Thisisthepublishedversion: Shafiullah,G.,Oo,A.,Jarvis,D.,Ali,A.andWolfs,P.2010,Impactofrenewableenergyinthefuturesmartpowersystem,inIECHAR2010:Challenges,TechnologiesandOpportunities:Proceedingsofthe2010InternationalEngineeringConferenceonHotAridRegions,KingFaisalUniversity,Al‐Ahsa,SaudiArabia,pp.65‐70.

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International Engineering Conference on Hot Arid Regions (lECHAR 2010)AI-Absa, KSA, Marcb 1-2, 2010

Impact of Renewable Energy in the Future SmartPower System

G. Shafiullah, A. 00, D. Jarvis, A. Ali, P. Wolfs

Abstract~ Current power systems create environmental impactsdue to utilisation of fossil fuels, especially coal, as carbon dioxideis emitted into the atmosphere. In contrast to fossil fuels, renewableenergy offers alternative sources of energy which are in generalpollution free, technologically effective and environmentallysustainable. There is an increased interest in renewable energy,particularly solar and wind energy, which provides electricitywithout giving rise to carbon dioxide emissions. This paperpresents a feasibility study undertaken to investigate theavailability and usefulness of renewable energy sources in CentralQueensland of Australia so as to further investigate the impacts ofrenewable energy sources in existing and future smart powersystem. The daily mean global solar irradiance and three hourlymean wind speed have been collected from the Rockharnpton AeroWeather Station, Queensland, Australia for this study. HybridOptimjzation Model for Electric Renewable (HOMER), acomputer model developed by National Renewable EnergyLaboratory (NREL) has been used to perform comparative analysisof solar and wind energy with diesel and hybrid systems. Initiallytotal net present cost (NPC), cost of energy (COE) and therenewable fraction (RF) have been measured as performancesmetrics to compare the performances of different systems. Finallyfor better optimisation, the model has been refined with sensitivityanalysis which explores perfonnance variations due to wind speed,solar irradiation and diesel fuel prices. From the simulation, it isshown that there are a number of factors that impact the integrationand perfonnance of renewable energy sources to the powersystems.

Keywords--Renewable Energy, Smart Grid, HOMER,Performances Metrics, Sensitivity Analysis.

1. INTRODUCTION

A recent issue of increasing public focus is the need forrobust, sustainable and climate friendly power

transmission and distribution systems that are intelligent,reliable and green. From the existing electricity grid it is notpossible to provide adequate services addressing energyefficiency, reliability and security, or the deployment ofclean renewable energy at the scale needed to meet theclean-energy demand for a new century. There are a numberof challenges in integrating renewable energy sources withthe existing power systems. Substantial research, planningand development are required for increased integration of

Manuscript received December 31, 2009.GM Shafiullah1

, Amanullah M. T. 002, Dennis Jarvis", ABM Shawkat Ali',

Peter Wolfs4

The first author GM Shafiullah is a PhD researcher with CQUniversityAustralia ( g.shafiullah@cqu.edu.au ).The presenting author Amanullah M T 00 is a lecturer in power systemswith CQUniversity (a.maungthanoo@cqu.edu.au )1,2 Faculty of Sciences, Engineering & Health, CQUniversity3 School of Computing Sciences, Faculty of Arts, Business, Infonnatics &Education, CQUniversity4 Faculty of Science and Engineering, Curtin University of TechnologylEmail:g.shafiullah@cqu.edu.au

renewable energy sources with the current powertransmission and distrihution network. Therefore at thebeginning of the 21" Century, the Governments, the utilitycompanies and the research communities are workingtogether to develop an intelligent grid system, nowcommonly known as the Smart Grid that reduces overallgreenhouse gas emissions with demand management andencourages energy efficiency, improves reliability, andmanages power more efficiently and effectively [1-3].

The Center for American Progress provides a conceptcalled a clean-electricity or clean energy "pipeline" whichproduces large scale renewahle electricity; deliver electricitynationwide on a new high capacity grid; manages all powergeneration and distribution with new sophisticatedinfonnation technology methods; allows consumers tocontrihute energy to the grid [2]. In April 2003, theDepartment of Energy (DOE), USA declared its 'Grid 2030'mission, the vision of which was: Grid 2030 energizes acompetitive North American Market place for electricity. Itconnects everyone to abundant, affordable, clean, efficientand reliable electric power anytime, anywhere. It providesthe best and most secure electric services available in theworld [4]. To fulfill this vision, Electrical Power ResearchInstitute's (EPRl's) IntelligridSM has under-taken aninitiatives to develop the technical foundation for a smal1power grid that links electricity systems withcommunication and computer technology to achievetremendous gains in reliability and customer services [5].Figure I shows a schematic diagram of EPRl's Intelligridmodel.

