Improving energy efficiency in industry - Savings through automation

2. Background on the relevance of energy efficiency

According to the Federal Climate Protection Act (KSG), Germany’s greenhouse gas emissions are to be reduced by 2045 to such an extent that net greenhouse gas neutrality is achieved [2]. Key components of the energy transition in Germany are, on the one hand, the expansion of renewable energies and, on the other, energy efficiency [3]. According to the BMWK’s study ‘Energy Efficiency Strategy 2050’, a significant reduction in demand among end users is therefore expected [4]. 

In 2023, the industrial sector accounted for 27.5 per cent of total final energy demand in Germany, according to the Federal Environment Agency [5]. For a transition towards greenhouse gas neutrality, final energy demand in industry (635 TWh/year [6]) must therefore also be reduced and met by renewable energy sources. Final energy demand in industry is largely determined by the process heat sector. This accounts for 67.5 per cent of final energy [7], [8]. In particular, the brief study ‘Energy Efficiency Measures in Industry’ [9] estimates significant energy-saving potential in this sector, which is described in greater detail in the brief study ‘Energy-Efficient and CO₂-Free Process Heat’ [10]. 

In the studies [1], [10], process heat is classified according to temperature levels, and the final energy demand for process heat – amounting to approximately 460 TWh/year – is allocated across these levels. The basis for this classification is an analysis commissioned by the Federal Environment Agency [11]. In addition to a breakdown into different temperature ranges, this analysis also allocates final energy consumption by sector. This enables the potential savings to be estimated, taking into account the specific applications and processes and using appropriate reference technologies.

3. Final energy saving potential and the role of automation

The brief study [1] identifies a cumulative economic final energy saving potential (i.e. the implementation of measures with a positive net present value) of 263 TWh/a, which can be realised with a total investment of €104 billion. The measures considered can be grouped into bundles of measures. Figure 2 illustrates the economic final energy saving potentials for various application areas (the area of the circles is proportional to the numerical value in TWh/year), the corresponding investment sums (x-axis) and the average payback period for all measures within the application area (y-axis). The position of the centre of each circle illustrates the weighting of the payback periods. Figure 2 shows that many energy efficiency measures pay for themselves within around five years. The greatest savings potential lies in the area of process heat. For the process heat application area, the individual packages of measures are evaluated in Figure 3. Here, the area of the circles is proportional to the numerical value in TWh/a representing the economic final energy saving potential of the individual packages of measures. The investment sums (x-axis) and the average payback period for all measures within the packages (y-axis) are also shown. The arrows indicate the shortest and longest average payback periods for the measures within a package. The position of the centre of each circle illustrates the weighting of the payback periods. 

The significant savings potential of efficiency measures such as ‘heat recovery/integration’ or ‘process conversion through electrification’ is evident. The investment costs for these measures are comparatively high. This analysis takes into account that efficiency measures – such as those to prevent waste heat, heat recovery/integration and waste heat utilisation – are implemented first, before electrification takes place. This significantly reduces the proportion that must be provided through changes in heat supply (e.g. electrification), thereby also reducing the associated high investment costs. 

Process automation is reflected in particular in the two sets of measures: ‘Improved user behaviour and/or control’ and ‘System optimisation’. These sets of measures are also present in the other application areas listed in Figure 2. All the measures grouped here are characterised by low investment costs and attractive payback periods. The first set of measures involves the adaptation and optimisation of existing control systems – for example, through a critical review of process temperatures and the targeted adjustment of parameters. For the ‘System optimisation’ package of measures, the focus is on implementing new control and automation mechanisms, such as oxygen control and automated blowdown in temperature ranges involving steam applications. 

Installing continuous condition monitoring of steam traps also enables the early detection of leaks or blockages, thereby preventing energy losses. The payback period for these measures is less than two years. Furthermore, retrofitting heat exchangers with temperature and flow measurements – with a payback period of just a few months – can enable better condition monitoring and thus increase energy efficiency. [12] 

Figure 4 shows the contribution of the two automation measure packages to the final energy saving potential for each temperature range. The economic final energy saving potential per temperature range is broken down into the contribution from the two automation measure packages (blue) and the remaining contribution from the other measure packages (orange). In the higher temperature ranges in particular, process automation accounts for a large proportion of the final energy saving potential (illustrated by the percentages on the right-hand side).

4. Examples of final energy savings through automation

Concrete examples best illustrate how easily energy and money can be saved through automation. The examples listed here are just a small selection. Further useful suggestions can be found in various guides, e.g. in [12], [13], [14], [15], [16], [17], [18], [19]. 

