{"id":103310,"date":"2024-04-15T12:00:00","date_gmt":"2024-04-15T10:00:00","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&p=103310"},"modified":"2025-03-05T10:30:05","modified_gmt":"2025-03-05T09:30:05","slug":"energy-efficiency-through-intelligent-electricity-data-acquisition","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/energy-efficiency-through-intelligent-electricity-data-acquisition\/","title":{"rendered":"Energy Efficiency Through Intelligent Electricity Data Acquisition"},"content":{"rendered":"\n

In view of the German government’s energy policy goals and the consistent growth of energy demand coupled with rising energy prices, monitoring and demand-based control of the energy requirements of the infrastructures used in the property management of industrial buildings and their technical systems is becoming increasingly necessary [1, 2]. With the added value of digital processes, complete with comprehensive monitoring, analysis and control of energy requirements, costs can be effectively reduced, energy efficiency can be increased and resources can be optimally utilized. This not only contributes to an improved environmental footprint, but also leads to cost savings, which strengthens the long-term competitiveness and profitability of a company [3].<\/p>\n\n\n\n

Within industrial properties, this can be achieved by introducing real-time energy monitoring. Real-time energy monitoring enables the time-dependent identification of potential energy savings through automated data acquisition and visualization. This effective method helps to gain more precise insight into time-dependent energy consumption and thus to identify opportunities for optimization [3]. Looking ahead to the increasing expansion of renewable energy sources, it is already possible to use real-time data acquisition to create a basis for adapting one’s own consumption to the volatile supply that renewable energy sources provide. By shifting or decoupling work steps in the manufacturing process, energy consumption can be adapted to the availability of renewable energy, and a contribution can be made towards grid stability.<\/p>\n\n\n\n

The automated real-time acquisition of data on electricity consumption forms the basis and the starting point for systematic energy monitoring and the added value of the information derived from it [4]. An effective increase in energy efficiency through energy monitoring is therefore fundamentally dependent on sound measurement data acquisition.<\/p>\n\n\n\n

Electricity data acquisition \u2013 the status quo and challenges in networking<\/h2>\n\n\n\n

Closer consideration of the current situation of consumption data acquisition from existing industrial buildings reveals that employees have to visit various buildings to manually read the consumption values from the energy meters. This is done either at annual or monthly intervals. For large properties with numerous buildings dispersed throughout the area and an established energy meter infrastructure, this process is extremely time-consuming, costly and prone to errors despite all due care. As a result, it is not possible to continuously record consumption data in real time, which means that deviations are not immediately recognizable. This makes it impossible to intervene promptly and preventively in the event of an unforeseeable error. This can be expensive for a company, because prevention and timely intervention when necessary are often more cost-effective than the failure or repair of a system [5].<\/p>\n\n\n\n

In many cases, only a single energy meter is installed to record total electricity consumption in individual parts of the building. Areas that only have one main meter cannot record the electricity consumption of individual sub-consumption points [6].<\/p>\n\n\n\n

As a result, it is not possible to precisely allocate electricity consumption for various types of electricity use, such as lighting control, heating, air conditioning and ventilation systems (HVAC) or electricity consumption at test benches in a time-dependent manner. To make matters worse, energy meters of different ages and with different interfaces and communication protocols are often installed. In some cases, analog energy meters are still in operation [5, 7].<\/p>\n\n\n\n

One of the most important requirements is that the ongoing operation of systems and the continuous power supply must not be disrupted or interrupted during the process of integrating the solution. In addition to this essential requirement, the communication infrastructure must also be able to cover large distances. This applies in particular to properties with dispersed facilities. The communication network should be robust enough to ensure reliable data transmission over long distances. This is crucial for the comprehensive networking of energy meters in different building complexes and over extensive sites.<\/p>\n\n\n\n

Another aspect that must be taken into account when choosing the communication infrastructure is the collection of data in basements or underground spaces, as this is where energy meters are usually installed. The selected technology must therefore be able to reliably collect and transmit data under difficult transmission conditions.<\/p>\n\n\n\n

The networking of energy meters requires careful consideration of various technological factors in order to ensure reliable, efficient and trouble-free integration into the existing infrastructure.<\/p>\n\n\n\n

When looking at existing buildings in industrial properties, the many challenges involved in recording electricity consumption data become apparent \u2013 especially in cases where replacing the existing meter infrastructure is impractical for time-related and economic reasons. The implementation of a suitable retrofit system is therefore essential. There are numerous systems for data collection and technical approaches for monitoring energy consumption. However, there is a lack of a universal and cost-effective solution that can be used in a variety of ways to record electricity consumption data in industrial properties.<\/p>\n\n\n\n

