa Island,
Greece. Energies, 14, 2021, pp. 1868.
[44] Reuter, W. H., Fuss, S., Szolgayová, J. and
Obersteiner, M., Investment in wind power
and pumped storage in a realoptions model.
Renewable and Sustainable Energy Reviews,
16, 4, 2012, pp. 2242-2248.
[45] Lemonis, A., Skroufouta, S., & Baltas, E., An
Economic Evaluation Towards Sustainability:
The Case of a Hybrid Renewable Energy
System in Greece. American Journal of
Environmental and Resource Economics,
7(1), 2022, pp. 37-47.
[46] Canales, F. A., Jurasz, J. K., Guezgouz, M., &
Beluco, A., Cost-reliability analysis of hybrid
pumped-battery storage for solar and wind
energy integration in an island community.
Sustainable Energy Technologies and
Assessments, 44, 2021, 101062.
[47] Suzer, A. E., Atasoy, V. E., & Ekici, S.,
Developing a holistic simulation approach for
parametric techno-economic analysis of wind
energy. Energy Policy, 149, 2021, 112105.
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
553
Volume 18, 2022
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Iasonas Nikas-Nasioulis: Data curation
management, Formal analysis, Investigation,
Methodology, Writing original draft, Visualization.
Maria Margarita Bertsiou: Writing - review &
editing
Evangelos Baltas: Validation, Conceptualization,
Supervision
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.53
Iasonas Nikas-Nasioulis,
Maria Margarita Bertsiou, Evangelos Baltas
E-ISSN: 2224-3496
554
Volume 18, 2022
