In early January, a group of researchers affiliated with the EnerSHelF project published the article “Day-Ahead Electric Load Forecast for a Ghanaian Health Facility Using Different Algorithms” in the peer-reviewed open access journal “energies”
The main scope of the research article is to identify a forecasting algorithm, which is most suitable for electric load-forecasting purposes. To address the peculiarities of the Ghanaian health sector, real load data from one of the project sites – the St. Dominic’s hospital in Akwatia – are used to conduct this comparison. The main idea of performing such forecasts is the possibility to apply a so-called model predictive control for PV-hybrid-systems, which uses predictions to optimize the dispatch of the PV-hybrid-system. It enables a higher efficiency and reliability compared to the widely used rule-based control.
The main finding of the research article is that forecast algorithms based on artificial intelligence, in particular long-short-term-memory neural networks, show the most promising results with regards to plasticity, robustness, and accuracy. However, the authors emphasize that they need to conduct further analysis with data from the field measurements and from the national utility provider. This will help to make a statement regarding the potential to generalize such forecasting methods.
Also, the exceptionally high measurement frequency of the electric load at the measurement sites is unique in this field, which enables the researchers to run simulations close to real conditions. By doing so, the gap between the theoretical development and the practical implementation of such algorithms becomes much smaller.
With the continuous travel restrictions due to the COVID-19 pandemic, the EnerSHelF project team was unable to meet physically during the past months. Accordingly, this year’s annual meeting of all work packages (WPs) took place online. With researchers and project partners from both Ghana and Germany, the meeting was packed with presentations and thriving discussions on recent progress being made across the individual work packages.
The results are as diverse as are the different disciplines involved. Within WP1, a comprehensive literature review of the political economy in Ghana considering the nexus of renewable energy and health facilities is about to be completed. Recently, WP2 managed to instal measurement equipment and PV systems at one pilot site. In WP3, the different sub-WPs developed load models and an installation tutorial for the measurement devices that was used by local partners. Furthermore, they collected blackout and load data from Ghanaian hospitals and set together high-resolution energy meteorological forecasts for the project sites. These forecasts are backed with data collected by newly installed automatic weather stations at all three field sites. Another milestone was the development of an assistance tool for the process of planning and implementing micro grid systems for Ghanaian hospitals as well as the identification of the geographical distribution of energy production, consumption, and infrastructure through GIS data analysis.
A key objective of the meeting was the knowledge exchange among all WPs to find and create synergies and to discuss preliminary results. The fruitful debates proved the increment value of these cross-disciplinary exchange as the different perspectives lead to a holistic project approach. To foster this exchange, individual interviews with researchers and partners were conducted by one of the scholars in WP4 to pinpoint challenges regarding interdisciplinary work but also the advantages it encompasses. On the second day of the meeting, these perspectives have been put into practice by multiple cross-WPs sessions. In the upcoming year, the EnerSHelF team aims to deepen the interdisciplinary exchange through monthly seminars.
Despite the challenges regarding the installation of equipment, collecting data, and conducting interviews in Ghana, the range of steps undertaken in the previous months allows for a promising outlook for the upcoming year 2021.
A team of German and Ghanaian researchers and technicians installed the equipment to collect meteorological data at the health facilties in Kumasi, Akwatia, and Kologo for the EnerSHelF project.
Report by Windmanagda Sawadogo, Samuel Guug, and Edmond Borteye
At the end of September, a team from University of Augsburg (UniA) and West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) met in Ghana to install Automatic Weather Stations (AWS) for the collection of meteorological data at the three pilot sites of the EnerSHelF project. Within the project, both partners collaborate in work package (WP) 3.2 under the lead of UniA to collect and evaluate in situ climate data (You can read interviews with both partners here and here). The aim of the WP is to forecast the key meteorological variables for solar power generation and consumption at the field sites. Thereby, WASCAL acts as an interface between the EnerSHelF project teams in Germany and local stakeholders, for instance, the Ghana Meteorological Agency. Furthermore, they are responsible to provide technical support in collecting and processing observational data from the local observatory networks. The installation of the AWS at the three field sites spread over a period of 14 days and the field trip’s schedule included a close engagement with local authorities, securing materials and civil works, as well as mounting of sensors and testing the installed equipment.