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Article

Energy Audit of Road Lighting Installations as a Tool for Improving Efficiency and Visual Safety Conditions

1
Department of Electrical Engineering, Czestochowa University of Technology, 42-200 Czestochowa, Poland
2
Faculty of Electrical Engineering and Computer Science, Rzeszów University of Technology, 35-213 Rzeszów, Poland
*
Author to whom correspondence should be addressed.
Energies 2025, 18(20), 5357; https://doi.org/10.3390/en18205357 (registering DOI)
Submission received: 4 August 2025 / Revised: 8 September 2025 / Accepted: 9 October 2025 / Published: 11 October 2025
(This article belongs to the Section F: Electrical Engineering)

Abstract

This study presents an analysis of the condition of street lighting based on a selected typical installation in one of the 1459 rural communes in Poland. The analysis was carried out on the basis of publicly available statistical data, local government reports, and information contained in national and European strategic documents. During the analysis, numerous irregularities and differences in the quality and energy efficiency of the lighting infrastructure were indicated. It was found that outdated sodium luminaires with high energy consumption, low durability, and limited luminous efficacy are used in many cases, which generates significant operating costs and negatively affects the environment. The authors emphasize that a lack of regular and professional lighting audits leads to the suboptimal use of energy resources, an insufficient level of road safety, and failure to adapt lighting to current technical standards and the needs of road users. A lighting audit is a key tool for diagnosing the technical condition, efficiency, and compliance of installations with relevant regulations and recommendations. It also allows for the identification of potential savings and determining the directions of modernization and implementation of energy-saving technologies, such as LED luminaires and intelligent control systems.The presented analysis demonstrates that energy audits are an effective tool for confirming efficiency improvements and enhancing visual safety conditions through better compliance with photometric standards (luminance, lighting uniformity). Direct accident statistics were not within the scope of this study.

1. Introduction

Modern road lighting systems are an important element of technical infrastructure, the role of which goes beyond the function of illuminating space. Ensuring the safety of road users, visual comfort, and the efficient management of electrical energy are the basic tasks of modern lighting solutions. In this context, the energy audit of road lighting installations is becoming increasingly important.
An energy audit allows for assessment of the condition of the existing lighting infrastructure, including its energy efficiency and compliance with applicable standards. As it results from the analyses presented in [1,2,3,4], conducting an audit allows not only for the identification of energy-saving opportunities but also provides a basis for planning rational modernization investments. This is particularly important in the context of the growing role of energy efficiency in climate policy and access to funds supporting sustainable development.
The lighting audit should be carried out in accordance with the applicable legal regulations and technical standards [5,6,7,8,9], which specify in detail the design criteria, requirements, and calculation and measurement methods for road lighting installations. In Poland, the conduct of an energy audit in the scope of modernization of public infrastructure, including road lighting, is regulated by the Act of 20 May 2016 on energy efficiency [10], which defines the obligations in the scope of rationalization of energy consumption and indicates the necessity of conducting energy audits in the case of applying for public funds for energy-saving investments. Audit requirements are also specified in the competition rules and guidelines of various Polish pro-ecological programs supported by EU programs, such as [11].
The authors of the article [12] indicated that the proper conduct of an energy audit should include several stages:
  • Inventory of the existing lighting system—identification of all light points, types of luminaires, light sources, poles, control devices.
  • Assessment of technical condition—analysis of component wear, compliance with standards, losses in light quality.
  • Energy and cost analysis—determining energy consumption, operating and service costs, ordered vs. actual power levels.
  • Simulations and modeling of modernization variants—based on calculation tools and photometric software (e.g., Dialux verssion 4.13.0.2), assessment of potential improvement scenarios.
  • Investment recommendations—proposal of specific solutions together with an analysis of their profitability (e.g., determination of the DGC indicator—dynamic unit cost of ecological effect).
Street lighting is responsible for 3–4% of total energy consumption in the European Union, and can even reach 40% of the electricity demand in cities, highlighting the importance of using audits as an element of energy efficiency management. The case study conducted in the article [12] clearly demonstrated that a well-performed audit of street lighting installations can be an effective instrument for reducing the energy intensity of urban systems.
LED technology has practically replaced other lighting technologies worldwide, and is much more energy efficient than any previous light-emitting technology. Many innovative technologies are being developed worldwide, such as PLED [13,14], with the aim of improving the efficiency of LED sources. A comparison of lighting technologies, presented in the analysis by Czech researchers [15], indicated the significant advantages of LED luminaires over traditional high-pressure sodium lamps. LEDs are characterized by higher luminous efficacy, better color rendering, longer durability, and the possibility of smooth control of the luminous flux. A special advantage is high luminance under scotopic vision conditions, which is crucial for the safety of road traffic at night.
Research conducted in the European Union on lighting focuses primarily on increasing energy efficiency, improving road safety, and reducing operating costs. A key direction of development is LED technology and intelligent control systems, which allow for adjustment of the light intensity to current traffic and environmental conditions [16].
In the design of lighting systems, multi-criteria models are applied to optimize the distribution, power, and type of luminaires. These models take into account not only technical parameters but also economic and environmental aspects, supporting the development of more sustainable solutions [16]. In parallel, methods for measuring lighting quality—such as average luminance—are being developed under real traffic conditions. This approach enhances the accuracy of system assessments and facilitates the implementation of European standards [17].
Field studies conducted in Belgrade have demonstrated that lighting with a correlated color temperature of 3000 K was rated significantly better by users compared to neutral white light of 4000 K, even though both variants exhibited comparable photometric parameters. This indicates that the design of lighting systems should not be limited solely to technical requirements, but must also consider visual comfort and users’ sense of safety [18].
Additionally, research carried out in Sweden showed that while road lighting for vehicles generally meets regulatory requirements, pedestrian and bicycle paths more often display deficiencies in luminance uniformity. The authors also emphasized that the greatest potential for improving energy efficiency lies not in reducing lighting classes, but in the use of intelligent dimming schedules. Such solutions can reduce energy consumption by up to 49% without compromising traffic safety [19].
At the European level, significant benefits resulting from the implementation of energy audits of road lighting have also been noted. For example, in the article [20], the authors identified the shortcomings of the current regulations in Spain regarding street lighting and indicated a number of practical solutions for improving energy efficiency and lighting quality. One of the conclusions in the context of the development of RES is the strong recommendation to integrate photovoltaics in lighting systems, especially in autonomous installations. The authors indicated that, in some cases, it is possible to cover up to 86% of the energy demand from RES. According to the report of the French Cour des comptes [21] published in 2021, the Vif commune implemented an LED lighting system with motion sensors on a bicycle path with a length of approx. 1.5 km, achieving a 70% reduction in energy consumption compared to a traditional lighting system. In Italy [22], as part of the “Torino a LED” project, 55,000 traditional sodium luminaires were replaced with LED luminaires with a control system, achieving significant energy saving effects. Real measurements showed an average 51% reduction in energy consumption after replacing the systems. At the same time, photometric standards (intensity, uniformity) were met or improved thanks to the use of LEDs, which was confirmed through simulations and field measurements.
In Poland, as exemplified by an analysis conducted at the Warsaw University of Technology [23], there is significant potential to improve the energy efficiency of road lighting by adjusting the luminance level to the actual traffic intensity. Reducing luminance at night in areas with low traffic intensity can lead to savings of around 38% per year. However, this requires the use of modern control systems and the conscious design of lighting systems. The importance of energy audits in Poland has also been emphasized in the context of the SOWA Program [24], which promotes the modernization of street lighting in municipalities. The audit is not only a formal requirement but, above all, a tool for planning modernization in accordance with normative requirements. An effective audit provides information on the technical condition of luminaires, energy consumption, operating costs, and lighting control options.
In the remainder of the article, the authors present the issues associated with properly conducting an audit for a selected public space related to road infrastructure in a typical rural commune in Poland. Four preliminary projects for the assumed classes of road lighting according to the luminance criterion (class M) and the illuminance criterion (class C) are presented. The obtained results of photometric and energy parameters are compared and assessed, as well as the forecasted energy consumption and reduction in CO 2 emissions. The purpose of this study is to analyze and compare several options for upgrading road lighting systems, assessing their energy and economic impacts as well as their impact on road safety.

