2014 Power and Energy Systems: Towards Sustainable Energy (PESTSE 2014)

Analysis on System Sizing and Secondary Benefits of Centralized PV Street Lighting System

Rakesh Babu Panguloori 1, PriyaRanjan Mishra2 Philips Research India, Bangalore, India

lrakeshbabu.panguloori@philips.com, 2mishra.priyaranjan@philips.com

Abstract - The combination of solar and LED lighting has

enabled interest in the municipalities and governing authorities

to lighten streets/remote areas without setting up electrical

infrastructure in a mere traditional way. For which, stand-alone

solar street lighting solutions are very popular and often built

with customized PV panels and overdesigned. Recently, AC­

centralized street lighting system is adopted by many of the street

lighting installers as such system is easy for installation,

maintenance and future grid interconnectivity. Generally, solar

off-grid solutions are designed for autonomy of 3-5 days to meet

lighting requirements under worst environmental conditions.

Hence, in situations like continuous sunny days (especially in

countries like India), the surplus solar energy gets unutilized,

which can be avoided in case of centralized system. This paper

presents analytical work on system sizing for two geographical

locations in India based on monthly averaged solar irradiance

and dusk-dawn length data. Comparison among three solutions

(decentralized, AC-centralized, DC-centralized) in terms of

system size, amount of surplus energy etc. is presented in this

paper. The effect of dust on PV performance is also considered

during analysis. An approach to use judiciously available surplus

energy in centralized system for other local energy needs is

discussed.

Keywords- distributed generation, solar street lighting system, renewable energy, centralized solar power system, power autonomy and distribution efficiency

I. INTRODUCTION

Solar energy has particular relevance in remote and rural areas, where around 290 million people live without access to electricity [1]. Solar energy is the cost-effective option for India to reduce energy scarcity without having to extend national grid services to provide a reliable and secure energy supply to remote areas [2]. India's national solar mission has targeted to deploy 20 million solar lighting systems for rural areas by 2022 [3]. Most of these solutions are well popular as decentralized systems. Providing street lighting is one of the most important and expensive responsibilities of a municipality/city administration to improve safety and comfort for both vehicular traffic and pedestrians. It also provides enhanced sense of security for motorists giving maximum road visibility.

Energy efficient technologies and design can reduce street lighting costs substantially, which will help municipalities to expand their services by providing lighting in low-income and other underserved areas. TERI has

978-l-4799-342l-8/14/$3l.00 ©20 14 IEEE

reported that by the introduction of LEDs, cost reduction of 25-30% is possible because of reduced panel size, freight and storage cost [4].

Various municipality/local governing bodies are thinking to do business around street light pole by providing other services apart from lighting. In the pursuit of making our highways and streets safer, "Adopt a Light" [5] developed the revolutionary concept of lighting up highways through advertising on street lighting infrastructure. Over the years, many leading organizations have joined the effort and are adopting highway lights for advertising and brand building. Thus in turn enhancing security and adding value to the city's landscape. Several services are possible by making street light poles intelligent and as energy control points. Intelligent street lighting system comprises of a wireless digital infrastructure that allows street lights to be controlled remotely and a computational device inside each street light with primary functionalities such as "security, energy management, data harvesting, advertising, video surveillance". Solar street lighting infrastructure can act as emergency charging stations to fuel electric cars or electric scooters and also as energy kiosks. This approach with multiple services will help to accelerate the sales and adaptation of electrical vehicles.

Fig. 1 shows the power architecture of a decentralized solar LED street lighting system. It functions independent of the utility grid. The solar energy is used to charge a self-contained battery during day time and the charged battery powers the LED light loads during night time. Battery capacity is usually designed for power autonomy of 3-5 days to meet lighting loads under varying environmental conditions, and often overdesigned [6]. Furthermore as the solar panel efficiency and LED lumen efficacy are improving day-by-day, optimal system sizing for different geographies (primarily solar panel capacity and battery capacity) becomes challenging. Many times such system needs customized solar panels resulting in further increase in cost of solar system.

PV Module

MPPT Charge

Controller

DC bus

12V r LED

Driver

Fig.l. Power architecture of decentralized PV street lighting system.

Though, the decentralized system meets the lighting loads even under worst cases but in most part of the year, the system remains underutilized. Since, the initial investment for an off­grid solar LED Street lighting system is higher compared to conventional grid powered street lights, it is more important to utilize the solar energy much more effectively. In any typical year, the surplus energy varies from 5% to 30% of total watt hour load per day. The small amount of surplus energy from a single street lighting system is not sufficient to meet local energy needs.