Figure 1 Atypical scenario of EPIU's Intelligrid Model [5]

The SmartGrids European Technology Platform [6]vision is that Europe's electricity network must be flexible(fulfilling customer needs); accessible (access to all networkusers, particularly for renewable energy sources and highefficiency local generation with low carbon emission);reliahle (assuring security and quality of supply); andeconomic (cost and energy efficient management).However, country like Australia, due to its availability ofcoal to produce cheap energy, is lack behind compared to

65

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2. MODEL EVALUATION

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A renewable energy hybrid model has been developedusing HOMER to explore the impacts of renewable energysources on the modem power grid. This section presentednecessary data collection procedure and the simulationsoftware used in this study to develop the hybrid model withthe measured performance metrics.

remote areas by utilising renewable energy sources and adiesel generator with a reverse osmosis desalination plant asa deferrable load. HOMER has been used to find theoptimum configuration for a hybrid power system. It hassbown that this hybrid power system is more effieientcompared to stand_alone system both economically andenvironmentally.

This paper investigates the impacts and integration ofrenewable energy sources with power system, analysing thebenefits and outcomes for a typical Australian powernetwork. In particular a feasibility study have heenundertaken to investigate the necessity of solar and windpower considering pollution, production cost and cost ofenergy. Tbis paper is organised as follows: Section IIdiscusses the evalnation of the model. Section III presentsexperimental setup to build a hybrid renewable energysystem. Results and discussions are described in Section IV.Section Y eoncludes the article with future directions.

2.2 Simulation Software

HOMER version 2.68 [17] has been used in this study toinvestigate the feasibility and cost analysis stndy ofrenewable energy sources. Homer models a power system'sphysical behaviour and its life-cycle cost which allows themodeller to compare many design options based on theirtechnical and economical merits, It can evaluate designoptions both for off-grid and grid-connected power systemsfor remote, stand-alone and distributed generationapplications. Inputs to Homer contain load data, renewablesource data such as photovoltaic, wind turbines, systemcomponents specification and cost, and various information

2.1 Data Collection

Data have been collected from the Australia Bureau ofMeteorology [16] for the location of Rockhampton andposition of the Rockharnpton Aero Weather Station (­23.3753°, 150.4775°, 10.4m). Daily mean solar radiationdata and three hourly mean wind speed data have beencollected from the year of 2007 as shown in Table I and 2respectively as a sample data. Data have been collectedusing a real time automatic system with perfonning qualitychecking.

a e ee :IY. 0 ar a !at

Day Radiation(kWh/m2/day)

Day 1 6.400000Dav2 5.838889Dav 3 7.377778Day 4 6.872222Day 5 8.366667

USA and European in an attempt to integrate renewableenergy sources and building smart grid infrastructure.Australia'~ reliance on coal-fired power gives it one of theworld's highest per-capita greenhouse gas emission rates [1­3, 7]. Therefore, it is necessary to reinvigorate theAustralian economy by building new generation,transmission and distribution systems for efficient use oflow-carhon electricity. In Australia, the Intelligent GridProgram [8] was launched on 19 August 2008 beingestablished under the CSIRO's Energy TransformedFlagship, and focuses on the national need to reducegreenhouse gas emissions [I]. The Townsville Solar CityProject administrated by the Australian Govemment andErgon Energy (A local Queensland based distribution utilityorganisation) has conducted 742 residential and commercialassessments, and installed 1445 smart meters, 160kW ofsolar panels and eight advanced energy storage systems.Ergon Energy is also working on analysing the impacts ofhigh photovoltaic's (PY) penetration on the grid. WesternPower's (a local Western Australia based transmission anddistribution utility organisation) Solar City program includesa PY saturation trial to test the impact of distributedgeneration on the network. The Solar cities program hashelped many distributors to understand the impact ofinverter connected renewable distributed generation (DG).This analysis included smart meters that collect bi­directional data to capture how much power the distributedgenerator is feeding back to the grid [1,9].

