Research and Development in Roof-Top Solar Potentiality Using LiDAR Technology
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The document discusses the application of Lidar technology for assessing the solar potential in Rajasthan, highlighting its significance for renewable energy development in the region. It outlines a methodology for automating solar photovoltaic deployment analysis, emphasizing the integration of demographic, engineering, and geographical data to optimize solar energy utilization. The paper also addresses challenges in urban information management necessary for effective solar PV assessment and outlines contributions to enhance environmental studies and renewable energy planning.
![thinning effective in the RANSAC script. That means the
output would be a conservative estimation of area available
for PV panels.
The methodology presented here is a continuation of previous
attempts made urban rooftop data for determination of the
regional PV potential on rooftops. However, this method is
more inter disciplinarily transparent, comprehensive and has
the advantage of relaxing the mandatory data quality. On its
own it is the next piece of the pyramidal procedure to estimate
solar photovoltaic potential from a regional level, to a
municipal level and now a household scale. Given these
qualities, it is suitable for use in regions without good LiDAR
data and part of it is possible for utilities in the developing
countries where these techniques are at an early stage of
VIII. References
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Visualization of LiD AR terrain models for
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[3] Moore, E., Freeman, T., Hensley, S., 2007. Spaceborne
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F. (Eds.), Remote Sensing in Archaeology. Springer,
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[4] Olz, S.; Sims, R.; Kirchner, N. Contribution ofcountries where these techniques are at an early stage of
development. The weakness of this methodology is a
compromise between mat hematical sophistication and
technical adaptability, between automation and intensive
supervision.The aspects mentioned in this paper, mainly
pertaining to the integration of spatial information in energy
modeling, are among the bottlenecks to the process of
integrating solar PV (and other forms of renewable energy)
into the current electricity grid.
VII. Conclusions
The paper provides a methodology for the application of
LiDAR to automated solar photovoltaic deployment analysis
on the regional scale. Ch allenges in urban information
extraction and management for solar PV deployment
assessment are determined and quantified. First, a
comprehensive examination and comparisons of existing
[4] Olz, S.; Sims, R.; Kirchner, N. Contribution of
Renewables to Energy Security. IEA INFORMATION
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http://www.iea.org/papers/2007/so_contri bution.pdf
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[6] Branker, K.; Pearce, J.M. Financial return for
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of Three Green Technologies for a Toronto Roof. M.Sc.
T hesis, University of Toronto, Toronto, ON, Canada,
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[8] Fthenakis, V.M.; Kim, H.C.; Alsema, E. Emissions from
photovoltaic life cycles. Environ. Sci. Technol. 2008, 42,comprehensive examination and comparisons of existing
algorithms and approaches to turn LiDAR point cloud into
2.5D urban sce nes was provided. A more cross -disciplinarily
transparent methodology that attains a 95% accurate
segmentation from raw and randomly chosen data was
demonstrated. The methodology implements what previous
literature recommends in terms of integrating cross
disciplinary competences in remote sensing, GIS, computer
vision and urban environmental studies. It is a robust
methodology that can work with poor -quality data and
reconstruct vegetation and building separately but
concurrently. Since the coarse selectio n of building regions is
crucial to reliable results considerable attention was focused
on this first step.The approach was data driven hence the
whole attempt can be regarded as a large scale optimization
problem aiming at best approximating the point clo ud.
Singular Value Decomposition, Random Sample Consensus
and Triangular Irregular Network were confirmed as essential
tools for the task. Rules of thumb were collected to
photovoltaic life cycles. Environ. Sci. Technol. 2008, 42,
2168 2174.
[9] Supported R&D
Activities in the Field of Photovoltaics. In Proceedings of
the 28th IEEE Photovoltaic Specialists Conference ,
Anchorage, AK, USA, 15
1734 1735.
[10] Cameron, M. The changing landscape of the global solar
electricity market: Opportunities and challenges for
European Industry. Photovolt. Bull. 2003 , 2003, 68.
[11] Hoffman, W. PV solar ele ctricity industry: Market
growth and perspective. Sol. Energy Mater. Sol. Cells
2006, 90, 3285 3311.
[12] Frankl, P.; Nowak, S.; Gutschner, M.; Gnos, S.
Technology Roadmap -Solar Photovoltaic Energy;
International Energy Agency: Paris, France, 2010; pp.
