Financial and economic crisis creates new data on the electricity for remote consumers: Case study Greece

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1 Financial and economic crisis creates new data on the electricity for remote consumers: Case study Greece Jacob G. Fantidis Dept. of Electrical Engineering Kavala Institute of Technology Kavala, Greece Pantelis Antoniadis Dept. of Electrical Engineering Kavala Institute of Technology Kavala, Greece Contsantinos Potolias Dept. of Electrical Engineering Kavala Institute of Technology Kavala, Greece Dimitrios V. Bandekas Dept. of Electrical Engineering Kavala Institute of Technology Kavala, Greece Nicolaos Vordos Dept. of Electrical Engineering Kavala Institute of Technology Kavala, Greece Abstract The financial and economic crisis in Greece has brought new taxes on the fossil fuels. During the depression (January 2009 June 2011) the diesel-oil price was rising more than 65%. The aim of this study is to investigate how this crisis has affected the electricity cost for a remote consumer. The HOMER software was used in order to find the optimum hybrid system for a typical country house in four different Greek Islands. The generality of Greek Islands are suitable for exploitation of wind energy for electricity generation. Due to the dramatically increased prices for diesel-oil over the last two years in Greece, the PV generators offer not only environmental benefits but also provide lower cost of energy and can displace the diesel engine generators. Keywords: Hybrid systems; Renewable energy; Financial crisis; Greeks Islands I. INTRODUCTION Energy is a fundamental ingredient in economic development and energy consumption is an index of prosperity and standard of living of people in a country. Global electricity demand is increasingly as developed countries run on to expand and developing ones grow even faster. Rapid depletion of fossil fuel resources, increasing of fuel prices such as oil or gas, climate effects, air quality issues and energy dependency concerns have caused increasing attention in the development and use of renewable energy. Renewable energy sources such as photovoltaic panels and wind turbines provide a realistic alternative for electricity generation. The individual fluctuation of the wind and solar resources can be overcome using hybrid renewable energy systems with battery backup [1-4]. In islands and in many remote areas the price asking for the grid extension is prohibitive and the cost of fuels increases drastically with the remoteness of location. In these areas most of the consumers are obliged to depend ISSN : X Vol. 1 No. 1 September-November

2 on the operation of small autonomous generators consuming large amounts of diesel oil. Although the diesel generators have really low initial cost is an expensive solution because have high operational cost [5]. In Greece owing to the country's unique geography exist several thousands of remote consumers [6-7], placed on the numerous small or medium sized islands. The aim of this study is to estimate how the new taxes on fossil fuels in Greece, as a result of financial and economic crisis, has affected the electricity cost for a remote consumer. HOMER (Hybrid Optimization Model for Electric Renewables) version 2.68 developed by National Renewable Energy Laboratory (NREL) was used as the simulation and optimisation tool [8]. The assessment criterion of the analysis is the net present cost (NPC). II. HOMER SOFTWARE HOMER is a modelling tool that facilitates design of standalone electric power systems [8]. The total net present cost is HOMER s main economic output. All systems are ranked in relation to net present cost, and all other economic outputs are calculated for the purpose of finding the net present cost. HOMER calculates the total NPC using the following equation: C NPC Cann, tot = (1) CRF(, i R ) proj where C ann,tot is the total annualized cost ( /yr), CRF is the capital recovery factor, i is the interest rate (%) and R proj is the project lifetime (yr). The CRF is calculated by proj ii ( + 1) CRF = Rproj ( i + 1) 1 R (2) In this study different hybrid options were analyzed to get an optimized hybrid system sizing. The financial parameters (initial capital cost, replacement cost, maintenance cost) and lifetime of each component are in Table I. Equipment performances and financial data have been assumed by market surveys and by literature [9-12]. The project life time has been considered to be 25 yr and the annual real interest rate has been taken as 6%. The spinning reserve input options and system constraints are given in Table II. If we reckon that the effects of temperature on the PV panels are insignificant HOMER uses the following equation to estimate the output of the PV panels: P Y f PV PV PV G T = (3) G T,STC where Y PV is the rated capacity of the PV array, meaning its power output under standard test conditions [kw], f PV is the PV derating factor [%], G is the solar radiation incident on the PV array in the current time step [kw/m 2 ] and T G is the incident radiation at standard test conditions [1 kw/m 2 ]. T,STC To calculate the output of the wind turbine in a particular hour, HOMER follows a three-step process: i)it takes the hour's wind speed data and adjusts it to the hub height, ii) it refers to the wind turbine's power curve to calculate the power output and iii) it multiplies that value by the air density ratio. TABLE I. COMPONENTS OF THE HYBRID SYSTEM ANALYSIS Characteristics Diesel generator PV module Wind turbine Battery Converter Model Typical Typical WES 5 TULIPO Trojan T-105 Typical Power 1 kw 1 kw 2.5 kw Nominal voltage 6V nominal 1 kw capacity 225Ah (1.35kWh) Life time h 25 year 15 year Lifetime throughput 845kWh 15 year Price /kwp 5000 /turbine 121 /battery 1000 /kw Replacement /kwp 4000 /turbine 108 /battery 1000 /kw Maintenance 0.15 /h 3 /kw 50 /turbine 1 /battery null ISSN : X Vol. 1 No. 1 September-November

