In this interview, Silvan Rummeny from Cologne University of Applied Sciences highlights the development of the advisor and planning tool MiGUEL. It is an open-source-based library which is developed within the EnerSHelF project and later made available online.
You are involved in the EnerSHelF project within work package 3.3a. Can you tell us about your role in the project and the goal of your work package?
On the one hand, our role in the EnerSHelF project is to improve the knowledge of load data of Ghanaian hospitals. On the other hand, we aim to improve the implementability of micro grid projects in the Ghanaian health sector by developing an advisor and planning tool for such micro grids. The tool can be used to design and evaluate Photovoltaic (PV)-diesel-hybrid systems for Ghanaian health facilities. Our goal is to provide users with suitable solutions on how to change the microgrid design and with which planning strategy they can achieve their micro grid development goals and roadmaps in the most cost-effective way. The target groups are project developers, engineering companies, and private as well as public grid operators who want to implement micro or mini grids.
With the project involvement of Cologne University of Applied Sciences, we continue a long-standing collaboration with St. Dominics Hospital in Akwatia as a valuable use case of a Ghanaian hospital. Under the lead of Prof. Thorsten Schneiders and his students, several photovoltaic power plants were previously installed in Akwatia. At the site, we collect detailed load measurements together with our partner University of Applied Sciences Bonn-Rhein-Sieg.
In EnerSHelF’s annual meeting, you presented MiGUEL. Can you explain what the acronym stands for and why you have developed it?
We called the above-mentioned advisor and planning tool MiGUEL which stands for Micro Grid User Energy Planning TooL. Like the well-known commercial tool HOMER, it is a tool to design and plan micro grids. However, simulations with HOMER were not satisfying since only rudimentary and simple models for the component simulation are used and it is only commercially available in full extent. By contrast, MiGUEL is an open-source-based library that builds on much more precise component simulation models. Furthermore, it is based on a planning guideline to develop micro grids, which I defined in my dissertation (see Fig. 1). The structure of the MiGUEL tool is shown in Fig. 2.
For simulations of the PV power output, we use the single diode and double diode model, which considers and processes the power generation in a more precise way. For this purpose, we access the functions and data of the open-source library pvlib. We are also able to process detailed meteorological data which are collected and simulated in this project by our partners WASCAL and University of Augsburg. For the simulation of a diesel generator, which is commonly used in Ghanaian hospitals, we developed an advanced model. It considers additional fuel consumptions by means of sudden load changes (e.g., when combined with a PV power plant).
Furthermore, detailed models of storages such as battery energy system storages and the power flow in the grid infrastructure are implemented into MiGUEL. A modular load model is under development specifically for Ghanaian hospitals that allows to construct an electrical load profile and to model a demand response potential.
All models are embedded in a micro grid system simulation. This annual or multi-annual simulation can be performed with different system designs and dispatch strategies. At the end of the project, the tool should be available with an additional graphical user interface based on the micro grid planning guideline shown in Fig 1. This enables persons, who are not familiar with programming in python, to install the application.
What were the challenges you faced when developing MiGUEL?
The first version of the design tool was implemented in MATLAB and MATLAB Simulink. However, we wanted to profit from the wider and more accessible open-source community of python as our programming language. The challenge was to transfer the tool into a logic structure which is implemented in python. In the end, we had to rebuild the tool in an object-oriented way and it can now be used in a much more modular way.
Additionally, we wanted to utilize available open-source libraries for the system component simulation. The challenge was to implement these libraries as they have different program structures and standards for the use of data.
In the end, a valuable validation of the tool depends on data. We got some good load and meteorological data from our use case in Akwatia. However, to get good data from other health facilities in Ghana is a challenge. We want to improve the availability of data by collecting electrical loads and meteorological parameters within the EnerSHelF project.
The first results show a potential for reduction of levelized costs of electricity of almost 10% by just adding PV power plants. However, if you want to increase CO2 emission savings and self-sufficiency, a battery must be implemented. There are also PV-Diesel-battery combinations available which are more profitable than the Diesel-only reference case. These results were published and presented on the 15th SDEWES Conference 2020 entitled “Planning of Sustainable and Stable Micro Grids for Ghanaian Hospitals with Photovoltaics”.
What are upcoming objectives for your work package?
Upcoming objectives of work package 3.3a are the completion and supplementation of existing component models in MiGUEL (e.g. the load model for Ghanaian hospitals and consideration of wind power plants). In cooperation with Samer Chaaraoui from University of Applied Sciences Bonn-Rhein-Sieg, we want to add further new or even better dispatch strategies and predictive functions. Furthermore, multifunctional optimization options like single-goal and pareto-optimizations will be implemented.
MiGUEL will be published on github and feedback on the graphical user interface and its functions will be given by our project partner WestfalenWIND Strom GmbH. Finally, MiGUEL and its planning optimization will be validated with data collected on different sites in Ghana. The results will be published internationally in a journal or conference.
Silvan Rummeny is a reasearcher and a doctoral candidate at the Cologne Institute for Renewable Energy (CIRE) of the University of Applied Sciences Cologne (TH Köln). After his bachelor’s degree in biomimetics and master’s degree in renewable energy, he worked on several projects at CIRE. His field of research is the planning of renewable based micro and mini grids. In his doctoral thesis, he creates a planning guideline and advisor planning tool for implementing such cellular power systems. He also is actively involved in the VDE ETG Technical Committee for Cellular Energy Systems. The project, which enables the utility of Bordesholm to achieve a microgrid capability, was awarded by the German Solar Prize 2020.