Abstract
AbstractThe electrical energy grid is currently experiencing a paradigm shift in control. In the future, small and decentralized energy resources will have to responsibly perform control tasks like frequency or voltage control. For many use cases, scheduling of energy resources is necessary. In the multi-dimensional discrete case–e.g., for step-controlled devices–this is an NP-hard problem if some sort of intermediate energy buffer is involved. Systematically constructing feasible solutions during optimization, hence, becomes a difficult task. We prove the NP-hardness for the example of co-generation plants and demonstrate the multi-modality of systematically designing feasible solutions. For the example of day-ahead scheduling, a model-integrated solution based on ant colony optimization has already been proposed. By using a simulation model for deciding on feasible branches, artificial ants construct the feasible search graphs on demand. Thus, the exponential growth of the graph in this combinatorial problem is avoided. We present in this extended work additional insight into the complexity and structure of the underlying the feasibility landscape and additional simulation results.
Funder
Carl von Ossietzky Universität Oldenburg
Publisher
Springer Science and Business Media LLC
Reference72 articles.
1. Baharlouei, Z., & Hashemi, M. (2013). Demand side management challenges in smart grid: A review. In 2013 IEEE Smart Grid Conference (SGC) (pp. 96–101).
2. Beaudin, M., & Zareipour, H. (2015). Home energy management systems: A review of modelling and complexity. Renewable and Sustainable Energy Reviews, 45, 318–335. https://doi.org/10.1016/j.rser.2015.01.046.
3. Behrangrad, M. (2015). A review of demand side management business models in the electricity market. Renewable and Sustainable Energy Reviews, 47, 270–283. https://doi.org/10.1016/j.rser.2015.03.033.
4. Boynuegri, A. R., Yagcitekin, B., Baysal, M., Karakas, A., & Uzunoglu, M. (2013). Energy management algorithm for smart home with renewable energy sources. In 4th international conference on power engineering, energy and electrical drives (pp. 1753–1758).
5. Bremer, J. (2006). Agenten-basierte simulation des planungsverhaltens adaptiver verbraucher in stromversorgungssystemen mit real-time-pricing. Diploma thesis, C.v.O. Universität Oldenburg, Department für Informatik (Abteilung Umweltinformatik)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献