However in a centralized street lighting system, cumulative surplus energy will be high enough to meet some of the local energy needs. The surplus energy can be used for charging electric vehicle battery or for providing charging outlets for mobile lighting units / mobile-phones etc. The centralized station can also work as micro power distribution center. This leads to lower pay-back period for the entire system, light weight and low cost pole structures along with several other benefits. There is also possibility for grid interconnectivity in future, which will further lead to reduction in battery capacity and hence further lower payback period. There is secondary benefit also; as the centralized system can be guarded within the fenced boundary to minimize the risks of theft and sabotage [7, 8, and 9]. It is also easy to operate and maintain centralized system. Dust deposition on PV panels significantly impact PV output performance [10]. This can be avoided in centralized system by cleaning panels at regular intervals which is nearly impossible to do in decentralized system. Finally, there is no need of design change in pole's mechanical structure.

The paper is organized as follows. Description of centralized power distribution architecture is presented in Section II. System design for three solutions (12V DC decentralized system, 230V AC-centralized system and 380V DC-Centralized system) for 20 pole system is presented in Section III. Calculation on surplus energy in three solutions along with an approach to use judiciously available surplus energy is given in Section IV. Finally, conclusions are given in Section V.

II. CENTRALIZED PV DISTRIBUTION ARCHITECTURE

Realizing the benefits of centralized system, many of the street lighting installers are executing centralized PV street lighting system [11, 12] as shown in Fig. 2. The solar energy is stored in batteries using MPPT charge controller. The power module called bus converter is used to step-up 48V battery voltage to higher voltage typically 230V AC or 380V DC for power distribution. It is typically designed on a 48V battery bank for a group of 20 street poles spread across 1-2 kilometers. The bus converter will be an inverter in case of AC centralized system and a simple DC-DC converter (single switch boost or LLC resonant converter) in case of DC centralized system. Various papers [13, 14, and 15] in literature clearly demonstrated benefits of solar integrated DC distribution for various applications. In Fig. 2, the power efficiency of bus converter plays major role in determining the overall system efficiency.

MPPT PV Charge

Array Controller

Distribution bus 230V AC I 380V DC

Fig.2. Power architecture of N-pole centralized PV street lighting system.

In [16], it is shown that DC centralized PV street lighting system is 15-20% more energy efficient than inverter based AC centralized solution. Higher energy efficiency of DC centralized system over conventional 230V AC system will meet the same watt hour load per day with reduced solar and battery component sizes. This will greatly reduce system capital cost. The next section deals with the analysis to calculate system sizes for 12V DC decentralized system, 230V AC-centralized system and 380V DC-Centralized system.

III. SYSTEM DESIGN AND COMPARISON

A. Load estimation

In off-grid applications, the only source of power for street lighting is battery. The load on battery needs to be estimated in the system to adequately size the battery and then the solar capacity. The daily consumption depends on No. of street poles (N), power output of each LED lamp (PLED)' efficiency of the LED driver (lldriver), power loss in the distribution system (P dloss), efficiency of the bus converter (llbusc) and the dusk to dawn length (Tdd). In this paper, monthly average dusk to dawn length data (Table-A in Appendix) is used for analysis. The daily load can be given as

Ld = X Tdd (1)

[NX PLED ) + Pdloss

lldriver llbusc

B. Distribution power loss

Street lighting is a serially distributed load with equal distance between consecutive poles. Referring to Fig. 2 the input current of the LED driver at any street pole is given as:

PLED IN= ----

lldnver XVN (2)

where IN, VN are the input voltage and current of LED driver of the Nth street pole. Assuming each LED driver or dwelling draws equal amount of current at its input. Using Kirchhoff current law, the branch currents can be written as:

tN-1 = IN (3)

I'N-2= IN-I+I'N-I=2.IN (4)

The distribution power losses can be calculated using (5) N , 2

Pdloss = 2xRL xLx I(I N-t ) (5) i=1

where RL is the cable resistance per km and L is the distance between two street light poles, Solving (5) gives

P -R L ( .PLED

J

2 [NX(N+l)X(2N+1) ] dloss - L X X X

11dnver X V N 6 (6)

From the above equation, it is observed that the power losses are directly proportional to square of the load power, inversely proportional to distribution voltage and has exponential dependence on the No, of street poles 'N'. Hence, higher voltage allows wide distribution network for street lighting.

C. Solar irradiation data

Solar insolation has great effect on performance of the PV system. Monthly average solar insolation data (measured in kWh/ml/day) is considered for system design and analysis in this paper. From Table-B in Appendix, it is clear that the worst radiation month is August for both Bangalore and New Delhi.

