Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 100 (2016) 360 – 365
3rd International Conference on Power and Energy Systems Engineering, CPESE 2016, 8-12 September 2016, Kitakyushu, Japan
Application of Geographic Information System to Power Distribution System Analysis Yusuke Kakumotoa,*, Yuki Koyamatsua, Atsushi Shiotaa,b, Yaser Qudaiha, Yasunori Mitania a
b
Dept. Electrical and Electronic Eng, Kyushu Institute of Technology, 1-1 Sensuicho Tobata-ku Kitakyushu Fukuoka 804-8550, Japan Dept. Information Technology Promotion at the General Affairs Bureau ,City of Kitakyushu, 1-1 Ootemachi Kokurakita-ku Kitakyushu Fukuoka 803-8501, Japan
Abstract This paper presents a new application of Geographic Information System (GIS) in the field of electric power engineering. GIS can analyze and visualize information related to Geography. Recently photovoltaic (PV) generation is introduced in the power system day by day for the needs of clean energy. If it is installed in large quantities, voltage variation occurs with a risk of worsening electric power quality. In this context the limit of introducing PV in the power system should be correctly grasped. This research focuses on distribution system with large amount of PV. In order to grasp the limit of introducing PV in the distribution system, PV generation should be evaluated correctly and analyze the state of the distribution system. Although PV generation is proportional to solar radiation, the amount of solar radiation is affected by the shadow of the building, the angle, and the direction. Therefore, it is difficult to grasp solar radiation falling on the PV panels accurately and calculate PV generation. GIS can solve the problem. GIS can model actual townscape and analyze the amount of solar radiation. By executing solar radiation analysis to the modeled townscape, the amount of solar radiation on any places in the town can be evaluated. Using the result of the analysis, PV generation installed on any places in the town can be estimated and more proper distribution system analysis can be performed than conventional analysis. © Published by by Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2016 2016The TheAuthors. Authors. Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of CPESE 2016. Peer-review under responsibility of the organizing committee of CPESE 2016 Keywords: Geographic Information System; distribution system; photovoltaic; smart grid
1. Introduction In Japan, there is a great demand of renewable energy triggered by the suspension of nuclear power plants after Great East Japan Earthquake in 2011. Highly expected renewable energies in the world are solar power and wind power. Solar power has high potential. If the whole area of Gobi Desert is covered with solar cells, all energy consumed in the world can be provided [1]. But photovoltaic can’t produce energy constantly because it depends on
*Corresponding author. Tel.: 090-7454-9902 E-mail address:
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1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the organizing committee of CPESE 2016 doi:10.1016/j.egypro.2016.10.189
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solarr radiation. Wind power also o has high pottential. If windd turbines are installed on thhe place wherre has good wiind cond ditions, they caan generate ellectric energy greatly and coonstantly. Butt it’s not easy to find the goood locations and a instaall wind turbinnes because wind w condition ns in Japan aree difficult to be b estimated ddue to changees of the seaso ons and typhoons t [2]. The location of photovoltaaic system cann be more easily chosen so it is more suiitable for narrow land of Japan. [3] Therefore, in Japan, solaar power is ddemanded mo ore than windd power. In aaddition, such as oduction of Feeed in Tariff (F FiT) and reducction in equipm ment prices arre spurring thee introductionn of photovoltaaic. intro By 2030, 2 cumulattive introduction amount off PV will reacch more than 100 1 GW. Phottovoltaic for rresidential usee is expeected to be insttalled constantly [4]. Iff photovoltaic is largely insttalled in distriibution system m, voltage variiation will occcur especially at the end of the distribution netwoork. It is possib ble to transcen nd stipulated vvoltage (101V± ±6V). Due to tthe over voltaage, output of PV P systeem is limited by power con nditioners [5]. To Avoid thhis situation, the t amount off photovoltaicc may be stricctly regulated by electrric utility in th he future. For that reasons ggrasping the in ntroduction lim mit beforehandd is necessary.. In P generation n should be properly calculaated and the sttate of the disstribution system order to achieve thhis purpose, PV uld be evaluateed. shou The amount off PV generatio on is related to the installattion situation of PV panel llike direction,, degree, shadow caused by high buuildings and trees. In other words, w the facctors influencin ng the PV genneration are geeospatial data.. In on, Geographicc Informationn System (GIS S) is used in thhe research. G GIS can manaage, order to calculate PV generatio yze, and show w the geospattial informatio on. One of thhe application n of GIS is ssolar radiationn analysis. So olar analy radiaation analysis is usually useed to estimate the area/periood of road freeeze [6]. Howevver, this functtion is applied d to calcu ulate PV generration in this paper. p Section 2 descrribes GIS tech hnologies. Secction 3 of this paper talks ab bout the utilizzation of GIS in power system s analysis and result. Seection 4 conclu udes. and some 2. Geographic Infformation Sy ystem Geographic G Infformation Sysstem (GIS) iss a technologgy for the creeation, managgement represeentation, searrch, analy