3 TABLE II. CONSTRAINTS USED IN SOFTWARE SPINNING RESERVE INPUTS IN SOFTWARE Parameters Value Minimum battery life N/A Maximum annual capacity shortage 10% Percent of annual peak load 0% Percent of hourly load 5% Percent of hourly solar output 50% Percent of hourly wind output 50% III. CASE STUDY: FOUR GREEK ISLANDS The electricity network of Greece may be divided into two main sectors. First is the main land national grid, based on the operation of centralized Thermal Power Stations. The second is the several thousands of remote consumers mainly in the Aegean and Ionian Archipelago areas, located on the several small and medium-sized scattered islands. In these areas the electricity production cost is extremely high [13-14]. Greek islands present big tourist development during the summer months due to theirs appreciable natural resources which has as a result the increase of electrical demand. In the present paper 4 different Greek islands were studied namely Limnos, Chios, Milos, and Karpathos (Fig. 1) [15]. Figure 1. Location of the four Greek Islands According to Kaldelis et al. [16] the electricity consumption during the summer, due to the visiting tourists, is more than twice the corresponding spring besides, on an hourly basis; there is considerable variation on the load requirement throughout the day. With the purpose to synthesize the load profile data for a typical country house different previous works are combined. Prodromidis and Coutelieris [17] separated a year into three periods and for every simulated period the days also divided into two categories: weekend and weekday. A previous work done from Kaldelis et al. [14] has been a great help in determining the hourly load variation for the 4 islands. In order to randomize the load profile and make it more realistic a 10% noise level has been added on a daily and hourly basis. The expected load consumption profile is depicted in Fig. 2. ISSN : X Vol. 1 No. 1 September-November

4 Figure 2. Expected yearly load consumption profile for a typical country house In order to calculate the performance of a hybrid system it is necessary to collect accurate meteorological data in target locations. In this study the long term meteorological parameters for each of the 4 considered sites in Greece are obtained from the HNMS (Hellenic National Meteorological Service) [18]. It is widely acknowledged that Greece possesses an excellent solar energy potential according to existing long-term measurements, as presented in Fig. 1. The average daily solar radiations at investigated locations are shown in Fig. 3. As it can be seen, the solar irradiation has the maximum values during the summer when the electricity demand is considerable higher. 8 Limnos Chios Milos Karpathos Jan Feb Mar Apr Solar radiation (kwh/m2) May Jun Jul Aug Sep Oct Nov Dec Month Figure 3. Average daily radiation for each island The long-term monthly average wind speeds are presented in Fig. 4. Milos with annual mean wind speed 6.74 m/s has a very good wind potential. The corresponding values from Karpathos, Limnos and Chios (5.18, 4.97, 4.53 m/s) although lower than the one of Milos, are good enough to feed contemporary wind-turbines for electricity production. Wind speeds are generally higher during the months December to March as compared to other months. This means that a wind turbine would produce more energy during these months as compared to the other months. However the data also shows that there isn t large fluctuation of monthly average wind speed from one month to another month. In the present paper, wind turbine of 2.5 kw from Wind Energy Solution is used. The wind power curve of the WES 5 Tulipo wind machine is shown in Fig. 5. WES 5 Tulipo, has 5 m rotor diameter and 6.25 m of tower [19]. ISSN : X Vol. 1 No. 1 September-November