2. Normative Requirements Related to Proper Road Lighting

The requirements for proper road lighting are defined in the standards [5,6,7,8,9], which present the requirements for selecting lighting classes and define the appropriate lighting parameters that must be met in a given situation. The standards distinguish three basic road lighting classes:
  • M—Class intended for roads with motorized traffic.
  • C—This class is intended for conflict zones; i.e., places where the use of class M is not recommended. Examples of such places include road intersections or roads with variable widths. Unlike class M, class C determines the intensity level, not the luminance.
  • P—This class is intended for areas where pedestrians and cyclists travel, such as paths and sidewalks. The requirements of these road users vary depending on factors such as speed, and therefore the class requirements are based on different values.
The update of these standards compared to the previously applicable ones has fundamentally changed not only the labeling of lighting classes, but also the methodology for their selection and classification. The standards in force until 2016 and the notes to these standards [25] proposed determining lighting classes by defining and specifying lighting situations, then selecting a lighting class based on their analysis.
The concept of lighting situation is not formally defined in the standards [5,6,7,8,9]. Instead, it results from the way in which a set of situations is presented and grouped, as well as from their detailed definition based on road characteristics, traffic characteristics, and environmental and weather influences. A lighting situation is defined by a set of all the factors on the road and in its surroundings that characterize the conditions in which traffic takes place. Unfortunately, the standards [5,6,7,8,9] do not include a procedure for defining lighting situations; however, they do provide guidelines for selecting lighting classes and defining appropriate lighting parameters. Particular attention is paid to the requirements of two road classes. The application of these classes depends on the geometry of the given area and on traffic and time conditions.
Road lighting classes M are intended for motor vehicle drivers on public transport routes (and, in some countries, also on residential roads), enabling driving at moderate to high speeds [5]. Another definition in [26] states that a street intended for motor traffic should be classified as class M; that is, this is how lighting should be classified in locations where technical solutions for streets with a designated area for vehicle traffic (roadway) and a designated pedestrian traffic area (sidewalk) predominate. Therefore, when illuminating the roadway, class M should be selected while, for the needs of pedestrian traffic area lighting, class P should be selected. Subsequent publications [27,28] have specified the use of M classes for the visual requirements of motor vehicle drivers on roads, across the entire spectrum of permissible vehicle speeds (motor vehicle drivers, public transport routes, medium and high traffic speeds). Luminance-related parameters are used to define the level boundaries in classes M (M1 to M6).
Lighting classes C are defined, in standards [5,6,7,8,9], as those intended for use in conflict areas on transportation routes where the traffic composition is predominantly motorized. Conflict areas occur wherever vehicle flows intersect or enter areas frequented by pedestrians, cyclists, or other road users. Areas exhibiting changes in road geometry, such as a reduced number of lanes or reduced lane or carriageway width, are also considered conflict areas. The risk of collisions between vehicles, between vehicles and pedestrians, between cyclists and other road users, and/or between vehicles and fixed objects is increased in such areas. For conflict areas, luminance is the recommended design criterion. However, when viewing distances are short and other factors prevent the use of luminance criteria, illuminance may be applied to part of the conflict area or to the entire area if luminance criteria cannot be applied to the entire area. A similar definition is given in [26]. Illuminance parameters are used to determine the level limits for class C.
In addition to the data necessary to select the lighting class resulting from the standards [5,6,7,8,9], street lighting designers and auditors should have information on:
  • road users (drivers of vehicles, including bicycles, personal transport devices, electric scooters, pedestrians, including people with special needs and people using mobility aids),
  • design speeds and permissible speeds,
  • road traffic volume,
  • existing lighting classes and luminaires used,
  • plans for road expansion or change of function,
  • development of the road’s vicinity,
  • local development plan for the road’s surroundings,
  • road traffic forecast over the life cycle of the lighting installation,
  • the need to cover the road area with video surveillance,
  • investor requirements.
Therefore, the appropriate lighting class should be selected according to the road’s function, design speed, general layout, traffic volume, traffic composition, and environmental conditions.

