Abstract

Within a general framework of urban lighting, an index aimed at reducing the energy consumption without affecting the comfort and security of the users is proposed. This index (termed Energy Efficiency Indicator or simply EEI) represents the attainable energy savings in an urban lighting system. The Energy Efficiency Indicator spans the range from 0 to 100 where a 0 value means zero energy savings, and a 100 value is obtained from the model for the maximum attainable energy savings. For low luminance levels, it takes into account the improvement of visual performance by correcting the standard photometry system (photopic) by the recommended system (mesopic) in the CIE 191:2010 technical report. In addition, an assessment for three different scenarios is made, in order to determine energy savings using different types of light sources, luminous flux control and corrections due to the use of the mesopic photometry system. Each scenario represents different sectors or areas of a city. Results show that the third scenario studied, which is based on LED lamps, having individual luminous flux control and considering the mesopic photometry system, obtained the greatest energy savings (EEI = 96).

1. INTRODUCTION Cities are the main centres of economic and residential activities, as well as places with higher population growth. Despite representing only 2.7% of the global surface area [1], the worlds cities are responsible for 75% of the global energy consumption and 80% of greenhouse gas emissions [2]. Some studies in Spain propose that new cities should tend to the self-sufficiency and thus reduce their energetic dependencies by means of promoting energy savings and energy efficiency in both building and public spaces [3]. Urban lighting, as an element of the public space design and a large energy consumer, is the subject of study in this work. It is worth noting that a poor lighting design can lead to a waste of energy, light pollution as well as to a deterioration of the visual comfort and security of the inhabitants living in an urban area. Lighting represents approximately 19% of world energy consumption. In Spain, for 2010, urban lighting was

responsible for 3,629 GWh/year, which represents 0,8% of the total national energy consumption that in turn is translated into 747,574 tonnes of CO2/year emitted into the atmosphere [4]. With the aim of meeting the objective laid out by the EU to reduce CO2 emissions by 20% before 2020 [5], European cities and decision-makers are taking actions to promote energy savings and the reduction of emissions of CO2 by providing funds for the development of projects targeting energy efficiency in public lighting, cogeneration of energy, and construction of net-zero buildings. The Energy Efficiency Indicator (EEI) presented in this work, can be easily applied and read by the non-expert and shows the potential savings that can be achieved by using different lamp technologies, luminous flux controls and the correction to the mesopic photometry. Even when the amount of electricity consumed by urban lighting is an important issue, it must be balanced against the comfort and security of users, and therefore, the EEI takes into account the visual performance as well. In the following sections, a brief description of the mesopic photometry system is briefly described, a number of important lighting design criteria based on visual performance are given, relevant studies related to the execution of visual tasks are listed and, finally, an example of application of the EEI in three different urban lighting scenarios closes the work.

2. VISUAL PERFORMANCE BASED ON MESOPIC PHOTOMETRY

Human vision is a complicated process in which the spectral luminous efficiency of the eye is influenced by a large number of factors [6]. In the mesopic region, which lies between photopic and scotopic vision, both cones and rods are activated. Under this situation, the eyes sensibility changes rapidly depending on factors such as luminance and the Spectral Power Distribution (SPD) of the light source used [7]. For these reasons, the CIE has recently published a recommended system for mesopic photometry that applies to the whole range of the mesopic region [6]. This system maintains the photopic V() and scotopic V() spectral luminous efficiency functions as upper and lower limits of the mesopic region [7]. The luminance levels in the edges of the mesopic region are

TOWARD A NEW MODEL OF SUSTAINABLE URBAN LIGHTING Lizeth Artemisa Snchez Balvs1, Jess M. Quintero2,4, Antoni Sudra-Andreu3,

Jos Juan de Felipe Blanch1 and Josep Carreras2 1Universitat Politcnica de Catalunya. SUMMLab, Espaa - felipe@mmt.upc.edu

2Institut de Recerca en Energa de Catalunya (IREC). Grupo de Iluminacin, Espaa - jcarreras@irec.cat 3Universitat Politcnica de Catalunya. CITCEA-UPC, Espaa - sudria@citcea.upc.edu