D. Battery capacity

The battery bank can be characterized by its nominal capacity. The calculation for an optimum number of batteries is based upon the number of autonomous days. To have long battery life, the maximum depth of discharge (MooD) of the battery is usually limited to 70%. In our analysis, we have also taken losses in wiring i.e. distribution loss and the efficiency of end load i.e. LED driver into account. These losses are considered while estimating the total load on the battery in (1). The storage capacity can be determined as

Batt( AH) = x D [ Ld )

11 batt X MOoD X V batt (7)

where llbatt represents charging/discharging efficiency of the battery, Vbatt the operating voltage of the battery and D the days of autonomy.

E. P V module capacity

The daily energy requirement, the battery efficiency, and equivalent hours of full sunshine (EHFS) determine the required PV module capacity. The PV capacity can be given as [9]

PV(Wp) j Lt

J

(8) l 11 ball x 11" x (l-ftemp)x(1-fduSI)X(l-ftnismalCh) x EHFS

Where llcc is charge controller efficiency, ftemp, fdust and t;nismatch the losses in PV array respectively due to cell temperature, dust and mismatch among several modules due to shadow and other factors.

In a typical off-grid street lighting application, solar and battery components are selected based on worst solar irradiation data with preferred three days of autonomy. A sample system design using above defmed equations is illustrated in Table-2 for worst radiation month and for the parameters considered in Table-I. Loss of PV energy due to dust is taken as 10% in decentralized system and in centralized

system it is taken as 0% and 5%. First the distribution power losses are calculated using (6) and substituted in (1) to obtain net load on battery. An average hour of operation per day for Bangalore in the month of August is II hrs (see Table-A in Appendix).

From Table-2, normalized 380V DC solution shows that each light pole requires 10% less solar capacity than 12V DC decentralized solution. However, the complete 20 pole 380V DC centralized solution requires 1750Wp capacity against 2200Wp capacity needed for 20 no's of 12V decentralized solutions. This is around 20% reduction in required solar capacity. As the environmental factors like solar insolation and the dusk to dawn length varies every day, in this study, system design is done for monthly averaged solar insolation and monthly averaged dusk to dawn length. Fig. 3 shows required solar capacities on monthly basis for three solutions for Bangalore location with solar system positioned for optimal year yield setting. Similarly, figures 4 and 5 shows solar capacities for New Delhi location for solar system positions, optimal year yield setting and best winter yield setting respectively. As seen in figures 3, 4, and 5 the 12V decentralized solution requires 2200Wp solar capacity (i.e. llOWp per pole) irrespective of location. Whereas for centralized solutions the solar capacities varies slightly based on location. The figures also show that the required solar capacities vary significantly over the year and illustrate the system needs only 70% of the maximum solar capacity in high insolation months March, April etc. If the PV system is placed for worst case, the excess solar capacity in high insolation months generates energy, which is surplus energy than the per-day lighting energy need. The next section deals with surplus energy calculation and means of using it.

TABLE T. EFFICIENCY AND PERFORMANCE INDICES

12VDC 230V AC 380V DC Parameters decentralized centralized centralized

No. of poles (N) I 20 20

Load on each pole (W), PLED 21 21 21

LED driver efficiency (%), lldriver 94 92 97

Battery voltage (V ban) 12 48 48 Efficiency of converter from battery to distribution bus (%), llbusc N.A. 95 95

Battery efficiency (%), llbal1 85 90 90 Maximum depth of discharge (%), MOoD 70 70 70

Charge controller eff (%), llee 90 94 94

Cable resistance (n! km), RL 7 7 7

Distance between poles (m), L 30 30 30 Environmental factors Loss of solar energy due to ambient temperature, t;em 0.1 0.1 0.1 Loss of solar energy due to dust, fdust 0.1 0 0 Loss of solar energy due to mismatch among solar cells, fmismatch 0.15 0.1 0.1

TABLE IT. SAMPLE CALCULATION OF SYSTEM CAPACITY IN VARIOUS CASES FOR WORST RADIATION MONTH AUGUST FOR BANGALORE

Parameters 12VDC

decentralized

Distribution power loss (W), P dloss 0

Avg. hours of operation per day, Tdd 11 Net load on battery (WH), Ld 245.74 Eq. hours of full sunshine (EHFS) 4.27

PV module capacity, PV(Wp) 109.27 Nearest available solar size (Wp)