3. Luminance Criterion or Illuminance Criterion

Lighting classes defined by the letters M or C specify lighting parameters and their levels for different types of road users or road sections, along with their visual requirements, movement dynamics, potential conflicts between them, and the space they move in. According to standards [5,6,7,8,9], road lighting in class M requires the luminance criterion, while class C requires the illuminance criterion.
The use of luminance or illuminance criteria in design, modernization, and verification of obtained photometric parameters is directly related to the definitions of these physical quantities.
Luminance can be described as the intensity of light perceived by a person viewing an illuminated surface, and is a directional quantity. At a point (field element) on a dry surface, its value (e.g., produced by a single luminaire) is proportional to the illuminance value at that point. However, the proportionality coefficient varies depending on the circumstances and depends on several factors:
  • the reflective properties of the road surface (all road surfaces reflect light in a practically directional manner),
  • the luminance and size of the light source in the luminaire,
  • the position of the field element under consideration on the road in relation to the luminaire and the observer’s position.
Figure 1 shows a schematic top view of a section of a two-lane roadway. Measurement points are arranged according to the luminance measurement grid recommended in the standard [7].
Circles with numbers (1–5) indicate luminance measurement areas on the road. According to the standard [7], measurements are made in a grid formed by the intersections of longitudinal lines (along the traffic path) and transverse lines (across the lane width). The number of areas depends on the road class and the length of the measurement section, but typically includes:
  • 5 areas transversely (roadway width),
  • 10 areas longitudinally (every 3 m with a 30 m measurement section).
Rows 1, 2, and 3 represent successive transverse rows of measurement areas (lines perpendicular to the road centerline) where road surface luminance is measured, and the “Luminance” arrow indicates the photometer’s viewing direction; namely, in the vehicle’s direction of travel. As the luminance measurement reflects the driver’s viewing conditions, it should be measured from a specific angle and height (typically 1.5 m above the road centerline).
Figure 2 shows a grid of luminance measurement points on the road in perspective view, in accordance with the requirements of the standard [7]. The measurement space is set in a Cartesian coordinate system (x,y), where the x-axis represents the road width (lateral direction) and the y-axis represents the road length (direction of travel/observation).
Points L 1 L 9 indicate subsequent locations of luminance measurement.
Under wet (damp) road conditions, additional complications arise. The required luminance value results directly from the reference to the risk of a road accident. It is expressed by the average luminance L A v g of a road section 60 m from the observer and encompassing one lamppost interval (module). In practice, the luminance technique is not useful when the road surface is undulating, patched, uneven, and its reflectance varies across the road surface; or if the observation distance is low (less than 60 m).
Illuminance E A v g is also a quantity characterizing reflected light, but is used when:
  • the observer’s position cannot be unambiguously determined,
  • the measurement section cannot be unambiguously determined,
  • the reflective properties of the surface are variable.
Illumination technology has been used successfully for many years. It is much easier to calculate and measure illuminance values. The “sense” of this technique is to generate appropriate, uniform levels of illuminance on the road, while waiting for the luminance to reach the desired level of illumination.
Figure 3 below shows a schematic plan view of the illuminance E measurement system on the road surface. This is a simplified technical diagram illustrating the arrangement of measurement points in a measurement grid in accordance with the [8] standard used when assessing road lighting levels.
Illuminance is measured horizontally on the road surface. A regular grid of points is most often used: 3 points across the lane and 10 points longitudinally along the measurement section (usually every 3 m over a 30 m section). This is shown in Figure 4.
Illuminance E is measured at each grid point. The following are calculated:
  • average intensity E A v g ,
  • minimum intensity E m i n ,
  • illumination uniformity U 0 = E m i n / E A v g .
The comparability of lighting requirements, which is the basis for the interchangeability of lighting classes, is approximate. In particular, the degree of approximation will vary depending on the type of surface and the photometric shapes of the luminaires used. An approximate transition from illuminance values to luminance values can be made based on the luminance index value, which is the ratio of the average illuminance value to the average luminance value. Such values are provided separately for light and dark surfaces, also depending on the luminaire’s distribution type.
The luminance level of the road surface is the primary criterion used in road lighting (class M roads). Illuminance is an additional criterion used in road lighting (class C roads).
The recommended design criterion for all road surfaces, including conflict areas, is the luminance parameter (class M). If the luminance criterion cannot be used, the illuminance criterion (class C) is acceptable. The relationship between luminance and average horizontal illuminance depends on the brightness of the road surface, represented by the diffuse luminance coefficient value Q 0 of that surface. Table 1 provides comparable classes M and C for different values of Q 0 for road surfaces.
As C lighting classes are intended for the same users as M lighting classes, the data in Table 1 should be primarily used to determine the C lighting class to be used in a given conflict area. The conversion of luminance to illuminance is not straightforward, as luminance describes the brightness of a light-emitting surface, while illuminance describes the amount of light incident on a given surface. To convert luminance to illuminance, additional information about the surface’s reflectance coefficient or the diffuse luminance coefficient is required.
Q 0 = L E
where
  • Q 0 —luminance coefficient in scattered light [ cd/m 2 · lx];
  • L—field luminance in scattered light [ cd/m 2 ];
  • E—field plane illumination [lx].
This formula assumes that light is scattered uniformly (the cosine law), which is a good approximation for most surfaces. In reality, depending on the angle of incidence of light and the surface properties, applying the formula may only yield an approximate result.

4. Analysis of the Existing Lighting Installation and the Lighting Modernization Project

This article presents the results of an inventory of road lighting infrastructure, the results of LED luminaire selection obtained during the design process, and an analysis of electricity consumption and CO2 emissions of the existing installation and the planned installation. Energy efficiency designs were developed and energy efficiency indicators [9] were determined, depending on active power consumption and reactive power flows. The feasibility of modernization was analyzed based on the actual location.
Comprehensive results of audit measurements for a selected local government unit have been presented in the paper [29]. Within the local government unit, a relatively straight road section was selected as a representative example, serving both as a transit road and a road with local traffic. It is home to shops, offices, a school, production plants, and a cemetery, indicating the potential for heavy pedestrian traffic along the road.
Figure 5 shows that, in the analyzed area, most installations are network lighting points associated with industrial transmission lines. This type of installation utilizes existing transmission poles, on which booms and luminaires are mounted. Although this solution allowed for financial savings during the construction of the lighting installation by utilizing existing poles, the lighting used often did not meet the requirements of the standards [5,6,7,8,9].
After a detailed site visit and documentation analysis, the authors decided to use LED sources with the parameters shown in Table 2 for further experimental analysis. For comparison, parameters of operating sodium sources were also included.
The overall condition of the analyzed lighting installation should be assessed as not differing from the average in other locations across the country. The assessment of the installation’s condition took into account its age, the type of light sources, the construction of the lighting fixtures, and the general degree of wear and tear, as assessed by appearance, such as the degree of contamination of the lighting fixtures. Based on the on-site inspection, it was determined that 10 lighting fixtures were installed on a straight section of the road. The power of the sources installed in the lighting fixtures was 100 W. Each pole has a 1.0 m long boom with a 0° inclination angle. The poles are located 5 m from the edge of the road and, in several cases, are located within a cemetery. The pole spacing varies, ranging from approximately 30 m to 81 m, as presented in Table 3.
As can be seen from Figure 6, in almost every case the distances between the columns in variant M(1:1) significantly exceed the design value of 30 m. The green column indicates the distance within the ±10% tolerance, while the red columns exceed this limit.
The road is straight with an asphalt surface and a variable width ranging from 7.2 m to 10.3 m. The road surface condition was assessed as good. The installed 100 W lighting fixtures consume 120 W of power. Based on this, the power requirement for road lighting was determined to be 1200 W. According to [30], the annual operating time of the lighting fixtures was assumed to be 4150 h. Table 4 presents the total power requirement and annual costs.
In addition to electricity consumption, it is necessary to analyze the CO2 emissions generated by a given lighting installation. To estimate the CO2 emissions, the study [32] was used. The CO2 emission factor for end-use electricity is 597 kg/MWh. Table 5 was developed based on the resulting estimates, which presents the expected annual CO2 emissions into the atmosphere.
Based on an analysis of the road and its surroundings, parameters were selected and used to choose the lighting class in accordance with the standards [5,6,7,8,9]. Speed was determined based on road signs and regulations, and traffic volume was estimated based on observations of road users over several hours at two different times of the day. Other parameters were determined based on a site visit, and navigation difficulty was determined as a subjective experience while driving the road at two different times of the day. It is worth noting that the current lighting fixtures operate at full power throughout the entire operating time, which is rare for lighting installations built at least a dozen years ago.
As the use of class M in the calculations for the analyzed road section may raise doubts, the calculations were also conducted taking into account the requirements for class C.
Designs and calculations were performed for the replacement of existing poles and electrical installations (options M(1:1) and C(1:1)), as well as for a complete modernization—a newly designed pole spacing with a new electrical installation (options M(N) and C(N)). Calculations were also performed for the use of sodium lamps in both the existing and modernized installations. Table 5 below summarizes the nominal parameters of the luminaires included in the analyses.
All simulations were conducted according to the following procedure:
  • Standard assumptions were adopted according to PN-EN 13201 [5] (classes M4 and C4).
  • Design spacing (30 m ± 10%).
  • Assessment criteria (average luminance/illuminance, uniformity, glare).
  • Tools used for calculations (Dialux with actual IES files from manufacturers).
  • Taking into account site conditions.