When integrating a retrofit system, the question arises of how to avoid structural measures and minimize both integration and maintenance costs [8]. Successfully addressing this issue requires careful planning and the selection of suitable technologies. Wireless technologies and Open-Source Software (OSS) from the Internet of Things (IoT) offer promising opportunities for the continuous collection of electricity data in order to increase the efficiency of existing industrial buildings [9]. IoT describes the networking of physical devices via the internet in order to exchange data and enable smart functions. These devices, such as sensors or actuators, collect and analyze information in different environments to perform certain actions. OSS stands for publicly accessible software withopen source code that is jointly created, improved and maintained by a community of developers. In the field of IoT, OSS is used to develop cost-effective and flexible solutions that can run on different devices and platforms and to promote interoperability between different IoT components.<\/p>\n\n\n\n

In this context, a cost-effective retrofit system was developed in collaboration with Robert Bosch GmbH at its Schwieberdingen site using common open-source IoT technologies.<\/p>\n\n\n\n

IoT retrofit of energy meters \u2013 smart measurement technology for data acquisition<\/h2>\n\n\n\n

The use of non-invasive sensor and measurement technology enables simple and quick installation in buildings without interruption to their supply, as well as uncomplicated integration into an energy monitoring system [10].<\/p>\n\n\n\n

This eliminates the need to manually read the electricity consumption values, and means that replacing the meter infrastructure is no longer necessary. Networking the energy meters helps to create comprehensive transparency of time-dependent consumption data while minimizing the error rate in data processing due to the absence of breaks in the data flow. In addition, facility managers have the opportunity to react to unplanned changes in consumption and take appropriate action \u2013 including the ability to make predictions regarding future time-dependent consumption. These additional functions strengthen the control and management of energy consumption by enabling an early and real-time response to changes while also allowing for long-term planning.<\/p>\n\n\n\n

The structure of a wireless retrofit solution can be divided into three main core areas: sensor and measurement technology for recording power consumption data, wireless data transmission via an IoT gateway and subsequent integration of the measurement data into an energy management system, or control technology (Figure 1).<\/p>\n\n\n\n

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Figure 1: End-to-end measurement data flow.<\/em><\/em><\/figcaption><\/figure>\n\n\n\n

The central component of the sensor and measurement technology is a digital energy meter of the Berg brand, type BME462. An electronic active and reactive energy meter (transformer meter), which can be operated both in the procurement and feed-in direction as a stand-alone solution or in parallel as an intermediate meter to existing energy meters. The recorded measurement data can be exchanged with various energy management or control systems via interfaces such as Modbus RTU, Modbus TCP, BACnet or M-BUS [11].<\/p>\n\n\n\n

A passive cable conversion current transformer (CT) is used as a sensor component to measure the electrical current flow. This is similar in function to a special transformer, which is designed to convert large, not directly measurable currents (primary current) into a smaller, directly measurable secondary current [12].<\/p>\n\n\n\n

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Figure 2: Circuit diagram of the cable conversion current transformers on energy meters.<\/em><\/em><\/em><\/figcaption><\/figure>\n<\/div>\n\n\n\n
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With the alternating current generated in this way and proportional to the primary current, it is possible to reliably measure the actual electrical current flow with connected standard measuring devices such as the BME462 (Figure 2) [13].<\/p>\n\n\n\n

In order to minimize the installation effort and avoid cutting the primary conductors, the CT consists of a separable measuring core. Another advantage is its small size, which means that a CT can be used in places that are difficult to access or where space is limited [14].<\/p>\n\n\n\n

Once the power consumption data has been recorded, wireless data transmission takes place via the LoRaWAN network protocol.<\/p>\n<\/div>\n<\/div>\n\n\n\n

Data transmission with LoRaWAN<\/h2>\n\n\n\n

The measurement data recorded by the sensor and measurement technology can be transmitted to a higher-level energy monitoring system or a control system both wirelessly and via cable using various communication protocols. In the smart home sector, long-established and widely used communication protocols for wireless local area networks (WLAN) are used to control sensors and actuators. These include WiFi, Bluetooth, Zigbee, Z-Wave and EnOcean. The decision to use these protocols is often based on either the existing infrastructure or the performance level sufficient for use in the home [15].<\/p>\n\n\n\n