Electricity load management – base load reduction: The external electricity consumption of the facility in question exceeds 500 kW at weekends and accounts for approximately 16 per cent of total consumption (2,500 MWh/year). Added to this is the electricity generated by a combined heat and power plant. In 2022, this base load consumption resulted in energy costs of at least €420,000 per annum. During site inspections carried out by two people on Saturdays (taking sixteen hours per person), systems were identified that accounted for a large proportion of the base load and which could be switched off or operated differently. Following the installation and programming of control systems on nine units, savings of approximately 250 MWh/a of electricity (10 per cent) or €49,000/a were achieved. The net present value of the measures is positive; the total investment was €82,000, and the payback period was approximately 1.67 years. 

Compressed air – control system: At another site, compressors of various sizes are integrated into a central compressor control system. The compressor control system was optimised simply by means of a software update. The electricity saving amounted to 16 MWh/a (0.03 per cent) or €2,388/a, with a total investment of €3,350. Positive net present value and a payback period of approximately 1.4 years. 

Compressed air – leak monitoring: Monitoring compressed air leaks can lead to significant electricity savings. Compressed air leaks can be detected using electricity meters fitted to the compressors and by carrying out inspections with ultrasonic devices. Identified leaks should be rectified as quickly as possible by repairing the leaks. The electricity saving was 10.1 MWh/year or €2,200/year, with a total investment of €4,240. Positive net present value and payback period of approximately 1.97 years. [13] 

Ventilation system – control: A large system was supplying a production hall, even though only one third of the hall needed to be specifically ventilated. The improvement measure involves sectioning off the hall. Sectioning means that only one third of the hall is ventilated as before, whilst the other two thirds are supplied with a reduced air flow, enabling a saving of around 50 per cent of the rated power for the new fan motors. At the same time, this measure reduces the heating requirement by around 30 per cent. The savings amount to 16.5 MWh/year of electricity (-65 per cent) and 104 MWh/year (30 per cent) of natural gas, totalling €13,510 per year. The investment required for automation and new fans was €55,368, with a payback period of approximately 3.9 years. 

Recooling plant – control system supported by a digital twin: Data from the recooling plant’s pumps covering a full year was analysed and interpreted. The result was an energy-optimised operation of the pumps, which are equipped with variable-frequency drives. To achieve energy-optimised control of the recooling plant, the system was replicated as a digital twin. Extrapolated over a year, the savings achieved amount to 411 MWh/year (at 10 ct/kWh, this equates to €41,100/year!) – and this was achieved without any technical investment. [12] 

Steam generation – O₂ control: The steam boiler at the plant in question does not have O₂ control (oxygen control). The safety air surplus required to comply with flue gas emission limits is quite high. By installing O₂ control on the steam boiler, around 8 per cent of natural gas (75 MWh/a or €7,506/a) was saved. The investment cost was €11,566, with a payback period of approximately 1.4 years. 

Production | Refrigeration system – control system: The refrigeration system for bag cooling is operated at an unfavourable operating point. The operation of the refrigeration system was optimised by installing a new control system and reprogramming it. The electricity saving amounted to 18 MWh/year or €3,300/year. The net present value was positive, the investment cost was €8,000 and the payback period was approximately 2.42 years. 

Production | Melting furnace – retrofitting of variable frequency drives: The dust extraction system of a melting furnace is controlled by butterfly valves. When the steel is transferred into the ladles, the valves are fully open; at other times, they are largely closed. A demand-based control system for the dust extraction systems, utilising frequency converters, was installed, resulting in electricity savings of 147 MWh per annum or €14,000 per annum. The investment cost was €41,000, with a payback period of approximately 2.92 years. 

Production | Hot rolling – new sensors and optimised control: The control system for the transport rollers in the hot rolling area was upgraded, automated and optimised at a cost of €57,600. Electricity savings amounted to 1,100 MWh/year or €64,000/year, meaning the payback period is approximately 0.9 years. 

5. Conclusion

The study presented here impressively demonstrates the opportunities available within German industry to produce the same output whilst using less final energy. Typical energy-saving measures include insulation and, above all, the recovery of waste heat. Further measures include improved user behaviour, optimised control and regulation systems, operational and maintenance measures, speed-controlled drives, the use of high-efficiency motors, and the use of free cooling. The modernisation of plant was also taken into account, as was the use of ambient heat. The switch to heat pumps is a particularly important measure, especially for heat up to 200 °C. 

It should be emphasised once again at this point that many of the measures can be implemented easily and with minimal investment. This applies in particular to the optimisation of control systems and automation. The specific examples listed above underscore this. 

In addition to the business benefits, the study [1] also highlights the macroeconomic benefits: energy efficiency measures reduce not only demand but also peak load. Fewer gas-fired power stations will need to be built by 2045, meaning that the investment required could be reduced by around €10 billion. Added to this are the avoided natural gas import costs for the power stations that are not built, amounting to around €1 billion per year, resulting in a cumulative economic benefit of €30 billion over 20 years for gas-fired power stations alone. 

