Institut für Wirtschaftsinformatik
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Ergebnisse nach Hochschule und Institut
Publikation Impact of prosumers on the accuracy of load forecast with neural networks(2020) Muff, Roswitha; Wache, HolgerMore and more prosumers will penetrate the power grid. But how do prosumers affect the accuracy of the day-ahead load forecast? In contrast to related research on prosumers and load forecast, this paper addresses the impact of different shares of prosumers on the load forecast for areas with several households. In order to answer this research question, the load forecast accuracies for a dataset without prosumers is compared to the ones of datasets with different shares of prosumers in an experimental setup using neural networks. A sliding window approach with lagged values up to seven days is applied. Apart from electricity consumption data weather and date data are considered. The conducted tests show, that the mean absolute percentage error increases from about 8% for a dataset without prosumers up to about 39% for a dataset with a share of prosumers of 80%. It can therefore be concluded that prosumers decrease the accuracy of the day-ahead load forecast with neural networks.04B - Beitrag KonferenzschriftPublikation Load management for idle capacity of power grids(Springer, 2019) Layec, Vincent; Wache, HolgerA major issue hampering a rapid substitution of fossil fuels by electricity from sustainable sources is the fear of congestion of the power grid and of associated costs of their reinforcement. The conventional approach prevents any rapid raise of electricity demand by encouraging other energy carriers and sector coupling. However, no approach investigates the utilization of the full capacity of the power grid alone, which are kept idle to provide sufficient reserve for the case of a failure. Therefore, we test a load management approach designed to utilize this reserve capacity. We verify in this paper the correct functionality of the system made of a device manager for cost optimization of schedules and of a grid manager to enforce the respect of power limits of the grid. This novel approach contributes to reduce emission of greenhouse gases without grid reinforcement.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation An Agent-based Model for Simulating Smart Grid Innovations(IEEE, 2018) Schädler, Philippe; Wache, Holger; Merelli, Emanuela; Mielczarski, Władysław; Wierzbowski, Michał; Olek, BłażejIn order to derive indicators for the future grid and market stability, in this paper an agent-based model is intro- duced, to simulate various scenarios. This includes new market designs, market mixes, emerging technological inventions and new regulations. Consumers demand energy based on seasonal variations or changing prices. The suppliers’ production might also depend on seasonal variations, on the local solar irradiation or its flexibility; the ability to react to the market requests. The model introduced in this paper has been used to describe an example scenario of the year 2035, representing a market mix that includes a variety different consumers and suppliers. Eventually it shows, how the model can be applied to model various scenarios and how the resulting grids frequency, the market prices and suppliers profit can be used as indicators for the grid and market stability.04B - Beitrag KonferenzschriftPublikation Shaping aggregated load profiles based on optimized local scheduling of home appliances(Springer, 01.02.2018) Hunziker, Christoph; Schulz, Nicola; Wache, HolgerWe present a new method to control an aggregated electric load profile by exploiting the flexibilities provided by residential homes. The method is based on a common energy price combined with inclining block rates, broadcasted to all households allowing them to minimize their energy provisioning cost. The distributed home energy management systems receive the price signal and use mixed integer linear programming for optimal scheduling of load, storage, and generation devices. The method provides excellent scalability as well as autonomy for home owners and avoids load synchronization effects. As proof of concept, an optimization algorithm for determining a day-ahead price is applied in two case studies. An excellent conformance between a given reference load profile and the resulting aggregated load profile of all households is demonstrated.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation A market-based smart grid approach to increasing power grid capacity without physical grid expansion(Springer, 01.02.2018) Bagemihl, Joachim; Boesner, Frank; Riesinger, Jens; Künzli, Michael; Wilke, Gwendolin; Binder, Gabriela; Wache, Holger; Laager, Daniel; Breit, Jürgen; Wurzinger, Michael; Zapata, Juliana; Ulli-Beer, Silvia; Layec, Vincent; Stadler, Thomas; Stabauer, FranzThe continuous increase of competitiveness of renewable energy in combination with the necessity of fossil fuel substitution leads to further electrification of the global energy system and therefore a need for large-scale power grid capacity increase. While physical grid expansion is not feasible for many countries, grid-driven energy management in the Smart Grid often interferes in customer processes and free access to the energy market. The paper solves this dilemma by proposing a market-based load schedule management approach that increases power grid capacity without physical grid expansion. This is achieved by allocating for a certain class of non-critical flexible loads called “conditional loads” the currently unused grid capacity dedicated to ensuring N−1 security of supply whereas this security level remains untouched for all critical processes. The paper discusses the necessary processes and technical and operational requirements to operate such a system.