110.00

Battery capacity, Batt(AH) 103.25 Nearest available battery size

12V,100AH

• Decentralized Sys • AC Centrali zed Sys . • DC Centrali zed Sys . 2400 ,-----------:-:-:-:-:-:---------

2200 +------------..-:......r+�:....-..._----2000 +---------___ �..___IIf-h�--=-.__...__.r_

� 1800+---------��ar__ll��-��.___II�

f' 1600 t.--_._--..------..-----__._­g J 1400 ta._ ___ ---1I----1I:::---1:::__ " a 1200

1000

800

600 Jan Feb Mar Api May Jun Jul Aug Sept Oct Nov Dec

Month

Fig. 3. Required solar capacities on monthly basis for various systems for Bangalore with optimal year yield setting

• Decentralized Sys. _AC Centralized Sys . • DC Centralized Sys

2400 ,---------------------

2200 t.----------------------',...= 2000 �-___ -------__..__ ___ -...___...__.-... �

� 1800 +a.._�-------�� __ -.�.___II�

� 1600 ,0' 'u g. 1400 u 8 1200 a

1000

800

600 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec

Month

Fig. 4. Required solar capacities on monthly basis for various systems for New Delhi with optimal year yield setting

• Decentralized Sys. .AC Centralized Sys. • DC Centralized Sys. 2400 ,---------------------2200 +-----------=�����---____ -

2000 t.--_._------..---..._ __ +-1 ...... --..---.r-__.-� 1800 te-___ ------tr-it--� 1600 +II.._ .... --..-_.r-_._-___ -·u g. 1400 u " 1200 a 1000

800 600

Jan Feb Mar Apr May JUII Jul Aug Sept Oct Nov Dec Month

Fig. 5. Required solar capacities on monthly basis for various systems for New Delhi with best winter yield setting

230V AC 380VDC 380V DC centralized centralized centralized (Normalized)

5 .93 1.95 0

11 11 I I

5354.7 5036 250.68 4.27 4.27 4.27

1830 1721 86.3

170x11=1870 250x7=1750 100.00

531.2 499.6 24.87

48V, 270AHx2 48V, 250AHx2 48V, 26AH

IV. CALCULATION OF SURPLUS ENERGY

As 12V decentralized system requires total solar capacity of 2200Wp for 20 poles, same PV capacity is considered in centralized system. Fig. 6 shows the surplus energy in each month for Bangalore location with 2200Wp PV capacity. It is seen that the surplus energy in a decentralized system is very small which is practically impossible to tap and utilize. But the cumulative energy over 20 poles is significant as illustrated in Fig. 6. The surplus energy is found to be around 25% of the total watt hour annual load. From Fig. 6, it is clear that the surplus energy is more in sunny months whereas in low insolation months the generated solar energy closely matches with the load demand. Table-3 shows cumulative surplus energy over a year for three solutions. In case of decentralized system, though the cumulative surplus energy is significant, it has no relevance in terms of utilization. The cumulative surplus energy in DC centralized system is 12-15% higher than in AC centralized system based on geographical location. This is mainly because of higher energy efficiency of DC centralized solar street lighting system over 230V AC system. The excess energy gains special importance especially in off­grid rural areas, where this energy can be utilized for their local energy needs. Fig. 7 shows an illustration of solar energy kiosk providing central charging outlets from DC centralized solar street lighting system. Energy services such as rechargeable LED lamps, radios or charged storage pack on rental basis can be executed. Though the present concept considers outdoor street lighting application, the concept can be applied for commodity lighting, public buildings or micro grids where each home acts as dwelling.

In rural areas, the households are scattered and spread across a few kilometers. Considering lack of safety awareness and lower power requirements, several small solar power distribution clusters with bus voltage 48 V (less than ESL V limit) could be sufficient to feed end consumers. In home energy usage scenario, there will be load diversity factor which further increases the surplus energy at each power distribution cluster. These small power distribution clusters can be interlinked at 380V DC to leverage surplus energy and create reliable energy network having single large energy kiosk. The illustration of such distribution system is shown in Fig. 8.

180.00 160.00

� 140.00 »

120.00 � 100.00 '" 80 00 "

� 60 00 Vl 40.00

20 00 0.00

--- Decen_single •••••• Decen_20pole - - AC-Centr --DC-Centr

./.� /,,' ' � , " ""

'X " . . ...

.. . .........

'.

---------------

Jan Feb Mar Apr May

� Z , ,,� ,

, � .. ,.--...

...•

.. ...

Jun Jui

Month

.... . ..... . ....