5. Analysis of the Lighting Installation Parameters When Adopting Class M

Using the provisions of the standards [5,6,7,8,9], class M parameters were selected based on parameters such as permissible vehicle speed, user traffic, road users, road dividers, parked vehicles, ambient lighting, and navigation difficulty. When adding the weights of the individual parameters, a score of 2 was obtained and, using the formula provided in the standard, the lighting class was determined as M4.
Taking advantage of the significantly lower traffic volume observed during night-time hours, after analyzing the number of cars on the road and other road parameters, it was possible to reduce the power of the luminaires by one lighting class between 11 p.m. and 5 a.m. The exact potential for power savings could then be estimated after appropriate calculations were performed; in particular, for each of the two modernization variants.

5.1. Variant M(1:1)—Luminance Criterion

First, a photometric design was prepared for the lighting installation, using the same pole configuration currently in use on the audit date. It was assumed that the entire section must meet the requirements of the standards [5,6,7,8,9]. Simulations using luminaires with sodium sources yielded results below the requirements for class M4, which was determined to be appropriate for the location in question. Selecting luminance luminaires with LED sources resulted in luminance results compliant with class M4 requirements using a luminaire with a total power of 103 W. Unfortunately, uniformity parameters consistent with the specified class were not achieved. The results are presented in Table 6 and Table 7.
Table 6 presents a summary of the demand for active power with road lighting variant M(1:1).
Based on the above results, it can be clearly stated that replacing the luminaires in the M(1:1) variant will result in an increase in luminance value to that required by class M4; however, the uniformity will remain significantly below the requirements [5,6,7,8,9]. This solution is incorrect, and the total power of the luminaire of 103 W compared to the total power of the sodium luminaire of 120 W only yields savings of around 11%.
In accordance with the recommendations of the standards [5,6,7,8,9], the annual electricity savings were calculated using the formula:
Δ Q 0 = T U ( M 0 M 1 ) 1000
where
  • Δ Q 0 —energy saved per year [kWh/year];
  • T U —time of use per year [h/year];
  • M 0 —total power of installed luminaires before modernization [W];
  • M 1 —total power after modernization [W].
Table 8 presents the annual savings in electricity costs and Table 9 shows the potential reduction in CO2 emissions after implementing the investment in variant M(1:1).

5.2. Variant M(N)—Luminance Criterion

Option M(N) requires a completely new design. In addition to selecting LED lighting fixtures, a new pole spacing was also planned. This solution eliminated the use of existing poles associated with the power line, and the number of lighting fixtures was increased to 15. In the new design, the fixtures were located every 20 m to 35 m and offset from the road edge by 2.3 m to 3.5 m. Table 10 indicates the exact distances achieved in the design.
Figure 7 presents a simplified design analysis of the arrangement of the designed columns.
Average spacing: 29.59 m
Design value: 30 m
Accepted tolerance: ±10% (27.0–33.0 m)
Interpretation:
  • Green bars in the chart indicate pole distances within the accepted tolerance.
  • Red bars indicate distances outside the ±10% tolerance range.
  • Dashed lines represent the limits of tolerance (27.0 m and 33.0 m).
  • The blue line indicates the design target spacing (30 m).
Table 11 presents a summary of the power demand for the entire street after redesigning the installation from scratch and using 15 LED lighting fixtures.
Table 12 presents the parameter results obtained as a result of simulation (data for an installation using luminaires with LED sources with a power of 72 W and, in a hypothetical variant, if traditional lighting fixtures with sodium sources were installed in the same luminaire locations). Only in the variant with LED luminaires were the requirements for class M4 met.
Based on Formula (2), it was calculated that the annual electricity savings would be 498 kWh. Table 13 presents the electricity costs for the new project in comparison to the initial version. Table 13 presents the annual electricity cost savings, and Table 14 presents the potential reduction in CO2 emissions after implementing the investment in variant M(N).
It is worth considering infrastructure control to reduce lighting requirements by one class between 11 p.m. and 5 a.m., due to the significant decrease in traffic volume. This approach is consistent with the lighting class selection. In the calculations for class M4, the power of a single luminaire after power reduction is 50 W, which translates to a 22 W reduction per luminaire. The assumption is that power will be reduced between 11 p.m. and 5 a.m., which translates to six hours of reduced lighting per day (or 2190 h per year).
Table 15 shows the additional savings that can be achieved by applying additional power reduction.
Table 16 provides data on the additional CO2 emission reduction in the event of additional power reduction.

6. Analysis of the Lighting Installation Parameters When Adopting Class C

According to the provisions of standard [9], class C4 was also selected as an alternative. Similar to the procedure for class M, a procedure for selecting the values of individual parameters was followed. Similarly to the previous variant, a photometric design of the installation was performed for class M in its original configuration, analyzing the positions of the luminaires as they were physically installed on the day of the audit. It was assumed that the entire section must meet the requirements of the standards [5,6,7,8,9]; this simplification was considered due to the repeatability of the situation.
Taking advantage of the significantly lower observed traffic volume during night-time hours, after analyzing the number of cars traveling on the road and other parameters used in selecting the road class, it was possible to reduce the power of luminaires by one lighting class between 11 p.m. and 5 a.m. The exact potential for power savings was then estimated after appropriate calculations.

6.1. Variant C(1:1)—Illuminance Criterion

The simulation yielded results below class C4, which was determined to be appropriate for the location in question. In the version using LED luminaires, the intensity result was consistent with class C4 using a luminaire with a total power of 100 W; however, uniformity parameters consistent with the specified class could not be achieved. All results are presented in Table 17 and Table 18.
Table 17 presents a summary of the demand for active power with road lighting variant C(1:1).
Based on the above results, it can be clearly stated that replacing the luminaires in variant C(1:1) will result in an increase in intensity to class C4, but uniformity will remain significantly below the requirements of the standard [9]. This solution is not recommended, even if the U 0 parameter requirements were met, as the total power of the luminaire (of 100 W) compared to the total power of the sodium luminaire (of 120 W) only provides savings of about 20%.
Based on Formula (2), it was calculated that the annual electricity savings would amount to 830 kWh. Table 19 presents the electrical power of the installation before and after its modernization and the annual electricity savings, while Table 20 details the potential reduction in CO2 emissions after the implementation of the investment in variant C(1:1).

