Wache, Holger
Lade...
E-Mail-Adresse
Geburtsdatum
Projekt
Organisationseinheiten
Berufsbeschreibung
Nachname
Wache
Vorname
Holger
Name
Wache, Holger
3 Ergebnisse
Suchergebnisse
Gerade angezeigt 1 - 3 von 3
- PublikationTechnoeconomic review of smart metering applications(Springer, 2023) Efkarpidis, Nikolaos; Geidl, Martin; Wache, Holger; Peter, Marco; Adam, Marc; Ould Abdeslam, Djaffar [in: Smart meters. Artificial intelligence to support proactive management of energy consumption]This chapter represents a brief version of the survey conducted in Efkarpidis et al. (Smart metering applications: main concepts and business models. Springer Nature Switzerland, Basel, pp. 1–164, 2022), where various smart metering applications are presented from the point of different stakeholders’ interests.04A - Beitrag Sammelband
- PublikationSmart metering applications. Main concepts and business models(Springer, 2022) Efkarpidis, Nikolaos; Geidl, Martin; Wache, Holger; Peter, Marco; Adam, MarcThis book presents a large number of smart metering applications from the points of view of different stakeholders. The applications are clustered with respect to three types of stakeholders: (a) end-customers, (b) energy service providers, and (c) authorities/research institutions or other organizations. The goal of the book is to examine the implementation potential for each application, considering the interests and benefits for the key stakeholders, main technical and regulatory requirements, as well as limitations and barriers. A business case for each application is created that can provide guidelines to the stakeholders involved in its realization. The book additionally investigates current business models for smart metering applications. A survey on the current techno-economic potential of such applications is conducted based on a questionnaire filled by various stakeholders. The book will be of interest to academic/research institutions, but also engineers in industry, authorities or other organizations.02 - Monographie
- 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