Furthermore, energy efficiency measures contribute to security of supply by reducing the need to import fossil fuels. Another benefit is the support provided in meeting the Federal Republic’s international commitments, thereby potentially avoiding specific fines for the federal government or for taxpayers. 

This article first appeared in atp magazine 4/2026. 

References 

[1] Meyer, J., Zaubitzer, L., Seeliger, A., Alsmeyer, F., Schmitt, L. (2025). Brief study: Macroeconomic and business assessment of energy efficiency in industry. Retrieved from: https://www.hs-niederrhein.de/fileadmin/dateien/Institute_und_Kompetenzzentren/SWK_E2/UmInMuen01-Kurzstudie-2025-10-22.pdf 

[2] German Federal Government. (2019). *Federal Climate Protection Act (KSG)*. Berlin. 

[3] Federal Ministry for Economic Affairs and Climate Action. (2024). Energy Transition. Retrieved from: https://www.bmwk.de/Redaktion/DE/Dossier/energiewende.html 

[4] Federal Ministry for Economic Affairs and Energy. (2019). Energy Efficiency Strategy 2050. Berlin. 

[5] Federal Environment Agency. (2025). Final energy consumption by energy source and sector. Retrieved from: https://www.umweltbundesamt.de/daten/energie/energieverbrauch-nach-energietraegern-sektoren 

[6] Federal Statistical Office (Destatis). (2024). Energy consumption of enterprises in the manufacturing sector: Germany, years, energy consumption by use, economic sectors, energy sources. Wiesbaden: Destatis. 

[7] Fraunhofer ISI. (2023). Preparation of application balances for the years 2021 to 2023 for the industry and GHD sectors. Study for the Arbeitsgemeinschaft Energiebilanzen e. V. 

[8] Federal Ministry for Economic Affairs and Climate Action. (2023). Energy efficiency in figures – developments and trends in Germany 2022. 

[9] Meyer, J., Madsen, M., Saars, L. (2023). Brief study: Energy efficiency measures in industry – Market-oriented and cost-effective energy-saving potential in industry. 

[10] Meyer, J., Zaubitzer, L., Alsmeyer, F. M. M. (2024). Brief study: Energy-efficient and CO₂-free process heat. Retrieved from: https://www.hs-niederrhein.de/fileadmin/dateien/Institute_und_Kompetenzzentren/SWK_E2/DENEFF-HSNR-PrzWrm-Kurzstudie-2024-07-24.pdf 

[11] Prognos AG, Fraunhofer ISI, Technical University of Munich. (2016). Database for the evaluation of energy efficiency measures in the 2005–2014 time series: Final report. Federal Environment Agency. 

[12] ZVEI & NAMUR. (2023). Sustainability through process automation. Retrieved from: https://www.zvei.org/pressemedien/publikationen/broschuere-sustainability-durchprozessautomation 

[13] Federal Association of Energy Consumers (VEA). (2023). Practical examples of energy-saving measures. Retrieved from: https://klimafreundlicher-mittelstand.de/klimafreundliches-handeln/praxisbeispiele-fuer-energieeinsparmassnahmen/ 

[14] Meyer, J., Möhren, S., Saars, L. (2022). A climate-neutral and competitive food industry by 2030: A guide to decarbonising process heat supply. Association of German Industrial Engineers e. V. 

[15] Initiative for Energy Efficiency and Climate Protection Networks. (2022). List of short-term energy-saving measures. Retrieved from: https://www.effizienznetzwerke.org/fileadmin/user_upload/2023/02/2023_Liste-zu-Kurzfristmassnahmen-fuer-Energieeinsparung.pdf 

[16] Meyer, J., Domning, A., Freiberg, M., Maurer, U., Mier, P., Schmidt, C., Strotmann, B., Wiesgen-Pick, A. (2024). Improving energy efficiency in spirits production: a guide with best-practice examples. Federal Association of the German Spirits Industry and Importers e. V. 

[17] German Energy Agency (dena). (2015). Energy efficiency in small and medium-sized enterprises. Retrieved from: https://www.dena.de/fileadmin/dena/Dokumente/Pdf/1419_Broschuere_Energieeffizienz-in-KMU_2015.pdf 

[18] Hesse State Energy Agency. (n.d.). Practical examples of energy efficiency. Retrieved from: https://www.energieeffizienz-hessen.de/energieeffizienz/praxisbeispiele/ 

[19] Umwelttechnik BW GmbH. (n.d.). Success stories in resource efficiency. Retrieved from: https://www.keffplusbw.de/de/services/erfolgsbeispiele 

Prof. Dr.-Ing. Jörg Meyer 
Niederrhein University of Applied Sciences 
SWK E² Institute for Energy Technology and Energy Management 
Krefeld South Campus 
47805 Krefeld 

Louisa Zaubitzer, M.Sc. 
Niederrhein University of Applied Sciences 
SWK E² Institute for Energy Technology and Energy Management 
Krefeld South Campus 
47805 Krefeld