4Universidad Nacional de Colombia, Dep. Ing. Elctrica y Electrnica, Colombia - jmquinteroqu@unal.edu.co E-mail: lizeth.artemisa.sanchez@estudiant.upc.edu

0,001 and 10 cd/m2 [6]. This range covers, among others, street luminance levels, emergency lighting, security lighting and public lighting for crime prevention purposes [7]. The recommended CIE photometric system [6] showed in Table 2 gives the correction factors that have to be applied in order to obtain the equivalent mesopic luminance level. These correction factors depend on the standard photopic luminance level and the so-called S/P ratio of the light source, which is essentially the ratio of the spectral energies lying within the scotopic and the photopic regions. For example, high pressure sodium lamps (HPS) have a S/P ratio from 0,65 to 1,05, while Metallic Halide lamps (MH) are from 1,25 to 2,45 S/P [6]. 2.1 Mesopic photometry applications A capital application of the mesopic system of photometry is road lighting, since the luminance levels at night fall into the mesopic region [6]. In this zone, both rods and cones in the retina are activated, which increases peripheral vision and enhances visual performance in specific tasks such as driving at night.

3. DESIGN CRITERIA FOR URBAN LIGHTING

The main goal of urban lighting is to provide an adequate environment for urban tasks while at the same time preserving comfort, high perception of security and adequate visibility for safe movement. The designs that fulfil these requirements encourage citizens to use the public space in urban areas. These aspects of the urban lighting are explained in more detail in Table 1.

4. THE ENERGY EFFICIENCY INDICATOR (EEI)

The EEI is intended to represent the energy savings that can be reached in an urban lighting system. EEI is ranged from 0 to 100. Essentially, there are three steps to calculate this index: (i) All possible technical scenarios of the urban lighting under study must be defined. This implies the definition of a data gathering system that includes all possible types of light sources, control gears, environmental and maintenance conditions, types of roads with their average illuminance (or luminance) levels and average representation of different possible luminous flux profiles corresponding to the lighting management of the lighting system. (ii) An equation that involves all these parameters is used to calculate the energy consumption for a large set of combinations of these input conditions and options. (iii) 100-percentiles (from zero to 100th) are calculated in order to rate the different scenarios. Here percentile 100th represents the worst case, or in other words, is the combination of input options having the highest energy consumption, while percentile zero represents the ideal scenario, since is the combination of

the input options with the least energy consumption. In these terms, energy consumption of percentile 100 represents zero energy savings, i.e. EEI = 0, and energy consumption of percentile zero represents the maximum attainable energy savings, i.e. EEI = 100. 4.1 Energy Consumption calculations Let us call Qsa the total energy consumption during one year per unit of illuminated area. The equation to calculate this is obtained from the Technical Regulation of Energy Efficiency in Public Lighting R.D. 1890/2008 [16]. To obtain the energy consumption Qsa, we cleared this equation for power and multiply it by the average number of hours that the light system is turned on. Doing so, the resulting equation reads, Q!" = !!!!"!!"#!!"!!!! !!""" !"#!! (1) Where: Em: Average illuminance level (lux); tua: Annual time of operation of the lighting system (h); aux: Efficiency of auxiliary elements (W/W); Knl: Nominal efficacy of lamps (lm/W); fm: Maintenance factor; fu: Utilization factor. From Equation 1, it can be inferred that a reduction of the energy consumption in practical terms can be obtained by two ways:

Reducing the annual equivalent operation time of the lamp (tua). Alternatively, this can be achieved by using different flux control techniques.

By improving the luminous efficacy of the lamp, i.e. applying a correction factor associated with an improvement of the users visual performance in the mesopic region.

Fig. 1. Trhee different luminous flux control profiles.