1 48.
tools for the task. Rules of thumb were collected to
incorporate in the development of such scripts for extracting
rooftops for solar pho tovoltaic potential. But there is still
room for the more mathematically rigorous or biologically
minded audience to contribute and orient the workflow to suit
their needs. Hence this can be regarded as the next step
towards a new generation of urban analysis software.](https://image.slidesharecdn.com/bkitproc-150823124653-lva1-app6891/85/Research-and-Development-in-Roof-Top-Solar-Potentiality-Using-LiDAR-Technology-7-320.jpg)
Research and Development in Roof-Top Solar Potentiality Using LiDAR Technology
- 1. Research and Development in Roof-Top Solar Potentiality Using LiDAR Technology Mr. Radhey Shyam Meena M.Tech Scholar (Power System) Student Member -The Institute of Engineering & Technology (IET), UACEE Mr. Jeetendra S Rathore Mr. Mukesh Lodha Mr. Manish Agarwal Ms. Shivani Johari M.Tech Scholar Asst. Prof. EED Asst. Prof. EED Head & Asst. Prof. EED Dept. Of Electrical Engineering Sri Balaji College Of Engineering & Technology Jaipur Rajasthan Technical University Kota Abstract: Energy security and its application is the key for economic growth to any country and state. The conventional generation is also the source of greenhou se gas emission attributing to global warming and has has adverse impact on climate. Therefore, a global shift towards sustainable renewable energy generation is being witnessed. India is blessed with abundant solar energy and if harnessed efficiently, Solar energy is extremely beneficial as it is non polluting and its generation can be decentralized. The state of Rajasthan receives maximum solar radiation Intensity in India with very low average rainfall. It also has desert land available in abundance. The refore, Rajasthan is likely to emerge as the global hub for solar power in the country. Challenge of climate change and global warming properties tha t could not be achieved before. LiDAR is extremely useful in atmospheric and environmental research as well as space exploration. It also have wide application in industry, defense, and military. LiDAR mapping is an accepted method of generating precise an d directly referenced spatial information about the shape and surface characteristics of the earth. Recent advancement in mapping systems and their enabling technologies allow scientists and professionals to examine natural and built environments across a wide range of scales with greater accuracy, precision, and flexibility then ever before. There are many considerations and trade offs that must be understood in order to make sound decisions about the procurement, processing, and application of LiDAR data. This paperChallenge of climate change and global warming continuously threaten the world community, and Rajasthan govt. Has also recognized the urgent need to tackle these challenges. In this paper a methodology is provided for the application of Light Detection and Ranging (LiDAR) to automated solar photovoltaic (PV) deployment analysis on the regional scale. Challenges in urban information extraction and management for solar PV deployment assessment are determined and quantitative solutions are offered. This paper highlights a need for connectivity between demographic information, electrical engineering schemes and geographical information systems (GIS) and a typical factor of so lar PV suitable roof area that can be extracted per method. conclusions are developed to provide guidelines for a final methodology with the most useful information in situations of incomprehensive GIS data to facilitate the processing of LiDAR, low budgets for both time and finance, and personnel with diverse expert in computer vision. The methodology can processing, and application of LiDAR data. This paper provide introductory and review information for application of LiDAR Technology in solar PV system. It has become an established method in todays technology for information collecting and elevation data across landscapes different project sites including for solar system , wind , and other new renewable energy sources. This is sensing technique as similar to radar but in radar we use radio wave and here we use laser light pulses. It collected ground based stationary and mobile collect points in site areas. Three dimensional representation also possible for new system of rail road and building development structures. LiDAR, which is commonly spelled and also known as LADAR or laser altimetry, is an acronym for light detection and ranging. It refer s to a remote sensing technology that emits intense, focused beams oflightand measures the time it takes for the reflections to bedetectedby the sensor. This information is used to computeranges, or distances, to objects. In thiswith diverse expert in computer vision. The methodology can be adapted for use anywhere that LiDAR and urban GIS data is available. Key Words : Light Detection and Ranging (LiDAR), Renewable Energy Source , Photovo ltaic, Computing Sensing, New Generation Technology. I. Introduction A.LiDAR LiDAR stand for Light Detection and Ranging, commonly known as Laser Radar. It is not only replacing conventional sensors, but also creating new methods with unique used to computeranges, or distances, to objects. In this manner, LiDAR is anal ogous to RaDAR (Radio Detecting And Ranging), except that it is based on discrete pulses of laser light. The three - dimensional coordinates (e.g., x,y,z or latitude, longitude, and elevation) of the target objects are computed from The time difference betw een the laser pulse being emitted and returned, The absolute location of the sensor on or above the surface of the Earth.