5 Wind speed (m/s) Jan Limnos Chios Milos Karpathos Feb Mar Apr May 3.7 Jun Jul Aug Sep Oct Nov Dec Month Figure 4. Wind potential for each island Figure 5. WES 5 Tulipo wind turbine power curve On the January of 2009 the diesel price in the Greek Islands was about 0.9 /L. However the financial and economic crisis in Greece has brought new taxes in the fossil fuels. According to the data from the Hellenic Minister of development [20], just 2.5 years later the diesel price were rising more than 65%. During the summer of 2011 the diesel price in Greek islands is about 1.5 /l. This means that the cost of operation for a typical diesel engine generator is extremely high. ISSN : X Vol. 1 No. 1 September-November

6 IV. RESULTS AND DISCUSSION 4.1 Limnos case Several simulations for various scenarios have been made by considering different combinations of wind turbines, PV panels, diesel generators and number of batteries. Table III summarizes the details of the optimal hybrid system. With diesel price 0.9 /l the optimal system for a typical country house in Limnos is a hybrid Wind Diesel generator Battery system with 1 WES 5 Tulipo wind generator, 1 kw diesel generator, 18.9 kwh storage batteries and 1 kw of power converter. The monthly average electric production is shown in Fig. 6. The renewable fraction is 86% while the diesel generator produces the rest 14%. This system has NPC equal to Unfortunately the use of diesel generator causes air pollution. It should be noted that in the present paper the analysis assumed no penalty cost to be imposed for the pollutant. Homer calculates six pollutants as simulation outputs: carbon dioxide (CO 2 ), carbon monoxide (CO), unburned hydrocarbons (UHC), particulate matter (PM), sulfur dioxide (SO 2 ) and nitrogen oxides (NO x ). Total emissions due to operation of the diesel generator are shown on Table IV. TABLE III. OPTIMU HYBRID SYSTEMS FOR THE LIMNOS ISLAND Diesel Optimum system Components Renewable NPC COE price fraction 0.9 /L Wind Diesel 1 wind turbine 2.5 kw, 1 kw diesel generator, 86% /kwh generator Batteries 18.9 kwh batteries, 1 kw power converter 1.5 /L Wind PV Batteries 1 wind turbine 2.5 kw, 1.8 kw PV panels, kwh batteries, 1 kw power converter 100% /kwh Figure 6. Monthly average electric production for the optimum system with diesel price 0.9 /L (Limnos case) TABLE IV. EMISSIONS FOR THE OPTIMUM HYBRID SYSTEM WITH DIESEL PRICE 0.9 /L (LIMNOS) Pollutant Emissions (kg/year) CO CO 2.01 UHC PM SO NO x 18 According to the results from Homer simulations for diesel price 1.5 /L the optimum financial solution is a hybrid Wind PV Battery system, with 1 WES 5 Tulipo wind generator, 1.8 kw solar panels, kwh storage batteries and 1 kw of power converter. This system has NPC equal to and uses 100% renewable energy in which 66% electricity comes from wind turbine and 34% electricity comes from solar radiation (Fig. 7). This diesel-free system evidently produces zero emissions. ISSN : X Vol. 1 No. 1 September-November