In the context of electricity data collection in industrial properties, smart home meters equipped with WLAN, such as the Shelly EM or various other smart meter sockets, are unsuitable due to their low availability in basements and the resulting high networking costs. Additional repeaters are required when setting up a comprehensive communication infrastructure. LANs that are designed for the efficient transport of large amounts of data across a relatively short range are not useful, as the amount of data generated in IoT applications is comparatively small [15, 16]. However, factors such as a long range, good building penetration and long battery life are important. Alternative technologies such as LoRaWAN or NB-IoT should therefore be considered.<\/p>\n\n\n\n

In this context, the Long Range Wide Area Network (LoRaWAN) is proving to be a promising technology for the wireless transmission of data in large-scale industrial properties. LoRaWAN is one of the so-called Low Power Wide Area Network (LPWAN) technologies and was developed specifically for the requirements of IoT.<\/p>\n\n\n\n

LoRaWAN is characterized by its long range and low energy consumption, which means that entire company premises can be covered cost-effectively with just a few gateways. Even in basements, where conventional radio technologies are of limited use, coverage is guaranteed thanks to the high and interference-free penetration of LoRaWAN. Due to the low data volumes transmitted in a LoRaWAN network, almost any number of sensors can be integrated into the network infrastructure via a single gateway \u0007\u0003[15]\b. These properties make LoRaWAN particularly suitable for applications in the field of electricity data acquisition in large industrial properties.<\/p>\n\n\n\n

For the retrofit solution developed, the BME 462 electronic energy meter was connected to an open-source LoRaWAN module via the Modbus interface integrated in the device. An RS485-to-LoRaWAN converter makes it possible to easily integrate non-network-compatible devices into an IoT network via LoRaWAN. This simplifies the IoT installation and thus reduces the resulting installation and maintenance costs. The converter has been specially developed for wireless sensor networks in the fields of smart metering, smart city and smart buildings.<\/p>\n\n\n\n

The LoRaWAN converter generates a data packet with the recorded consumption data and dispatches periodic or event-driven transmissions via the LoRa radio protocol to an open source LoRaWAN gateway. The transmitted data is received by LoRaWAN gateways in the surrounding area and forwarded to the LoRaWAN network server. The gateway acts as an interface between the wireless sensors and the network server. The gateway enables data integration into existing network infrastructures by connecting a LoRa wireless network to an IP network via WiFi or Ethernet. In addition to WiFi and Ethernet, LoRaWAN gateways offer other interfaces such as Modbus, M-Bus and BACnet for easy integration into energy monitoring or building automation.<\/p>\n\n\n\n

Open-source software for measurement data integration in an EM system<\/h2>\n\n\n\n

A LoRaWAN network server is required to integrate the measurement data transmitted via the LoRaWAN into an energy monitoring system landscape. This server receives the data from the gateways and makes it available for further processing via an API. There are various ways of integrating a LoRaWAN network server into a specific infrastructure. One option is to use already established LoRaWAN cloud service providers. One of the best-known providers is The Things Network (TTN) from the Netherlands. TTN is a global collaborative ecosystem that develops and offers LoRaWAN-based solutions such as network servers, devices and cloud services.<\/p>\n\n\n\n

One advantage of cloud service providers is the rapid integration of data into a company’s own systems. However, it should be noted that in some cases the use of TTN is not possible due to a company’s internal security guidelines. This could be due to concerns about data outflow from the company or denied data inflow into the company.<\/p>\n\n\n\n

The local operation of a dedicated LoRaWAN network server, such as the open-source server ChirpStack, is ideal for such scenarios. This ensures greater control over security aspects and makes it possible to handle all data traffic internally. By providing the network server locally, it can be ensured that all data remains within the company’s own infrastructure [17].<\/p>\n\n\n\n

Another option is to use LoRaWAN gateways with integrated network servers [18]. However, it should be noted that higher numbers of gateways entail higher maintenance and installation costs. The selection of this option should therefore be weighed carefully, particularly with regard to scalability within large-scale properties and the resources required for maintenance work. The choice of the appropriate integration method depends on the company’s specific requirements, security guidelines and resource capacities.<\/p>\n\n\n\n

The goal of utilizing open-source software was pursued in the development of the retrofit solution. The use of OSS in energy monitoring and building automation offers numerous possibilities and advantages. One of the main advantages is the flexibility of OSS solutions. Companies can freely adapt the source code to their specific requirements, which enables customization to the respective use cases or internal company processes [19]. The openness of OSS also enables transparency, security and interoperability. This allows companies to better understand their systems and interact seamlessly with other technologies via open interfaces [20].<\/p>\n\n\n\n