- 2. F i gu r e 1. Sc he m ati c d i ag ram o f A ir bo r n e L iD A R p er fo rmi n g l i ne s can ni n g r e s u l ti n g i n pa r all e l l in es of m e as u re d po i n ts (oth er s c an pa tte rn s e x i st , bu t th i s o n e is fa i rl y c o mmo n) T h er e ar e tw o cl a ss es of r em o t e se n s in g t echn ol o gi es tha t ar e dif f er en t i at ed b y th e so ur ce of en er gy us ed t o det ec t a t ar get : Pa s si v e S y st em s A ct i v e Sy s t em s . Pa s s iv e s y s t em s det ect r ad i at i o n t h at i s ge n era t ed by a n ext ern al s ou r ce o f en e rgy , s uch as th e su n, w hil e a ct i ve S o la r P h o t ovo l t ai c (PV ) e n e rgy c on ver si o n o ff e rs a s us t ai nab l e m et h o d o f pro duci n g el ec tr i ci ty to prov i de for S o ci et y n ee ds. T h e adv an ta ge o f PV i n ge n era t i on o f e le ct r ic i ty are - L o n g t e rm e co n o mi c g ro w t h i m p ro v em en t f or a n y c oun tr y t h at agg re s si v el y devel o ps t h e t ec hn ol o g y . P ro v i de a as s i st a n ce in e n er gy s ec uri t y . No at m o s ph e ri c em i s s i o n s o r ra d i o act i v e w as t e ge n era t io n du ri n g us e. It a ct s a s a dis t ri b ut ed el ec tri cal gen e rat i o n s our ce a nd h e n ce r ed uc es t h e de pen de n c e a n d p re ss ur e o n t h e cen t ra l uti l i t y ext ern al s ou r ce o f en e rgy , s uch as th e su n, w hil e a ct i ve s ys t em s ge n e ra t e an d d i re ct e n e r gy t ow a rd a t arge t a n d s ubs e quen t l y de te ct t h e ra di at i on. L iD A R s ys t em s a re ac t iv e s ys t em s be caus e t h ey em i t p ul s es o f l i ght (i . e. th e l as er b e am s ) an d det ect th e r ef l e ct ed l ig ht . T h i s ch a ra ct eri s t i c a l lo w s l id ar da ta t o b e co ll e ct ed at n i g ht w h en t h e ai r i s us ua l ly cl ea r er a n d th e sky c on ta i n s le s s a ir tr a f fi c t h an i n t h e da yt i m e. I n fa ct , m o s t l ida r dat a ar e co l l ect e d at ni ght . U n li ke r adar, l i da r c ann o t pe n et rat e cl o uds , ra in , or de n s e h az e a n d mus t be f l ow n du ri n g fa ir wea th er. L i DA R i n s tr u m ent s c an ra p idl y m eas u r e th e E art h s u rf ace , at s am p l in g ra te s g r eat er t h an 150 ki l o h e rt z (i . e., 15 0, 00 0 pu ls e s pe r s eco n d). T h e r es ul ti n g p ro duct i s a den s e ly s pa ced n et w or k o f h i gh ly a ccur at e geo re f er en ce d el ev a ti o n po i nts o f t en cal l ed a po in t cl o ud th a t c an be r ed uc es t h e de pen de n c e a n d p re ss ur e o n t h e cen t ra l uti l i t y l i n es in s ys t em s wi t h h ig h pot e nti a l f o r b la cko ut s an d ov er l o ads . T his has l ed t o i n t erna t io n al c oo p e ra ti o n an d t ec hn o l og y in ve st m e nt o v er t h e pa s t 2 5 ye ar s , w h i c h in t u rn ha s gi v en ri s e t o fan t a st i c gai n s in s o l ar P V c el l pe rfo r ma n ce a n d a p re dic t ed c h angi n g l an ds ca pe in R& D act i v i ti e s fo r s o l ar c el l t ec hn o l ogi e s . S o la r ce l ls ma de f r o m a v ar i et y of m a te ri al s hav e dem o n s t rat e d ef f i ci en ci es ov er t en pe r cent an d a re c urr e nt ly m an uf a ct u re d gl ob a l ly . A s th e t echn ol o gi ca l pr o fi ci en c y of t h e s o l ar cel l in dus t ry m at u re d , t h e t ot a l s h i pm e n t s o f s o l ar cel l s in cre as ed r api d l y. In th e l as t dec ade gl o b al s o l ar PV de plo y m en t h a s in c r ea s ed f r o m 1 G W t o 16 G W w i t h an annua l gr o w t h ra t e o f m or e tha n 40% , T h i s gr o w th r at e, w h i l e i m pr es s i v e, m us t b e ke pt i n co n t ext of t h e gl o b al en e rgy ma rke t. T h e in cre as in g t echn ol o gi ca l c om pe ti t i v en e ss o f s o l a r P V , am o n g o t h er ki nds o f ren ew ab l e e n ergi es , ha s co n t ri b ut ed t o- A n ew l o gi c o f i n f ras t ruc t ur e P r ov i s i on al . A para d igm sh i f t in en e rgy po l ic y .el ev a ti o n po i nts o f t en cal l ed a po in t cl o ud th a t c an be us ed t o ge n era t e thr ee- di me n si o n al rep r es ent at i o n s o f th e E art h s u rf a ce a n d i t s f ea t ure s. M an y L i D AR s y s te m s o pera t e i n t h e n ea r-i n fra r ed regi o n o f t h e e l ect ro m a gn et ic s pect r um, a lt h o ug h s o m e s en s o rs a ls o ope ra te i n t h e gr ee n b an d t o pen et rat e w a te r an d det ec t b ot t o m fea tu r es . T h e se b at h y m et ri c l i dar s y st e ms ca n b e us ed in ar ea s w i t h re la t i ve l y cl ea r w at er t o m e as u re s ea f l o or e l ev at i o n s . B. P ho tovo l tai c S yste m A para