South Africa's private sector - under signi cant pressure to become energy ecient and employ sustainability principles - has long been implementing energy saving mechanisms. Unfortunately, there seems to exist many misplaced incentives in South Africa's public sector that prevent it from embracing energy-ecient technology. With the falling cost of LED lighting and the rising cost of electricity, however, conversions are increasingly cost ecient. E ecting these changes are increasingly urgent given the national utility-imposed rolling blackouts and climate change concerns. The primary education sector is a particularly attractive test case, since money saved on utilities can be allocated to desperately needed value-adding services in schools. From a technical perspective, however, the cost-bene t of replacements and the range of options facing decision makers could be overwhelming. To assess the impact of replacing uorescent lights with LED lights at schools in South Africa, we propose a model that draws on smart metering data, a bench-test assessment of available LED lights and tari rates. The model was validated with eld tests at three schools and used to assess the impact at seven local schools. The results show that the setup cost di ers substantially from the life-cycle cost, and that buying the cheapest lights could prove to be the costliest decision over the light's life cycle. The results also show that lights contribute from 42% to 57% of electricity expenditure, and that monetary savings of 21% to 39% are achievable by replacing uorescent tubes with the most ecient LED lighting option available. Keywords: School electricity; School lights; Energy usage; Smart meter; School energy pro les; LED lights; Eciency improvement; Energy saving 1. Introduction South Africa's 23,471 public schools use an estimated 2.2 GWh energy per year: this results in an annual electricity expense of about ZAR 2.9 billion (ca. US$ 179 million). With the country's electricity utility in dire straits, tari hikes are inevitable and in ation-beating. From 2008 to 2018 the increase in cost was 446% [1]. Moreover, every cent spent on the inecient use of energy potentially diverts funds away from desperately 5 needed educational resources (its primary purpose), infrastructure investment, and much needed maintenance [2{ 5]. Given the mammoth challenges faced in basic education itself, however, insucient attention is given to these Corresponding author Email address: mjbooysen@sun.ac.za (M.J. Booysen) Preprint submitted to Energy and Buildings July 23, 2020 energy ineciencies. 1.1. Electricity usage at schools The South African government's Regulations Relating to Minimum Uniform Norms and Standards for Public School Infrastructure require that all schools must have access to electricity, water, sanitation, electronic connec- tivity and perimeter security by November 2020 [6]. Between 1994 and 2010 substantial progress in the area of 5 electri cation has been made through the Integrated National Electri cation Plan (INEP) in terms of universal ac- cess to electricity [7]. More than 12,000 schools were grid connected and 3,000 schools were electri ed with non-grid technology: only 239 remain without electricity. Theoretically this should make a range of bene ts available to learners, such as: (1) lighting and extended study hours, (2) use of the internet, computers and televisions in classrooms, (3) enhanced sta retention, (4) better 10 school performance and (5) co-bene ts to sanitation, health and communities [4]. Despite this high electri cation rate, schools' access to the potential bene ts of the services is distributed unequally [4, 8]. There remains a daunting backlog in terms of basic infrastructure in schools. In 2018, around 1,000 schools still had no sports facilities; 4,358 still only had illegal plain pit latrines; and 1,027 remained without perimeter fencing. Even more concerning is the manifestation of an apparent digital divide: nearly 17,000 schools 15 do not have access to the internet, and 20,070 schools do not have laboratories and computer laboratories. Rather than spending their way out of this desperate situation, educational investment per pupil actually decreased by 8% over the 2010 to 2017 period [9]. Security of electricity supply has also been negatively a ected by the struggling state utility, Eskom { where rolling blackouts are often applied to prevent a national shutdown [10]. Internationally, a large contributor to energy usage at schools is lightning [11]. Fortunately, recent advances in 20 lighting technology has increased the eciency of lights - from a typical 90 lm/W for the ubiquitous uorescent lights to a typical 100 lm/W for LED lights { an 11% improvement. It is imperative to explore the lighting landscape at schools especially since South African schools almost exclusively still use uorescent lights and could thus bene t from such savings. 1.2. Lighting in schools 25 Studies on lighting at schools span various areas including energy savings, indoor environmental quality and student productivity. In this section we present some of these studies on the use, impact and bene ts of lighting in schools. Salvia et al. [12] explored the importance and function of public lighting on the municipal level which we have extended to schools. Many accounts exist of older, inecient lighting technology used in schools, which contributes 30 to a large portion of electricity bills. Examples of this can be seen in Spain, by Gamarra et al. [13] and Lizana et al. [14], where schools lighting usage is estimated 21 - 25%, and in South Africa [15] where a study of a single school found that lighting accounted for 46% of energy usage. To date, most studies have emphasised technical questions rather than sustainable management. Sustainability in public lighting includes optimal lighting solutions considering functions of the system, reducing operation expenses 35 and minimising electricity usage [12]. They further state that monetary savings through energy reductions could be up to 50%, however this includes all municipal lighting. 