7 Figure 7. Monthly average electric production for the optimum system with diesel price 1.5 /L (Limnos case) In order to give a general overview of the situation, sensitivity analysis is also realized. Generally the wind speed and the fuel cost are usually site dependent, so if we consider these parameters as sensitivities variables with values 4, 4.5, 4.97, 5, and 5.5 m/s for the wind speed and 0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, and 2 /L for the diesel price, the results are shown in Fig. 8. For diesel cost higher than 1.33 /l and wind speed more than 4.9 m/s the PV panels replace diametrically the diesel generator. Figure 8. Sensitivity of wind speed to diesel price for the hybrid systems (Limnos). 4.1 Chios case In this case with diesel price 0.9 /l the optimum system is a hybrid Wind PV Diesel generator Battery system with 1 wind turbine, 0.1 kw PV panels kwh storage batteries and 1 kw of power converter (Table V). This system uses 88% renewable energy comes from wind turbine (85%) and PV generators (3%) while 12% electricity comes from diesel generator (Fig. 9a). The NPC is and the emission due to operation of the diesel generator are listed on Table VI. For a diesel price 1.5 /l the optimal system contain 1 WES 5 Tulipo turbine generator, 1.5 kw PV panels, 27 kwh storage batteries and 1 kw of power converter with NPC ISSN : X Vol. 1 No. 1 September-November

8 (Table V). Approximately 66% of the total electricity comes from wind turbine and the rest 34% comes from PV generators (Fig. 9b). There are no GHG (Green House Gases) emissions as there is no fossil fuels generator. TABLE V. OPTIMUM HYBRID SYSTEMS FOR THE CHIOS ISLAND Diesel Optimum system Components Renewable NPC COE price fraction 0.9 /L Wind PV Diesel 1 wind turbine 2.5 kw, 0.1 kw PV panels, 1 kw 88% /kwh generator Batteries diesel generator, kwh batteries, 1 kw power converter 1.5 /L Wind PV Batteries 1 wind turbine 2.5 kw, 1.5 kw PV panels, 27 kwh batteries, 1 kw power converter 100% /kwh Figure 9. Monthly average electric production for the optimum systems with diesel price 0.9 or 1.5 /L (Chios case) TABLE VI. EMISSIONS FOR THE OPTIMUM HYBRID SYSTEM WITH DIESEL PRICE 0.9 /L (LIMNOS) Pollutant Emissions (kg/year) CO CO 1.77 UHC PM SO NO x 15.8 Wind speed with seven discrete values (3.5, 3.75, 4, 4.25, 4.53, 5 and 5.5 m/s), and diesel price with fourteen discrete values (0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9 and 2 /L) were used as sensitivity variables. Fig. 10 shows the appropriate implementation of hybrid systems under different wind speed and diesel price. From Fig. 10 is obvious that for diesel price 0.97 /L or above the hybrid Wind PV Battery system is the most financial viable solution. ISSN : X Vol. 1 No. 1 September-November

9 Figure 10. Sensitivity of wind speed to diesel price for the hybrid systems (Chios). 4.1 Milos case In accordance with Homer simulations (Table VII) if we consider that diesel price is equal to 0.9 /L the optimal hybrid system is a combination of 1 wind turbine, 1 kw diesel generator, kwh storage batteries and1 1 kw of power converter with NPC Diesel generators provide approximately the 7% of total energy demand and the WES 5 Tulipo turbine provides the other 93% (Fig. 11a). The use of diesel generator has as effect more than 0.5 t of CO 2 entering into the local atmosphere each year (Table VIII). However the current diesel price in Milos is about 1.5 /L and the calculations indicate that the new optimum systems incorporates 0.9 kw PV generators in place of diesel generator and requires 27 kwh storage batteries. The new optimum system has slightly higher NPC (16275 ) but has zero GHG emissions. Fig. 11b shows that wind turbine produces the 82% of the total energy served while PV generators produce 18% of the energy. TABLE VII. OPTIMUM HYBRID SYSTEMS FOR THE MILOS ISLAND Diesel Optimum system Components Renewable NPC COE price fraction 0.9 /L Wind Diesel 1 wind turbine 2.5 kw, 1 kw diesel generator, 93% /kwh generator Batteries kwh batteries, 1 kw power converter 1.5 /L Wind PV Batteries 1 wind turbine 2.5 kw, 0.9 kw PV panels, 27 kwh batteries, 1 kw power converter 100% /kwh TABLE VIII. EMISSIONS FOR THE OPTIMUM HYBRID SYSTEM WITH DIESEL PRICE 0.9 /L (MILOS) Pollutant Emissions (kg/year) CO CO 1.31 UHC PM SO NO x 11.7 ISSN : X Vol. 1 No. 1 September-November