d igm sh i f t in en e rgy po l ic y . H ow e ver, i n th e deb a te s on u rb an a n d r egi o nal dev el opm e n t a n d r egi o nal in fr a st ruc tu r e po li c y , t h e in t eg rat i o n of di f fe re n t di s ci pl i n es (G eo gra p h i c I n fo rm at i on S y s t em (G IS ), e n v i ro n m en t al m o del in g, u rb an pl a nnin g , el ec tr i cal an d m e ch ani ca l e n gi n e eri n g) and t h ei r ro l es in th e de li v er y of ut i l i ty s erv i ce s s t i l l s eem s t o b e t ake n f or g r ant ed by t h e pub l i c and w i thi n ea ch si n gl e di sc i pl i n e an d to b e l ef t t o e n gin ee r s, n et w or k ope ra to rs and na t io n a l u t il i t y re gul at o rs . Co n s equen tl y , t h e re ha s b ee n li t t l e r es ea rc h o n t h e u rb an an d r egi o n al i mp a ct s of uti l i t y r es tr uct u ri n g and t h e c h a n g in g e n v i ro n m en t f o r u rb an and r eg i o n al go vern an c e w i t h a
- 3. large -scale introduction of PV. To take advantage of PV anding of the urban local potential (roof space and solar exposure among others) is critical for utility planning, accommodating grid capacity, deploying financing schemes and formulating future adaptive policies . The paper describes a methodology that is part of the complex process of assessing solar PV potential for a region using the Renewable Energy Region (RER). Specifically the methodology provides an application of Light Detection and Ranging (LiDAR) of urban to automated solar PV deployments on a municipal unit, which can be scaled up first to the level of a city and then the cities within the RER region. The primary stakeholders for this research are local and 002 2 )()()( TALTR R A RRTR t RP fovrbg r a t r Here Pr(R)=Optical power received from range R in J/s t = Transmitted pulse energy in J Ta= Atmospheric one way path transmittance time in s w = Angular scattering coefficient in m- 1 sr1 Ar/R2 = Projected solid angle of r eceiver as seen from scatterer at range R in sr = Overlap function L A = Incident back ground power in WThe primary stakeholders for this research are local and regional utilities companies,municipal government and academic research on regional ener gy modeling. Challenges in urban information extraction and management for solar PV deployment assessment are determined and quantified. This study provides the following contributions: A methodology that integrated the cross -disciplinary competences in remote sensing (RS), GIS, computer vision and urban environmental studies. A robust methodology that can work with low - resolution, spatially and temporally inconsistent and incomprehensive data and reconstruct vegetation and buildings separately and concur rently. Recommendations for future generations of software. II. Main Equations Concept LbgArfov= Incident back ground power in W The LiDAR equation for analog detection or photon counting bg r a t r NTR R A RRTR h RN 02 2 )()()( Here Nr(R) = Number of photons received from range R t = Transmitted pulse energy in J Ta = Atmospheric one way path transmittance time in s w= Angular scattering coefficient in m- 1 sr1 Ar /R2 = Projected solid angle of receiver as seen from scatterer at range R in sr = Overlap function Range calculated from light travel time dt Rn c dR )( Minimum range resolution, is the range uncertainty, which = Nbg= Received background photons in ph III. Technical Platforms Airborne topographic LiDAR systems are the most common LiDAR systems used for generating digital elevation models for large areas. The combination of an airborne platform and a scanning LiDAR sensor is an effective and efficient technique for collecting elevation data across tens t o thousands of square miles. For smaller areas, or where higher density is needed, LiDAR sensors can also be deployed on helicopters and ground -based (or water -based) stationary and mobile platforms. LiDAR was first developed as a fixed -position ground - based instrument for studies of atmospheric composition, structure, clouds, Minimum range resolution, is the range uncertainty, which results from the smaller of the laser pulse width or the A/D sample rate: n tclengthpulse R 22 t = Optical pulse width or interval, n = Reference index of medium The LiDAR equation that is used for solution of optical power received from range R is given blow - for studies of atmospheric composition, structure, clouds, and aerosols and remains a powerful tool for climate observations around the world. Modern navigation and positioning systems enable the use of water - based and land -based mobile platf orms to collect data. IV. Installation Story A. LiDAR & PV In order to determine PV potential for a city the ideal circumstance is having access to a 3D urban model , which requires that individual buildings are represented, next to urban vegetation, st reets, and other objects of the city
