How smart are our companies really? a case study of the current rollout of smart meters in Germany

1 Introduction

Germany is one of the nations in the European Union (EU) that has established 2032 as the deadline for the implementation of its national power metering policy. By 2030 at the latest, the remaining EU nations want to have implemented 80% of the deployment for power meters (European Commission, 2020). Thus, the majority of EU nations are still in the initial rollout process. This aim is too distant in the future, though, given how quickly the energy revolution and the digital transformation are developing.

The rollout of smart meters has stalled and should therefore be urgently investigated in terms of its acceptance and benefits. Although at present one out of every two companies has started with implementation, this means that half of all companies have not yet taken any action (PwC, 2022).

The study by (Berger et al., 2022) addresses the fact that companies are interested in implementation if they can achieve energy savings. The study addresses companies that consume more than 6,000 kWh per year.

The typical annual power usage of private households and many small businesses in the commercial, trade, and service sectors is frequently less than 6,000 kWh. This indicates that the two customer categories mentioned above are not covered by the mandated legal rollout of smart meters. These consumer organizations are free to install smart meters. In addition, there are uncertainties and information deficits regarding the technology and its advantages (Knayer and Kryvinska, 2022).

This is confirmed by, among other things, the numbers for smart electricity meter implementation in Germany. Of the 51 million metering points in Germany, just 0.26% are equipped with a smart meter (Bundesamt, 2022). An important aspect could be that stakeholders do not know what a smart meter or an intelligent meter is. The work of (Schneider, 2020) found that in a representative household survey, 68% of the population did not know the term “smart meter” or “intelligent metering systems”. The work of (Chawla et al., 2020) also highlighted this information gap among stakeholders.

It is common knowledge that only few studies have examined the standards for the acceptance of this technology in the workplace. Rather, almost all studies are in the household setting (Gumz and Fettermann, 2023), and most deal with technical (Depuru et al., 2011; Abu Arqub, 2018; Abu Arqub, 2020) and economic (Brophy Haney et al., 2009) aspects as well as the costs (Faruqui et al., 2010) of the technology.

An amendment to the Act on the Digitization of the Energy Transition was passed at the beginning of 2023. In it, the annual costs of smart meters for end customers are reduced, and an obligation for energy suppliers to offer the necessary dynamic tariffs is anchored. Unfortunately, the consumption limit of 6,000 kWh per year for a mandatory retrofit remains (BUNDESMINISTERIUM FÜR WIRTSCHAFT UND KLIMASCHUTZ, 2023).

The study by Umweltbundesamt (2021) looks at the possible effects of smart meter rollout in Germany. On average, the meters consume three times as much electricity as conventional meters and are subject to more frequent replacement cycles. A positive effect in terms of costs and environmental compatibility can be achieved only if households actively participate.

Thus, this paper introduces a discussion on whether the current deployment strategy should be reconsidered or whether the increase in acceptance and the associated additional benefits of the technology for all kind of users (Companies and Households) should be made more concrete.

The aim of this paper is to present the current implementation status of the technology in the context of a case study and to question why this status is the case. Additionally, this article emphasizes the results from (Knayer and Kryvinska, 2022) that the intended rollout is excluding significant customer groups. It also demonstrates the necessity for more investigation into how well and widely businesses are utilizing technology. Finally, these results are to be combined with data from (Knayer and Kryvinska, 2023). The frequencies of efficiency potentials of the cross-cutting technologies lighting, energy monitoring, energy purchasing and peak load management collected there can be compared with the companies with smart meters and with the companies without smart meters. This allows conclusions to be drawn at the technology level as to whether companies with a smart meter are more efficient in these cross-cutting technologies than companies with an analog meter.

Section 2 presents the methodology of the paper, which follows a case study and uses data from a funding project. It also describes the type of data collection, the data basis, and the evaluation methodology used. Section 3 presents the findings of the study and leads to the discussion in Section 4, where the results are critically evaluated. Section 5 summarizes the main findings of the study.

