Interview with Prof. Stefanie Meilinger from Bonn-Rhein-Sieg University of Applied Sciences. She explains the overall aim of work package 3 and how different data is used to optimize the operation of PV Solar solutions at health facilities in Ghana.
Work package 3 (WP 3) works on examining ways for the country- and sector specified optimization of PV solutions. What is the overall aim of this work package?
Briefly speaking, WP 3 and its sub work packages look at different factors that are influencing the operation of solar PV hybrid systems at the three selected health facilities. There are two strings of internal and external factors, which must be considered: The available solar resources and the demand for electricity. Our aim is to improve both data bases to enhance and optimize the PV solutions.
The data on solar resources depend on climatic factors and on weather conditions. This information is collected by looking at historical climate data and local measurements performed in Ghana by WP 3.2. The collected data is critical to forecast how much energy can be produced at what time. The measurements include both local solar radiation, temperatures, and other meteorological variables.
The work on the demand for electricity of the health facilities is the domain of WP 3.1. Theresults of their measurements will be analysed to identify typical patterns of electricity demand. The structure of the demand curves is determined by various factors: The size of the health facility, the medical equipment used, and other power consumers. Taken together with the solar resources, it serves as the data base to select the appropriate size of the PV-hybrid system. This is supported and backed by an IT-based tool developed by WP 3.3. Another IT tool developed within WP 3.3 serves an optimal system operation. The collected data help to develop forecasting tools for energy production and demand. These forecasts will be used for automized decision making on how to run the system.
At the end, WP 3.4 is looking at the overall performance of the PV-hybrid solutions to analyse, how the system can be implemented in the surrounding community and beyond. This entails both an electrification strategy as well as a market introduction strategy for the health sector in Ghana.
You are the coordinator for WP 3, but you also lead sub work package WP 3.3. You mentioned that its aim is to develop a tool for dimensioning the PV hybrid system and a digital tool for optimizing system operation. Can you explain the specific purpose and the functioning of the tool in more detail?
WP 3.3 works on two different computerized applications for the system planning and optimized operation. Both are based on different algorithms and mathematical equations that help to set the size of diesel generators, PV-systems, and batteries but also to optimize the operation.
The first application consists of a tool that allows for a reliable and thorough economical dimensioning of the PV-hybrid system. This includes an evaluation of the economic and technical feasibility and the ecological potentials it offers. For this purpose, an existing model has been modified. To achieve comprehensive results, the tool will integrate different features derived from the collected data on solar resources, electricity demand, and other factors. One is a sensitivity analysis with different input parameters such as climatological data on radiation, wind, and temperature. Another feature analyses different configurations of technical components – for instance diesel generators. Furthermore, the tool includes considerations regarding possible constraints such as budgetary matters, local restrictions, or limited roof area for the installation of PV panels.
The second application is directed at the operation of the PV hybrid system and how to optimize it. Again, the tool relies on meteorological forecasts and energy demand forecasts, which have been developed by WP 3.1 and WP 3.2. The aim of this application is to include a battery- and load management feature. By this, we plan to avoid damage on the battery and generator but also to consider the energy access to and quality of the public grid. All the information will help to teach the system how to act optimal in different settings influenced by weather conditions, possible blackouts, and load structure.
What are the results so far, and the next steps?
Our work depends on the data collected at the field sites but also theoretical considerations. So far, we are only able to use existing historical data from one of the health facilities – Akwatia – where a PV system has been installed in 2016 by Prof. Thorsten Schneiders of WP 3.1. We use this information in first model runs, which combine the data with different system sizes, variations of battery sizes, climatic data, and different diesel usage patterns. As you can see, our model and tool development has started, however, due to Covid-19 we could not start measurements at all field sites yet. All the equipment has arrived in Ghana, but our researchers are not able to install it because of the travel restrictions. At the moment, we are seeking a solution in close collaboration with our Ghanaian partners.
Stefanie Meilinger is a professor for sustainable technologies at the International Centre for Sustainable Development at University of Applied Sciences Bonn-Rhein-Sieg (H-BRS). Her research foci are renewable energies, energy efficiency, sustainable mobility, and sustainable technological transformation processes. She studied philosophy and physics at Johannes Gutenberg Universität Mainz and Indiana University Bloomington, USA, before getting her PhD in environmental science from ETH Zürich in cooperation with the Max Planck Institute for Chemistry in Mainz. She then worked in various positions as a researcher and specialist in the public and private sector (e.g. Max Planck Institute for Chemistry, Environmental Resource Management GmbH, Lufthansa Systems AG, and Deutscher Wetterdienst). In 2013, she was appointed as a professor at H-BRS and is part of various international research projects on sustainable technological processes.