- 4. in fra str ucture such as wa terc our ses, power supply lin es, and in dividual obje cts like str eet signs or f oun ta in s. A Digital Sur fa ce Mode l (D SM) derived from point c louds a cqui re d by LiDAR or ste re o- photogr ammetry will indirec tly repr esent buildi ngs. While such models ca n be gener ated e asily a nd even automa tic ally, they on ly repre se nt the a ppr oxima te roof shape s without ge neraliz ation a nd without distinguishing betwee n in dividual buildi ngs on the one hand and betwee n buildi ngs a nd other ob jects like ground and vegetatio n on the other ha nd. If building or building block outline s (e.g., from ca dastral maps) are pr ovide d, mode ls ext rac ted fr om the combined LiDA R and G IS data a re enhan ced and sur fac e models ca n be gene rate d forindividual buildi ngs o r blocks. Howeve r, th ese models still do n ot a llow a distinc tion B. S ys t em De t ec ti on R el i ab l e an d a ccu r at e b ui l d in g ge n era t i on f ro m L i DA R dat a r equi re s a n u m b er o f pr oc es s es be yo n d ca pt u re o f a ccur at e ra w da t a. T h es e a re b uil di ng det ect i o n , o b je ct s egm ent at i o n , b ui l din g ext ra ct i o n , r o of s h a pe r eco n s t ruc ti o n a nd m o del in g qua li t y a n al y s is . T h e m a j o ri t y of av a i la b l e l i t e ra t ur e: Co n ce n tra t es o n i ndi v i dua l as pec ts o nl y an d h e n ce de ta ch es t h e rea de r f r om th e b i g pi c tu r e; O nl y us e s (a ss o ci a t ed) dat a of cer t ai n (e xce ll e nt) qual i t y o r c us to m i ze d c la s s if i e rs tha t a re o n l y pr of es s i on al l y kn ow n o r n o t publ i cl y av ai l a bl e (e Co gn i t i o n , F e at u re A na l ys t ); an d H a s li m it e d a ppli c at i on s i n te r m s o f t h e degr ee o fHow eve r, th es e m o del s s t il l do n ot a l lo w a d i s t in c ti o n b et w ee n in d i v i dual r o of f a ce s , n o r b et w ee n r o of a n d dorm e rs o r ot h e r o bj ect s , w h i c h is im po rt ant i n t h e co n t ext o f s ol a r PV in s ta l la ti o n s b e caus e a w h o le r o of PV i n st a ll a ti o n i s n o t al w a ys f ea s i bl e . Furt h e rm o re, art i fa ct s o f dat a ac qui si t i o n , e. g. , ca us ed by o c cl uded a re as , s am pl ing di s t an ce , o r re ma i nin g geo -r ef e re n ci n g e rro r s, ar e t y pi cal l y fo un d in s uc h m o del s. Ve rt i ca l w al l s m ay a ppea r sl ant ed o r n ot appea r a t al l duet o t h e 2. 5D g ri d r ep re se nt at i on. Af t er t h e c l ean -up of suc h err o rs , ro of s i zes w i ll gen e r al l y be s m al l e r th an th e ir a ct u al s i zes , t h e r eby r educi n g th e ir s h ado w i n g po t en ti al . I n t h e ext r em e ca s es , s hado w e f fec ts of adj ace n t bui l di n gs m a y n o t b e capt ur ed. T o in c rea s e th e re l ia b il i t y of th e b ui l di n g m o del s as w el l as th e r an ge o f po ss i b l e appl i ca ti o n s , add i t io n a l k n o w l edge o n b uil di n gs ha s t o b e i n co r po rat e d i nt o t h e m ode li n g pr o ces s . T y pi ca l a s sum p t i o n s ar e t o de f in e w al l s a s be in g v er t i cal an d ro o fs a s b ei n g a c om po s i te of pl a n ar f a ces . T hi s l eads to an H a s li m it e d a ppli c at i on s i n te r m s o f t h e degr ee o f c om pl exi t y t h a t t h e pr o duct a ll o w s . A l t h o ug h u r ba n t ext u re m o del in g i s hig h l y d y n a mi c (due t o t h e nat u r e o f th e m o del ed o bje ct ) an d c o mpl i ca t ed (due t o t h e r equi re d pr ec is i o n and i n t e r di sc i pl i nar y i n th e n um be r o f i n v o l ved e xpert i s e and t h e inh e re n t int era c ti o n b e tw een h um a n s a nd th e ur b an e n vi r o n me n t). T h e m e th o do l o g y for b ui l din g de te ct i on sub s equen t ly der i ve d a n d des cri b ed h e r e w a s de s ign ed t o co m pr om i s e b et w e en co s t sa v in gs an d t h e s m o o th es t a n d m o s t ef fe ct i ve l y e st a b li s h e d l ea rni n g c urv e po s s i bl e for an a udi e n ce as s u me d t o h av e n o p r ev i o us t ra i nin g i n co m put e r p r og r am mi n g , r em o t e s en s in g o r d i git a l i m age pr o ces s i n g. A n u n de rs t andi n g o f t h e c om pl exi t y of GIS dat a i n t eg r at i o n in e n ergy m o del i n g m ea n s an i m p ro v ed i n t er - di sc i pl i nar y app re ci at i o n fo r th e v al ue o f