Germany needs to save energy in view of the current gas and electricity crisis. With two new energy-saving ordinances, specific measures and target values are now being specified with which Germany is to save energy in the public sector. The ordinances are to apply in the short term from September and October 2022 for six and 24 months respectively. M2M SIM cards and the use of intelligent building technology can help to implement and monitor the specified measures.
On August 24, 2022, the German Federal Ministry of Economics and Climate Protection (BMWK) promulgated two new energy saving ordinances. The amendment to the Energy Conservation Act (EnSiG) passed in the summer empowers the federal government to adopt corresponding ordinances. Both ordinances contain specific measures and benchmarks aimed at saving energy - particularly electricity and heating energy - throughout Germany. The first ordinance has already been in force since 1.9.2022, limited to a period of 6 months. The second ordinance still requires the approval of the Bundesrat. It is to apply from 1.10.2022 for a total of 24 months.
The ordinances stipulate, for example, that the minimum temperature stipulated in rental agreements does not have to be maintained temporarily for six months and that the upper temperature limit in public buildings is lowered from 20 to 19 degrees. If possible, corridors or areas of public buildings in which people do not live should no longer be heated at all. Exceptions will only apply if a higher temperature is necessary for health or technical reasons. From October, it is also to be prohibited to illuminate monuments or places of interest from the outside. The only exceptions are security and emergency lighting. Exceptions will also apply to short-term cultural events or public festivals, as well as all situations in which light is necessary, for example to avert danger or to secure road traffic. If retail business premises are heated, they may not keep their store doors and entrance systems permanently open. Illuminated advertising systems must be switched off between 10 p.m. and 6 a.m. the following day. Exempt from this - again for safety reasons - are illuminations on passenger shelters or in bus shelters and railroad underpasses.
In this extraordinary situation, intelligent technology can help companies, authorities and municipalities maintain an overview and successfully implement measures. Whether for regulating and controlling lighting solutions or monitoring heating systems, sensors, control units and M2M SIM cards help to collect and control data in an automated manner and allow remote intervention if necessary. Automation in buildings (smart buildings) can contribute quite a bit to energy efficiency. In the following, we briefly explain three possible customer applications in the context of building automation and energy saving for IoT SIM cards:
Smart lighting or intelligent lighting solutions are, among other things, about operating the lighting in indoor and outdoor facilities with individual lighting times and a light level adapted to demand. This applies both to self-triggering basement lighting in apartment buildings and to street lighting in large cities. For efficient energy use, light must be provided where residents and inhabitants need it. In other places, energy consumption can be reduced. In the long term, this not only saves energy costs but also protects the environment, for example by protecting birds, bats and insects from permanent exposure to light.
Remote-controlled city lighting network:
Intelligent street lighting systems are a way for cities to conserve resources both economically and ecologically. In the smart city context, they are already being implemented by cities worldwide. The goal behind the deployment of smart lighting systems is to improve processes around urban lighting and realize associated savings. Typically, the systems collect data on energy and lighting requirements, transmit them to a central control center, from where they are evaluated - and from where the systems can be accessed remotely if necessary. This not only significantly shortens the response times of municipal authorities, but also reduces travel costs for personnel and the deployment of personnel in general. Light intensity is monitored and controlled via controllers mounted on luminaires, for example, and switch-on times are programmed or exceptions are stored for specified periods - whether on a regular basis or as an exception, such as for special events. Since these facilities are based on determined demand, lighting or energy is primarily provided when it is actually needed. Unnecessary lighting periods are eliminated, resulting in an immediate reduction in energy consumption and operating costs.
Predictive maintenance is probably one of the most widespread use cases of the IoT in the context of Industry 4.0. Here, the condition data of machines is recorded and collected in order to actively maintain plants. Real-time processing of the collected machine data enables forecasts to be made, which in turn are used as the basis for maintenance cycles. This reduces machine downtimes, for example, as impending failures can be derived in advance from the data. Technicians can thus intervene before damage actually occurs. The benefits of predictive maintenance take effect on many levels:
Predictive maintenance can benefit companies on two levels: On the one hand, predictive maintenance helps to reduce the downtime of plants and machines, thus maintaining or increasing production efficiency and reducing costs for unplanned downtime. On the other hand, regular maintenance increases the service life of machines and plants.
Optimal maintenance cycles and processes:
Precise advance planning of upcoming maintenance and any downtime that may occur as a result means that the processes around it can be better coordinated. Instead of having to react to a sudden breakdown and possibly having to stop production at short notice, maintenance can be scheduled and production adjusted accordingly. In other words, you decide on the most appropriate time for maintenance, rather than being surprised by it.
Improved machine performance:
Continuous analysis of collected data makes it possible to improve the performance of plant and machinery. In the long run, this makes it possible to achieve higher productivity.
Remote access or remote maintenance of technical devices (in English: Remote Maintenance and Control) is about using M2M communication to access devices from almost anywhere in the world. In this way, end devices can be monitored and maintained remotely - it is no longer necessary for a team to be on site for routine checks or a software update, for example. On-site deployments can be limited to actual needs thanks to remote accessibility, allowing companies to plan deployments more efficiently and cost-effectively.
There are now many possible applications and uses: From monitoring industrial machinery to wind turbines to networked heating systems in commercial buildings. Whereas in the past a service team would arrive to deal with a problem with a machine or device, thanks to the IoT (Internet of Things), customer service today can start an initial diagnosis remotely, even without being on site, and may thus be able to solve a problem without having to travel to the site. The risk of programming or configuration errors is increasing, especially with systems that are becoming increasingly software-heavy. Remote diagnosis via an M2M connection is usually sufficient to identify the error and often to correct it directly.
Especially with regard to the efficiency of heating systems, the Internet of Things offers many new possibilities. To monitor and control energy consumption, for example, the performance data of the heating system can be transmitted directly to property managers or housing companies. A gateway installed on the heating system serves as an interface and can both read and transmit data - the temperature of the flow and return, the pressure or the amount of heat consumed. With intelligently controlled heating systems, energy savings of up to 15 % on average are possible for hot water and heating.