Raspberry PI Microgrid Control System. This project demonstrates a flexible and low cost energy management platform for a grid-connected microgrid, involving an electric vehicle and a Photovoltaics system. A major focus of this work has been simplicity, low costs, scalability, and interoperability with other Distributed Energy Technologies. The system uses the IEEE-1902 Power Lan protocol, Internet Protocol (IP), Python modules, a Raspberry Pi, and Internet of Things (IoT) real-time power meters. It avoids proprietary technologies and communication to increase market penetration and connectivity with other DER technologies as stationary batteries. The flexible system has been tested at an Austrian residential building and shows a 32% reduction in building energy costs and a reduction in EV charging costs of 50%. A major goal of this project is to stimulate interest in microgrids, PV, and electric vehicles. The project has been supported partly by Bioenergy2020+ GmbH.

Controller Movie. Info on the movie: The controller settings have been chosen to charge the EV when energy (generated from the PV and purchased from the utility) is cheaper than 10€cent/kWh (dashed blue line in the movie needs to be below 1000). Please note that a moving average of the last 5 time-steps has been used for this to avoid cycling around the 10€cent/kWh mark and this means that the controller does not react immediately to prices below 10€cent/kWh. The red line represents the power purchased from the utility (including EV), the green line the PV output and the black line the EV charging. The price threshold for charging (in our case 10€cent/kWh) can be freely changed.

Project report





EnRiMa. The aim of the EU project Energy Efficiency and Risk Management in Public Buildings (EnRiMa) was to develop a decision-support system (DSS) to enable building operators to control energy flows in energy-efficient buildings and areas of public use. This process was achieved by setting up an integrated management of conflicting goals such as cost minimization, energy efficiency and emission-reduction requirements as well as risk management. General objectives are: a) adopt an interdisciplinary approach to meet operators energy needs in a more efficient, less costly and less CO2 intensive manner, b) combine the proven methodology for modeling energy flows in buildings with recent advances in effective coping with uncertainties, c) facilitate the operators’ on-site generation dispatch, off-site energy purchases from diverse sources and open positions in energy markets, d) enable long-term planning aimed at increasing energy efficiency, specific analysis of retrofits and/or expansion of on-site energy sub-systems, in order to meet forthcoming EU targets for reducing CO2 emissions, and e) improve energy efficiency and sub-system integration in line with EU targets. Operational objectives are : a) integrated analysis of energy sub-systems and their interactions, b) improved forecasting of electricity and fuel prices as well as energy loads, c) DSS Engine for integrated management of energy-efficient sites, d) customized and user-friendly interface to the DSS Engine linked to a user’s existing ICT architectures, e) testing and quantification of benefits of the DSS engine, f) validation of the DSS in different EU facilities, g) promoting adaptation of the system for various buildings and/or spaces of public use. Beneficiaries: The EnRiMa DSS will help managers of public buildings to find best strategies for adopting and controlling energy resources, such as energy purchases, small-scale on site distribution generation with combined heat and power (CHP) applications or installation of renewable energy technologies.

Austrian EnRiMa test object is online and for Sankey diagram please click here.

Official EnRiMa website

Official EnRiMa leaflet


INNOSPIRIT. The objective of the INNOSPIRIT project is to improve technology transfer of innovations to cities and regions in parts of Austria and Hungary. INNOSPIRIT is funded through the EU’s European Regional Development fund to improve collaboration between regions to enable economic convergence. Campus Pinkafeld and CET started a collabaration to test EnRiMa in a building in Austria. Within the project good practice examples were developed that show how to transfer technology most effectively and how to provide new methodologies and services in cities and regions. The project’s link to EnRiMa is through the EnRiMa test site Campus Pinkafeld, which is one of the two University of Applied Science Burgenland campuses. As an example of exemplary practice concerning technology innovation and transfer, Campus Pinkafeld and CET collaborate and identified a good EnRiMa candidate building within INNOSPIRIT.







DER-CAM. The Distributed Energy Resources Customer Adoption Model (DER-CAM) is a flexible decision support tool for decentralized energy systems, designed by Lawrence Berkeley National Laboratory and developed in the General Algebraic Modeling System (GAMS). Two major versions of this tool are available: Investment & Planning DER-CAM, and Operations DER-CAM:

  • Investment & Planning determines the optimal investment portfolio of Distributed Energy Resources (DER)s based on DER cost and performance characteristics, tariff information , and historic/simulated hourly load and PV generation data, from a given building, campus, or microgrid. This version is mostly used for microgrid design. For more info on microgrids please visit Microgrids at Berkeley Lab.
  • Operations provides detailed optimized operation schedules for existing DERs in a building or microgrid, on a week-ahead basis, using forecasted loads and weather data. Operations DER-CAM is capable of running in 1-hour, 15-min, 5-min, or 1-min time steps. This version has been used for microgrid controllers.

For more information on how to access DER-CAM, please visit Berkeley Lab's DER-CAM site.

CET supported Lawrence Berkeley National Laboratory with new DER-CAM features.



WebOpt. This web based service aims to provide DER-CAM beginners with basic guidance on whether distributed energy resources (DER) are of interest for their use cases. Following technologies can be considered: fuel cells, internal combustion engines, gas turbines, micro turbines, all with and without combined heat and power (CHP), PV, solar thermal, absorption chillers, heat pumps, electric, and heat storage. The tool already contains some basic examples, which can be modified. These examples may be modified by the user to better fit a site’s unique circumstances. After the load profile selection, the user will be prompted to select a tariff, the cost option, and so on, until all of the parameters are specified. Based on the user selections, the solution set will be adjusted to provide ballpark results to the user.

Please click here for more information on WebOpt and how to access it for free.

If you are already a sophisticated DER-CAM user, you can request the full microgrid design tool features from How to access DER-CAM for free.