News-based simulation of electrical load flows

Electric power grids form the backbone of energy supply. Due increasingly growing demand for electrical energy, a continuous grid expansion is essential for many supply regions. Originally, electric power grids were designed as strict top-down structures. This design  requires that the whole grid structure must withstand stress caused by electrical boundary parameters such as currents, voltages and power and therefore was possible to do additions to the power grid, while keeping the top-down structure, without having to do significant changes afterwards.

Nowadays, due to the liberalization of the energy markets and the increasing energy demand, additional feed-in of electrical energy exists in the area of ​​the medium voltage and low voltage levels. Some examples are wind and biomass power stations. However, this changes the situation of the power energy grid, since new feed-in points in operation alter the electrical parameters in the whole range of the affected voltage level. Therefore it is vital to be able to assess the impact of the affected part of the grid well before planning or commissioning new power stations. This led to the development of load flow analysis methods.

In this thesis, the focus is on the implementation of a message-based load flow analysis method based on a forward / backward step method. The OMNeT ++ open-source framework is used to implement the method, which makes it possible to build graph models and to exchange messages between the nodes of the graph.

Furthermore, the integration of the algorithm into the architecture of the simulation platform DAVIC is highlighted. DAVIC is a simulation platform of the institute for computer technology, which is intended to simulate money, communication and energy flows in energies.

As a result, a solution has been implemented which makes it possible to model a simple electrical distribution network consisting of power and line nodes in graph form and to perform a load flow analysis for the given parameters. Furthermore, an approach for a Monte-Carlo simulation was developed. The calculation results are comparable to those of matrices-based methods or commercial software packages.

About Lampros Fotiadis

Lampros Fotiadis MEng, MBA, was born in 1980 in Greece. His passion for engineering led him to receive his Engineer’s degree (MEng equivalent) from the Electrical and Computer Engineering school of the Aristotle University (Greece) in 2004. During his studies, he specialised in Electronics and Computer Engineering. In his diploma thesis, he simulated and implemented a multi-zone fuzzy-logic heating system using a real-time reconfigurable System-on-Chip. Pursuing a holistic approach to solving engineering problems, he successfully earned an MBA degree from the University of Macedonia (Greece) in 2006 and his master thesis examined the relation between European environmental policies and the European Energy market. He worked as an expert IT and Physical security consultant for more than 10 years and his expertise include system design and requirement analysis, system integration and product management. His recent areas of interests are Data Science, Machine Learning, Autonomous Driving and Smart Grids. Since February 2017 he is working as project member at the Institute of Computer Technology in the Energy&IT Group, where he is especially contributing know-how as IT and physical security consultant in the areas of smart grids and industry 4.0.
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