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Proactive Scheduling of Mixed Energy Resources at Different Grid Levels
University of Applied Sciences and Arts Northwestern Switzerland, Switzerland.
Universita della Svizzera italiana, Switzerland.
University for Continuing Education Krem, Austria.
RISE Research Institutes of Sweden, Digital Systems, Data Science.ORCID iD: 0000-0003-4293-6408
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2024 (English)In: IEEE Transactions on Sustainable Energy, ISSN 1949-3029, E-ISSN 1949-3037, Vol. 15, p. 952-Article in journal (Refereed) Published
Abstract [en]

The optimal utilisation of distribution grids requires the proactive management of volatilities caused by mixed energy resources installed into different grid levels, such as buildings, energy communities (ECs) and substations. In this context, proactive control based on predictions for energy demand and generation is applied. The mitigation of conflicts between the stakeholders' objectives is the main challenge for the control of centralized and distributed energy resources. In this paper, a bi-level approach is proposed for the control of stationary battery energy storage systems (SBES) supporting the local distribution system operator (DSO) at the transformer level, as well as distributed energy resources (DERs) operated by end customers, i.e., EC-members. Model predictive control (MPC)- based and hybrid approaches merging rule- and MPC-based control schemes are evaluated. Simulation studies based on a typical European low voltage (LV) feeder topology yield the performance assessment in terms of technical and economic criteria. The results show an advantage of hybrid approaches with respect to the DSO's cost savings from peak shaving. From the EC's perspective, both hybrid and MPC-based schemes can achieve effective cost savings from proactive energy management.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2024. Vol. 15, p. 952-
Keywords [en]
Controllers; Costs; Electric power distribution; Electric substations; Energy management systems; Energy resources; Level control; Model predictive control; Predictive control systems; Bi-level energy management framework; Cost saving; Deterministics; Distributed Energy Resources; Level controllers; Low-level controllers; Management frameworks; Model-predictive control; Predictive models; RBC; Robust; Stakeholder; Transformer; Uncertainty; Upper level controller; Energy management
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-67990DOI: 10.1109/TSTE.2023.3320055Scopus ID: 2-s2.0-85173370167OAI: oai:DiVA.org:ri-67990DiVA, id: diva2:1814343
Note

The transnational project SONDER has received funding inthe framework of the joint programming initiative ERA-NetSmart Energy Systems’ focus initiative Integrated, RegionalEnergy Systems, with support from the European Union’sHorizon 2020 research and innovation programme under grantagreement No 775970. 

Available from: 2023-11-24 Created: 2023-11-24 Last updated: 2024-06-10Bibliographically approved

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Brännvall, RickardGustafsson, Jonas

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