10 Figure 11. Monthly average electric production for the optimum systems with diesel price 0.9 or 1.5 /L (Chios case) In the case of Milos the sensitivity analysis was also realized. Fourteen discrete values for diesel price (0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9 and 2 /L) and seven for wind speed (5.5, 6, 6.5, 6.75, 7, 7.5, and 8 m/s) were used in this sensitivity analysis (Fig. 12). From Fig. 12, it becomes clear that for diesel price higher than 1.25 /L the PV generators replace the diesel generator. For the measured annual mean wind speed (6.75 m/s) the absolute substitution of PV panels for diesel generator is financial viable for diesel price higher than 1.02 /L. Figure 12. Sensitivity of wind speed to diesel price for the hybrid systems (Milos). ISSN : X Vol. 1 No. 1 September-November

11 4.4 Karpathos case Only 2.5 years ago the optimum autonomous system in a typical country house in Karpathos was a Wind PV Diesel generator Battery system with NPC (Table IX). This system was renewable fraction about of 90% (87% due to the wind generator and 3% owing to the PV panels) while the 1 kw diesel generator provide 10% of the total energy served (Fig. 13a). However, with current diesel price about of 1.5 /L the PV panels are capable to displace the diesel generators (Fig. 13b). Table X shows the components of new optimum system and its financial information. From environmental point of view, it was calculated that more than 670 kg of GHG can be avoided entering into the local atmosphere each year. Fig. 14 exhibits the sensitivity analysis in term of diesel price (0.7, 0.8, 0.9, 1, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9 and 2 /L) and wind speed (4, 4.5, 5, 5.18, 5.5, and 6 m/s). From Fig. 14 is obvious that when diesel costs at least 1.11 /L the PV panels produce energy with lower cost than diesel generators. TABLE IX. OPTIMUM HYBRID SYSTEMS FOR THE CHIOS ISLAND Diesel Optimum system Components Renewable NPC COE price fraction 0.9 /L Wind PV Diesel 1 wind turbine 2.5 kw, 0.1 kw PV panels, 1 kw 90% /kwh generator Batteries diesel generator, 21.6 kwh batteries, 1 kw power converter 1.5 /L Wind PV Batteries 1 wind turbine 2.5 kw, 1.3 kw PV panels, kwh batteries, 1 kw power converter 100% /kwh Figure 13. Monthly average electric production for the optimum systems with diesel price 0.9 or 1.5 /L (Karpathos case) ISSN : X Vol. 1 No. 1 September-November

12 TABLE X. EMISSIONS FOR THE OPTIMUM HYBRID SYSTEM WITH DIESEL PRICE 0.9 /L (KARPATHOS) Pollutant Emissions (kg/year) CO CO 1.62 UHC PM SO NO x 14.5 Figure 14. Sensitivity of wind speed to diesel price for the hybrid systems (Karpathos). 4.5 Common trend It is revealed that wind energy is advantageous in the Greek Islands however, with diesel price approximately of 1.5 /L in all circumstances which was studied in this paper, the PV panels can replace easily the diesel generator. Considering that diesel-oil prices are continuously increasing (not only in Greece but worldwide), a future raise in the price of diesel is the most probable scenario, which will encourage inhabitants to invest in renewable sources such as the wind and the solar. Interesting information of this study is the fact that for every typical country house there is a considerable amount of surplus electrical energy that must be dumped because it cannot be used to serve a load or charge the batteries. Table XI shows the excess electricity for four islands for the optimum systems with diesel price 1.5 /L. Excess electricity can be used during the winter to serve a thermal load by means of resistive heating or during the summer to desalinate. TABLE XI. EXCESS ELECTICITY FOR THE OPTIMUM HYBRID SYSTEMS WITH DIESEL PRICE 1.5 /L Island Excess electricity per year Limnos 5223 kwh (62.4%) Chios 4338 kwh (57.8%) Milos 5452 kwh (63.3%) Karpathos 5130 kwh (61.9%) V. CONCLUSIONS Four Greek Islands was chosen in order to evaluate how the financial and economic crisis in Greece has affected the cost of electricity for a typical autonomous country house. HOMER software was used in order to ISSN : X Vol. 1 No. 1 September-November