a s t rea m li n e d a n d co m pre h e n s i ve da ta s ys t em . F u r th e r, th e ab i l it y t o ca rr y o ut pa rt o f t h e p ro ce dure w i l l h el p f a ci l it a te t h e pe n et rat i o n o f s o l ar PV in to t h e cu rr e n t el ect ri c i ty gri d . I n t h e ab s en ce ofro o fs a s b ei n g a c om po s i te of pl a n ar f a ces . T hi s l eads to an i dea li z at i o n of t h e bui l d in gs. T h e tra n s i t io n z o n e o f t w o n ei g h b o ri ng ro o f f ace s , f o r exa m ple , b ec o me s a s t ra ig h t l i n e defi n e d by t h e i n t e rs ec t io n o f t w o r o of pl an es . T h e i m port an ce o f th es e co n s i de ra ti o n s i s r ai s ed w h e n it co m es t o PV s ys t em des i gn an d pe r ro o f i n st al l at i o n : t his enhan c ed m o del i s s uf fi ci en t i nput f o r ra pi d r o of as s es s m en t . H en c e a m o del i ng m et h o d i s n e eded f o r PV app l i cat i o n s t ha t i s: A cc ura t e,i. e., i t s h o uld p ro duce s i m pl e pol y gon al m ode l s f i tt i n g t h e i n pu t po in t cl o uds i n a p r eci s e m ann e r . Rob us t : re ga rdl es s o f th e d i ve rs i t y an d c om pl exi t y o f b uil di n g r o of s h ape s t h e me th od s h o uld al w ay s g e n era t e b uil di n g m ode ls co m p ri s ed o f fl at p la n es tha t ar e as co n t i n uo usl y an d s mo o t h l y c o nn ect e d a nd t ra n si t i o n ed as po s s i bl e even w it h t h e e xi st en ce o f un des ir ed el em en t s s uch a s re s idua l n o i s e and s m al l r oof f e at ure s . Com pl em ent a ry t o t h e 2 . 5D c hara ct eri st i c: th e m et h o d s h o ul d c rea t e 2 .5D po l y g o n al m o del s co mpo s e d of det a il e d ro of s and ve rt i ca l w al l s c o nn ect i ng r o of l ay er s . s o l ar PV in to t h e cu rr e n t el ect ri c i ty gri d . I n t h e ab s en ce of c ada s tra l dat a, th e re are s ev era l ef f e ct i v e m et h o ds fo r b ui l din g det ect i o n t hat w o rk we l l on la rger b uil d i n gs al t h o ugh s m a ll er b ui l di n gs ar e of te n m i ss ed . Bui l d in g det ect i o n ca n b e c arri ed o ut s o l el y on t h e L i DA R dat a o r i n h y br i d w it h o th er da ta s uc h as ae ri al p h o t os an d e xi st i n g bui l di ng out l i n es . B ui ldi n g o utl i n es are t h e int er s ect i o n o f t h e b uil d i n gs w i th i t s s urr o u n dings , in ge n era l t h e t erra in . T h e o ut l i n es t hat ar e us ed fo r th e ap p ro a ch us ed h e re h a v e t w o a dv ant age s : f i r st l y , t h e y r ep r es en t t h e re al s hape a nd s iz e o f t h e ro o f , a n d n o t t h e di m e n s i o n o f t h e ba s em en t . A nd s eco n dl y , a ppl yi n g th e s am e da ta a s us ed f or t h e ev al uat i o n e n s ur es t h e co m para b i li t y of t h e r es ult s d ur i n g t h e p ro ces s of t h e ev al u a ti o n . T h e y c on cl uded t ha t la s er sc anni n g i s m o r e s ui t ab l e t h a n tr adi t io na l ph ot o gra mm e tr y fo r de ri v i n g b ui l d in g h ei g ht s , ext ra ct in g pl ana r ro o f f ac es an d ri dges o f th e r o of s . H ow e ve r, ph ot o gra mm e tr y a n d a e ri al i ma ges l ea d to b et t er re sul t s in b ui l din g o ut l in e an d l e n g t h det e rm ina t io n. det a il e d ro of s and ve rt i ca l w al l s c o nn ect i ng r o of l ay er s . V. Me th od o l o gy As o ut l in ed a bov e, a w i de r an ge of te ch ni ques h a v e b ee n us ed t o ext ra ct bui l di n g geo m et r y , an d in p ar ti cul a r r o of ge om e tr y ,
- 5. from LiDAR point clouds and from ima ger y with or with out in depen dent buildin g outline data. Our focus is on rapid, models to assess photovoltaic solar potential of neighborhoods. Unlike most of th e methods de scribed above, exa ctness is n ot deemed as esse ntia l a s is generality to a wide var iety of situations and e fficienc y in spi te of rea listically mixed data quality. The me thodology used here is base d on th e following five a ssumpt ion s: (i) in dividual building r oof ar ea s c an be modeled pr ope rly by a composition of plane r faces; (i i) anything below a chosen eleva tion cutoff is irre levant for sola r PV potential assessment; (iii) tre e ca nopies are opaque ; (i v) sma ll windo ws on the roofs, overha ngs on th e wa lls, Heating, Vent and Air Conditioning free for P V pa nels; (v) the h eight of the obje ct an d subseque ntly th e altimetr y of th e Digital Surf ace Model (D SM) is the differen ce betwe en LiDARs z value s an d an a vailable D EM and (vi) ther e is no discrepan cy in the form of ur ban structure s betwe en Aer ial Photos (A P) a nd LiDAR (i . e., t h