Design and Dispatch of Decentralized Energy Systems using Artificial Neural Networks

authored by: Lukas Koenemann, Astrid Bensmann, Johannes Gerster, Richard Hanke-Rauschenbach
Abstract: Decentralized energy systems, pivotal in transitioning towards a sustainable energy future, require intelligent dispatch strategies for the operation of flexible components in order to integrate inflexible renewable energy sources economically. Conventional rule-based dispatch strategies often fail to optimally exploit the capabilities of flexible system components, while optimal dispatch models, based on the assumption of perfect forecasting, tend to overestimate their performance. This paper investigates the effectiveness of artificial neural networks (ANNs) as a dynamic dispatch strategy for distributed energy systems (DES), evaluating their performance in operational scenarios with a predefined system layout and during the system design optimization phase. Our analysis shows that ANN-based dispatch strategies outperform conventional rule-based methods by up to 8.19% in operational efficiency according to training datasets and by 3.19% in validation datasets. However, they fall short of optimal dispatch strategies by 4.52% and 1.59% in training and validation datasets, respectively. When applied to system design optimization, ANN-based strategies outperform rule-based approaches by 5.80-9.19% but underperform against optimal dispatch designs by 10.63%. Crucially, the study highlights that dispatch strategies not only influence overall system costs but also significantly impact the sizing and configuration of individual system components. This underlines the importance of incorporating intelligent dispatch strategies like ANNs early in the design process to ensure a balanced and cost-effective system architecture.
Organisation(s): Institute of Electric Power Systems
External Organisation(s): WETEC Systems GmbH
Type: Conference contribution
Pages: 2307-2318
No. of pages: 12
Publication date: 30.06.2024
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: General Energy, General Engineering, General Environmental Science
Sustainable Development Goals: SDG 7 - Affordable and Clean Energy
Electronic version(s): https://doi.org/10.52202/077185-0198 (Access: Closed)