2 Indoor environmental quality a ects the health and comfort of occupants [16]. Bluyssen [17] explored light quality as one of four indoor environmental factors with parameters and controls for each factor. Light quality parameters include luminance and illuminance, re ectance, colour temperature and colour index, view and daylight, and frequencies. The controls for lighting quality include luminance distribution, integration of arti cial and natural lighting, and daylighting entrance. The indoor environmental lighting quality parameters of importance to this 5 article are luminance and illuminance. The role of lighting, as a part of indoor climate parameters, extends to productivity. Hviid et al. [18] monitored 92 children over four weeks through questionnaires and three performance tests that focused on lighting conditions and ventilation rates. Their experiment included a warm colour temperature light with a lower light level (2900K at 450 lux) and dynamic cool colour temperature light with a higher light level (4900K at 750 lux), where the 10 dynamic light mimics outdoor lighting conditions. Both of these lighting conditions were combined with tests at a low and high ventilation rate. They found most improvement in performance under the combined scenario with the dynamic cool colour temperature light with high ventilation. These improvements were in student processing speed (6.6%), concentration (8.3%) and maths skills (11.8%). The e ect of lighting alone had a smaller improvement in the performance tests. Alazraki and Haselip [19] found that un-electri ed Argentinian schools could not start 15 early in the morning due to low light levels. A similar study in Kenya showed that a solar-powered electri cation project enabled after hours teaching [4, 20]. This bene t also extended to improved security and protection of school property. 1.3. Lighting interventions in schools In this section we aim to systematically map and explore the state of the literature on lighting and energy savings 20 in the education sector. Although our review is speci c to schools and the studies that discuss light interventions in schools, a recent review of general buildings can be found in [44]. We have explored 27 studies on various levels of the education system: namely, elementary, primary, middle, secondary and tertiary educational buildings (i.e. universities). However, most of them were secondary schools. In our sample we have also included a general building review for lighting interventions as this discusses the lighting 25 of a school. Table 1 contains a summary of lighting studies and shows a literature review map of lighting in educational buildings. In those cases where information was omitted in the articles it is indicated in our table as N/A and, where not mentioned, it is indicated as N/M. These articles were gathered from searches in journals using keywords (and combinations) such as "Energy consumption", "School building", "Lighting retro t" and "Energy eciency". 30 The studies were analysed against three categories of interventions used by the schools: 1) day-lighting (\Day." column); 2) lighting replacement (\Retro." column); and 3) light controls and automation (\Auto." column). The light interventions listed in the table have the following de nitions. Day-lighting is the utilisation of natural light in classrooms. Light replacements are the substitution of current lighting types with better technology. Light control and automation use electronics to control the amount of arti cial light in classroom. For the majority of studies 35 (17 out of 28), the lighting intervention referred to a light retro t or replacement intervention. A few studies also combined interventions, making combinations with day-lighting and automation, or combinations that included all 3 Table 1: Literature review map of lighting in educational buildings Lighting interventions Geography Schls Core focus Scholar level Initial Day. Retro. Auto. E(%) Ref. EU 4 EE interventions in schools Secondary FL No Yes No 0.5-7 [21] Belgium 1 Daylighting in classrooms Secondary FL Yes No Yes 18-46 [22] Canada 3 Real-time electricity analysis N/M N/A N/A N/A N/A N/A [23] Greece 10 Simulation of EEMs Secondary FL, IN No Yes No 8-40 [24] Greece 24 Building interventions Elementary N/M Yes No No 1.5-2.7 [25] Switzerland 1 Building automation analysis N/M N/M No No Yes N/A [26] USA 289 EEM and student learning Elementary,Middle N/M Yes Yes Yes N/M [27] USA 1 School evaluation Elementary FL No No No N/A [28] Serbia 9 Savings with LEDs Secondary FL No Yes No 53-60 [29] Italy 1 School retro t with lighting Primary FL No Yes No 35 [30] Canada 1 School model and energy audit Secondary FL No Yes No N/M [31] Spain 1 Retro t project N/M FL No Yes No 11 [32] Italy 2 Procurement and school eciency Primary,Middle FL No Yes No N/M [33] Italy 2 Cost-optimal analysis of retro ts N/M FL No Yes Yes N/M [34] Italy 1 Methods approach for EEMs Tertiary FL No Yes Yes 10-13 [35] Vienna 1 School retro t method N/M N/M Yes No No N/M [36] South Africa 1 Modelling of school lighting Primary FL No Yes No 46 [15] Spain 2 Light improvement in schools Secondary FL No Yes No 10-12 [13] Portugal 4 Lighting use in schools Secondary N/M No Yes Yes 28-40 [37] Portugal 1 IoT and EEM kindergarten Kindergarten N/M No No Yes N/M [38] Jordan 1 Illuminance in school buildings Tertiary N/M Yes No Yes N/M [39] EU 11 EEM in tertiary buildings Tertiary FL Yes Yes Yes 4-16 [40] Taiwan 231 Review on school electricity Elementary,Secondary CFL No Yes No 40 [41] Greece 1 Retro t lighting with control General FL Yes Yes Yes 18-22 [11] UK 1 Assess building performance Secondary FL Yes No Yes N/M [42] Turkey 1 Lighting system on campus Tertiary Fl,CFL,LED,MH No Yes Yes 31-60 [43] Turkey 3 School retro ts Primary IN Yes Yes Yes 60 [44] General 1 Building lighting review General N/M Yes No No 24 [45] Day.: Daylighting, Retro.: Retro tting, Auto.: Automation, E: Percentage reduction in energy. Initial: FL - Fluorescent, IN - Incandescent, MH - Metal Halide, LED, Light-emitting diode, CFL - Compact uorescent light, N/M -not mentioned in the paper. the interventions. Although the schools were from di erent regions, they mostly had uorescent lights installed (17 out of 20 studies). All the light replacements at schools were done with LED lights except for one study from Turkey, [43], where LED lights were too expensive and uorescent lights were used instead to the replace incandescent lights. The bulk of the studies reported a percentage energy saved from their light interventions. For the light retro t 5 intervention the energy saved ranged from 8% to 60%. The day-lighting interventions resulted in 2% to 40% of energy saved and for the automation intervention the energy savings ranged from 18% to 60%. Various energy-saving methods were used in the literature shown in Table 2. We identify these methods as the following categories: combined intervention; scenario comparisons; system comparisons; simulations; surveys and audits; energy evaluation tools; intervention evaluation; and modelling. 