Another decisive factor is the cost savings, as no licensing fees are incurred and powerful software solutions can still be used [21]. These advantages make the open-source approach an attractive option for companies looking for cost-efficient, flexible and innovative software solutions to record their energy consumption. Large companies such as Microsoft, Google and Bosch are becoming increasingly active in the development of OSS. Bosch, for example, has launched several open-source technologies in the field of Industrial IoT, Digital Twins and Smart Building Solutions in the form of an IoT Suite [22]. By making use of these technologies, small and medium-sized companies can also operate on an equal footing with international corporations.<\/p>\n\n\n\n

For these reasons, the open-source LoRaWAN network server ChirpStack is used. This is software developed by the community for use within its own infrastructure. The network server receives the data from the gateways and forwards it to the corresponding applications. It acts as an intermediary between the gateways and the applications. Communication can take place via various communication protocols. In the field of IoT, Message Queuing Telemetry Transport (MQTT) can be used in conjunction with LoRaWAN. MQTT is a lightweight protocol that enables the efficient and scalable transmission of messages. This is particularly important for wireless networks such as LoRaWAN.<\/p>\n\n\n\n

MQTT’s publish-subscribe model is well suited for LoRaWAN-based IoT applications where sensors can publish measurement data and various applications can subscribe to this data. MQTT additionally offers features such as message queuing and quality of service to prevent data loss and ensure robust communication in wireless networks [23].<\/p>\n\n\n\n

If the energy monitoring system used already supports MQTT, the measurement data can be integrated directly from the network server. In some cases, however, this support is not provided or companies may wish to send the data in parallel to other applications \u2013 for example, to save it in a time series database in order to obtain historical information for data analyses or forecasts.<\/p>\n\n\n\n

Node-RED can be used as an intermediate component here. Node-RED is an OSS that offers a graphical interface for linking different data sources and target systems. It enables visual programming of so-called flows, in which individual nodes are connected to each other in order to route data from a source to a target application. If required, data can be filtered and converted into a different format or structure to adapt it to the requirements of different systems. The transformed data can then be sent to different target systems using different communication protocols. Node-RED enables efficient and customizable data processing between the energy monitoring system and other target systems. This enables a seamless integration and use of the data for different purposes.<\/p>\n\n\n\n

Prototype implementation and evaluation<\/h2>\n\n\n\n

For evaluation purposes, three prototypes were constructed and installed at two different locations. The first prototype is a fully mobile energy meter that was installed at Stuttgart University of Applied Sciences. It is currently being used to continuously record electricity consumption in a test laboratory at the university.<\/p>\n\n\n\n

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Figure 3: Mobile prototype of the smart meter retrofit system.<\/em><\/em><\/figcaption><\/figure>\n<\/div>\n\n\n\n
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This mobile prototype enables measurement between a CEE three-phase socket (16A, 400V, 5-pin) and the consumer. Another option is to connect 220V consumers via grounded sockets using a three-phase current distributor and read out accordingly (Fig. 3).<\/p>\n\n\n\n

In collaboration with Robert Bosch GmbH, two further prototypes were designed at the Schwieberdingen site and installed in power distribution units on two buildings. All three prototypes are based on commercially available hardware components and use the same software. The prototypes at Bosch and the university differ only in the use of the LoRaWAN network server. <\/p>\n<\/div>\n<\/div>\n\n\n\n

While the university’s prototype uses TTN cloud services, Bosch has opted for an on-premise solution due to the company’s security guidelines. An on-premise solution is also currently being evaluated at the university. The transmitted data contains information on voltage, current, power in kW and energy in kWh. These can be easily integrated into an energy monitoring system.<\/p>\n\n\n\n

The system has great potential, as it is not only cost-effective thanks to the use of standardized IoT technologies and open-source software, but can also be installed quickly and without complex structural measures. The setup on a three-phase power distribution board with three individual conductors each consists of three CT 18 50\/1A current transformers, a Berg BME462 smart meter, a Dragino RS485 to LoRaWAN module and a Dragino LPS8N indoor LoRaWAN gateway.<\/p>\n\n\n\n

The total costs for the hardware used with a LoRaWAN gateway amount to approximately 1200 euros, and costs without a gateway to approximately 950 euros, not including costs for installation by an electrician. Depending on the infrastructure to be covered, the LoRaWAN gateway only needs to be purchased once. It is also highly scalable and can be adapted to individual requirements. The successful installation and continuous evaluation make the developed retrofit solution a promising tool for the efficient monitoring and control of energy consumption in industrial properties.<\/p>\n\n\n\n