0 20 40 60 80

100

13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 % lu

min

ous f

lux Full luminous flux (12 hours of operation time per day)

A1 = 100% fcf = 1

0 20 40 60 80

100

13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12 % lu

min

ous f

lux

Bi-level luminous flux control

A2 = 88% fcf = 0,88

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100

13 14 15 16 17 18 19 20 21 22 23 24 1 2 3 4 5 6 7 8 9 10 11 12

% lu

min

ous f

lux

Individual fixture luminous flux control (40% to 100%)

hours

A3 = 58%

fcf = 0,58

Fig. 1 shows trhee different luminous flux control profiles. The correction factor fcf for each type of luminous flux control is obtained as the area percentage of the luminous flux profile as compared to the full luminous flux.

Once the type of lamp, level of photopic luminance and type of luminous flux control have been defined, two correction factors can be calculated: fcm and fcf. The correction factor for the luminance in the mesopic region fcm is obtained from Table 2, while fcf is calculated from the flux profile selected, as shown in Fig. 1.

Table 1 Summary of the parameters that define mesopic visual performance in the urban lighting objectives.

Table 2 Correction factors for mesopic photometry. HPS MH LED FL

S/P= 0,65 S/P= 1,85 S/P= 2,25 S/P= 2,45 Lp L

mes Lp L

mes Lp L

mes Lp L

mes 0,5 -6 0,5 13 0,5 19 0,5 22

0,75 -5 0,75 11 0,75 15 0,75 20 1 -4 1 9 1 12 1 14

1,5 -3 1,5 6 1,5 9 1,5 10 2 -2 2 5 2 7 2 8

Source: Table 11 of the Recommendation CIE 191:2010 [7]

Finally, Equation 2 shows how to calculate the total energy consumption during one year per unit of illuminated area considering corrections for mesopic photometry and the profile of the luminous flux control. !!" = !!(!!"!!")!!"#(!!"!!") !!!! !!""" !"!!! (2)

The nominal luminous efficacy of the lamp (Knl), utilisation factor (fu) and three different factors needed to calculate the luminaire maintenance factor (fm), i.e. Lamp Lumen Depreciation Factor (LLD), Lamp Survival Factor (LSF)

Urban Lighting Aims

Visual tasks Design criteria Investigations results

Safe movement Visual orientation -Luminance levels To provide suitablelighting levels on signage and key landmarks within the city [8]. Also it is possible to reduce the illuminance of the pavement by one class of the S-series when using lighting of CRI>60 [9], [10].

Ability to detect obstacles on the pavement and road.

-Spectral Power Distribution (SPD) of lamps. -Contrast: luminance difference between the target and its background.

Using lamps with a broad SPD as metal halide lamps [7]. Contrast is defined by the relative luminance difference between the target and its background [6]. Obstacle detection increases when the illuminance is increased, and the dispersion -due to light source type and observers' age- in obstacle detection between 0.2 lux and 2.0 lux is greater than that between 2.0 lux and 20 lux" [11]. At 0,2 lux is better obstacle detection under the ceramic metal halide (CMH) lamps than the high-pressure sodium (HPS) lamps. At 2 lux and 20 lux there appears to be no difference in obstacle detection between the lamps [11].

Perception of safety

Perception of spatial brightness of the area.

-SPD Lamp -Luminance levels

Light sources that provide a perception of greater brightness such as CMH lamps are perceived as producing a safer environment [12][13]. At equal illuminance, CMH and fluorescent lamps are significantly brighter than HPS lamps [13], [14].

Facial recognition -SPD Lamp

The detection and recognition of pedestrians can be improved through the use of lighting of higher S/P ratio [7]. Greater ease of facial recognition using CMH lamps as compared to HPS lamps [14]. If HPS lamps are used for facial recognition of pedestrians at a distance of 4 metres, the illuminance required is two times higher than that needed when using white light sources [8].

Perception of comfort

Disability of glare -Glare control -Luminaries photometry

To install luminaries that distribute light efficiently and that the correct optics and lamp position. In Spain, light distributions having beams directed up more than 5% above the horizontal plane are not allowed by regulation [15]. Streets illuminated with white light such as CMH are more comfortable than streets illuminated with HPS [14].