10 Out of the sixteen studies included in the light intervention literature in school buildings, the majority (8 out of 16) of the methods used involved scenario comparisons. This entailed combinations of multiple interventions done at schools and comparisons of them for the optimal option. Four of the studies investigated a combined-intervention approach, where multiple interventions were done in the same project. Four of the studies also included simulation, modelling or energy performance tools in order to evaluate retro ts. These methods were mostly in addition to 15 other methods. Two studies evaluated systems, where an implementation of a di erent systems were done for the same intervention. Only one study presented an individual intervention evaluation, where only one interventions is 4 Table 2: Literature review map of methods used for lighting intervention studies Geography Method description Method category Ref. EU Erhorn-Kluttig et al. [21] improved the energy performance of school building with multiple retro ts to school buildings. They report the measured lighting energy di erences with no model included.Combined interven- tion[21] Belgium Delvaeye et al. [22] compared the energy savings of daylight control systems through monitoring. System comparison [22] Greece Katsaprakakis and Zidianakis [24] investigated low energy lighting installation among multiple school building upgrades. Light replacements are simulated with shorter LED lights.Combined interven- tion[24] Greece Tsikra and Andreou [25] investigated energy saving and comfort interventions in schools with light shading systems and building envelope changes. Their evaluation was done through simulation.Combined interven- tion and simulation[25] Serbia Josijevi c et al. [29] presented a method of estimating savings with LED retro ts. They analysed the lighting share of total electricity consumption and the savings due to LED replacements. Their method excluded modelling.Intervention evalua- tion[29] Italy Ferrari and Romeo [30] simulated the retro ts and their cost-e ectiveness in schools. Multiple scenarios were compared.Scenario comparison [30] Spain Berardi et al. [32] simulated a retro t school project with multiple measures. The lighting retro t was evaluated in terms of energy and cost.Combined interven- tion[32] Italy Bonomolo et al. [34] analysed lighting retro t scenarios in schools. Di erent scenarios (partial installation and control systems) are considered for the cost-optimal option. The lighting replace- ments used a constant pro le.Scenario comparison [34] Italy Bellia et al. [35] presented a methods approach for implementation of the cost-optimal EEMs. They modelled the retro t changes compared to a reference building. A speci c lighting model was excluded.Scenerio comparison, modelling[35] South Africa Gibberd [15] evaluated retro t potential for schools using energy audits and an energy performance tool. Lighting share of electricity was modelled using a constant lighting pro le.Energy performance tool[15] Spain Gamarra et al. [13] analysed EEMs in schools. They showed the impact of lighting replacements and other measures. A constant lighting pro le was considered.Scenario comparison [13] Portugal Louren co et al. [37] investigated light-use management in schools with simulated models considering seasonality. Their results showed reductions through lighting interventions. Light energy models were excluded.Scenario comparison and simulation[37] EU Pati~ no-Cambeiro et al. [40] economically evaluated multiple EEMs in schools. They present the simplistic lighting intervention only showing energy and cost reduction using a constant lighting pro le.Scenario comparison [40] Greece Doulos et al. [11] optimised lighting consumption in classrooms. They evaluated lighting control systems with di erent photosensors.System comparison [11] Turkey Gorgulu and Kocabey [43] analysed outdoor campus lighting energy saving using retro t scenarios. A constant lighting pro le was used excluding the control light system EEM.Scenario comparison [43] Turkey Moazzen et al. [44] de ned a multi-parameter approach to understand the (cost, energy and envi- ronmetal) bene ts of EEMs. They considered implementing partial replacements, full replacements and/or lighting control systems. Simulation of a constant lighting pro le was used excluding the control system.Scenario comparison [44] evaluated for the project. None of these studies present a meaningful way to understand and model the lighting interventions in terms of impact on electricity usage and cost thereof. Where light replacements were considered, a constant-usage pro le was used instead of a scaling-usage light pro le as presented in this study. It is also clear from Tables 1 and 2 that most of the related studies were done in developed countries, with 5 Turkey, Jordan and Russia (Siberia) the only developing countries represented. Moreover, only a single study with a single auent school has originated from the continent of Africa. 1.4. Contribution To contribute towards solving the problems faced by South African education facilities { such as lack of basic infrastructure, large electricity bills and large energy consumption - we explored replacing lights with ecient LED 10 lights in schools and the savings (monetary savings, peak demand reductions, and energy savings) that are possible through such interventions. We introduce a validated model to assess the impact of LED light replacements - the most prevalent light intervention from the literature - at schools. To parameterise the model, we performed bench tests to characterise 5 Tariff structures Bench tests with individual lightsSimulated load profiles after replacements Life-cycle costRunning savingsSmart meter data (hourly) Lights contribution Measured load profiles after replacements RMS Error Number of lights at schoolModel development and validation ResultsData acquisition ModelNumber of lights replaced Figure 1: Three phases of work presented in this paper. the LED lights that are commonly used for replacements. We used this model to estimate the contribution of lighting to schools' electricity expenses; to assess the impact of LED replacements at seven schools; and to perform life cycle cost assessments of the tested LED lights. We present a holistic approach to lighting impact at South African schools consisting of three phases: data acquisition; modelling; and implementation of the lighting interventions. The following sections discuss the method 5 used; the lighting impact model; the lighting bench tests; and the results of our study. 2. Method We took a phased approach to assess the impact of our light replacement campaign at the schools. In the rst phase, we characterised each school's electricity load pro le with smart meter data. From these pro les, we evaluated their electricity cost from the applicable electricity tari structures. In the second phase, we developed 10 and validated a model to estimate contribution of lighting to the hourly load pro le during a school day. To this end, we performed bench tests of individual lights, replaced the majority of lights at three schools, and measured the change. During the third and nal phase, we used the validated model and smart meter data from seven schools to establish the contribution of lights to the eventual bill; determine the life-cycle costs of the tested LED replacement lights; and calculate the running savings ( nancial, peak demand, energy, and CO2) achieved by LED replacements. 