6.2. Variant C(N)—Illuminance Criterion

Option C(N) requires a completely new design. In addition to selecting LED lighting fixtures, a new pole spacing was also planned. This solution eliminates the use of existing poles associated with the power line. This design increased the number of lighting fixtures to 13, with their exact spacing detailed in Table 21.
Figure 8 presents a simplified design analysis regarding the arrangement of the designed poles.
As can be seen from Figure 8, most values were within ±10% of the design value (i.e., 31.5–38.5 m), as marked in green. The average value was very close to the adopted design value.
Table 22 presents a summary of the power demand for the entire street after redesigning the installation from scratch and using 13 LED lighting fixtures.
Table 23 summarizes the results obtained for the new lighting installation using 51 W LED luminaires and a hypothetical scenario where sodium luminaires were installed in the same locations. Both scenarios met the requirements of the C4 class standard.
Based on Formula (2), it was calculated that the annual electricity savings would amount to 2228.55 kWh. Table 24 presents the electricity costs for the new project and compares them to the initial version, while Table 25 details the potential reduction in CO2 emissions after implementing the investment in variant C(N).
It is worth considering infrastructure control to reduce the lighting requirements by one class between 11 p.m. and 5 a.m., due to the significant reduction in traffic volume. This approach is consistent with the lighting class selection. In the calculations for class C4, the power of a single luminaire after power reduction is 40 W, which translates to an 11 W reduction per luminaire. The assumption is that power is reduced between 11 p.m. and 5 a.m., which translates to six hours of reduced lighting per day (or 2190 h per year).
Table 26 shows the additional savings that can be achieved by applying the proposed power reduction.
The table below (Table 27) provides data on the additional reduction in CO2 emissions in the event of additional power reduction.

7. Calculations of Energy Indicators for the Considered Lighting Modernization Variants

To determine the conditions for connecting a lighting installation to the power grid, the maximum electricity demand was calculated at the electrical design stage, taking into account the full power for 100% simultaneous control of all lighting fixtures and the power consumption of other installation components, such as control and monitoring devices. The consumption with the full power of the installation and the designed reduction levels for lighting class levels were calculated, including the values of the following parameters: active power, reactive power, cos ϕ , and tg ϕ . Electricity consumption was considered to be distributed in accordance with the relevant regulations [30].
Road lighting should be designed to achieve the highest possible energy efficiency with minimal environmental impact. The following should be specified for the lighting installation:
  • Total active power of the system—P [W],
  • Power Density Index (PDI)— D P [W/lx· m 2 ],
  • Annual Energy Consumption Index (AECI)— D E P [ Wh/m 2 ].
The following input parameters were used to calculate the energy indicator values:
  • Lighting system power P [W]—the power of all components related to the illuminated surface (individual areas) and necessary for the operation of the lighting system. The calculations take into account the power P of lighting fixtures, ballasts, lighting control devices, and so on.
  • Illuminated surface area [ m 2 ]—this can be an elementary area identical to the calculation area or the entire length of the lighting system. The indicators apply to all areas with regular or irregular shapes, such as intersections, including roundabouts, squares, parks, pedestrian zones, and so on.
  • The average illuminance value in the analyzed area, E A v g [lx], is assumed as the average horizontal illuminance for class C; meanwhile, for class M, a constant value of illuminance in a given area is assumed, which is calculated based on the luminance value in accordance with Table 7.4.2 of the standard [9] at the same calculation points where the luminance value was determined. The indicators D P and D E P are applied to all road traffic areas covered by lighting.
The index D P for a given section illuminated by road lighting, divided into sub-areas, under a given operating condition can be calculated using the formula:
D P = P i E A v g , i A i
where
  • P i —power measured on section i [W];
  • E A v g , i —average illuminance of the measured section i [lx];
  • A i —surface of the measured section i [ m 2 ].
The power P in area i is calculated based on the individual power ratings of the lighting fixtures installed in the analyzed area, taking into account the power required for control equipment and other electrical devices necessary for the proper operation of the lighting installation. The power P should be calculated for the entire installation according to the following formula:
P = k = 1 n P k + P a d
where
  • P—total power of the lighting installation [ W ] ;
  • P k —power of the k-th lighting point [ W ] ;
  • P a d —total power of devices not included in P k but necessary for the operation of the road installation [ W ] ;
  • n—number of light points related to the installation or section being assessed.
The total power of the lighting installation P must be calculated as the full power of 100% luminaire control. The index  D P should be calculated for 100% of the installation’s power P and for intermediate states related to the assumed levels of power reduction. However, it should be noted that individual sections of the same road may have different power regulation levels. The shape of the area used to calculate the index D P should be identical to that used in the lighting design to calculate lighting parameters, in accordance with the standards [5,6,7,8,9].
The index D P should always be presented and used in conjunction with the the index D E P to assess the energy efficiency of a given lighting system. To compare and monitor the energy performance of a lighting installation, the energy consumption factor takes into account the annual cumulative energy consumption of the lighting illuminating the road. The index D E P is calculated using the following formula:
D E P = P j t j A
Based on the collected and processed data, the energy efficiency indicators D P and D E P were determined for variants M(1:1), M(N), C(1:1), and C(N), which are presented in Table 28.
In the table, the ( + ) sign indicates compliance with the normative recommendations for typical values in accordance with [9], while the ( ) sign indicates non-compliance with the normative recommendations for typical values in accordance with [9].
Based on the nominal data of LED luminaires, energy efficiency indicators resulting from reactive power flows D Q and D E Q were determined for variants M(1:1), M(N), C(1:1), and C(N). These indicators have been proposed by the academic community [33] in an effort to more accurately estimate reactive power and energy flows.
The reactive power density index D Q is calculated as follows:
D Q = Q i E A v g , i A i
where
  • Q i —reactive power measured on the section i [var];
  • E A v g , i —average illuminance of the measured section i [lx];
  • A i —surface of the measured section i [ m 2 ].
The annual reactive energy consumption indicator D E Q is calculated using the formula
D E Q = Q j t j A
The calculated indicators are presented in Table 29.