This article was created as part of the impulse project “SenSim4iCity <\/em>\u2013 Sensors and Simulation for Energy Efficiency and the Environment”, at the Institute for Applied Research at Stuttgart University of Applied Sciences in collaboration with Robert Bosch GmbH as a project partnerat the Schwieberdingen site. The result presented here is based on the findings from Sub-Project 2, entitled “Smart Wireless Solutions for Industrial Buildings”.<\/em><\/em><\/p>\n

Bibliography <\/h2>[1] Klimaschutz in Zahlen \u2013 Aktuelle Emissionstrends und Klimaschutzma\u00dfnahmen in Deutschland, Bundesministerium f\u00fcr Wirtschaft und Klimaschutz. BMWK. Berlin 2022\r
[2] Dena-Leitstudie: Integrierte Energiewende \u2013 Impulse f\u00fcr die Gestaltung des Energiesystems bis 2050, Deutsche Energie Agentur (dena). Berlin 2018\r
[3] Berg Energie GmbH: Berg Energie GmbH. URL: berg-energie.de\/wie-energiemonitoring-zur-steigerung-der-betrieblichen-effizienz-beitraegt\/, Abrufdatum 19.12.2023.\r
[4] Deutsche Energie Agentur GmbH (dena): Energieeffizienz durch Digitalisierung \u2013 Daten als Potenziale f\u00fcr Energiewende und Klimaschutz. Berlin 2023.\r
[5] Rusch, S.: Industr.com. Q-LOUD. 2019. URL: www.industr.com\/de\/mit-retrofit-zum-smarten-energiedatenmanagement-2356432, Abrufdatum 19.12.2023.\r
[6] EHA \u2013 Energie Handels Gesellschaft mbH & Co. KG (EHA): EHA. 2020. URL: www.eha.net\/blog\/details\/zwischenzaehler-strom-untermessung-strom.html#:~:text=Die%20Unterz%C3%A4hler%20erfassen%20den%20Stromverbrauch%20einzelner%20Verbraucher%20%28z.,und%20erm%C3%B6glichen%20so%20die%20exakte%20Zuordnung%20des%20Stromverbrauch, Abrufdatum 19.12.2023.\r
[7] Jehle, R.: Powertage. Tesenso GmbH \u2013 IoT Solutions. 2022. URL: content-powertage.conteo.site\/de\/c\/iot-retrofit-loesung-fuer-energiezaehler-schafft-planungsgrundlagen-fuer-industrieareal.22201, Abrufdatum 19.12.2023.\r
[8] GMS \u2013 Mediaservices: GMS -Mediaservices. 2021. URL: www.gms-mediaservices.de\/news-2021\/retrofit-loesungen-fuer-smarte-gebaeude\/, Abrufdatum 19.12.2023.\r
[9] Bachor, M.; Freunek, M.: IoT-L\u00f6sungen als Alternative zum klassischen Smart Metering. In: Realisierung Utility 4.0, Band 2. Wiesbaden 2019.\r
[10] Pereira, C. J.: Industry of Things, Q-Loud GmbH. 2018. URL: www.industry-of-things.de\/nicht-ohne-mein-m-bus-smartes-energiemanagement-dank-retrofit-a-739328\/, Abrufdatum 19.12.2023.\r
[11] Berg GmbH: www.berg-energie.de. 2021. URL: www.berg-energie.de\/wp-content\/uploads\/2021\/09\/Datenblatt_BME_462.pdf, Abrufdatum 19.12.2023.\r
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[13] Berg GmbH: www.berg-energie.de. 2023. URL: berg-energie.de\/stromwandler-funktion-anwendung\/, Abrufdatum 19.12.2023.\r
[14] Berg GmbH: www.berg-energie.de. 2021. URL: www.berg-energie.de\/wp-content\/uploads\/2021\/02\/Datenblatt_KBR_18.pdf, Abrufdatum 19.12.2023.\r
[15] Deos AG: LoRaWAN in der Geb\u00e4udeautomation. Rheine 2021.\r
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[19] Forschungsbeirat der Plattform Industrie 4.0\/acatech (Hrsg): Open Source als Innovationstreiber f\u00fcr Industrie 4.0. M\u00fcnchen 2022.\r
[20] Bosch Connected Industry: Bosch Connected Industry \u2013 Digital Twins und Ecosystem. URL: www.bosch-connected-industry.com\/de\/en\/portfolio\/bosch-semantic-stack\/ecosystem, Abrufdatum 14.11.2023.\r
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[23] Amazon AWS: Amazon AWS. URL: aws.amazon.com\/de\/what-is\/mqtt\/, Abrufdatum 19.11.2023.<\/div>

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