15 2.1. Data acquisition The study takes place in and around Stellenbosch, in the Western Cape province of South Africa. It forms part of a larger project, in which the electrical pro les of sixteen schools were analysed with smart meters [46]. Schools in South Africa are categorised into ve groups - called "quintiles" - based on the income levels of the surroundings areas. The schools in our study are of di erent auence levels (increasing auence from Quintile 1 - 5) and include 20 both primary and secondary schools. In this paper we report on the measured impact of actual light replacements at three of these schools, and on the simulated impact of light replacements at these and another four schools for which we had sucient information. We used two types of smart meters to analyse, to a high time resolution, the electricity usage of the schools: municipal billing electricity smart meters with a 30 minute resolution and, where these were not installed, we used a 25 6 Table 3: Basic tari structures (2019/2020 tari s) according to which the schools are billed. Tari structure Component Symbol Summer Winter Unit Commercial (COM4) Energy rCOM 1.99 1.99 ZAR/kWh Industrial (IND1)Energy rIND,E 0.98 0.98 ZAR/kWh Peak demand charge rIND,d 248.43 248.43 ZAR/kVA Time of use (ToU)Peak energy rToU,pk 1.55 4.87 ZAR/kWh Standard energy rToU,std 1.02 1.46 ZAR/kWh O -peak energy rToU,o 0.77 0.86 ZAR/kWh Peak demand charge rToU,d 47.49 47.49 ZAR/kVA third-party retro t clamp-on smart energy meter with a 10 minute resolution [47]. Demand pro les were generated from these meters. We used the tari structures in two ways: rst, to determine what proportion of the school's electricity cost is attributable to lighting, and then in the results section to assess the nancial impact of replacing the lights with LED lights. 5 Each school in our study is billed according to one of three tari structures shown in Table 3. There are two main variable components that are charged by the municipality. The rst is the energy rate: this is used to charge school users for every kWh unit (i.e. magnitude of energy) used. This energy rate varies based on the tari structure. For the commercial and the industrial tari s, this energy rate remains constant regardless of the time of the day. For the Time-of-use (ToU) tari , however, the energy rates charged at schools di er based on the time of day. The 10 second component is the demand charge. This component is charged for each kVA unit (i.e. the magnitude of apparent power) used by a school. For each school in our study we obtained the monthly utility bills and a monthly summary of bills over the last year from the local municipality (council), which acts as the electricity retailer. 3. Bench tests: Individual lights 15 Eight often-used and readily available LED light replacements were tested under the same conditions to de- termine their power and illuminance characteristics. These lights and summary of the results are shown in Table 4. We used bench tests to measure the actual performance of the individual lights to determine the power draws of the uorescent lights, S , and the replacement LED lights, SLED. The bench test consisted of measuring active 20 power and power factor with a digital power meter, a Yokogawa 2533. Table 4: Comparison of lights power characteristics OrbitX Philips ClearSky ClearSky Philips LighTec Philips Osram CorePro EcoFit Master VLE Substitute 19W 20W 22W 32W 22W 22W 21W 22W Cost [ZAR] 180 170 145 170 80 148 180 120 Active power [W] 18.8 20.5 23.5 27.5 22. 0 21.9 20.8 21.9 Power factor 0.96 0.96 0.89 0.71 0.61 0.55 0.95 0.95 Apparent power [VA] 20 21 26 39 36 40 22 23 Max lux [lx] 813 560 809 900 569 670 770 736 % of statutory EOL brightness 106% 73% 105% 117% 74% 89% 100% 96% Demand reduction [VA] 42 40 35 22 25 22 39 38 Energy savings [W] 41 40 37 33 38 38 39 38 7 The power draw of each light was measured with the same power meter for all lights to con rm the speci cations quoted by the light manufacturers. As shown in Table 4, the OrbitX light's power draw was lower than speci ed and the other lights measured above or equal to their speci ed power draws. The power factor was also measured for all the lights with the same meter since the ToU tari structure includes reactive/apparent power: a lower power factor indicates an increased reactive power usage of the light. The uorescent tubes have high power factors - 5 almost 0.98. This needed to be matched otherwise the schools billed with ToU tari s could receive a replacement that may increase the bills. The OrbitX and the Philips CorePro lights measured the same power factor of 0.96. The Philips Master VLE and Osram substitute measured a power factor of 0.95. The rest of the lights measured lower power factors ranging from 0.55 - 0.89. Such lower power factors result in higher apparent power, measured in VA, and this is also included in their bill under demand charge. From these measurements the demand reductions 10 and energy savings were calculated for each light. The lights with lower power factors had higher apparent powers and therefore lower demand reductions. The energy savings of each light was calculated by subtracting the power used by the lights for the school hour from the uorescent lights for the same amount of time. The OrbitX and Philips CorePro lights had the highest savings: 41 W and 40 W respectively. Although these tests show the key parameters, the savings and life cycle cost projections will show which lights perform best in the long term. 15 Finally, illuminance was measured for all lights under the same experimental setup. The maximum lux of each light was measured with a light meter. It was repeated in the same room for the eight LED lights at the same height. Their light output was then compared to the minimum statutory illuminance required. A simulation in Dialux was used to iteratively determine the minimum illuminance required at the beginning of life to achieve the minimum statutory illuminance of 200 lux at the end of life at the far side of a typical classroom. This gave 767 20 lux at the beginning of life. The classroom room illuminance requirement is 300 lux (SANS standard 10114-1). The percentage measured illuminance compared with the required beginning of life illuminance was then calculated. These conditions were one dark room with a measured ambient illuminance of 0 :1 Lux, and the lights measured individually at a height of 0.78m. The light meter was placed at 0.78 meters below the middle of the tested light. The OrbitX and both ClearSky lights measured a light level that is higher than the required level, but the others 25 were all below 100% of the statutory brightness. 