The EnerSHelF project, coordinated by the Hochschule Bonn‑Rhein‑Sieg (H‑BRS) and carried out in partnership with the Cologne Institute for Renewable Energy (CIRE), Kwame Nkrumah University of Science and Technology (KNUST), University of Augsburg (UniA), the West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) and the Reiner Lemoine Institut (RLI), focused on the optimisation of country‑ and sector‑specific data for the design and operation of photovoltaic‑hybrid systems in Ghana. The work package 3.1, “Electricity demand of the Ghanaian health sector”, produced a detailed load model for the St. Dominic Hospital (SDH) in Akwatia. Two measurement systems were installed: a grid‑analysis set of two UMD 98 devices from PQ PLUS at the generator and transformer houses, and a load‑profiling system that recorded minute‑by‑minute consumption for the hospital’s administration, nursing, and medical departments. Despite challenges with remote data transfer, the collected data revealed a sharp drop in grid supply during midday, attributed to a 90 % self‑consumption of local PV output, and a complete blackout between 17:10 and 17:18 on 26 December 2022, during which all three phases fell from 250.7 V to 0 V. Voltage interruption and dip events were simultaneously logged, confirming a direct link between voltage dips and the blackout. These observations provide the first empirical evidence of PV‑diesel interaction in a Ghanaian hospital setting.

The project also developed and validated the MiGUEL simulation tool, a Python‑based platform that accepts user‑defined load profiles, climate data from PVGIS, and system parameters to generate a PDF report and CSV output for in‑depth analysis. Sensitivity studies were performed by varying a single input parameter across multiple system configurations—grid‑connected and off‑grid—while keeping the base parameters constant. The base scenario used a 15‑minute resolution over the year 2022, a 0.14 US$/kWh electricity price, 1.385 US$/l diesel price, a 3 % discount rate, and a 10‑year lifetime. CO₂ factors of 0.135 kg/kWh for the grid and 0.2665 kg/kWh for diesel were applied. The tool outputs levelised cost of electricity (LCOE) and annual CO₂ emissions, enabling direct comparison of hybrid versus conventional configurations. Although specific numerical results for each variant are not listed in the report, the methodology allows stakeholders to quantify cost and environmental benefits for each design choice.

Beyond the technical deliverables, the project produced a comprehensive database of sector‑specific demand profiles and a validated forecasting model for solar radiation and temperature in Ghana. These data sets are intended for use in system design (WP3.3) and for developing an electrification strategy for the health sector (WP3.4). The MiGUEL tool was presented to university partners in Ghana and Brazil and will be incorporated into vocational training programmes at institutions such as SENAI. The tool will be released on GitHub one to three months after project completion, and its application is planned for other grid‑capable power‑grid projects starting three months post‑completion.

The project ran from 1 June 2019 to 31 May 2022, but due to COVID‑19 travel restrictions it was extended to 31 December 2022, with an additional cost‑neutral three‑month extension concluding on 31 March 2023. The budget was spent as planned, with staff, travel, and measurement equipment being the main cost drivers. No additional funding was required, and no significant changes to the project scope were necessary during implementation. The final report summarises that, despite incomplete data sets, the project achieved its goal of generating reliable load data, validating PV‑diesel interactions, and providing a flexible planning tool that can accelerate the deployment of hybrid renewable energy systems in emerging economies.