Wind generation is one of the fastest growing and costeffective resources among different renewable energysources. In addition to solar and wind, bio-gas andgeothennal are also useful renewable energy sources thatcan playa key role in reducing carbon emissions [9]. As thepenetration [10] of renewable energy continues to increase,it is time to rethink to develop a sustainable, green powersystem which is capable to integrate the various renewableenergy sources. Fortunately an operational smart grid hasthe potential to mitigate some of the difficulties encounteredby renewable energy g~neration. Renewable energy sourcessuch as wind or solar: are weather-driven, and therefore non­scheduled as these sources depend on wind flow or solaractivity respectively. The use of smarter grid operationsallows for greater penetration of variable energy sourcesthrough more flexible management of the system.Integration studies are continuing to improve performance,though there are still a few existing challenges [11-12].

Zoulias and Lymberopoulos [13] investigated a techno­economic analysis of the integration of hydrogen energytechnologies in renewable energy-based stand-alone powersystems using HOMER simulation tool. The experimentalresult shows that the replacement of fossil fuel based gensetswith hydrogen technologies is technically feasible andeconomically favourable compared to the PY-diesel systemas long as a 50% reduction on the cost of electrolysers and a40% reduction on the cost of hydrogen tanks are made,Kaiser and Aditya [14] developed a model using HOMERsimulation tool to find out the best technically viablerenewable based energy system for the consumers located inSaint Martin Island, Bangladesh. Experimental resultsshowed that it will be better to create PY-wind minigridcombination system for 50 homes instead of single homesystem.

Setiawan et al. [15] presented a design scenario forsnpplying electricity and fulfil clean water demand m

66

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3.2.2 Wind EnergyThree hourly wind speed data (m/s) were imported in

HOMER to synthesised based on weibull factor k~1.74,auto correlation factor~O.901, diurnal patternstrength~O.0271, and hour of peak wind speed~22. Figure 5shows the monthly wind speed between 4.557 and 7.427mls. Wind speed also varies with seasonal condition as likesolar radiation. From Figure 5 it has seen that there is ashortage of wind speed between June to August, and higherspeed from October to March.

3.2 Renewable Energy Sources

3.2.1 Solar EnergyDaily solar radiation data were imported in HOMER to

calculate daily radiation and monthly average values ofclearness index. Figure 4 illustrates that solar radiation ishigh between October to December. The average annualclearness index is 0.568 and the average daily radiation is5.68. Figure 4 demonstrates the daily radiation in kWh/m2

per day and the clearness index curve over the period of thewhole year. Considering the radiation variation, thesensitivity analysis is done with four values around the meanradiation.

of optimisation. It simulates thousands of systemconfigurations, optimises for lifecycle cost and generatesresults of sen~itivity analyses on most of the inputs. Itrepeats the optimisation process for each value of the input,so it is possible to examine the effects of changes in thevalue on the results [17-19].

In this paper NPC, RF and COE have been considered asperformance "metrics to evaluate and compares differentsystems. The total NPC of a system is the present value ofall the costs that it incurs over its lifetime, minus the presentvalue of all the revenue that it earns over its lifetime. Costsinclnde capital costs, replacement costs, O&M costs, fuelcosts, emissions, penalties, and the costs of buying powerfrom the grid. Revenues inclnde salvage valne and grid salesrevenue [16-17].

On the other hand COE is the average cost per KWh ofelectricity. To calculate the COE, HOMER divides theannualised cost of producing electricity (the total annualisedcost minus the cost of serving the thermal load) by the totaluseful electric energy production. The NPC is a moretrustworthy number than the COE therefore in this analysisNPC has counted as the primary metrics [16-17].

The renewable fraction is the portion of the system's totalenergy production originating from renewable powersources. HOMER calculates the renewable fraction bydividing the total annual renewable power production (theenergy produced by the PV array, wind turbines, hydroturbine, and biogas-fuelled generators) by the total energyproduction.

3. HYBRID RENEWABLE ENERGY SYSTEM

To investigate the strategic impacts of renewable energyin the smart power system in this paper, a model has beendeveloped and simulate with HOMER to identify theoperational characteristics of different renewable energysources with the existing power grid. This paper alsocalculates the cost of different hybrid systems and comparestheir performances based on performance metrics such asNPC, RF and COE. Simulation, optimisation and costanalysis of the model has been performed and finalrecommendation has been made. In this study solar andwind energy have been connected with a Grid-cOlmectedsystem and designed a PV/Wind/Grid hyhrid system. Thishybrid system consists of an electric load, renewable energysources (Solar and Wind) and other system componentssuch as, PV, Wind turbines, Converter, Grid.

