Thomas Leber

A generalized load management gateway coupling smart buildings to the grid

Buildings are currently largely passive participants in the electric grid. As functional and residential buildings are responsible for a sizeable share of energy consumption in the industrialized world, use in demand side management schemes is a promising area in a future smart power grid. As each individual building, especially in the residential sector, offers only limited load shifting potential and associated financial gain, acceptance of demand response programs that require manual user interaction is unlikely. Instead, schemes based on automatic control are a viable alternative. This paper proposes a building agent, which acts as load management gateway, autonomously managing a building as a single unit, utilizing load models on one hand and a generic communication scheme that avoids close coupling of building and grid on the other hand. The agent manipulates the consumption profile of the building in a way, which matches the demands of the smart grid and offers the resulting load shifting potential to the grid.

Improving energy efficiency of buildings using data mining technologies

Building automation systems record operation data including physical values, system states and operation conditions. This data is stored, but commonly not automatically evaluated. This historic data is the key to efficient operation and to quick recognition of errors and inefficiencies, a potential that is not exploited today. Instead, today the evaluation during operation delivers only alarming in case of system failures. Analysis is commonly done by the facility manager, who uses his experience to interpret data. Methods from data mining and data analysis can contribute to a better understanding of building operation and provide the necessary information to optimize operation, especially in the area of Heating, Ventilation and Air Conditioning (HVAC) systems. Increases in energy efficiency and can be achieved by automated data analysis and by presenting the user energy performance indicators of all relevant HVAC components. The authors take a first step to examine operation data of adsorption chillers using the X-Means algorithm to automate the detection of system states.

Smart demand response scenarios

Automated demand response has the potential to be an essential future tool for maintaining the balance of supply and demand in electrical energy systems with a very high density of generation from renewable sources. Although this scenario can become true in the near future, only very few actual implementations of automated demand response can be found in Europe. This paper is tackling this by analyzing current demand response implementations, placing them into a matrix of different aspects and strategies, with the goal to provide a systematical basis of current application scenarios of demand response, highlighting barriers and starting points for further development decisions. Recommendations for important and possible near future application scenarios of demand side energy management concepts in Austria are the result of this analysis by a multidisciplinary team of researchers. This paper describes related and important future work for Austria in demand response in context of a defined scenario kit. Aspects and strategies of each scenario are described in the following subsections.

Erfolgsversprechende Demand-Response-Empfehlungen im Energieversorgungssystem 2020

ZusammenfassungAutomatisiertes Lastmanagement hat das Potenzial, in einem zukünftigen, mit Kommunikationsinfrastruktur ausgestattetem Stromnetz durch Verschiebung von elektrischen Lasten trotz einer hohen Dichte an erneuerbarer Erzeugung die Leistungsbalance zu gewährleisten. Dieses Paper stellt eine systematische Herangehensweise vor, die eine umfassende Bewertung und Weiterentwicklung von Lastmanagement-Szenarien ermöglicht. Es wird ein neuer Ansatz zur Integration der Entwicklung und Bewertung solcher Szenarien vorgestellt und vier erfolgsversprechende Modelle von Komponenten zukünftiger elektrischer Energieversorgungssysteme eingehender analysiert. Das Problem fehlender Umsetzungen wird anhand dieser Szenarien beispielhaft für Österreich durch eine interdisziplinäre Betrachtung des Phänomens Lastmanagement hinsichtlich technischer, sozialer, ökonomischer und ökologischer Aspekte untersucht. Ergebnis dieser Betrachtung sind neben Analyseergebnissen eine Bewertung der Szenarien und die daraus gewonnenen Empfehlungen für neue Rahmensetzer und die Forschungsförderung.

Preparations for demand response on a municipal level

The balance of supply and demand in the electric grid is easier to manage with electricity storages built into the system, in Austria, typically pumped storage hydro power stations are used for this purpose. This article discusses necessary preparations for implementing an alternative to conventional electricity storages, by using private, public, and commercial infrastructure of a rural municipality in Lower Austria. The water supply system, waste water system, thermal-, and pumping processes are prepared to being managed as one virtual energy storage, while maintaining user comfort for inhabitants. Implementing this proposed system is the first attempt to analyze the effectiveness and the user acceptance of automated demand response in Austria. Possible targets for demand side management have been identified, measured, modeled, and equipped with demand response technology. The proposed system aims to show that successful demand response is possible with little investment and without compromising the customer comfort.

Smart energy grids in Austria - innovative solutions and concepts

Through the increasing electricity generation from renewable energy sources the power infrastructure not only in Europe received new stimuli to find unique and novel solutions. Especially the integration of information exchange into the infrastructure lead to the definition of the actual research topic of smart grids. Austrian researchers and industry alike have built a strong community over the years that brought quite a number of interesting and innovative approaches and solutions to very different challenges the smart grid still has to face. This work will give an overview on the Austrian solutions and concepts for a smart energy grid.

Modeling renewable energy sources to promote proactivity in the distribution grid

Due to growing share of renewable energies in the last decades, the power grid has to deal with a great amount of unpredictable and volatile energy. In order to protect it from overloads and hence resulting risks, models to predict a-priori the energy produced from renewable energy sources are of great necessity. Such forecast models serve as important tool for the Distribution System Operators (DSOs). In this work, forecast models for photovoltaic (PV) and hydroelectric power generation are presented, aiming to their utilization from the grid operator as tool for scheduling switching activities in the distribution grid. The models are successfully evaluated through recorded power output data, provided by the DSO of Carinthia, Austria.

Software architecture for a smart grids test facility

In the joint smart grids application project “Intelligent low voltage grid” of SIEMENS and Vienna University of Technology, households are emulated with transformers representing photovoltaic facilities and current sinks representing the loads. The purpose is to test new control concepts in small scale before a field trial. One example is the use of smart meter measurement for controlling a local transformers tap changer. For the interconnection and management of the emulation devices, a software infrastructure is needed. In this paper, the basic design of the software components and their interactions are presented. It is a flexible, extendable architecture which consists of a central server and multiple specialized clients. A communication service based on remote procedure calls was written, where Google Protobuf is used for the data exchange. In two applications, the realization of the concept is demonstrated.

Optimizing neighborhood consumption of renewables through clustering and H 2 storage: An economic assessment of an Austrian community

Renewable energy sources make the matching of production and storage in the electric grid a major challenge. Aside of introducing additional storage the possibility of on-site consumption of renewable energy is a valid option. The system boundary is not necessarily a single building, but may consider neighborhoods of buildings, which can be clustered in order to maximize use of local generation. Clusters of producers and consumers achieve a higher on-site consumption ratio and thereby show economic advantages. This is shown in a scenario where clustering of consumers connected to common a PV plant increases the discounted cash flow significantly, making it economically viable without subsidies. For additional benefits also the effect of Demand Side Management (DSM), short and long term storages are investigated.