8. Conclusions from the Calculations and Discussion

This article presented designs for road lighting classes M and C, which are designed for various road lighting situations. The results were analyzed to determine the potential energy savings. Figure 9 and Figure 10 below present the projected electricity consumption for the analyzed variants.
Comparing Figure 9 and Figure 10, it is clearly visible that the variants with power reduction from 11 p.m. to 5 a.m. based on the illuminance criterion (variant C(N-R)) resulted in lower projected energy consumption (approximately 25%) than those based on the luminance criterion. According to the simulations and calculations, fewer poles were used for the C(N) variant than for the M(N) variant. However, for road safety reasons, the authors recommend the luminance criterion for such road sections.
Figure 11 presents the determined active and reactive power density indices, while Figure 12 presents the annual active and reactive energy consumption indices for the variants considered in this article: M(1:1), M(N), C(1:1), and C(N).
Analyzing the indicator values obtained through calculation, it can be noted that the optimal solution turned out to be the variants with a designed new power and lighting installation.
The results of the analysis, as illustrated in Figure 13, clearly show the advantages of modernization variants with newly designed installations. In particular, the C(N) option provided the highest benefits, with annual financial savings exceeding 2600 PLN and a reduction in CO2 emissions of more than 1300 kg compared to the baseline installation. Other variants, such as M(1:1) or M(N), offer only limited improvements in terms of both costs and environmental effects. This means that a comprehensive redesign of the lighting system, rather than a one-to-one replacement of fixtures, will ensure the most significant long-term benefits. The results highlight that modernization not only improves photometric performance and road safety, but also guarantees measurable financial savings and a substantial reduction in environmental impacts.
This study was based on a single case study of a rural road segment, where photometric measurements, Dialux simulations, and energy analyses were carried out. Therefore, the results should be interpreted as illustrative of the methodology, rather than as universally generalizable findings.
Recent international studies have confirmed the relevance of combining energy audits with visual safety condition considerations. Pasolini et al. [34] assessed context-adaptive street lighting, highlighting efficiency gains and compliance with photometric requirements. Velásquez et al. [35] presented national-scale evaluations of public lighting modernization projects, confirming substantial energy savings and CO2 reductions. Carrese et al. [36] investigated LED-illuminated crosswalks, showing measurable impacts on driver speed and pedestrian visibility, thus linking photometric improvements with safety outcomes. These works indicate that case-study-based audits, such as the present one, form part of an internationally recognized research stream. Our contribution extends this line of research by including reactive power indicators ( D Q , D E Q ) alongside standard photometric and energy metrics, which are rarely addressed in street lighting audits.

9. Limitations

The analysis focuses on photometric and energy performance indicators ( D P , D E P , D Q , D E Q ), in compliance with PN-EN 13201. While improved luminance and uniformity are widely recognized as proxies for visual safety conditions, the present study did not include a before/after crash analysis or statistical evaluation of accident data. Such analyses require extensive datasets and are beyond the scope of this technical audit. Future research could combine audits with long-term road safety studies to establish direct correlations between lighting modernization and accident reduction.

10. Final Conclusions

Based on the selection of lighting classes, the determination of photometric parameters, calculations of active power demand, CO2 emissions, and an assessment of energy efficiency indicators ( D P , D Q , D E P ), the following conclusions can be drawn:
  • The choice of road lighting class should always be based on relevant standards [5,6,7,8,9], but must also take into account local conditions to ensure adequate road safety.
  • A simple one-to-one replacement of sodium luminaires with LED fixtures—as in variants M(1:1) and C(1:1)—does not provide satisfactory results. Although it improves certain parameters, the savings and performance gains remain limited and, in some cases, the overall power demand may increase.
  • A detailed analysis of the energy and photometric performance showed that modernization projects designed from scratch—as in variants M(N) and C(N)—deliver the most favorable outcomes. They ensure the lowest projected energy consumption, the greatest reduction in CO2 emissions, and compliance with photometric requirements.
  • Among these, variant C(N) achieved particularly strong results, combining significant energy savings with full compliance to the illuminance criterion; however, for safety reasons, the luminance-based approach (M(N)) remains preferable for some road sections.
  • The determined energy efficiency indicators confirmed that newly designed systems reach values comparable to reference benchmarks from the standard [9], which validates their long-term effectiveness.
  • Additional savings and environmental benefits can be obtained by applying autonomous night-time power reduction, which is increasingly available as a standard feature in modern LED luminaires. In the case of lighting modernization, the authors recommend the use of modern smart lighting systems based on motion sensors and wireless communication as the target direction.
  • Finally, attention should be paid to reactive power flows, as negative values of D Q and D E Q may generate additional—and often unexpected—costs after modernization.