Aug Sept Oct Nov Dec

Fig. 6. Surplus energy in each month for Bangalore with 2200Wp installed solar capacity

PV Array

MPPT Charge

Controller

Charge outlets for lighting

services I

48 V

DC bus

L:C,-,-,-,,,--,-�

i p 1 �ED

��

Fig. 7. An illustration of solar energy kiosk providing central charging outlets from DC centralized solar street lighting system

TABLE III. CUMULATIVE ANNUAL SURPLUS ENERGY OVER A YEAR WITH 2200Wp INSTALLED SOLAR CAPACITY

Dust factor Banl!:3lore New Delhi

(%) EHFS (13') EHFS (29') EHFS (44') Type of solution Optimal year yield setting Optimal year yield setting Best winter yield setting

Decentralized system

AC Centralized system

DC Centralized system

AC Centralized system

DC Centralized system

10

0

0

5

5

48V-380V rn Bidirectional converter

230V l<iJ

475

1107

1278 927

1060

Fig. 8. View of distribution system with 48V DC clusters interlinked with 380V DC to leverage surplus energy

The street poles can be fed on 380V distribution link. If utility grid is available in the vicinity of the village, a hybrid solar system could be an option to consider where PV capacity can be chosen for high insolation month i.e. minimum capacity required in figures 3, 4, and 5. The deficit energy in other months can be complimented from the utility grid. The required energy from utility grid in AC and DC centralized systems is tabulated in Table-4. As seen in Table-4, DC solution consumes around 25% less energy from utility grid resulting in lower running cost.

429 370

1175 1069

1322 1218

983 894

1106 1019

TABLE IV. DEFICIT ENERGY OR ENERGY NEEDED FROM UTILITY GRID

Dust Bane:alore New Delhi

Type of factor EHFS (13') EHFS (29') EHFS (44') solution (%) 1125Wp 1125Wp 1170Wp AC Centralized system 0 600 550 544 DC Centralized system 0 429 404 395 AC Centralized system 5 461 423 418 DC Centralized system 5 330 311 304

V. CONCLUSIONS

In this paper, detailed system sizing for 12V DC decentralized system, 230V AC-centralized system and 380V DC-centralized systems is presented based on monthly averaged solar irradiance and dusk-dawn length data. The study shown that 380V DC centralized solution requires 20% less solar capacity than 12V DC decentralized solution. In 12V DC decentralized system, the annual surplus energy as high as 25% of the total watt hour annual load remains unutilized which can be avoided in centralized systems. The cumulative surplus energy in DC centralized system is 12-15% higher than in AC centralized system based on geographical location. This is mainly because of higher energy efficiency of DC centralized solar street lighting system over 230V AC centralized system. A means of utilizing that excess energy by establishing energy kiosks is discussed. The study also shown that, in hybrid power system, DC centralized

solution consume around 25% less energy from utility grid than AC centralized solution.

ApPENDIX

TABLE A Monthly average dusk to dawn length data for Bangalore and New Delhi

Month Bangalore (Hr:Min) New Delhi (Hr:Min)

Jan 12:10 12:45

Feb 11:25 12:00 Mar 11:05 11:10

Apr 10:55 10:30 May 10:45 09:50 Jun 10:40 09:35

Jul 10:45 10:00 Aug 11:00 10:25 Sept 11:10 11:05

Oct 11:35 12:00 Nov 12:00 12:30 Dec 12:05 13:05

Year (Avg.) 11:17 11:14

TABLE B Monthly average solar insolation data (measured in kWh/m2/day) for

Bangalore and New Delhi

Bangalore New Delhi

EHFS (\3") EHFS (29°) EHFS (44°) Optimal year Optimal year Best winter

Month yield setting yield setting yield setting

Jan 6.41 5 .17 5.54

Feb 6.79 5.91 6.13

Mar 6.61 6.48 6.38

Apr 5 .87 6.20 5 .76

May 5 .82 5 .89 5 .20

Jun 4.85 5.42 4.72

Jul 4.34 4.76 4.23

Aug 4.27 4.61 4.21

Sept 4.73 5 .28 5 .06

Oct 4.79 5 .81 5.91

Nov 5 .13 5 .56 5.93

Dec 5.74 4.96 5 .37

Year (Avg.) 5.45 5.50 5.37

ACKNOWLEDGEMENT

The authors would like to acknowledge and thank Sudheer Kumar for his valuable input on technical specifications of present decentralized solar street lighting system. We also acknowledge Philips Innovation Campus for providing valuable support and Dr. Narendranath Udupa & Geetha Mahadevaiah for their encouragement.

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