4. Model 4.1. Model development In this section we develop the model used to calculate the impact of replacing the uorescent lights at schools with energy-ecient LED lights. The approach is demonstrated in Figure 2 and described below. The main 30 unknowns are the di erence in power draw between the lights, the number of replaced lights, and the times at which the lights are turned on during the typical school day. An adjusted lighting utilisation pro le is needed since the load pro le for each school di ers in time and amplitude (see Figure 3). We estimate this pro le from the whole school's average weekday load pro le before the light replacements. Accordingly, we estimate the times at which there are substantial changes in the number of lights 35 that are switched on, and subsequently, the number of lights turned on for each hour of the day. To achieve this, 8 a proportional load function, p(t), is used to represent the light utilisation. This function is partially tted to the speci c school's total load pro le with 0% of the replaced lights assumed to be on when the school is at or near to its base-load at night, and 100% of the replaced lights are turned on when the school's load is near maximum in the middle of the school day. Four in iction points are then identi ed from the school's average load pro le: tam,0% , tam,100% ,tpm,100% andtpm,0% . 5 These in iction points are assumed to occur at the same times on the projected light usage pro le and transferred to the proportional load function, as shown Figure 2b. The proportions in the transitions between the 0% and 100% levels are calculated using proportional interpolation with the school's total load pro le as base. This resulting load pro le of only the LED lights (see Figure 2c) is produced by scaling the proportional load function by the expected load of all the replaced lights, and is given by 10 sschool,LED (t) =np(t)SLED (1) where sLEDis the load of one LED light and nis the number of lights that were replaced. The load reduction due to the replacements is also proportional to the light usage pro le. The school's projected energy usage after the light replacement is given by s(t)school,proj =s(t)school,before np(t)[S SLED] (2) where s(t)school,before is the average measured load pro le of the school during a school day before the light replace- ment; p(t) is the proportional light load factor shown in Figure 2b; and [ S SLED] is the complex di erence in 15 power usage between a single uorescent and LED light. The resulting projected load pro le for the whole school with the replaced lights is shown in Figure 2d. Since sis complex, the power draw is a ected by the di erence in apparent power and real power. The apparent power combines the active and reactive power components expressed in kVA and is charged as the demand used. The real power is the active component that a ects the energy usage expressed in kWh and is charged as energy 20 used. The di erence between the energy usage of the installed lights and the replacement lights was used to calculate theoretical savings. These calculated savings would di er based on the selected replacement light and the number of lights replaced. Each schools' theoretical savings therefore were calculated based on their unique choice of replacement light and the number of lights replaced. 25 4.2. Model assessment Lights were replaced at three schools as shown in Table 5: one primary school and two secondary schools. We replaced the lights at these schools and measured their electricity usage before and after the intervention. These replacements were done in three to ve workings days for each school. The schools' interventions di ered slightly in terms of lights used and the installation of lights. Although most 30 of the current lights were uorescent lights, the schools had di erent lamp xtures installed. The current lights in the schools were identi ed and counted through surveys. Their power usages ranged from 58W to 60W for 1.5m T8 9 /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000003/uni00000018 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/uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000014/uni00000003/uni00000045/uni00000048/uni00000049/uni00000052/uni00000055/uni00000048(a) The average load pro le of School 1 before replacement, sschool,before . /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000003/uni00000015/uni00000013 /uni00000013/uni00000015/uni00000013/uni00000017/uni00000013/uni00000019/uni00000013/uni0000001b/uni00000013/uni00000014/uni00000013/uni00000013/uni00000033/uni00000048/uni00000055/uni00000046/uni00000048/uni00000051/uni00000057/uni00000044/uni0000004a/uni00000048/uni00000003/uni00000046/uni0000004b/uni00000044/uni00000051/uni0000004a/uni00000048/uni00000003/uni0000000b/uni00000008/uni0000000c /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000013 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni0000002f/uni0000004c/uni0000004a/uni0000004b/uni00000057/uni00000003/uni00000058/uni00000057/uni0000004c/uni0000004f/uni0000004c/uni00000056/uni00000044/uni00000057/uni0000004c/uni00000052/uni00000051 (b) Proportional load function, p(t). /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000003/uni00000018 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 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000013 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni00000035/uni00000048/uni00000053/uni0000004f/uni00000044/uni00000046/uni00000048/uni00000050/uni00000048/uni00000051/uni00000057/uni00000003/uni00000049/uni0000004f/uni00000058/uni00000052/uni00000055/uni00000048/uni00000056/uni00000046/uni00000048/uni00000051/uni00000057/uni00000003/uni0000004f/uni0000004c/uni0000004a/uni0000004b/uni00000057/uni00000056 /uni00000035/uni00000048/uni00000053/uni0000004f/uni00000044/uni00000046/uni00000048/uni00000047/uni00000003/uni0000002f/uni00000028/uni00000027/uni00000003/uni0000004f/uni0000004c/uni0000004a/uni0000004b/uni00000057/uni00000056 (c) The projected light utilisation scaled to the energy usage of the re- placed uorescent lights and the replacement LED lights. /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000003/uni00000018 /uni00000013/uni00000018/uni00000014/uni00000013/uni00000014/uni00000018/uni00000015/uni00000013/uni00000015/uni00000018/uni00000016/uni00000013/uni00000028/uni00000051/uni00000048/uni00000055/uni0000004a/uni0000005c/uni00000003/uni0000004c/uni00000051/uni00000003/uni0000004e/uni0000003a/uni0000004b/uni00000003/uni0000000b/uni00000050/uni00000048/uni00000044/uni00000051/uni00000003/uni00000049/uni00000052/uni00000055/uni00000003/uni00000048/uni00000059/uni00000048/uni00000055/uni0000005c/uni00000003/uni0000004b/uni00000052/uni00000058/uni00000055/uni0000000c /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000013 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000014/uni00000003/uni00000053/uni00000055/uni00000052/uni0000004d/uni00000048/uni00000046/uni00000057/uni0000004c/uni00000052/uni00000051(d) The projected load pro le after replacement, sschool,proj . Figure 2: The