e se dat as e ts w e re co l le ct ed a t or n ear t o th e s am e t i me ). A m o n g m ult i pl e l ev el s of re tu rn s t hat L i D AR of f er s, th e la s t r et u rns of t h i s ar ea w er e use d fo r r oo f co n s t ruc t io n si n c e t h e y w e re co n s i der ed t o m o s t l i kel y rea ch t h e cl o s es t t o t h e gr o un d h e n ce t h e la s t o b je ct o n th e g r oun d o r t h e g ro u n d i t s el f wo uld b e pi cke d up by t h e l as t pul s es . E spe ci al l y fo r b ui ld i n gs la s t a n d f i r st ret u rns ar e t h e sa m e ( in z v al ues ), w h i c h w as c h ecke d w it h th e cu rr e n t da t as et . A c om pl et e f low c h ar t s h o w i n g t h e s t eps t hat pr ec ede t h e c re at i on of a DS Mov erha n gs o n th e w a ll s , H eat i n g , Vent an d A i r Co n di t io ni n g f a ci l it i es (H VACs) an d a n t e nnas do n o t o ccup y s o l a rge a s pace t h at i t s o mi s s i o n adds s i gn if ic an t ar ea t o t h e ro o f a re a s h o w i n g t h e s t eps t hat pr ec ede t h e c re at i on of a DS M pr es ent ed in t hi s pape r an d a pp li e d fo r t hi s s im ul at i on is gi v en i n Fi gu re s. - F ig. 1(a). Th e c l ass i fi cati on o f p oi n ts b as ed o n th e o b je c ts th ey co rr es p on d to was c a rri e d o u t Fi g. 2 (b ) R oo f s egr egati o n was do ne u s i n g MatL ab (a ) (b)
- 6. F i g. 1(c ) C o ns tr u c ti o n and I r rad i an ce Mo d el i ng P V R oof F i tti ng T h e s ub po i n t s a t thi s po in t ar e r ea dy t o b e s egm en te d an d us ed f o r rec on st r uct io n . I n a m at h em a ti c al s e n s e, s in c e t h e as s um pt io n is th a t ea ch pl a n e can b e r ep r es ent ed b y a di st i n ct i n t e r pol a ti o n i n r egi o n g ro w i n g . E q uat i o n s fo r h ori z o n t al ro of f a ce s ar e rel a ti v el y ea s y to c o n s truc t , b ut t h o se f o r s l an t e d f a ce s h a ve f i r st t o b e re co gn i z ed b y R A NSAC be for e bei n g l i n ea rl y re gr es s ed by th e S in gul ar v a lue Dec om po s i t io nas s um pt io n is th a t ea ch pl a n e can b e r ep r es ent ed b y a di st i n ct equa t io n i n t h e Ca rt es i an coo r dina t es , s egm e nta t i on is t o der i ve s uch e quat i on s , w h i ch are i n t u rns us ed f or l i n ea rl y re gr es s ed by th e S in gul ar v a lue Dec om po s i t io n ( SVD ) a l gor i thm . F i g. 3 . A v e rti c a l cu t o f an e x ampl e h ou se ne xt to a tre e s h o w i ng the bu ffe r an d th e e l ev ati o n c u to ff. I n add i t i on i t s ho w sF i g. 3 . A v e rti c a l cu t o f an e x ampl e h ou se ne xt to a tre e s h o w i ng the bu ffe r an d th e e l ev ati o n c u to ff. I n add i t i on i t s ho w s th e v er t i ca l ex te nt o f th e fo u r ri n gs u s ed fo r cl as s if i c ati o n. V I. Di sc u s s i on and F u t u r e W o rk As c an be s ee n th e re s ult s a re w i th in n u ll err or g i v en fi v e key as s um pt io n s : (i ) i ndi vi du al b ui l di n gs ca n be m ode l ed pro perl y by a co m po s i ti o n o f pl a n e r f ac es ; (i i ) an y t h i ng b el ow a ch o s en e l ev at i o n cu t o ff i s i rr el ev a nt f or s o l ar PV po t ent i al as s es s m en t ; (i i i ) t ree can opi e s a re o paque; ( i v ) sm a ll w i n do w s o n t h e ro of s , o ver han gs on t h e w al l s , H V ACs a n d ant enna s do n o t o ccup y s o la rge a s pac e t h at t h ei r o m i s si o n a dds s i gn i f i can t ar ea t o th e r o of ar ea f ree fo r PV pa n el s ; (v ) t h e h ei g ht of t h e ob jec t a n d s ubs eque n t l y t h e a l ti m et r y of t h e D S M i s t h e dif f e re n ce b et w e en L iD A R s Z v a l ues and t h e D E M ; an d (v i ) n o di sc r epa n c y i n rea l ti m e ur b an st r uct u res b et w een a eri al p h o to s (AP ) a n d L i DA R . Ne i t h er w i l l i t af fe ct t h e v al i d it y of th e D SM a s t h e el e va t i on i s pr es er v ed. T h e r oo f ar ea , h o w ev er , w i l l b e s m al l er , s i n ce t h e ro of ar ea w a s t w i ce r educe d: t h e f i rs t t i m e by th e use o f a b u f f er a l on g t h e e dges a n d th e se co n d t i me by t h e po in t