ysis and shariing of geospattial informatio on [7]. GIS m manages data in a film calleed layer. The layer consists of posittion informatiion and attribu utes informatiion. As shownn in Fig.1, GIIS constitutes a model of thhe real world by supeerimposing layyers, which rev veals the geog graphical distriibution and geeographically related data. D Data used in GIS G calleed geospatial ddata is based on a so-called d big data witth a variety off functions. T Typical featurees and geospattial data of GIS is show w Digital Surface Modeel (DSM) is co onsidering thee height of treees and buildin ngs, wn in Fig. 2, where Tracking functtion handles the while Digital Elevvation Modell (DEM) is reepresenting grround surfacee in details. T on information n by GPS. Spaatial statistics functions agggregate the objjects in the vieew. trajectory of the accquired positio ork Geoccoding is respponsible aboutt coding the teext address. 33D function haandles the threee-dimensionaal data. Netwo analy ysis function pperforms the analysis of the network datta. Finally, Sp patial analysis function simuulates the eveents whicch might occurr in the targeteed area, for ex xample, simulaating the tsunaami[8]. To evaluate PV V power generrations in the distribution d syystem, DSM as a the geograpphical data andd 3D and Spattial analy ysis as the funnction of GIS are used. DSM M is used to m measure the diirections and ddegrees of PV V panels for so olar radiaation analysis on panels. 3D D is used to ex xpress the heiight of buildin ngs and trees. Spatial analyysis includes, for exam mple, solar radiation analyssis tool which h calculates th the amount off solar radiatiion falling onn PV panels and a describing tool whhich can expreess grid netwo ork and installled equipmentt on the map [[9]. To combinne the geospattial data with the functtion of GIS, distribution sysstem analysis iis supported.
Fig.1. The basicc principle of GIS S
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Fig g.2. Geographicall data-function of GIS
3. Calculating PV V power generration using solar s radiatioon analysis too ol When W objects liike trees cast a shadow on PV P panels, pow wer generation n is greatly droopped becausee of deterioration in so olar radiation. It is importan nt to considerr shadow effecct on PV pow wer generation . The effect ccan be calculated with power generration consideering solar rad diation analyssis, by using the functions of GIS withh Digital Surfaace del (DSM). Thhrough the DSM M data shadow w effect on soolar radiation analysis a can bee taken in accoount as shown n in Mod Fig.3 3.
F Fig.3. Image of Diigital Surface Model
u DSM ass the geographhical data and d 3D as the fuunction of GIS S. The heightt of Fig.4 describess townscape using build dings is expresssed by the brrightness of co olor, that is, thhe brighter describes the highher. Solar raddiation measuring point surrounded bby high buildiings is shown in Fig.4. To clarify the shaadow effect att the measurinng point, the two O is the origiinal townscape shown in Fig g.4, the other one is the buillding to have the diffeerent DSM datta are used. One meassuring point. T This condition n is made by clipping c the ooriginal townscape using onne of the functtion of GIS. The T resullt of solar raddiation analysiis is shown in n Fig.5. The oone line showss the solar raddiation at the measuring po oint without surroundinngs and the otther line show ws the solar radiation in the case where thhere are high bbuildings arou und m point. This figu ure means thaat the solar raadiation is deteriorated by the shadow m made by a hiigh the measuring build ding next to thhe measuring point p as shown n in Fig.6. In tthe figure the measuring m poiint is marked w with a concenttric circle.
Fig.4. Solar radiation measuring point (maarked with a circlee) surrounded by high buildings (m marked with doubble circles)
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Fig.5. The result of ssolar radiation ana alysis
Fig.6. (a) Visualization V of solar radiation aroound the measurin ng point at 10:00, (b) At 10:30
In n addition, solar radiation varies v greatly y depending oon the weatherr. However, ssolar radiationn analysis which conssiders weatherr change in GIS takes a lon ng time for thhe computing process. Therrefore, solar raadiation analy ysis undeer the sunny ccondition and solar radiatio on meter is ussed in this research to conssider the weatther change. The T solarr radiation inclluding weatheer and shadow effects at the measuring po oint is expresseed by the folloowing equation n: ܴܵ ܴ ൌ ܴܵ ൈ ݇
(1)
ܴܵ ܴ[kW/m2] is tthe solar radiaation including g weather andd shadow effects. ܴܵ [kW/ W/m2] means thhe value which ha solarr radiation meeter measures and as a resu ult SR includees the weather effect. ݇ meaans the ratio oof analyzed so olar radiaation at the meeasuring pointt to that at the point where ssolar radiation n meter is set. U Using this equuation PV pow wer geneeration is expreessed by following equation n: ܲ ൌ ܴܵ ൈ ܣ ൈ ߟ ൈ ߙ ൌ ܴܵ ൈ ݇ ൈ ܣ ൈ ߟ ൈ ߙ (2) wherre ܲ [kW/m2] is the calculatted PV power generation, ܣ is the arrea of PV paneel, ߟ is the effi ficiency of pow wer conv version, and ߙ is temperatu ure correction coefficient (T TCC). Efficien ncy of power cconversion inccludes efficien ncy of so olar panel andd that of poweer conditioning g system (PCS S). TCC repreesents the deteerioration of eefficiency duee to high temperature, where the facttor is only valid in the case of crystal siliccon based solaar cells [10]. Inn this calculatiion, C is assumed tto be expressed as a linearr function of temperature [11]. Calculateed PV power generation with w TCC ܣ ൌ ͷͲ [m2],, ߟ=0.15 is sho own in Fig.7.