2 Methods

The research data used were collected as part of a funding project between 2016 and 2020 and were anonymized (Umwelttechnik BW GmbH, 2021). A total of 386 companies were surveyed. In total, extensive data on 12 different cross-cutting technologies were recorded and analyzed (Knayer and Kryvinska, 2023).

The data on metering technology were also recorded during on-site inspections with the help of an energy consultant. A distinction was made between analog and digital meters and smart meter technology. In terms of meter technology, simple and closed-ended questions were asked, and the answers were noted. Electricity consumption was checked against energy bills. The standardized questions about the available metering technology were discussed with the employee responsible for the energy topic.

The selection of participating companies was random, as companies interested in the project voluntarily and proactively approached the Chamber of Commerce and Industry (CCI). Due to this self-determined active participation of the companies, the procedure could be repeated at any time, and complete data collection could be carried out.

The data were compared again with the companies in 2022 in the form of a telephone interview (Adams, 2007). Thus, the validity of the information is current. The reconciliation aimed to clarify whether a change in the survey years had taken place. Changes were taken into account in the evaluation.

2.1 Description of the collected data

Table 1 shows the number and size of the participating companies. The metering technology of these companies is evaluated in the study.

TABLE 1

TABLE 1. Participating companies.

Company size is based on the definition of the EU Commission (Kommission and EMPFEHLUNG DER KOMMISSION vom 6, 2003). The participating companies are 180 manufacturing and 206 nonmanufacturing companies.

2.2 Questions about meter technology

Simple and closed-ended questions, which could be answered with “yes” or “no”, were asked. The following questions were included in the case study:

- Do you know what a smart meter is?

- Do you know the difference between a digital meter and an intelligent meter?

- Do you know the government’s rollout strategy regarding smart meters?

- Do you know the benefits of smart meters for businesses?

The questions were intentionally more general to obtain as clear a statement as possible. The respondents were all familiar with the energy topic and thus could at least be classified as knowledgeable.

2.3 Evaluation method

Figure 1 shows the procedure of the evaluation method, which is divided into four steps. In step I, the subject of the study, the 386 companies, is first examined in terms of its implementation status of the technology. The aim here is to show which technology (analog, digital, smart meter) has already been installed. Then, in step II, which companies have an obligation to implement the technology and which can retrofit voluntarily are examined. This examination is performed on the basis of energy bills. In step III, the questions are evaluated. Step IV. aims to compare the frequencies of efficiency potentials in the selected cross-cutting technologies of lighting, energy monitoring, energy purchasing, and peak load management of those companies with a smart meter and those companies without a smart meter.

FIGURE 1

FIGURE 1. Procedure of the evaluation method.

2.3.1 Status of the implementation of metering technology

The data on the metering technology are entered in an Excel matrix. A distinction is made between analog, digital and smart meter technology. The absolute and relative frequencies of the individual technologies are shown. This information indicates the implementation status in the sample companies.

2.3.2 Check for the obligation to implement

The check for a possible implementation obligation is carried out on the basis of electrical energy consumption. Companies with electricity consumption of more than 6,000 kWh per year have an obligation to implement smart meters in Germany. This consumption limit determines whether conversion to a smart meter is mandatory. Companies with an electricity consumption of less than 6,000 kWh per year can carry out a voluntary conversion.

Companies with electricity consumption of more than 100,000 kWh per year have already installed RLM (registered load profile measurement) meters in Germany but should also carry out a conversion. The reason is that it is precisely this customer group that could access the load profiles much more easily and transparently through the conversion and thus generate savings. Therefore, consumers with an electricity consumption greater than 100,000 kWh per year are also considered in the evaluation.

The distinction is made with the help of the current electricity bills.

2.3.3 Evaluation of the questions

Just as important as the actual state of implementation is the question of why. The answers to the questions in Section 2.2 were noted for each company and then entered into the Excel matrix. Only yes or no answers were permitted. An evaluation can be shown with the statistical frequencies for each answer option. The sum of the yes and no answers is obtained to determine the reasons for or against the technology of the participating companies.