Acceptability (colour of the light source)

CRI (Colour Rendering Index) CCT (K) (Correlated Colour Temperature)

and Luminaire Dirt-Depreciation Factor (LDF) are showed in Table 3.

Table 3 Values for nominal luminous efficacy, utilisation and maintenance factors for four different light sources (values taken from ref. [16]).

The annual energy consumption values per unit of illuminated area, Qsa, were calculated for 24 different scenarios combining different options on the type of road and light source (Table 3), luminous flux control (Fig. 1) and the correction factors for mesopic photometry (Table 2). Taking the minimum value of energy consumption obtained (0,378 kWh/m2 corresponding to percentile zero) as the maximum energy efficiency combination (ideal scenario) and the maximum value of energy consumption (6,914 kWh/m2 corresponding to percentile 100th) as the minimum energy efficiency combination (worse scenario); we can define the energy savings or energy efficiency indicator, EEIp.u as in Equation 3. In these terms EEIp.u equals zero for the worst scenario (maximum energy consumption), and EEIp.u equals 1 for the ideal scenario (minimum energy consumption). Fig. 2 shows the corresponding percentiles (0 to 100th) of Qsa for all the 24 scenarios evaluated (PQsa) and represented in a scale from 0 to 1, along with their corresponding EEIp.u values. !!"!.!. = 1 !!!" (3)

Fig. 2 Percentiles for Qsa and calculated EEIp.u. values.

Finally, we let EEI span the [0,100] interval by multiplying by a 100 factor as is shown in Equation 4. !!" = !!"!.!. 100 (4)

5. USING THE ENERGY EFFICIENCY INDICATOR

As an example of application, EEI was applied in three different scenarios described in (Table 4). Each scenario represents a type of city or a typical neighbourhood in a city. Scenario no. 1: Lighting in road and pedestrian areas with HPS lamps. HPS lamps are highly efficient and have relatively long lifetimes (16 000 hours). However, their use comes at the expense of a extremely poor colour rendering (CRI of HPS25) [14]. Implementation of illuminance levels given by the R.D. 1890/2008 [16] and the luminous flux control type is Full Luminous Flux control (the most popular and inexpensive one). Scenario no. 2: Installation of different lamps and luminous flux control for each type of road and pedestrian area could be a faithful representation of a real city. Places with intensive pedestrian activity should be illuminated by white light sources characterized by excellent colour rendering. Scenario no. 3: Lighting in road and pedestrian areas with LED lamps with excellent colour rendering and a relatively high efficacy. Implementation of illuminance levels given by the R.D. 1890/2008 [16] and the luminous flux control type is Individual Fixture Luminous Flux control (the most expensive gear and control system).

0,0

0,2

0,4

0,6

0,8

1,0

0 1 2 3 4 5 6 7

PQ

sa -

EE

I p

.u.

[a.

u.]

Energy consumption Qsa [ kWh/m2 ]

Percentiles for Qsa (PQsa) EEI p.u.

Lamp type

Knl [lm/W]

fu LLD LSF LDF fm Road Pedestrian Road Pedestrian Road Pedestrian Road Pedestrian Road Pedestrian

HPS 86,69 0,38 0,28 0,94 0,94 0,94 0,94 0,89 0,86 0,79 0,76 MH 79,5 0,38 0,3 0,76 0,76 0,94 0,94 0,89 0,86 0,64 0,61 LED 80,95 0,55 0,65 -- -- -- -- -- -- 0,80 0,80 FL 72,73 0,22 0,22 0,93 0,93 0,99 0,99 0,89 0,86 0,82 0,79

Table 4 Description of different elements for the three scenarious studied of a urban lighting system.

Scenario No.1 Scenario No.2 Scenario No.3

Street Type Em (lux)

Street area p.u.

