Loads management based on Photovoltaic and Energy Storage System
Die Arbeit wurde betreut von Prof. Dr. Ing. Lucian Vinţan (scientific advisor) und Dr. Ing. Arpad Gellert (Coordinator) und ist in englischer Sprache verfasst.
“Urgent and concrete action is needed to address climate change” – this statement starts the chapter about “Climate Change, Energy, and Environment” in the final declaration of the G7 Summit 2015 Declaration (G7 2015). The seven major advanced economies recognize, that the global dependency on fossil fuels and its effect on climate change and global security is one of the biggest threats of our time.
With the German energy transition (“Energiewende”), followed by subsidy programs in many other countries, a lot of effort and money was put in the development of alternative forms of electricity production using renewable sources like wind and solar.
Today photovoltaics (PV) installations enable the decentralized production of electricity from solar at competitive costs in many places around the world, but innovative ideas are required to overcome the fluctuating nature of renewable sources. With properly designed PV installations, only up to 30 % (Quaschning, Weniger and Tjaden 2012) of the produced electricity can be self-consumed. Reasonably sized energy storage systems based on batteries increase this ratio up to 70 % (SolarServer). To further increase it, a more intelligent approach is required.
This dissertation proposes a new approach for an energy management system that optimizes the local, decentralized production and consumption of electricity, based on an energy storage system and a previously developed basic energy monitoring and management system (“FEMS”).
The proposal uses prediction techniques to estimate the future electricity production and consumption. It also takes into account the Added Value of available, manageable loads, in order to establish an energy management schedule. Furthermore a basic toolchain is proposed to support the development and optimization process. Finally a first implementation of the software is provided to evaluate the feasibility of the approach.
The document is structured in six chapters:
Chapter I. “Introduction” (from page 7) describes the evolution of the renewable energy market and how the recent changes are enabling new technologies. It continues with an introduction to the purpose of this thesis. The chapter finishes with a brief overview on the company behind this paper and a presentation of the photovoltaics installation example.
Chapter II. “Concept” (from page 14) discusses, what can be done to optimize the production and consumption of electricity in a scenario with photovoltaics and an energy storage system. It concludes with a proposed architecture for an intelligent energy management system.
Chapter III. “Theory” (from page 26) gives an overview on the state of the art in the fields that are influencing the proposed system. It continues with a description of general functionality and optimization of the applied machine learning system for predictions and finishes with a detailed view on the development toolchain.
Chapter IV. “Implementation” (from page 38) discusses the realization of the proposed architecture. It also presents the “FENECON Energy Management System” (FEMS) device as well as the “FENECON Online-Monitoring”, which were designed and developed by the author prior to this paper, and shows, how the proposed system can enhance the existing functionality to control external devices.
Chapter V. “Result” (from page 50) presents the results of the development toolchain and the simulation of the proposed energy management architecture. It also gives a preview of the expected results when managing real loads and suggests next steps for further studies on the subject.
The paper finishes with a “Conclusion” in Chapter VI. (from page 60).
- Masterarbeit/Dissertation (PDF): Dissertation Stefan Feilmeier – Loads management based on Photovoltaic and Energy Storage System
- Präsentation (PDF): Presentation – Stefan Feilmeier – Loads management based on Photovoltaic and Energy Storage System