Sustainable Resource Planning by Means of Smart Grids

Smart measurement technology is indispensable due to the challenges of the energy transition – this is the only way can optimize existing and new stations and plants to meet demand. Holger Biermann of Stadtwerke Tuttlingen GmbH reports on how data acquisition with EFEN-SGIM Module works and what advantages result from it.

„Electromobility is picking up speed“ states Mr. Holger Biermann, team leader of the technical customer service of Stadtwerke Tuttlingen GmbH (swt). The swt itself now has 8 e-vehicles in its fleet. „We deliver quality of life“ promises the lettering on the cars. After many years with the company, Ms. Manuela Renner, Marketing Officer, can confirm: these are not empty words, but the guiding principle of swt: the enthusiasm to ensure a sustainably functioning infrastructure in both the energy and leisure sectors.

However, the energy and mobility turnaround are known to be a double-edged sword. The energy supply is becoming more volatile and high-load windows can no longer be accurately predicted due to loads from decentralized feeders and grid loads from charging stations and wall boxes. In order to meet these challenges and continue to deliver the „quality of life“ in the future, swt needs an overview of the grid load. The information at what time and at what level the grids are under load needs to be retrievable “ in real time and preferably from a PC,“ Mr. Biermann specifies.

Demand-driven optimization of networks with extensive service

Ms. Renner explains that sustainability has an enormous influence on swt’s economic activities: „We think carefully before we invest“. Limited human and monetary resources are used consciously after careful consideration. „Of course, we rely on partners providing support five years from now“, Mr. Biermann adds, “EFEN is already established on the market with very good products.“ Moreover, swt and EFEN share a long-term partnership.

The existing problem: network expansion is finite. „There is not endless space in the sidewalks,“ Mr. Biermann points out, so the task of reinforcing the network is proving difficult. Consequently, it is essential to utilize the networks according to demand. The first step to do that is to record the measurement data with an accurate time stamp. In fact, this is also the prerequisite for being able to control the systems in the future as needed, explains Mr. Biermann.

Modular system can be used flexibly

swt would like to be able to read out all the relevant data quickly and flexibly when requests are made for an increase in power or for new charging stations. These were the initial requirements that swt placed on a system and which, according to Mr. Biermann, have now been implemented „to our complete satisfaction“ through the use of the modular Smart Grid Interface Module (SGIM).

Mr. Biermann is enthusiastic about the system: it is particularly advantageous that it „can be retrofitted without any problems and can even be used on a mobile basis“. The measured values are sent to the control center via Mod-Bus and to the password-protected SGIM cloud via GSM where the data can be read out by any computer at any time if required. Out of interest, he currently reads the data every week. It is also possible to set an alarm where the system will report if a feeder somewhere reaches its limits. „So far, everything is in the green,“ Mr. Biermann assures us.

Smart insights in transformer stations

Currently, several new transformer stations are being built. swt adds about two per year. Two years ago, the first new compact station with smart metering technology was already put into operation equipped with the SGIM for busbar mounting in combination with the EFEN E³-NH-La-Lei Gr.2. The most important insight today is that the existing and required performances differed significantly. „I think we’re about halfway there at the moment,“ Mr. Biermann reports on one project. In other words, by using smart technologies, in this specific case the SGIM, the overcapacity can be identified and therefore, the networks can be optimized according to the actual demand saving costs and valuable resources.

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