Author Contributions

Conceptualization, M.K., T.P. and H.W.; methodology, M.K., T.P. and H.W.; validation, M.K., T.P. and H.W.; investigation, M.K., T.P. and H.W.; analysis, M.K. and D.W.; data curation, M.K. and D.W.; writing—original draft preparation, M.K.; writing—review and editing, M.K. and T.P.; theoretical modeling, M.K. and T.P.; software, M.K., T.P. and H.W.; resources, D.W.; visualization, M.K., T.P. and H.W.; supervision, M.K. and T.P.; project administration, T.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Additional supporting materials, including preliminary datasets from the unpublished Master’s thesis of D. Węclewski (2025), which served as background for this research, are available upon request from the corresponding author. All results and analyses in the manuscript were verified, reprocessed, and extended by the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Luminance measurement points on a road according to normative requirements in Poland. Source: author’s own study.
Figure 1. Luminance measurement points on a road according to normative requirements in Poland. Source: author’s own study.
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Figure 2. Luminance measurement points. Source: author’s own study.
Figure 2. Luminance measurement points. Source: author’s own study.
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Figure 3. Measurement points of illuminance. Source: author’s own study.
Figure 3. Measurement points of illuminance. Source: author’s own study.
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Figure 4. Measuring grid of illuminance on the road with coordinate markings (x, y). Longitudinal axis of the road—y, transverse axis—x. Source: author’s own study.
Figure 4. Measuring grid of illuminance on the road with coordinate markings (x, y). Longitudinal axis of the road—y, transverse axis—x. Source: author’s own study.
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Figure 5. Analyzed road section. 1—industrial zone, 2—gas station, 3—cemetery, 4—office/school, 5—food zone, “black circles”—operating sodium light fixtures. Source: author’s own study.
Figure 5. Analyzed road section. 1—industrial zone, 2—gas station, 3—cemetery, 4—office/school, 5—food zone, “black circles”—operating sodium light fixtures. Source: author’s own study.
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Figure 6. Spacing between lighting poles in variant M(1:1). Source: author’s own study.
Figure 6. Spacing between lighting poles in variant M(1:1). Source: author’s own study.
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Figure 7. Spacing between lighting poles under variant M(N). Source: author’s own study.
Figure 7. Spacing between lighting poles under variant M(N). Source: author’s own study.
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Figure 8. Spacing between lighting poles in variant C(N). Source: author’s own study.
Figure 8. Spacing between lighting poles in variant C(N). Source: author’s own study.
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Figure 9. Estimated electricity consumption for the lighting installations: original state, variant M(1:1), variant M(N), and variant M(N-R) with power reduction. Source: author’s own study.
Figure 9. Estimated electricity consumption for the lighting installations: original state, variant M(1:1), variant M(N), and variant M(N-R) with power reduction. Source: author’s own study.
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Figure 10. Estimated electricity consumption for the lighting installations: original state, variant C(1:1), variant C(N), and variant C(N-R) with power reduction. Source: author’s own study.
Figure 10. Estimated electricity consumption for the lighting installations: original state, variant C(1:1), variant C(N), and variant C(N-R) with power reduction. Source: author’s own study.
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Figure 11. Determined active and reactive power density indicators: Variant C(1:1), variant C(N), variant M(1:1), and variant M(N). Source: author’s own study.
Figure 11. Determined active and reactive power density indicators: Variant C(1:1), variant C(N), variant M(1:1), and variant M(N). Source: author’s own study.
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Figure 12. Determined indicators of annual active and reactive energy consumption: Variant C(1:1), variant C(N), variant M(1:1), and variant M(N). Source: author’s own study.
Figure 12. Determined indicators of annual active and reactive energy consumption: Variant C(1:1), variant C(N), variant M(1:1), and variant M(N). Source: author’s own study.
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Figure 13. Annual financial savings and CO2 emissions for the analyzed variants. Source: author’s own study.
Figure 13. Annual financial savings and CO2 emissions for the analyzed variants. Source: author’s own study.
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Table 1. Lighting classes M and C of comparable lighting levels for different values of Q 0 for road surfaces, according to [5].
Table 1. Lighting classes M and C of comparable lighting levels for different values of Q 0 for road surfaces, according to [5].
Lighting Class M M1M2M3M4M5M6
Lighting Class C
If: Q 0 0.05  [ cd/m 2 · lx] C0C1C2C3C4C5
If: 0.05 < Q 0 0.08  [ cd/m 2 · lx] C0C1C2C3C4C5C5
If: Q 0 > 0.09  [ cd/m 2 · lx] C0C1C2C3C4C5C5C5
Table 2. Electrical and photometric parameters of the tested lighting lamps.
Table 2. Electrical and photometric parameters of the tested lighting lamps.
Technology
Source LED LED LED Soda
PowerP[W]10310072120
Luminaire flux Φ [lm]16,14012,44711,4798526
Luminous efficiency λ [lm/W]15712415971
ColorCCT[K]4000400040002000
Color renderingRa[-]70.072.071.530.0
Power factorcos ϕ (100% load)[-]0.950.950.950.85
Table 3. Exact location of the poles of the modernized lighting installation.
Table 3. Exact location of the poles of the modernized lighting installation.
Pole NumbersPole Spacing [m]
n1–n252.3
n2–n330.0
n3–n437.6
n4–n540.7
n5–n634.2
n6–n737.1
n7–n841.3
n8–n981.3
n9–n1060.1
Table 4. Summary of total power and costs.
Table 4. Summary of total power and costs.
The power of the source P j [W]100
Number of lighting fixturesn[pcs.]10
Total power Σ P j [W]1200
Price for electricityC[zł/kWh]1.199 *
Number of hours per yeart[h]4150
Annual costsN[zł]5971.02
* Source: [31].
Table 5. Estimated CO2 emissions related to electricity consumption.
Table 5. Estimated CO2 emissions related to electricity consumption.
ParameterUnitValue
Energy consumption[kWh]4980.0
CO2 emission index[kg/kWh]0.597
Reduction of CO2 emissions[kg]2973.06
Table 6. Power requirement for a set of lighting fixtures with variant M(1:1).
Table 6. Power requirement for a set of lighting fixtures with variant M(1:1).
ParameterUnitValue
Number of lighting fixtures (n)[pcs.]10
Power of one fixture ( P j )[W]103
Total power ( P 10 = n · P j )[W]1030
Table 7. Summary of measurement results with variant M(1:1).
Table 7. Summary of measurement results with variant M(1:1).
Type of LightingClass L ¯ [cd/m2] U 0 [-]
High-pressure sodium lamps 0.300.01
LED 0.770.01
RequirementsClass M40.750.40
L ¯ [ cd/m 2 ]—average luminance value; U 0 [-]—general uniformity.
Table 8. Potential annual savings with variant M(1:1).
Table 8. Potential annual savings with variant M(1:1).
ParameterUnitValue
Total power before modernization[W]1200.0
Power after modernization[W]1030.0
Number of hours per year[h]4150.0
Price for electricity[zł/kWh]1.199 *
Annual savings[zł]845.89
* Source: [31].
Table 9. Impact of power reduction on CO2 emissions with variant M(1:1).
Table 9. Impact of power reduction on CO2 emissions with variant M(1:1).
ParameterUnitValue
Power reduction[W]170.0
CO2 emission index[kg/kWh]0.597
Reduction in CO2 emissions[kg]421.18