3.1 Electric Load

A typical load system has been considered for thisanalysis considering Australian average monthly loaddemand. Daily load demand has illustrated in Figure 2 inwhich 13:00 to 16:00 time period has been observed as peakdemand. The electric 'load has a seasonal variation inDecember, January and February as peak months due tosummer while March to June requires fewer loads due towinter which is shown in Figure 3. The annual average ofthe electric load is 200 kWh/day and the annual peak load is27 kW of the data collected for this study.

67

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3.3 Hybrid System Components

The major components of the grid-connected hybridsystem are PV panels, Wind turbines, and a powerconverter. For economic analysing, number of units to beused, capital, replacement and Operation and Maintenance(O&M) cost, operating hours have defmed in HOMER inorder to simulate the system.

3.3.1 PhotovoltaicThe initial installation cost of photovoltaic arrays may

vary from $4.00 to $5.00 [20]. For an optimum solution, theinstallation cost for a 1.0 kW stand-alone PV array isassumed $4000 and O&M cost is considered practicallyzero. Sizes of the photovoltaic arrays are varied I to 4 kW.

3.3.2 Wind turbinesFor this study BWC Excel-R 7.5 kW DC wind turbine has

been used which is manufactured by Bergey Windpower[21]. The installation, capital and O&M cost ofthis turbineis respectively $17500, $15000 and zero.

3.3.3 Power ConverterA converter is required to convert AC-DC or DC-AC.

The installation costs for a 1.0kW converter is $800,replacement cost is $700 and O&M cost is consideredpractically zero.

3.3.4 GridThis proposed system is a Grid-connected system in

which the Grid acts as a backup power component. The gridis activated and snpply electricity when there is not enoughrenewable energy power to meet the load. Moreover, thegrid functions as a storage system so a grid-connectedsystem does not need any battery [22].

4. RESULTS AND DISCUSSIONS

To evaluate the performances of different hybrid systemsin this study optimal systems and the sensitivity analysishave been measured using HOMER simulation tools. Toidentify an optimal hybrid system, the PV-wind grid­connected system may be varied assuming the electricityfixed at O.3$/kWh. Figure 6 shows the proposed hybridsystem developed with HOMER.

4.1 Optimization Results

Simulation has been conducted considering differentvalues for solar radiation, wind speed and power consideringmore flexibility in the experiments. The optimisation resultsfor specific wind speed (5.67m1s), solar irradiation (5.68kWh/m' per day), and grid electricity price (0.3$/kWh) areillustrated in Figure 7. It is seen that, a wind based powersystem is economically more feasible with a minimum totalnet present cost (NPC) of $ 212456 and a minimum cost ofenergy CaE of $0.228/kWh than the PV-wind system;however the economic perfonnance of a PV-wind system is

68

almost similar to the wind only system. This difference isdue to the abundant of wind energy resource and the cost ofwind turbine generator is less than the solar array modules.This wind and PV-wind system represents greater RF (0.64)which means the bigger proportion of renewable energygeneratIOns.

Figure 6 Hybrid renewable energy system with HOMER

~f- ~,~ 3 16 1000 $65,300 11,519 $212,546 0.228 0.64

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Figure 7 Optimization results with wind speed (5.67mJs), solarirradiation (5.68 kWh/m2 per day), and grid electricity price

(O.3$ikWh)

The best optimum NPC ($174,340), CaE (0.187) and RF(0.93) have achieved from the wind speed (8.0 m1s), solarirradiation (3.68 kWh/m' per day), and grid electricity price(O.4$/kWh) shown iu Figure 8. However, in this caseelectricity price is more than usual. Therefore, it is requiredto conduct further study with more and useful data. FromFigure 7 and 8 it has been observed that PV-wind system orwind only system is more economical compared to thestandard grid system.

From the cash flow summary in Figure 9 it bas shownthat in the optimised PV-wind system most of the cost isrequired for the grid component while least money is for thePY. Therefore it can be stated that most of the cost is due togrid component and converters while renewable energysources requires less expenditure which is one of the mostuseful features of renewable energy resources. Anothermajor advantage is this optimised PV-wind system emitted12,061 kg carbou dioxide per year, while optimised standardgrid system emitted 46,136 kg per year.