light projection model stages, representing the school's usage before and after the intervention, are shown with the modelled light utilisation. Table 5: Details of schools where lights were replaced Scholar levelTari Quint. Learners Lights installedLights re- placedLabour cost [ZAR]Light cost [ZAR]Supplier School 1 Secondary COM4 1 800 240 240 0 43,200 OrbitX School 2 Primary COM4 4 900 420 220 6,000 39,200 Philips School 3 Secondary ToU 4 1100 510 194 4,400 34,200 OrbitX lights - almost triple the average LED light power rating. Based on the bench test results, the active power of the nominally installed uorescent light to be used in the model was chosen as 60W with the measured power factor of 0.98. Figure 3a shows the results for School 1, a secondary school, at which 240 uorescent lights were installed, of which 240 classroom lights were replaced with OrbitX LED lights. The lights were replaced by the caretakers and 5 the researchers, at no extra labour costs. The installation took ve afternoons to complete. A three-week baseline was used for the energy pro le before the light intervention, which is referred to as the before pro le. A nine-week period was used after the light intervention, which is referred to as the after pro le. These were consecutive periods and only weekdays were considered. The overall mean reduction was 85 kWh per school day { an energy reduction of 35% on the pre-existing lights. 10 The reduction in peak demand was 8 kVA { a reduction of 26% from the peak demand on the pre-existing lights. The RMS (root-mean-squared) error between the prediction and the measured pro les was 6 kWh over a day. This is 2% of the daily energy usage before the replacement. The maximum observed error in load was 1 kVA, which is 3% of the maximum peak load observed from before the replacement. 10 Figure 3b shows the results for School 2, a primary school, at which 420 uorescent inside lights and 20 metal halide outside lights were installed. Of these, 240 lights were replaced: 220 classroom lights with Philips EcoFit; and 20 outside lights with lights from a combination of suppliers. At this school contracted technicians installed the replacement lights at a labour cost of ZAR 6,000. The installation took three afternoons. A 20 week baseline was used for the energy pro le before the light intervention, which is referred to as the before pro le. A consecutive 5 four-week energy measurement period was used after the light intervention, which is referred to as the after pro le and only weekdays were considered. Between the before and after energy pro les the overall mean reduction was 65 kWh per school day { an energy reduction of 27%. The reduction in peak demand was 9 kVA { a reduction of 18% from the peak demand on the pre-existing lights. Although the projected and after energy pro les are close, they di er by energy error of 5 kWh 10 (2% of daily energy used before). The maximum observed error in load was 0.7 kVA, which is 1% of the maximum peak load observed from before the replacement. Figure 3c shows the results for School 3, another secondary school. This school had 510 uorescent lights installed, of which 194 inside lights were replaced with OrbitX LED lights. Contracted technicians installed the replacement lights in two afternoons at a labour cost of ZAR 4,400. 15 For this particular school, the same one week period was used for both before and after energy measurement periods, referred to as before and after pro les respectively. Although only weekdays were considered, these periods were not consecutive periods but were one year apart. Between the before and after energy pro les the overall mean reduction was 81 kWh per school day: 23%. The reduction in peak demand was 13 kVA { a reduction of 37% from the peak demand on the pre-existing lights. 20 Although the projected and after energy pro les are close, they di er by energy error of 7 kWh (2% of daily energy used before). The maximum observed error in load was 2 kVA, which is 5% of the maximum peak load observed from before the replacement. Figure 3d shows the average di erence between the measured and the projected pro les for the three schools over a 24 hour period. 25 5. Results 5.1. Contribution of lighting costs in schools We used the following to calculate the lighting portion of the annual school bill, before and after light replace- ments: municipal bills, smart-meter data, tari structures, and our model. Figure 4 shows the billing information for each school and the estimated contribution of lighting to the annual bill rst with uorescent lights, and then 30 with LED replacements. Before the impact of the lighting interventions, the annual lighting costs for the observed schools ranged from ZAR 41,250 to ZAR 109,340. For the schools on the commercial tari , annual lighting costs ranged from ZAR 41,250 to ZAR 63,740. The annual lighting costs of the two ToU schools were ZAR 101,580 and ZAR 109,340. The school with the industrial tari had a lighting cost of ZAR 76,190. 35 The overall cost impact of lights before interventions ranged from 31% to 57%, with a median contribution of 40%. For the four schools on the commercial tari , lighting was responsible for 31% to 43% of the bill. At the two 11 /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 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 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000013 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000014/uni00000003/uni00000045/uni00000048/uni00000049/uni00000052/uni00000055/uni00000048/uni00000003/uni0000000b/uni00000034/uni00000014/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000014/uni00000003/uni00000044/uni00000049/uni00000057/uni00000048/uni00000055/uni00000003/uni0000000b/uni00000034/uni00000014/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000014/uni00000003/uni00000053/uni00000055/uni00000052/uni0000004d/uni00000048/uni00000046/uni00000057/uni0000004c/uni00000052/uni00000051(a) School 1 (Secondary): 240 lights were replaced with OrbitX lights, resulting in 35% energy saving and 9 kVA demand reduction on in-term days. /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 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 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000013 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000015/uni00000003/uni00000045/uni00000048/uni00000049/uni00000052/uni00000055/uni00000048/uni00000003/uni0000000b/uni00000034/uni00000017/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000015/uni00000003/uni00000044/uni00000049/uni00000057/uni00000048/uni00000055/uni00000003/uni0000000b/uni00000034/uni00000017/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000015/uni00000003/uni00000053/uni00000055/uni00000052/uni0000004d/uni00000048/uni00000046/uni00000057/uni0000004c/uni00000052/uni00000051(b) School 2 (Primary): 220 lights were replaced with