As part of the LEAP-RE project portfolio, SETaDISMA aims to tackle the African mini-grid sector as a whole, addressing the challenging topics of technological, energy planning, digitalization research and development and related capacity building/ The project focuses focuses on communities to be electrified for the first time (green-field projects), as well as brown-field cases where old mini-grids are repowered including renewable sources.
Data collection: a key step to understand electricity users’ needs
In order to tackle SETADISMA objective to study brown and green-field mini-grid together with the inclusion of digital technologies and fully integrated socio-economic models, data collection is an important step in designing effective projects. This is a necessary condition for developing mini-grid systems to implement decentralized energy systems, as layed out by the latest global market analysis conducted by IEA. The data collection methodology involves mapping customers based on their socio-economic status and geographical location, as well as performing a cluster sampling of targeted customers, such as households, commercial businesses, schools, and hospitals.
One of the regions that was studied by Strathmore University for SETaDISMA is Faza Island, in the coast of Kenya. Overall, the island shows great potential for renewable energy production, particularly solar, that could power the mini-grid in the future. The data collected provided insights into the impact of the existing diesel mini-grid on the quality of life of the close to 6,000 connected customers. The majority of the households reported significant improvements in their energy access, with a corresponding increase in their productive activities. The mini-grid also provided reliable and affordable energy, which helped to reduce the financial burden of energy expenses for the households. However, the data collection process also revealed some challenges that the households faced. For instance, some households reported difficulty in paying for the electricity consumed due to financial constraints. The mini-grid also faced technical challenges, such as power outages, which affected the reliability of the electricity supply.
The data collection experience for the connected on-grid and off-grid population on Faza Island highlights the importance of understanding the impact of energy access interventions on the communities they serve. It also underscores the need for continued monitoring and evaluation to identify and address any challenges that may arise. The insights gained from this data can help energy providers and policymakers optimize the mini grid service and plan for its expansion to serve more households. Understanding the consumption patterns of the local community will enhance future operations and planning and the quality of life of the community.
Energy modelling, a tool for sizing and optimizing microgrids for local circumstances
In the context of SETaDiSMA, computer-based simulation and mathematical optimization of minigrids is a core activity. The project aims at identifying state of the art methodologies for resource availability, demand and supply technologies modelling. Research team from Politecnico di Milano has recently published an open access research article on the journal Renewable and Sustainable Energy Transition describing a set of new features developed for the open source microgrid sizing software MicroGridsPy.
The original version of the model takes into account twenty years of evolving electricity demand, and identifies the optimal combination of PV panels, wind turbines, batteries and size of back-up diesel generator to satisfy the demand at the minimum installation and operation costs, given the local availability of resources. Thanks to the newly implemented features the software is now capable of modelling third generation microgrids and their eventual future connection to the national grid, and optimize the system not only by minimizing the total costs but by means of a two-objective optimization optimize also greenhouse gases emissions. Finally, the software can now size new microgrids (greenfield) or act on existing systems (brownfield). The model is then tested on two case studies, one in Rwanda and one in Mozambique to showcase the interaction of the different features implemented.