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Technical Validation of the RLS Smart Grid Approach to increase Power Grid Capacity without Physical Grid Expansion(SciTePress, 05/2019) Christen, Ramón; Layec, Vincent; Wilke, Gwendolin; Wache, Holger; Donnellan, Brian; Klein, Cornel; Helfert, MarkusThe electrification of the global energy system and the shift towards distributed power production from sus- tainable sources triggers an increased network capacity demand at times of high production or consumption. Existing energy management solutions can help mitigate resulting high costs of large-scale physical grid rein- forcement, but often interfere in customer processes or restrict free access to the energy market. In a preceding paper, we proposed the RLS regional load shaping approach as a novel business model and load management solution in middle voltage grid to resolve this dilemma: market-based incentives for all stakeholders are pro- vided to allow for flexible loads that are non-critical in customer processes to be allocated to the unused grid capacity traditionally reserved for N-1 security of supply. We provide a validation of the technical aspects of the approach, with an evaluation of the day-ahead load forecasting method for industry customers and a load optimization heuristics. The latter is tested by a simulation run on a scenario of network branch with provoked capacity bottlenecks. The method handles all provoked critical network capacity situations as expected.04B - Beitrag KonferenzschriftPublikation Poster abstract: SmartStability. A multi-agent simulation environment for flexibility trading in households(Springer, 01.02.2018) Wache, Holger; Künzli, Michael; Schulz, Nicola; Bichsel, Jürg; Hall, MonikaThe increasing number of volatile energy sources, such as solar power plants, challenges the power network operators, the energy brokers as well as the electricity market actors. In this work, a multi-agent based approach will be introduced that allows multiple households to trade flexibilities, on top of the usual selling of produced energy to the paying consumer. Flexibility trading allows different optimisations for different actors. They can slightly shift their electricity consumption, e.g. by turning boilers on/off, to optimise the system (e.g. follow a predefined schedule). Simulation results indicate that a flexibility market consisting of only few households can already help to optimise the system.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Using consumer behavior data to reduce energy consumption in smart homes(2015) Schweizer, Daniel; Zehnder, Michael; Wache, Holger; Zanatta, Danilo; Rodriguez, Miguel; Witschel, Hans FriedrichThis paper discusses how usage patterns and preferences of inhabitants can be learned efficiently to allow smart homes to autonomously achieve energy savings. We propose a frequent sequential pattern mining algorithm suitable for real-life smart home event data. The performance of the proposed algorithm is compared to existing algorithms regarding completeness/correctness of the results, run times as well as memory consumption and elaborates on the shortcomings of the different solutions.04B - Beitrag KonferenzschriftPublikation Smart Stability – Market-economic interaction of smart homes for improved power network stability(2015) Lammel, Benjamin; Schulz, Nicola; Bichsel, Jürg; Wache, Holger; Farooq, Abdul; Hoffmann, Caroline; Mettler, FabianIn this article, the "SmartStability" concept is introduced and first results are shown. The concept is based on the exchange of electrical energy within a network of households that possess temporal flexibilities in consuming or providing energy from or to the network. The exchange is governed by a market-economic negotiation principle between the households. Temporal flexibility is achieved by exploiting thermal capacities of the buildings themselves and those of warm water storages, and by allowing certain temperature bands. Electric and thermal energy forms are coupled by means of heat pumps and electric water boilers. The physical energy exchange takes place via the electrical grid. The behaviour of a SmartStability network has been simulated, based on physical models of the energetic resources within each network unit, and by interlinking the individual units to form the entire SmartStability network within a multi-agent environment. Goal of several simulation scenarios was the adaptation of the time-dependent power consumption profile of the network to a given schedule. Networks consisting of 5 to 100 houses have been simulated. The simulation results show that deviations from schedule can be reduced by approx. 50% by the market-economics-based self-optimization and the resulting intelligent operation of resources. By additionally using battery storages, the deviation from schedule can be further significantly reduced.05 - Forschungs- oder ArbeitsberichtPublikation Enterprise Architecture for Cloud Computing(IEEE, 2012) Aureli, Laura; Pierfranceschi, Arianna; Wache, HolgerIn this paper we describe an approach to graphically externalize the cloud potential of a company, considering ist architectural description. For this purpose it is shown how current architectural description can be extended, in terms of knowledge and graphical representation. The goal is to focus on the most important features and aspects to consider during the evaluation of shifting into a cloud environment. Even if each company has different strategies and approaches to its business activities, there are some domains related to the shift in a cloud environment that should be considered in any case. This paper shows how these main areas can be taken into account in order to extend the architectural representation of a company and express its cloud readiness.04B - Beitrag Konferenzschrift