䢹 䢸䢰䢷 䢸 䢷䢰䢷 䢷 䢶䢰䢷 䢶 䢵䢰䢷 䢵 䢴䢰䢷 䢴 䢳䢰䢷 䢳 䢲䢰䢷 䢲 䢲
䣕䣱䣮䣣䣴䢢䣴䣣䣦䣫䣣䣶䣫䣱䣰䢢䣝䣭䣙䢱决䣟
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䣒䣘䢢䣒䣱䣹䣧䣴䢢䣉䣧䣰䣧䣴䣣䣶䣫䣱䣰䢢䣝䣭䣙䣟
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䢳䢰䢴 䢳䢰䢳 䢳 䢲䢰䢻 䢲䢰䢺 䢲䢰䢹 䢲䢰䢸 䢲䢰䢷 䢲䢰䢶 䢲䢰䢵 䢲䢰䢴 䢲䢰䢳 䢲 䢲
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䢳䢲 䢳䢴 䢳䢶 䣖䣫䣯䣧䢢䣝䣪䣱䣷䣴䣟
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Fig.7. (a) Callculated PV poweer generation, (b) Solar radiation measured m by solar rradiation meter
d PV power geeneration is loow in the morn ning, which reeflects the shaddow effect at the Itt is found that the calculated meassuring point. U Using the solaar radiation an nalysis and thiis calculation, PV power gen eneration instaalled at any plaace can be b grasped acccurately. App plying this fun nction to distrribution system m analysis, m more proper siimulation can be perfo ormed comparred to conventtional simulatiion. In additioon, this functio on should be uuseful for a peerson who inteend to in nstall a PV paanel on the ro oof top of hiss/her house, ssince expected d power geneeration from th the panel can be evalu uated before innstallation. 4. Po ower distribu ution system analysis a consiidering the sh hadow effect on o PV generaation The distributionn system mod del used in thiis paper is shoown in the Fig g.8. The analyysis have beenn executed in the owing conditioons: Total routte length of the distribution system is 4.14 4 [km], the nuumber of housee connected with w follo the distribution d system is 240 an nd the rate of PV P generationn introduction is 30 [%]. Eveery bus of thiss system contaains the load and PV geeneration.
Fig.8. Distributiion system modell
In n the analysis,, two differentt situations aree considered: One is that alll PV systems are influenced by the shadow in th he morning, the other one is that all PV sy ystems are nott influenced by y the shadow. The result off voltage analy ysis is sh hown in Fig.9.. The figure describes d the shadow s effectt in the mornin ng. The resultt of the simullation shows that distribution system m analysis con nsidering the shadow effecct is possible. By obtaining solar radiatioon on the all PV P systeems using GIIS, and grasp ping PV geneeration using the calculation method inn this researcch, more prop per simu ulation in the ddistribution sy ystem can be performed. p Thhis method can n give the soluution to evaluaating the statee of the distribution d system.
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䢳䢲䢹 䢳䢲䢸䢰䢷 䢳䢲䢸 䢳䢲䢷䢰䢷 䢳䢲䢷 䢳䢲䢶䢰䢷 䢳䢲䢶 䢳䢲䢵䢰䢷 䢳䢲䢵 䢳䢲䢴䢰䢷 䢳䢲䢴 䢳䢲䢳䢰䢷 䢳䢲䢳 䢳䢲䢲䢰䢷 䢳䢲䢲 䢲 䢢
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䣅䣱䣰䣵䣫䣦䣧䣴䣫䣰䣩䢢䣶䣪䣧䢢䣵䣪䣣䣦䣱䣹䢢䣧䣨䣨䣥䣶 䣐䣱䣶䢢䣥䣱䣰䣵䣫䣦䣧䣴䣫䣰䣩䢢䣶䣪䣧䢢䣵䣪䣣䣦䣱䣹䢢䣧䣨䣨䣧䣥䣶
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Fig.9. The result of distribution system analysis
5. Conclusion This paper introduces an example of GIS application to electric power engineering field. Calculation method for PV power generation considering shadow effect is developed using solar radiation analysis tool in GIS. This calculation can be applied not only for power distribution system analysis but also for estimation of expected PV generation. To evaluate and manage the influence of large scale PV introduction in a power distribution system, the developed methods can monitor the dynamic behavior and steady state of distribution system and grasp the PV introduction limit in the system. This paper gives a solution for the best utilization of PV systems.
Acknowledgements This research was supported by the Ministry of Internal Affairs and Communications at Kitakyushu City of Japan. The authors would like to thank to the research members for their kind assistance.
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