2.3.4 Comparison of frequencies of efficiency potentials in selected cross-cutting technologies with existing metering technology

After it is known which companies have installed a smart meter, a comparison between companies with smart meters and conventional analog meters is to be carried out. The comparison is to be carried out with the selected cross-cutting technologies of lighting, energy monitoring, energy purchasing and peak load management. These technologies were included in the comparison because they are very simple energy efficiency measures that are usually already implemented in companies. If the measures have already been implemented, this results in a low energy efficiency potential. The data on the frequency of efficiency potentials of the selected cross-cutting technology will be determined and compared with each other. In addition, the potentials will be analyzed with the results from the study (Knayer and Kryvinska, 2023).

3 Results

3.1 Implementation status and Obligation to implement the measurement technology

Table 2 shows the implementation status and the implementation obligation of the companies. Of the 386 participating companies, 318 (82.4%) are required to install a smart meter, while the remaining 68 (17.6%) companies can retrofit voluntarily.

TABLE 2

TABLE 2. Implementation status and obligation to implement the measurement technology.

Only 34 (10.7%) of the companies required to implement have installed a smart meter. Furthermore, 256 (88.5%) of these companies have already installed modern (digital) metering equipment that could be retrofitted using a smart meter gateway. 28 of the 318 companies nevertheless still have analog meters in use.

No company that can voluntarily perform a retrofit has installed either a smart meter or a modern (digital) metering device. These companies still have analog meters in use.

3.2 Evaluation of the questions

The evaluation of the questions is shown in Table 3.

TABLE 3

TABLE 3. Evaluation of the questions.

The evaluation shows that 222 (57.51%) of the companies surveyed know what a smart meter is. However, only 34 companies (10.7%) have installed a smart meter.

The question about the difference between a digital meter and a smart meter is answered with yes by 249 companies (64.51%). This result coincides with the high number of digital meters installed, i.e., 256 (80.5%).

The question about the rollout strategy of the government and the question about the benefits of smart meter technology are answered in the affirmative by less than one-third of the companies in both cases. This result means that two-thirds of the companies show a strong need for information here.

3.3 Comparison of frequencies of efficiency potentials in selected cross-cutting technologies with existing metering technology

The 34 companies with installed smart meters were compared with the 28 companies with analog meters. The 34 companies are 25 manufacturing and 9 nonmanufacturing non-SMEs. The 28 companies with an analog meter are all manufacturing non-SMEs. In order to be able to present a comparison between manufacturing non-SMEs, the 9 nonmanufacturing companies were removed from consideration. Thus, all 53 companies are manufacturing non-SMEs. The results of the comparison can be seen inTable 4.

TABLE 4

TABLE 4. Energy efficiency potentials of selected cross-cutting technologies sorted by manufacturing non-SMEs with and without smart meters.

The potential is relatively similar for lighting technology in both the companies with smart meters and the companies without smart meters, but lower. The results are insignificantly different from the overall potential of the companies listed here. When it comes to energy monitoring, peak load management and energy purchasing, the results are clearer. Here, companies with a smart meter have an efficiency potential of around 20%, which corresponds to an implementation level of 80%. By comparison, companies with an analog meter have an implementation status of only 36%, with an efficiency potential of 64%. Nevertheless, in both areas, the companies with a smart meter are more efficient than those still equipped with an analog meter.

4 Discussion

4.1 Starting point of this work and objective

Companies lack knowledge about the technology’s advantages and are hesitant about it. This is true even for businesses that are required by law to install the equipment and have annual power usage above 6,000 kWh. They will refit the technology but not put it to use.

Furthermore, there are not many studies that have looked at the technology’s acceptability standards in the workplace. Instead, there are several studies that focus on the household sector (Knayer and Kryvinska, 2022).

However, it is still unknown what factors affect smart meters’ adoption and utilization in businesses.

The advantages of deploying smart meters for businesses have not received enough investigation.

4.2 Main conclusion of the study

Of the 386 participating companies, 318 (82.4%) are required to install a smart meter, but only 34 (10.7%) of the companies have installed one.