EcoFit lights, resulting in 27% energy saving and 13 kVA demand reduction on in- term days. /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 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 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000013 /uni00000057/uni00000042/uni00000044/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000014/uni00000013/uni00000013 /uni00000057/uni00000042/uni00000053/uni00000050/uni00000042/uni00000013/uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000016/uni00000003/uni00000045/uni00000048/uni00000049/uni00000052/uni00000055/uni00000048/uni00000003/uni0000000b/uni00000034/uni00000017/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000016/uni00000003/uni00000044/uni00000049/uni00000057/uni00000048/uni00000055/uni00000003/uni0000000b/uni00000034/uni00000017/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000016/uni00000003/uni00000053/uni00000055/uni00000052/uni0000004d/uni00000048/uni00000046/uni00000057/uni0000004c/uni00000052/uni00000051 (c) School 3 (Secondary): 194 lights were replaced with OrbitX lights, resulting in 25% energy saving and 6 kVA demand reduction on in-term days. /uni00000013/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000013/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000013/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000017/uni0000001d/uni00000013/uni00000013 /uni00000014/uni00000019/uni0000001d/uni00000013/uni00000013 /uni00000014/uni0000001b/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000013/uni0000001d/uni00000013/uni00000013 /uni00000015/uni00000015/uni0000001d/uni00000013/uni00000013 /uni00000003/uni00000016 /uni00000015 /uni00000014 /uni00000013/uni00000014/uni00000015/uni00000016/uni00000028/uni00000051/uni00000048/uni00000055/uni0000004a/uni0000005c/uni00000003/uni0000004c/uni00000051/uni00000003/uni0000004e/uni0000003a/uni0000004b/uni00000003/uni0000000b/uni00000050/uni00000048/uni00000044/uni00000051/uni00000003/uni00000049/uni00000052/uni00000055/uni00000003/uni00000048/uni00000059/uni00000048/uni00000055/uni0000005c/uni00000003/uni0000004b/uni00000052/uni00000058/uni00000055/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000014/uni00000003/uni00000003/uni00000048/uni00000055/uni00000055/uni00000052/uni00000055/uni00000003/uni0000000b/uni00000034/uni00000014/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000015/uni00000003/uni00000003/uni00000048/uni00000055/uni00000055/uni00000052/uni00000055/uni00000003/uni0000000b/uni00000034/uni00000017/uni0000000c /uni00000036/uni00000046/uni0000004b/uni00000052/uni00000052/uni0000004f/uni00000003/uni00000016/uni00000003/uni00000003/uni00000048/uni00000055/uni00000055/uni00000052/uni00000055/uni00000003/uni0000000b/uni00000034/uni00000017/uni0000000c(d) Average energy error between the projected and measured savings. Figure 3: The light pro les of schools, representing the school's usage before and after the intervention, are shown compared to the light projections for the speci c school. schools on the ToU tari lighting was responsible for 38% and 55%. The school with the industrial tari had a lighting contribution of 57%. After replacing the lights, their contribution reduced to ZAR 13,390 to ZAR 34,430, which is equal to 12% to 30% of their electricity bills, with a median of 17%. 5.2. Running savings 5 The running savings are shown in Table 6. The school's individual smart meter data and the model were used to calculate the energy saved during an average school day. These savings were then extrapolated to usage for a school year (196 days), taking seasonality into account. The calculations assume OrbitX T8 lights, except for School 2 where the Philips EcoFit was used. The projected energy saved per school day was 80 to 190 kWh. The schools reduced their daily carbon emissions 10 by 80 to 180 kg CO 2. The projected demand reduction per year ranges from 80 to 290 kVA. The yearly projected energy saved was 14,710 to 38 :030 kWh. The running savings of the projected replacements resulted in an energy cost di erence of ZAR 15,020 to ZAR 60,850 and a load cost di erence of ZAR 13,510 to ZAR 37,150 across all the schools. The total cost di erence was between ZAR 25,740 to ZAR 76,750. 15 12 31% 12%40% 17%55% 28%40% 17%57% 30%43% 22%38% 16% 050,000100,000150,000200,000250,000300,000 Before After Before After Before After Before After Before After Before After Before After School 1, 240 lights Q1, Sec., COM4School 2, 420 lights Q4, Pri., COM4School 3, 510 lights Q4, Sec., ToUSchool 4, 380 lights Q1, Pri., COM4School 5, 300 lights Q3, Pri., IND1School 6, 370 lights Q3, Pri., COM4School 7, 600 lights Q5, Pri., ToUAnnual cost and lighting contributions (ZAR)Other Lighting before Lighting after Δ Bill = -21%Δ Bill = -27%Δ Bill = -37% Δ Bill = -27% Δ Bill = -39% Δ Bill = -27%Δ Bill = -26%Figure 4: Lighting proportion of annual electricity bills before the replacements, and projected contributions after replacement of all the lights. Table 6: Running savings achieved by the projected contribution of the LED replacements of all lights at each school Tari School- day energy reduction [kWh =d]Carbon footprint [kg=d]Peak demand reduction [kVA=m]Demand cost di erence [ZAR =y]Energy reduction [kWh =y]Energy cost di erence [ZAR =y]Bill re- duction [ZAR =y] School 1 COM4 90 90 120 0 16,760 29,340 29,340 School 2 COM4 120 110 240 0 24,250 42,440 42,440 School 3 ToU 180 170 250 13,510 36,040 57,660 71,170 School 4 COM4 130 120 190 0 25,010 43,770 43,770 School 5 IND1 80 80 150 37,150 15,020 14,720 51,870 School 6 COM4 80 80 140 0 14,710 25,740 25,740 School 7 ToU 190 180 290 15,900 38,030 60,850 76,750 5.3. Life-cycle costs for di erent light choices The savings were calculated over six years. They take into account the number of school days per year and assume that a school has 600 lights per school using the mathematical expression. We assumed lights are on for an average of six hours per school day. The assumptions are based on a sample school light count and school operating hours. 