- 7. thinning effective in the RANSAC script. That means the output would be a conservative estimation of area available for PV panels. The methodology presented here is a continuation of previous attempts made urban rooftop data for determination of the regional PV potential on rooftops. However, this method is more inter disciplinarily transparent, comprehensive and has the advantage of relaxing the mandatory data quality. On its own it is the next piece of the pyramidal procedure to estimate solar photovoltaic potential from a regional level, to a municipal level and now a household scale. Given these qualities, it is suitable for use in regions without good LiDAR data and part of it is possible for utilities in the developing countries where these techniques are at an early stage of VIII. References [1] Smith, Michael E, 2007. Form and meaning in the earliest cities: a New approach to ancient urban planning. Journal of Planning History 6, 3 e 47 [2] Devereux, B.J., Amable, G.S., Crow, P., 2008. Visualization of LiD AR terrain models for archaeological feature detection. Antiquity 82, 470 e479 [3] Moore, E., Freeman, T., Hensley, S., 2007. Spaceborne and airborne radar at Angkor: introducing New technology to the ancient site. In: Wiseman, J., El - Baz, F. (Eds.), Remote Sensing in Archaeology. Springer, New York, pp. 185 e216. [4] Olz, S.; Sims, R.; Kirchner, N. Contribution ofcountries where these techniques are at an early stage of development. The weakness of this methodology is a compromise between mat hematical sophistication and technical adaptability, between automation and intensive supervision.The aspects mentioned in this paper, mainly pertaining to the integration of spatial information in energy modeling, are among the bottlenecks to the process of integrating solar PV (and other forms of renewable energy) into the current electricity grid. VII. Conclusions The paper provides a methodology for the application of LiDAR to automated solar photovoltaic deployment analysis on the regional scale. Ch allenges in urban information extraction and management for solar PV deployment assessment are determined and quantified. First, a comprehensive examination and comparisons of existing [4] Olz, S.; Sims, R.; Kirchner, N. Contribution of Renewables to Energy Security. IEA INFORMATION Paper. 2007. Available online: http://www.iea.org/papers/2007/so_contri bution.pdf (accessed on 17 March 2011). [5] Wong, J.L. Getting out of the shade: Solar energy as a National Security Strategy. China Secur. 2009, 5, 88 100. [6] Branker, K.; Pearce, J.M. Financial return for government support of large - scale thin film solar photovoltaic manufacturing in Canada. Energy Policy 2010, 38, 4291 4303. [7] Myrans, K. Comparative Energy and Carbon Assessment of Three Green Technologies for a Toronto Roof. M.Sc. T hesis, University of Toronto, Toronto, ON, Canada, 2009. [8] Fthenakis, V.M.; Kim, H.C.; Alsema, E. Emissions from photovoltaic life cycles. Environ. Sci. Technol. 2008, 42,comprehensive examination and comparisons of existing algorithms and approaches to turn LiDAR point cloud into 2.5D urban sce nes was provided. A more cross -disciplinarily transparent methodology that attains a 95% accurate segmentation from raw and randomly chosen data was demonstrated. The methodology implements what previous literature recommends in terms of integrating cross disciplinary competences in remote sensing, GIS, computer vision and urban environmental studies. It is a robust methodology that can work with poor -quality data and reconstruct vegetation and building separately but concurrently. Since the coarse selectio n of building regions is crucial to reliable results considerable attention was focused on this first step.The approach was data driven hence the whole attempt can be regarded as a large scale optimization problem aiming at best approximating the point clo ud. Singular Value Decomposition, Random Sample Consensus and Triangular Irregular Network were confirmed as essential tools for the task. Rules of thumb were collected to photovoltaic life cycles. Environ. Sci. Technol. 2008, 42, 2168 2174. [9] Supported R&D Activities in the Field of Photovoltaics. In Proceedings of the 28th IEEE Photovoltaic Specialists Conference , Anchorage, AK, USA, 15 1734 1735. [10] Cameron, M. The changing landscape of the global solar electricity market: Opportunities and challenges for European Industry. Photovolt. Bull. 2003 , 2003, 68. [11] Hoffman, W. PV solar ele ctricity industry: Market growth and perspective. Sol. Energy Mater. Sol. Cells 2006, 90, 3285 3311. [12] Frankl, P.; Nowak, S.; Gutschner, M.; Gnos, S. Technology Roadmap -Solar Photovoltaic Energy; International Energy Agency: Paris, France, 2010; pp. 1 48. tools for the task. Rules of thumb were collected to incorporate in the development of such scripts for extracting rooftops for solar pho tovoltaic potential. But there is still room for the more mathematically rigorous or biologically minded audience to contribute and orient the workflow to suit their needs. Hence this can be regarded as the next step towards a new generation of urban analysis software.