Approximately 40% of the stakeholders surveyed do not know what a smart meter is. This follows the results of (Chawla et al., 2020) where about 50% of the respondents did not know what an SM was. It is therefore unlikely that rejection of the technology, as often described in the literature, is based on purely technical aspects. Here, the information and awareness deficit of companies becomes clear, which is also reflected in the question about the rollout strategy. Compared to the results of (Schneider, 2020), the results in the household sector are even more serious. Here, 68% of the respondents did not know what a smart meter or an intelligent meter is.

Only approximately one-third of the companies are aware of the government’s strategy. Therefore, the awareness of those affected with regard to the technology should be increased. The greater the benefits are, the greater the acceptance and, thus, the implementation of the technology.

This is all the more important in Germany because many consumer groups (households and small businesses) are not obliged to install the technology and, instead, have the option to retrofit voluntarily.

However, companies that are obliged to install the technology should also be trained so that they actively use the technology. This point is also shown by the results of this study because although the difference between digital and smart meters is known (64.51%), mainly digital meters are installed (80.5%). This result is because the advantages of the technology are not known (25.65%) or because value-added services are not yet available in a way, that is, compatible with the market. The work of (Gumz and Fettermann, 2023) also indicates that a major obstacle is unfamiliarity with the technology.

The results from the efficiency comparison show that the efficiency potential in the selected cross-cutting technologies tends to be lower for companies that have already installed a smart meter. Studies such as Kollmann and Moser (2014); Anda et al. (2013) have already identified and partially proven savings of 4%–12% or even up to 57% (D’Oca et al., 2014) with smart meters. However, these results were mostly not possible on a technology level, but were based on the total consumption of different actors. Moreover, these only considered households as end customers. The results in this comparison for the cross-cutting technology lighting technology differ only insignificantly from the results from (Knayer and Kryvinska, 2023) which indicate the potential with 52% for manufacturing non-SMEs. The results are clearer for energy monitoring, peak load management and energy purchasing. Companies with a smart meter have a potential of 20%, which corresponds to an implementation level of 80%. In comparison, companies with an analog meter have only 36% implementation status, with a potential of 64%. From the work of (Knayer and Kryvinska, 2023), 38% efficiency potential can be read off for the companies observed here in this cross-cutting technology.

Although the government has reduced costs through the amendment, households and small businesses remain unaffected due to the consumption limit of 6,000 kWh per year. In addition, value-added services such as dynamic tariffs will not become mandatory for all energy suppliers until 2025.

In particular, industry and commerce should be investigated more specifically and more frequently in connection with technology adoption.

4.3 Limitations of the work

Companies were surveyed as part of an efficiency program; it may be that the employees responsible for the energy topic are not responsible for the digitization strategy in the company. In addition, the person responsible for energy may not necessarily be responsible for compliance with and the review of all legal requirements related to digitization and energy. This includes the rollout strategy, which is usually maintained in a legal register as part of an ISO 50001 energy management system.

The questions were deliberately posed in a simple and closed-ended manner (only yes or no answers allowed). However, this method also means that, if necessary, the tendency was to give a no answer if the stakeholders did not immediately know what was at stake.

4.4 Further research and contributions

It was shown that many companies are not yet sufficiently informed about smart meter technology and are therefore not involved in the rollout.

This work is intended to raise awareness of the fact that not only technical and financial barriers but also information plays a decisive role in the decision for or against a technology. In addition, the results show that the previous communication strategy should be expanded to include all participants. This also needs to be done several times.

In the course of a successful rollout, aspects of sustainability with regard to replacement cycles of digital electricity meters compared to conventional meters as well as the consideration of the electricity self-consumption of smart meters should be reviewed and reduced in perspective. The replacement cycles will be significantly shortened, and thus, existing resources will be used more frequently. These cycles should be extended in the future, e.g., in the form of more robust construction. At the same time, it is necessary to consider environmentally compatible reprocessing and recycling of the meters. Since digital meters have a higher rate of self-consumption, whether energy efficiency can be improved must also be examined. In Germany alone, this aspect affects more than 50 million metering points.

