Simulation of a Cellular Energy System including hierarchies and neighborhoods

Energy Informatics

Methodology

Reinhard German¹  Gabriel Dengler¹  Peter Bazan¹ 

[1] Computer Science 7, Friedrich-Alexander-Universität Erlangen-Nürnberg, Martensstraße 3, 91058, Erlangen, Germany;

关键词: Cellular approach;    Energy cell;    Local neighborhoods;    Electric power system;    Simulation;   

DOI  :  10.1186/s42162-022-00243-2

来源: Springer

【 摘 要 】

The massive use of small energy resources and storage units causes a transition from a traditionally centralized to a decentralized energy system. To structure and coordinate the emerging changes in the energy system, the concept of Energy Cells (ECs) was developed. Several ECs can be combined to form a hierarchically superordinate EC. These hierarchically superordinate ECs can in turn be combined and thus form a complex hierarchy. An EC encapsulates coherent parts of an energy system and can communicate as well as exchange energy with other ECs at a different or the same level. It follows the idea of local balance of energy provision and demand. A network of ECs forms a Cellular Energy System (CES). In this paper, we develop a concept for modeling and simulating a CES. We accomplish this by beginning with atomic components like consumers, producers, and storage units and aggregating them with Hierarchical Controllers (HCs). Such a hierarchically structured energy system is part of various proposals. However, we are able to add neighborhood relations by introducing Local Controllers (LCs). This is more realistic and also opens many degrees of freedom for control strategies in such a system. Following the recursive structure of the CES itself, we define recursive functions for visiting the CES architecture and realizing various control strategies. We evaluate our approach in a series of partially randomized scenarios, showing notable differences in the performance of the CES regarding different control strategies in a larger example. We also provide a theoretical analysis of the computational complexity of the suggested approach.

【 授权许可】

CC BY   
© The Author(s) 2022

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