The monthly average electric energy production isrepresented in Figure 10. Wind turbine produces 63,795kWh/year and grid produces 35,850 kWh/year. In thissystem wind turbine contribnted 64% and PV arraycontributed only I % of the total energy production. Furtheranalysis need to undertaken to increase the contribution ofPY array modules.

cf Jk!!1 40 1000 $ 137-81JO 2,644 $170,1300 0.183 0,83

cf'i' AA!!1 4D 1000 $ 14tCliJO 2,608 $174,340 0,187 093

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'f.'i' !!1 1000 $4,800 n061 $376,299 0.403 0.01

Figure 8 Bestoptirnum results with wind speed (3.68m/s), solarirradiation (8.0 kWhim2 per day), and grid electricity price

(O.4$/kWh)

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However, Grid-wind system is snitable than the grid onlysystem if the electricity price grows up to $O.l/kWh. Ithappened due to availability of large amonnt of windenergy.

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Figure 12 shows a surface plot in which NPC and CaEhas measured in which wind speed and electricity price arevariables with a fixed solar radiation of 7.68 kWh/m2/day.From these graphical representations, it has concluded that aparticular system would be optimal at a certain sensitivityvariables or conditions.

Figure 10 Monthly average electric energy production

4.2 Sensitivity Results

Sensitivity analysis is a measure that checks thesensitivity of a model when changing the value of theparameters of the model aud also changing the structure ofthe model. This analysis is useful in support decisionmaking or the development of recommendations of themodel. In this paper sensitivity analysis has beenundertaken to study the effects of variation in the solarradiation and wind speed and to made appropriaterecommendation in developing hybrid renewable energysystem. The simulation software simulates the long-termimplementation of the hybrid system based on theirrespective search size for the predefined sensitivity values ofthe components. The model has been simulated based on thethree sensitivity variables: wind speed, solar irradiation andgrid electricity price and different NPC, CaE and RF valueshave been observed as a model ontpnt.

HOMER simulates all the systems in their respectivepredefined search spaces. Simnlation is l1l1dertaken for everypossible system combination and configuration for a periodof one year. The sensitivity variable has been set for solarirradiation (G~3.68, 5.68, 7.68, 9.58, 10.68), wind speed(v=3.0, 4.0, 5.0, 5.67, 6.0. 7.0, 8.0), and the grid electricityprice (p=0.05, 0.1, 0.2, 0.3, OA). A total of 175 sensitivitycases were run for each system configuration. Thesimnlation was carried out with an Intel Core 2 Duo CPU,3.2 GB of RAM with Windows XP Operating System.

From the sensitivity analysis output optimal system type(OST) and surface plot were highlighted to explore themodel characteristics considering solar radiation, windspeed and grid electricity price. Figure 11 shows that thePV-wind system is feasible when the grid electricity price ismore than $O.3/kWh and wind speed is more than 3.0 mlswhile solar radiation is fixed at 9.68 kWh/m2/day.

Based on the optimisation resnlts it has observed thatwind energy plays a key role in this hybrid energy system asmore than 50% of energy has produced from wind turbineswhile less than 5% energy has prodnced from solarradiation. A major reason for these results is renewableenergy sources are weather-driven and possible to get windenergy 24 hours a day, 7 days a week and 365 days a yearwhile solar energy mostly depends on snnshine, which maybe 6 to 8 hours a day. Therefore the wind energy resourcehas more impacts on the implementation of hybridrenewable energy system for the future smart powernetwork.

Figure 12 Sensitivity analysis with surface plot

5. CONCLUSIONS

To investigate the impacts of renewable energy sources insmart power network, a feasibility study has beenundertaken to explore the characterises, and cost analysis ofgrid connected hybrid renewable energy system nsingHOMER simnlation software. The study simnlates a PV­wind grid-connected hybrid system in central Queenslandregion. The daily solar radiation and three hourly windspeed data were collected from the Rockhampton Aero

".

69

Weather Station. In 2007, the mean solar radiation was 5.68kWhlm2/day and wind speed was 5.67m/s. The optimizedhybrid renewable energy system was developed consideringmanufacturing cost, and efficiency which includes a BWCexcel-R wind turbine, and lkW PV module. Experimentalresults show that the COE of energy of the optimized systemis 0.23/kWh while the standard electricity is defined as0.3/kWb. The sensitivity analysis indicates that PV-windhyhrid system is feasible under specific meteorologicalconditions in Central Queensland region, while wind-gridsystem is most suitable for most of the conditions. From thedeveloped model it has clearly observed that wind energyhas more impact in this hybrid system than the solar energy.However, this study is still in introductory stage and needsto be developed in different areas. Therefore furtherinvestigations are suggested on the following areas:

• Experimental analysis with large volume of data,specially focus on solar radiation

• Analyse the characteristics and availability ofrenewable energy sources (solar and wind).

• Analyse the impact of renewable energy sourceswith the smart power systems.

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