Finally, the efficiency comparison carried out is to be extended to other cross-cutting technologies. The aim must be to investigate whether smart meter technology can help companies to change their energy consumption behavior and generate savings.

5 Conclusion

The aim of this work was to investigate the question of the implementation status of smart electricity meters in companies and the level of knowledge of the technology in the companies.

To that end, a survey was conducted in 386 companies as part of a funding project. In addition to the implementation status, which companies would have to carry out a mandatory retrofit of the technology was examined. These results were blended with four questions and evaluated. The results show an information deficit and, thus, a need for research on the technology in the corporate environment, as the majority of the companies do not know what a smart meter is (42.49%). In addition, it is not known what advantages the technology brings (known by only approximately a quarter of the companies). Finally, the legal framework, the so-called rollout strategy, is known by only approximately one-third of the companies. Among other things, this contributes to the fact that companies have a very low implementation rate of 10.7%.

The results can be used to expand the current communication strategy, as more and better targeted information can contribute to a better understanding and alignment of technology in organizations.

The technology is still considered a driver of the energy transition. Therefore, in addition to the acceptance of this technology by users, raising prior awareness, if necessary several times, is of enormous importance.

The results of the efficiency comparison can also be further expanded. With the comparison of frequencies, it is possible to derive a trend between the use of a smart meter and the implementation of efficiency measures in the companies. Furthermore, the transmitted data from the smart meter can be used, for example, to provide companies with energy saving recommendations. This goes hand in hand with the value-added services and the planned benefits such as dynamic tariffs.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Acknowledgments

In addition, we are very grateful to the Chamber of Commerce and Industry Stuttgart and, in particular, Dipl. Ing. Steffen Koci. He made the survey of the companies possible in the first place. This study was supported by the Faculty of Management of Comenius University in Bratislava.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbreviations

EU, European Union; kWh, kilowatt hour; RLM, registered load profile measurement; SM, Smart meter.

References

Abu Arqub, O. (2020). Numerical simulation of time-fractional partial differential equations arising in fluid flows via reproducing Kernel method. HFF 30, 4711–4733. doi:10.1108/HFF-10-2017-0394

CrossRef Full Text | Google Scholar

Abu Arqub, O. (2018). Numerical solutions for the Robin time-fractional partial differential equations of heat and fluid flows based on the reproducing kernel algorithm. HFF 28, 828–856. doi:10.1108/HFF-07-2016-0278

CrossRef Full Text | Google Scholar

Adams, J. (2007). Research methods for graduate business and social science students. Response, Los Angeles: first. publ.

Google Scholar

Anda, M., Brennan, J., and Paskett, E. (2013). Combining smart metering infrastructure and a behavioural change program for residential water efficiency: Results of a trial in the southern suburbs of Perth. West. Aust. 40.

Google Scholar

Berger, S., Ebeling, F., Feldhaus, C., Löschel, A., and Wyss, A. M. (2022). What motivates smart meter adoption? Evidence from an experimental advertising campaign in Germany. Energy Res. Soc. Sci. 85, 102357. doi:10.1016/j.erss.2021.102357

CrossRef Full Text | Google Scholar

Brophy Haney, A., Jamasb, T., and Pollitt, M. G. (2009). Smart metering and electricity demand: Technology, economics and international experience. Cambridge: Apollo - University of Cambridge Repository.

Google Scholar

Bundesamt, Statistisches (2022). Verteilung der Stromzählerarten in deutschen Haushalten im Jahr 2021. Available at: https://de.statista.com/statistik/daten/studie/298727/umfrage/verteilung-der-zaehlertechnik-in-deutschen-haushalten/#:∼:text=Die%20Statistik%20zeigt%20die%20Verteilung,Deutschland%20mit%20ele-ktronischen%20Messeinrichtungen%20ausgestattet (accessed January 12, 2023).