Lamp type

Flux control

Lamp type Flux control

Lamp type Flux control

ME1 30 0,05 HPS Full flux HPS Bi-level LED Individual fixture ME2 20 0,05 HPS Full flux MH Bi-level LED Individual fixture ME3 15 0,05 HPS Full flux MH Bi-level LED Individual fixture ME4 10 0,2 HPS Full flux LED Individual fixture LED Individual fixture

Hist. Centre 20 0,05 HPS Full flux MH Bi-level LED Individual fixture Res-Comer 15 0,3 HPS Full flux MH Bi-level LED Individual fixture Residential 10 0,2 HPS Full flux LED Individual fixture LED Individual fixture

Plazas/Low flux 7,5 0,1 HPS Full flux FL Full flux LED Individual fixture Note: Average illuminance level (Em) and road types are taken from [16].

6. RESULTS In scenario no. 1, where HPS lamps are used, a negative performance is obtained when evaluated in the mesopic region, as seen in Table 5 and Fig. 3. This is explained by an S/P ratio for HPS lamps lower than 1,8, making them unsuitable for energy savings using mesopic photometry.

Table 5 Scenario no. 1. Energy consumption results Qsa [kWh/m2] and its evaluation with EEI, including the analysis of

photometric performace in the mesopic zone.

Street Type Qsa (kWh/m2) EEI

Phot. Mes. Phot. Mes. ME1 5,072 5,176 8 7 ME2 3,381 3,522 28 24 ME3 2,536 2,642 45 40 ME4 1,691 1,799 70 67

Hist. Centre 4,749 4,947 10 9 Res-Comer 3,562 3,710 24 21 Residential 2,375 2,526 47 45

Squares/ Low flux 1,781 1,895 68 64

Weighted Ave.Values 2,847 2,982 38 35

The results of scenario 2 indicate that the diversity of luminous flux controls and lamps in an urban lighting system reduces the energy consumption (Table 6) and therefore the assessment using the EEI is higher than the scenario 1 (Fig. 3). However, for this study, the EEI considers only the technological part of the urban lighting system and does not consider other aspects that could be evaluated in an urban lighting system with diverse technology as the optimal.

Table 6 Scenario no. 2. Energy consumption results Qsa

[kWh/m2] and its evaluation with EEI, including the analysis of photometric performace in the mesopic zone.

Street Type Qsa (kWh/m2) EEI

Phot. Mes. Phot. Mes. ME1 4,464 4,555 14 12 ME2 4,013 3,682 17 22 ME3 3,010 2,761 33 38 ME4 0,708 0,595 96 98

Hist. Centre 5,261 4,826 6 10 Res-Comer 3,946 3,620 19 23 Residential 0,599 0,504 98 99

Squares /Low flux 2,593 2,125 43 54

Weighted Ave.Values 2,542 2,309 44 50

Table 7 Scenario no. 3. Energy consumption results Qsa

[kWh/m2] and its evaluation with EEI, including the analysis of photometric performace in the mesopic zone.

Street Type Qsa (kWh/m2) EEI

Photopic Mesopic Photopic Mesopic

ME1 2,125 1,986 55 61 ME2 1,417 1,265 80 83 ME3 1,062 0,949 89 93 ME4 0,708 0,595 96 98

Hist. Centre 1,199 1,070 85 88 Res-Comer 0,899 0,803 94 95 Residential 0,599 0,504 98 99

Squares/ Low flux 0,450 0,378 100 100

Weighted Av. Values 0,866 0,762 94 96

Although the luminous efficacy of LED lamps is lower than that for HPS lamps (80,95 lm/W vs. 86,69 lm/W, respectively) major savings are obtained with the LED lamps (Table 7), because the utilization factor (fu) on LEDs is higher compared to HPS lamps (0,55 vs. 0,38, respectively). Without considering the implementation of costs for different lamp technologies and luminous flux control systems, it is clear that LED technology with individual fixture luminous flux control provides maximum energy efficiency, being thus the scenario no. 3 the best rated, showing EEI= 96 for mesopic photometry, see Table 7 and Fig. 3.

Fig. 3 General EEIp.u for 3 scenarios.

