Wache, Holger
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Wache, Holger
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- PublikationImpact of prosumers on the accuracy of load forecast with neural networks(2020) Muff, Roswitha; Wache, Holger [in: Abstracts from the 9th DACH+ Conference on Energy Informatics]More 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 Konferenzschrift
- PublikationTechnical 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, Markus [in: Smartgreens 2019. 8th International Conference on Smart Cities and Green ICT Systems, Heraklion, Crete, Greece, May 3-5, 2019. ProceedingsHeraklion, Crete, Greece,]The 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 Konferenzschrift
- PublikationTechnical validation of the RLS smart grid approach to increase power grid capacity without physical grid expansion(SciTePress, 2019) Christen, Ramón; Layec, Vincent; Wilke, Gwendolin; Wache, Holger; Donnellan, Brian; Klein, Cornel; Helfert, Markus [in: Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems]The 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 latter04B - Beitrag Konferenzschrift
- PublikationFlexible capacity addition case study at reduced grid tariff without security of supply(2019) Layec, Vincent; Wache, Holger [in: 2019 16th International Conference on the European Energy Market (EEM)]Energy intensive industries are sensitive both to the reliability and to the costs of their energy supply system. With renewable energy becoming more affordable, their weather dependent over- and under production will cause more volatile and higher spot price, but fees prevent the roll-out of Power- to-Gas. In this paper, we differentiate the new flexible loads of energy conversion and storage like Power-to-X or batteries from the regular loads of the core activity of industries and we design the tariff system of flexible loads in such a way to be financially attractive, by abandoning a security of supply that they actually do not need. In a previous work, the technical functionality of a load management system solving the grid congestion issues was described. Here we aggregate the yearly energy balance and the associated costs in six case studies to verify that the roll-out of the new flexible loads is economically viable. The financial attractiveness of the roll-out of new flexible loads with reduced tariff system and future drop in technology price is verified in all these customers and the tariff reduction for conditional loads is the decisive factor of the profitability in four of them.04B - Beitrag Konferenzschrift
- PublikationUsing consumer behavior data to reduce energy consumption in smart homes(2015) Schweizer, Daniel; Zehnder, Michael; Wache, Holger; Zanatta, Danilo; Rodriguez, Miguel; Witschel, Hans Friedrich [in: Proceedings of the IEEE 2015 International Conference on Machine Learning and Applications]This 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 Konferenzschrift
- PublikationEnergy saving in smart homes based on consumer behavior: A case study(IEEE, 2015) Zehnder, Michael; Wache, Holger; Witschel, Hans Friedrich; Zanatta, Danilo; Rodriguez, Miguel [in: First IEEE International Smart Cities Conference (ISC2-2015)]This paper presents a case study of a recommender system that can be used to save energy in smart homes without lowering the comfort of the inhabitants. We present an algorithm that mines consumer behavior data only and applies machine learning to suggest actions for inhabitants to reduce the energy consumption of their homes. The system looks for frequent and periodic patterns in the event data provided by the digitalSTROM home automation system. These patterns are converted into association rules, prioritized and compared with the current behavior of the inhabitants. If the system detects opportunities to save energy without decreasing the comfort level, it sends a recommendation to the inhabitants.04B - Beitrag Konferenzschrift
- PublikationIntelligent Dynamic Load Management Based on Solar Panel Monitoring(04.04.2014) Wilke, Gwendolin; Schaaf, Marc; Wache, Holger; Gatziu Grivas, Stella; Ryter, Remo; Mikkola, Topi; Bun, Eric04B - Beitrag Konferenzschrift
- PublikationEnterprise Architecture Frameworks for Enabling Cloud Computing(26.08.2010) Tripathi, Uttam Kumar; Wache, Holger; Ebneter, Daniel; Stella Gatziu GrivasCloud computing has emerged as a strong factor driving companies to remarkable business success. Far from just being an IT level support solution cloud computing is triggering changes in their core business models by making them more efficient and cost-effective. This has generated an interest for a lot of companies to try and adopt cloud computing for their existing and new business process. In this research we present an approach which a company can use to analyze if its operations can be positively impacted by moving to the cloud. Further we describe our approach using which the company can make that transition to the cloud.04B - Beitrag Konferenzschrift
- PublikationTowards an Integrated Approach to Assess the Potential of an Enterprise to Mature Knowledge, 5th Conference Professional Knowledge Management - Experiences and Visions(Gesellschaft für Informatik, 25.03.2009) Brun, Roman; Hinkelmann, Knut; Telesko, Rainer; Thönssen, Barbara; Bludau, Hans-Bernd; Koop, Andreas; Hinkelmann, Knut; Wache, Holger [in: Lecture Notes in Informatics (LNI) - Proceedings]In this paper we describe a multi-dimensional framework for knowledge maturing and learning. The framework consists of seven dimensions and supports the assessment of the knowledge management as-is-state in a company as well as the selection of appropriate approaches and methods for a further improvement. The paper also discusses the relationship to comparable approaches (e.g. intellectual capital statements) and ends with open issues for a proper implementation of the maturity framework.04B - Beitrag Konferenzschrift
- PublikationKnowledge Engineering Rediscovered: Towards reasoning Patterns for the Semantic Web(2009) Van Harmelen, Frank; Wache, Holger; Ten Teije, Annette; Noy, Natasha [in: K-CAP '09: Proceedings of the fifth international conference on Knowledge capture]The extensive work on Knowledge Engineering in the 1990s has resulted in a systematic analysis of task-types, and the corresponding problem solving methods that can be deployed for different types of tasks. That analysis was the basis for a sound and widely accepted methodology for building knowledge-based systems, and has made it is possible to build libraries of reusable models, methods and code. In this paper, we make a first attempt at a similar analysis for Semantic Web applications. We will show that it is possible to identify a relatively small number of task-types, and that, somewhat surprisingly, a large set of Semantic Web applications can be described in this typology. Secondly, we show that it is possible to decompose these task-types into a small number of primitive (atomic) inference steps. We give semi-formal definitions for both the task-types and the primitive inference steps that we identify. We substantiate our claim that our task-types are sufficient to cover the vast majority of Semantic Web applications by showing that all entries of the Semantic Web Challenges of the last 3 years can be classified in these task-types.04B - Beitrag Konferenzschrift