Google Scholar

BUNDESMINISTERIUM FÜR WIRTSCHAFT UND KLIMASCHUTZ (2023). Entwurf eines Gesetzes zum Neustart der Digitalisierung der Energiewende Gesetzentwurf der Bunderegierung. United Kingdom: GNDEW.

Google Scholar

Chawla, Y., Kowalska-Pyzalska, A., and Oralhan, B. (2020). Attitudes and opinions of social media users towards smart meters’ rollout in Turkey. Energies 13, 732. doi:10.3390/en13030732

CrossRef Full Text | Google Scholar

Depuru, S. S. S. R., Wang, L., Devabhaktuni, V., and Gudi, N. (2011). “Smart meters for power grid — challenges, issues, advantages and status,” in 2011 IEEE/PES Power Systems Conference and Exposition (PSCE 2011), Phoenix, AZ, USA (Piscataway, NJ: IEEE), 1–7.

Google Scholar

D’Oca, S., Corgnati, S. P., and Buso, T. (2014). Smart meters and energy savings in Italy: Determining the effectiveness of persuasive communication in dwellings. Energy Res. Soc. Sci. 3, 131–142. doi:10.1016/j.erss.2014.07.015

CrossRef Full Text | Google Scholar

European Commission (2020). Directorate general for energy, tractebel impact, benchmarking smart metering deployment in the EU-28: Final report. Luxembourg: Publications Office.

Google Scholar

Faruqui, A., Harris, D., and Hledik, R. (2010). Unlocking the €53 billion savings from smart meters in the EU: How increasing the adoption of dynamic tariffs could make or break the EU's smart grid investment. Energy Policy 38, 6222–6231. doi:10.1016/j.enpol.2010.06.010

CrossRef Full Text | Google Scholar

Gumz, J., and Fettermann, D. C. (2023). Better deployments come with acceptance: An investigation of factors driving consumers’ acceptance of smart meters. Curr. Sustain. Renew. Energy Rep. doi:10.1007/s40518-023-00208-3

CrossRef Full Text | Google Scholar

Knayer, T., and Kryvinska, N. (2022). An analysis of smart meter technologies for efficient energy management in households and organizations. Energy Rep. 8, 4022–4040. doi:10.1016/j.egyr.2022.03.041

CrossRef Full Text | Google Scholar

Knayer, T., and Kryvinska, N. (2023). The influence of energy management systems on the progress of efficient energy use in cross-cutting technologies in companies. Energy Effic. 16, 12. doi:10.1007/s12053-023-10086-9

CrossRef Full Text | Google Scholar

Kollmann, A., and Moser, S. (2014). Smart Metering im Kontext von Smart Grids. Sweden: Nachhaltig Wirtschaften.

Google Scholar

Kommission, Europäische, and Empfehlung der Kommission vom 6, (2003). Mai 2003 betreffend die definition der Kleinstunternehmen sowie der kleinen und mittleren unternehmen: (2003/361/EG). Brussels and Luxembourg: European Commission.

Google Scholar

PwC (2022). Smart-Meter-Roll-out - standortbestimmung der grundzuständigen Messstellenbetreiber. Umsetzungsstand Herausforderungen beim Roll-out intelligenten Messsyst., 2022.

Google Scholar

Schneider, C. (2020). Den Rollout im Blick: - die Kenntnis der Bevölkerung von Smart Metern/intelligenten Messsystemen Eine repräsentative Untersuchung in den Bundesländern Baden-Württemberg, Bayern und Hessen. Available at: https://www.ich-bin-zukunft.de/wp-content/uploads/2020/06/SmartGridsBW2020_Bekanntheit_Smart-Meter_V09.pdf (accessed January 12, 2023).

Google Scholar

Umweltbundesamt (2021). Erkenntnisse zu Umweltwirkungen von Smart Metern: Erfahrungen aus dem Einsatz von Smart Metern in Europa. Dessau-Roßlau: Federal Environment Agency.

Google Scholar

Umwelttechnik BW GmbH (2021). Regionale kompetenzstellen netzwerk energieeffizienz (KEFF). Available at: www.keff-bw.de.

Google Scholar