7. CONCLUSIONS Through an application example, it was demonstrated that the Energy Efficiency Indicator (EEI) is a reliable and easy-to-use tool to assess urban lighting systems. Using the EEI, it is possible to know quickly, in a simple and intuitive way, the energy savings that can be obtained in different urban lighting systems depending on the type of road, light sources, luminous flux control and photometry system that is used. The application of this indicator comes in handy either for the lighting industry or decision makers, whenever the most efficient and sustainable lighting system has to be chosen for a city. Using different luminous flux controls and the correction for mesopic photometry for lamps with factor S/P >1,8 such as LED or MH lamps, was obtained an weighted average EEI = 50 (scenario 2), and up to EEI = 96 for that in scenario 3 with LED lamps and a fancy luminous flux control. Nevertheless, as a subsequent study, the EEI should be complemented taking into account the economic cost of acquisition, implementation and management of the different urban lighting systems analysed.

8. REFERENCES

[1] United Nations. Urban Population, Development and the Environment Department of Economic and Social Affairs, United Nations. (2007). Available in: http://www.un.org/esa/population/publications/ 2007 PopDevt/Urban 2007.pdf

[2] C. Ash, B.R. Jasny, L. Roberts, R. Stone, A. Sugden. Reimagining cities-introduction. Science. (2008) 319(5864), 739.

[3] S. Rueda; R. De Cceres; A. Cuch; L. Brau. El Urbanismo Ecolgico. Su aplicacin en el diseo de un ecobarrio en Figueres. Ed. Agencia de Ecologa Urbana de Barcelona. (2012), pp. 304.

[4] IDEA (Instituto para la Diversificacin y Ahorro de la Energa). 2a Plan de Accin Nacional de Eficiencia Energtica en Espaa 2011-2020. Madrid (2011). Available in:http://www.idae.es/index.php/mod.documentos/mem.descarga?file=/documentos_11905_PAEE_2011_2020._A2011_A_a1e6383b.pdf> Last consulted: April 2012.

[5] D. Radulovic; S. Skok; V. Kirincic. Energy efficiency public lighting management in the cities. Energy, (2011), 36(4) 1908-1915.

[6] Commission International de LEclairage (CIE). Recommended System for Visual Performance Based Mesopic Photometry. CIE 191:2010, Vienna (2010).

[7] S. Fotios; T. Goodman. Proposed UK guidance for lighting in residential roads. Lighting Research and Technology, (2012), 44(1), 69-83.

[8] P. Raynham; T. Saksvikrnning. White light and facial recognition. The Lighting Journal, (2003); 68: 2933.

[9] British Standards Institution (BSI). Code of Practice for the Design of Road Lighting Part 1: Lighting of Roads and Public Amenity Areas. BS5489-1:2003, London: BSI, 2003.

[10] P.R. Boyce; S. Fotios; M. Richards. Road lighting and energy saving. Lighting Research and Technology, (2009); 41: 245260.

[11] S Fotios; C. Cheal. Obstacle detection: A pilot study investigating the effects of lamp type, illuminance and age. Lighting Research and Technology, (2009), 41(4), 321-342.

[12] M Kostic; L. Djokic. Recommendations for energy efficient and visually acceptable street lighting. Energy, (2009), 34(10), 1565-1572.

[13] S. Fotios; C. Cheal. Lighting for subsidiary streets: investigation of lamps of different SPD. Part 2 Brightness. Lighting Research and Technology, (2007), 39(3), 233-249.

[14] C. Knight. Field surveys of the effect of lamp spectrum on the perception of safety and comfort at night. Lighting Research and Technology, (2010), 42(3), 313-329.

[15] OTPC (Oficina Tcnica para la Proteccin de la Calidad del cielo). Resumen de recomendaciones para la iluminacin de instalaciones de exteriores o en recintos abiertos, (2010). Available in http://www.iac.es/adjuntos/otpc/recom2010.pdf Last consulted Abril, 2012.