13 perform all quantifications. It is clear that the maximum electricity comes from wind which predicts that wind is more feasible than the solar in the Greek Islands which was studied. The simulations indicate also that, due the additional taxes in the fossil fuels, the Wind PV generators Batteries systems are the optimum solutions. From environmental point of view, it was found that PV generators offer not only financial benefits but also cause zero air pollution. Bearing in mind that the fossil fuel prices are continuously raising, while the PV and wind generator cost are constantly decreasing, the use of environment friendly renewable energy sources seems the only solution for the future. REFERENCES [1] S. S. Dihrab and K. Sopian, Electricity generation of hybrid PV/wind systems in Iraq, Renewable Energy vol. 35, pp , [2] S. K. Nandi and H. R. Ghosh, Prospect of wind PV battery hybrid power system as an alternative to grid extension in Bangladesh, Energy vol. 35, pp , [3] K. Nigim, N. Munier and J. Green, Pre-feasibility MCDM tools to aid communities in prioritizing local viable renewable energy sources. Renewable Energy vol. 29, pp , [4] D.J. Maddaloni, M.A. Rowe and G.C. Van Kooten, Network constrained wind integration on Vancouver Island, Energy Policy vol. 36, pp , [5] A.A. Setiawan, Y. Zhao, C.V. Nayar, Design, economic analysis and environmental considerations of mini-grid hybrid power system with reverse osmosis desalination plant for remote areas. Renewable Energy vol. 34, pp , [6] J.K. Kaldellis, Optimum autonomous wind power system sizing for remote consumers, using long-term wind speed data. J Appl Energy vol. 71, pp , [7] J.K. Kaldellis, D. Zafirakis, E.L. Kaldelli and K. Kavadias, Cost benefit analysis of a photovoltaic-energy storage electrification solution for remote islands. Renewable Energy vol. 34, pp , [8] NREL (National Renewable Energy Laboratory), HOMER Computer Software, Version 2.68 beta. Retrieved from [9] S.K. Nandi and H.R. Ghosh, A wind PV battery hybrid power system at Sitakunda in Bangladesh, Energy Policy vol. 37, pp , [10] A. Demiroren and U. Yilmaz, Analysis of change in electric energy cost with using renewable energy sources in Gökceada, Turkey: An island examplerenewable and Sustainable Energy Reviews vol. 14, pp , [11] A. Rajoriya and E. Fernandez, Sustainable energy generation using hybrid energy system for remote hilly rural area in India, International Journal of Sustainable Engineering vol. 3, pp , May [12] B.E. Türkay and A. Y.Telli, Economic analysis of standalone and grid connected hybrid energy systems, Renewable Energy vol. 36, pp , [13] G.N. Prodromidis and F.A. Coutelieris, A comparative feasibility study of stand-alone and grid connected RES-based systems in several Greek Islands. Renewable Energy vol. 36, pp , [14] J.K. Kaldellis, D. Zafirakis, and E. Kondili, Optimum sizing of photovoltaic-energy storage systems for autonomous small islands. Electrical Power and Energy Systems vol. 32, pp , [15] [16] J.K. Kaldellis, D. Zafirakis, E.L. Kaldelli, K. Kavadias, Cost benefit analysis of a photovoltaic-energy storage electrification solution for remote islands. Renewable Energy vol. 34, pp , [17] G.N. Prodromidis and F.A Coutelieris., A comparative feasibility study of stand-alone and grid connected RES-based systems in several Greek Islands. Renewable Energy vol. 36, pp , [18] Hellenic National Meteorological Service ( [19] [20] Hellenic ministry of development ( ISSN : X Vol. 1 No. 1 September-November