Table 10. Analysis of spacing between lighting poles with variant M(N).
Table 10. Analysis of spacing between lighting poles with variant M(N).
Pole NumbersPole Spacing [m]
n1–n220.0
n2–n329.4
n3–n427.4
n4–n532.8
n5–n636.0
n6–n732.7
n7–n828.9
n8–n933.8
n9–n1030.0
n10–n1127.0
n11–n1230.2
n12–n1329.6
n13–n1431.9
n14–n15 24.5
Table 11. Power requirement for a set of lighting fixtures with variant M(N).
Table 11. Power requirement for a set of lighting fixtures with variant M(N).
ParameterUnitValue
Number of lighting fixtures (n)[pcs.]15
Power of one fixture ( P j )[W]72
Total power ( P 10 = n · P j )[W]1080
Table 12. Summary of measurement results with variant M(N).
Table 12. Summary of measurement results with variant M(N).
Type of LightingClass L ¯ [cd/m2] U 0 [-]
High-pressure sodium lamps 0.710.15
LED 0.840.43
RequirementsClass M40.750.40
L ¯ [ cd/m 2 ]—average luminance value; U 0 [-]—general uniformity.
Table 13. Potential annual savings with variant M(N).
Table 13. Potential annual savings with variant M(N).
ParameterUnitValue
Total power before modernization[W]1200.0
Power after modernization[W]1080.0
Number of hours per year[h]4150.0
Price for electricity[zł/kWh]1.199 *
Annual savings[zł]597.10
* Source: [31].
Table 14. Impact of power reduction on CO2 emissions with variant M(N).
Table 14. Impact of power reduction on CO2 emissions with variant M(N).
ParameterUnitValue
Power reduction[W]120.0
CO2 emission index[kg/kWh]0.597
Reduction in CO2 emissions[kg]297.31
Table 15. Financial savings resulting from the use of additional power reduction for the entire route with variant M(N).
Table 15. Financial savings resulting from the use of additional power reduction for the entire route with variant M(N).
ParameterUnitValue
Reduced power of a single luminaire[W]22
Number of hours per year[h]2190.0
Price for electricity[zł/kWh]1.199 *
Annual savings[zł]750.98
* Source: [31].
Table 16. Additional reduction in CO2 emissions as a result of the use of reduced luminaire power with the M(N) variant.
Table 16. Additional reduction in CO2 emissions as a result of the use of reduced luminaire power with the M(N) variant.
ParameterUnitValue
Power reduction[W]330
CO2 emission index[kg/kWh]0.597
Reduction in CO2 emissions[kg]431.45
Table 17. Power requirement for a set of lighting fixtures with variant C(1:1).
Table 17. Power requirement for a set of lighting fixtures with variant C(1:1).
ParameterUnitValue
Number of lighting fixtures (n)[pcs.]10
Power of one fixture ( P j )[W]100
Total power ( P 10 = n · P j )[W]1000
Table 18. Summary of measurement results with variant C(1:1).
Table 18. Summary of measurement results with variant C(1:1).
Type of LightingClass E ¯ [lx] U 0 [-]
High-pressure sodium lamps 5.00.014
LED 11.00.06
RequirementsClass C410.00.40
Table 19. Potential annual savings with variant C(1:1).
Table 19. Potential annual savings with variant C(1:1).
ParameterUnitValue
Total power before modernization[W]1200.0
Power after modernization[W]1000.0
Number of hours per year[h]4150.0
Price for electricity[zł/kWh]1.199 *
Annual savings[zł]995.17
* Source: [31].
Table 20. Impact of power reduction on CO2 emissions with variant C(1:1).
Table 20. Impact of power reduction on CO2 emissions with variant C(1:1).
ParameterUnitValue
Power reduction[W]200.0
CO2 emission index[kg/kWh]0.597
Reduction of CO2 emissions[kg]495.5
Table 21. Analysis of spacing between lighting poles with variant C(N).
Table 21. Analysis of spacing between lighting poles with variant C(N).
Pole NumbersPole Spacing [m]
n1–n236.9
n2–n335.7
n3–n437.1
n4–n519.6
n5–n622.9
n6–n735.5
n7–n835.7
n8–n934.8
n9–n1039.5
n10–n1142.1
n11–n1235.3
n12–n1337.4
Table 22. Power requirement for a set of lighting fixtures with variant C(N).
Table 22. Power requirement for a set of lighting fixtures with variant C(N).
ParameterUnitValue
Number of lighting fixtures (n)[pcs.]13
Power of one fixture ( P j )[W]51
Total power ( P 10 = n · P j )[W]663
Table 23. Summary of measurement results with variant C(N).
Table 23. Summary of measurement results with variant C(N).
Type of LightingClass E ¯ [lx] U 0 [-]
High-pressure sodium lamps 10.40.40
LED 10.20.40
RequirementsClass C410.00.40
Table 24. Potential annual savings with variant C(N).
Table 24. Potential annual savings with variant C(N).
ParameterUnitValue
Total power before modernization[W]1200.0
Power after modernization[W]663.0
Number of hours per year[h]4150.0
Price for electricity[zł/kWh]1.199 *
Annual savings[zł]2672.03
* Source: [31].
Table 25. Impact of power reduction on CO2 emissions with variant C(N).
Table 25. Impact of power reduction on CO2 emissions with variant C(N).
ParameterUnitValue
Power reduction[W]663.0
CO2 emission index[kg/kWh]0.597
Reduction in CO2 emissions[kg]1330.4
Table 26. Financial savings resulting from additional power reduction for the entire route with variant C(N).
Table 26. Financial savings resulting from additional power reduction for the entire route with variant C(N).
ParameterUnitValue
Reduced power of a single luminaire[W]11
Number of hours per year[h]2190.0
Price for electricity[zł/kWh]1.199 *
Annual savings[zł]375.5
* Source: [31].
Table 27. Additional reduction in CO2 emissions as a result of reduced luminaire power with variant C(N).
Table 27. Additional reduction in CO2 emissions as a result of reduced luminaire power with variant C(N).
ParameterUnitValue
Power reduction[W]143
CO2 emission index[kg/kWh]0.597
Reduction in CO2 emissions[kg]186.96
Table 28. Calculated energy efficiency indicators D P and D E P of the analyzed lighting installation. The calculations took into account the value of the analyzed area, A = 3735 m 2 .
Table 28. Calculated energy efficiency indicators D P and D E P of the analyzed lighting installation. The calculations took into account the value of the analyzed area, A = 3735 m 2 .
M(1:1)M(N)C(1:1)C(N)
Number of luminaires[-]10151013
P k [W]103010801000663
P a d [W]20.621.62013.3
E A v g [lx]18.5201110.2
t[h]4150415041504150
D P [mW/lx· m 2 ]15.20514.74724.82717.752
D P —typical values ( + ) ( + ) ( + ) ( + )
D E P [ kWh/m 2 ]1.1671.2241.1330.751
D E P —typical values ( ) ( ) ( ) ( + )
Table 29. Calculated energy efficiency indicators D Q and D E Q for the analyzed lighting installation. The calculations took into account the value of the analyzed area, A = 3735 m 2 .
Table 29. Calculated energy efficiency indicators D Q and D E Q for the analyzed lighting installation. The calculations took into account the value of the analyzed area, A = 3735 m 2 .
M(1:1)M(N)C(1:1)C(N)
Number of luminaires[-]10151013
c o s ϕ [-]0.930.930.930.93
t g ϕ [-]−0.4−0.4−0.4−0.4
Q k [var]−494.4−518.4−480−318.4
t[h]4150415041504150
D Q [mvar/lx· m 2 ]−6.082−5.899−9.931−7.101
D E Q [ kvarh/m 2 ]−0.467−0.49−0.453−0.301
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MDPI and ACS Style

Kurkowski, M.; Popławski, T.; Wachta, H.; Węclewski, D. Energy Audit of Road Lighting Installations as a Tool for Improving Efficiency and Visual Safety Conditions. Energies 2025, 18, 5357. https://doi.org/10.3390/en18205357

AMA Style

Kurkowski M, Popławski T, Wachta H, Węclewski D. Energy Audit of Road Lighting Installations as a Tool for Improving Efficiency and Visual Safety Conditions. Energies. 2025; 18(20):5357. https://doi.org/10.3390/en18205357

Chicago/Turabian Style

Kurkowski, Marek, Tomasz Popławski, Henryk Wachta, and Dominik Węclewski. 2025. "Energy Audit of Road Lighting Installations as a Tool for Improving Efficiency and Visual Safety Conditions" Energies 18, no. 20: 5357. https://doi.org/10.3390/en18205357

APA Style

Kurkowski, M., Popławski, T., Wachta, H., & Węclewski, D. (2025). Energy Audit of Road Lighting Installations as a Tool for Improving Efficiency and Visual Safety Conditions. Energies, 18(20), 5357. https://doi.org/10.3390/en18205357

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