[16] Spain. REAL DECRETO 1890/2008, de 14 de noviembre, por el que se aprueba el Reglamento de eficiencia energtica en instalaciones de alumbrado exterior y sus Instrucciones tcnicas complementarias EA-01 a EA-07. Boletn Oficial del Estado, 19 de noviembre de 2008, nm. 279, p. 45988.

9. ACKNOWLEDGMENTS This research at IREC was partially supported by the European Regional Development Funds (ERDF, FEDER Programa Competitivitat de Catalunya 2007-2013). Lizeth Snchez would like to acknowledge to the Mexican National Council for Science and Technology (CONACYT; grant 211124) for the funding.

0 20 40 60 80

100

Scen.1 Scen.2 Scen.3

EEI

Photopic Mesopic

General EEI for 5 Scenarios

10. BIOGRAPHY Lizeth Artemisa Snchez Balvs was born in Mexico

City in 1985. She received her Environmental Engineering degree at the Instituto Politcnico Nacional (National Polytechnic Institute, IPN) in 2007. She studied for a Masters' degree in Sustainable Development from 2008 to 2010 at the Universitat

Politcnica de Catalunya (Technical University of Catalonia, UPC). She is currently a PhD student in Sustainability at the UPC. Her research interests include urban sustainability, urban metabolism and its application in urban lighting. Jess M. Quintero received the degree of Specialist in

Industrial Automation and Control from the National University of Colombia in 2007, a B.S.E.E. degree from the National University of Colombia in 1992 and a Specialist degree in Informatics and Communications Technology from

Los Andes University, Colombia in 2002. Since 2004, he has been at the National University of Colombia in Bogot, where he is a Senior Lecturer on Electrical and Electronics Engineering, with appointments in the Light and Lighting program. He is in his fourth year of a Ph.D. Program in Electrical Engineering studies at the Universitat Politecnica de Catalunya (UPC) in Barcelona, Spain and is doing a Ph.D. Fellowship at the Institute for Energy Research of Catalonia (IREC). His research centers on high-power light-emitting diodes, luminescent materials and color quality of light sources. Antoni Sudri-Andreu received the M.Sc.E.E and the

Ph.D. degrees from Universitat Politcnica de Catalunya (UPC), Barcelona, Spain, in 1979 and 2005, respectively. In 1979, he joined Electronics Engineering Department, UPC, as a part-time Assistant Professor. He joined the Research and Development Department of a private railway industry in 1980, where he developed static converters

for traction and auxiliary services in trains. In 1985, he joined the Electrical Engineering Department, Universitat Politcnica de Catalunya in Barcelona, Spain as a Full-Time Associate Professor. He has managed numerous industry research projects and as a consequence, in 2001, he founded the Centre of Technological Innovation in Static Converters and Drives (CITCEA), Universitat Politcnica de Catalunya, with the support of the Catalan Government. Since 2001 he is the Director of CITCEA. Also from January 2009 to December 2011 he was the head of the power electronics and power electric systems

research lines of recently created Catalonia Institute for Energy Research (IREC). Jos Juan de Felipe Blanch is currently full-time

professor of the Technical University of Catalonia. He received his Naval Machines Engineer degree (1991), Master of Educational Formation (1995) and PhD (2004) at the Technical University of Catalonia. His principal scientific

and professional activities are centred in dynamic systems analyses applied in territorial problems with an integrated vision of the different visions of the sustainability. He also is an expert reviewer to the FP6 INSURE (Contract no. 505358). He has published several articles in journals and participated in several projects. Josep Carreras received his B.S., M.S. and PhD. (Cum

Laude, with Honours) in Physics from the University of Barcelona. He has published more than 30 articles in several SCI journals, has filed two patents, participated in more than 15 different projects at a national and international level. Since June 2009, he is working for IREC, where currently he is the Head

of the Lighting Group, leading research in novel concepts for Energy Efficient Lighting, Colour Science and Technology, Simulations, Photometry, and Intelligent Lighting with advanced communication and computation functionalities. He also helped in the definition of the research strategies and infrastructures from the early stages of the Institute and is currently managing the group and supervising several projects in close collaboration with industrial partners.