5 Table 7 represents the three typical tari structures: a at fee (commercial tari ) for energy, time-of-use and the industrial tari . The manufacturer guarantee periods were used to calculate the replacement periods. The net savings for each light were calculated. The monthly savings of the light compared to the uorescent tubes were considered. The price of the light, labour and replacement costs were considered and deducted. Over a six year period the OrbitX lights had the highest net savings for all the tari structures as ZAR 360 ( at rate), 10 ZAR 450 (ToU) and ZAR 950. However, lights that compared well in the at rate tari structure were the LighTec and the Osram lights with a ZAR 10 di erence. For the ToU tari this di erence was greater at ZAR 10 by the Osram light. The absolute life-cycle cost includes the cost of the lights (labour, light and replacement) and their cost due to using the lights or energy costs. Over a six year period the OrbitX light had the lowest cost overall as ZAR 500 15 ( at rate), ZAR 540 (ToU) and ZAR 780 (ind). The second-best light for the at tari was the Osram Substitute at ZAR 500 and for the time-of-use and industrial tari s it was the Osram Substitute at ZAR 560 and ZAR 840 respectively. The light with the most cost over the period was the Philips CorePro, di ering by more than ZAR 230 13 Table 7: Comparison of the life-cycle cost and savings over six years of energy ecient lights on Commercial 4 (COM4), Time-of-use (ToU) and industrial 1 (IND1) tari s. OrbitX ClearSky Philips ClearSky Philips LighTec Philips Osram EcoFit CorePro Master VLE Substitute 19W 22W 22W 32W 20W 22W 21W 22W [ZAR] [ZAR] [ZAR] [ZAR] [ZAR] [ZAR] [ZAR] [ZAR] COM4 Per light: Savings 360 280 310 200 120 350 280 350 Per light: Cost 500 570 540 650 730 500 570 500 Per school: Savings 213,030 170,220 187,770 119,580 74,350 208,700 168,390 208,700 Per school: Cost 298,180 340,980 325,440 391,620 436,860 302,510 342,820 302,510 ToU Per light: Savings 450 360 350 240 220 370 370 440 Per light: Cost 540 630 650 760 780 620 624 560 Per school: Savings 270,910 216,880 208,710 141,250 129,680 222,850 223,060 261,600 Per school: Cost 326,300 380,330 388,490 456,000 467,520 374,360 374,420 335,600 IND1 Per light: Savings 950 770 590 460 700 550 850 890 Per light: Cost 780 970 1,140 1,280 1,040 1,180 890 840 Per school: Savings 571,250 463,140 355,270 275,340 416,970 331,840 507,130 536,680 Per school: Cost 470,660 578,770 686,640 766,570 624,940 710,070 534,780 505,230 Savings: Net savings vs. uorescent, and Cost: Absolute life-cycle cost. from the least expensive light for the time-of-use and at rate tari structures. The light with the most life-cycle cost for the industrial tari was the ClearSky 32W. When viewed in the short term, the OrbitX light is the most expensive - considering it is only the tube - and the Philips EcoFit costs the least, but they di er substantially in energy and light quality. When viewing them over the longer term, the OrbitX light saves more and costs less. 5 With the gures of savings and cost per light over six years, the projections were linearly scaled up to a school level of 600 lights. For the at rate tari , the best light is the OrbitX and second is the Philips EcoFit. For the time-of-use and industrial tari s the best light is the OrbitX and second is the ClearSky 22W. The savings for the best light amounts to ZAR 213,030 for the at tari , ZAR 270,910 for the time-of-use tari , and ZAR 571,250 for the industrial tari . 10 The absolute life-cycle cost on a school projection level for the at rate ranged between approximately ZAR 298,180 and ZAR 436,860. For this tari , the OrbitX lights - the least expensive option - would cost a school ZAR 298,180. The Philips EcoFit and ClearSky lights would cost a school between ZAR 325,440 and ZAR 391,620, at least ZAR 27,000 more than the least expensive option. The Philips CorePro has a larger di erence in cost of almost ZAR 140,000 in comparison with the least expensive option. 15 Considering the absolute life-cycle cost in a ToU tari structure for a school, the range of cost is between approximately ZAR 326,300 and ZAR 467,520. The arrangement of lights is ranked similarly to the previous tari structure, however the Osram Substitute light was the second least expensive ToU option, with a ZAR 9,300 di erence in comparison with the least expensive option. The cost for the industrial tari ranged from ZAR 470,660 and ZAR 766,570, the most expensive of all the 20 tari s. The light cost order is like the time-of-use tari . The most expensive light is the ClearSky 32W followed by the Philips EcoFit. The replacement cost of the lights had a large impact on the absolute cost. This was based on the manufacturer's written guarantee - although the lights may last longer. Their guarantees were as follows: OrbitX (six years), Philips EcoFit (three years), ClearSky 22W ( ve years), ClearSky 32W ( ve years), Philips CorePro (three years), LighTec 25 14 ( ve years), Philips Master VLE ( ve years) and Osram Substitute ( ve years). Linear extrapolation was used to calculate the costs for all at six years. 6. Conclusion South Africa is under pressure to grow its economy, reduce emissions, and to ensure energy security and a ord- ability. This is especially true of the often-neglected primary education sector, which is struggling to meet even its 5 primary obligations. One easy answer to reduce costs, reduce electricity demand, reduce emissions, and improve the prospects in the education sector is to replace the outdated uorescent lights with energy-ecient LED lights. Despite existing publications describing international e orts to replace lights at schools, little is known of the cost of replacements, the nancial and environmental bene ts of such replacements, and the e ect of choosing one of the many available lights as a better replacement. Moreover, none of the existing research reviewed for this has 10 developed a model with which to assess the impact; none of them have evaluated the available lights for the purpose; very few have considered developing country contexts, and none of them have considered schools in Africa. To that end, we explored electricity used at public schools in South Africa, assessed the proportion of the annual cost attributable to lighting, determined the nancial and environmental bene ts of replacements, and assessed the available options. We developed a model that was validated with smart meter data and partial light replacements 15 at three schools. We used the model to assess the impact at seven schools for which we had smart meter data and light audits. Bench tests of the available lights proved that di erent savings can be achieved through the lights tested. The savings of some were more than double that of others, and the life-cycle costs varied from ZAR 298,180 to ZAR 766,570 between lights and tari structures. 20 At the schools in our sample, we found that lighting constitutes from 31% to 57% of annual electricity costs before LED replacements. By replacing all the lights, the annual electricity bills were reduced by 21% to 39%, and the proportion of lighting from 12% to 30%. Future work could include case and/or pilot studies of di erent light replacements for the two tari structures at schools. This would be for veri cation of the light cost and savings projections. Furthermore, decision makers 25 could include the bench test results in their speci cations for LED lights criteria. This study showed the value of longer-term projections compared with the short-term cost of the lights. We found that the most expensive light in the short them yielded the most savings in the long term, and that the price tag and long-term savings do not necessarily correspond to light quality.