Advanced Restoration Management Strategies in Smart Grids: the Role of Distributed Energy Resources and Load Priorities
dc.authorid | Ahmadi, Bahman/0000-0002-1745-2228 | |
dc.authorid | Ozdemir, Aydogan/0000-0003-1331-2647 | |
dc.authorscopusid | 56487372400 | |
dc.authorscopusid | 26665865200 | |
dc.authorscopusid | 7006505111 | |
dc.authorwosid | Ahmadi, Bahman/Gsd-7380-2022 | |
dc.authorwosid | Ceylan, Oguzhan/Aag-1749-2019 | |
dc.authorwosid | Ozdemir, Aydogan/A-2223-2016 | |
dc.contributor.author | Ahmadi, Bahman | |
dc.contributor.author | Ceylan, Oguzhan | |
dc.contributor.author | Ozdemir, Aydogan | |
dc.date.accessioned | 2025-03-15T20:06:54Z | |
dc.date.available | 2025-03-15T20:06:54Z | |
dc.date.issued | 2025 | |
dc.department | Kadir Has University | en_US |
dc.department-temp | [Ahmadi, Bahman] Univ Twente, Facul Elect Engn Math & Comp Sci, Enschede, Netherlands; [Ceylan, Oguzhan] Kadir Has Univ, Dept Management Informat Syst, Istanbul, Turkiye; [Ozdemir, Aydogan] Kadir Has Univ, Dept Elect & Elect Engn, Istanbul, Turkiye | en_US |
dc.description | Ahmadi, Bahman/0000-0002-1745-2228; Ozdemir, Aydogan/0000-0003-1331-2647 | en_US |
dc.description.abstract | Fast restoration following long outages is a challenge in the smart city management process. It is necessary to accurately characterize the real operating conditions of the system for optimal restoration. This study focuses on two key factors of a practical distribution system restoration. The first factor is cold load pickup (CLPU), which commonly occurs after an outage and is caused by thermostatically controlled loads. A time-dependent CLPU is modeled to accurately describe the restored load behaviors. The second factor is the effect of the distributed generators (DG), energy storage systems (ESSs), and load priority factors on the system's restoration process. To address this challenge, a robust optimization model is proposed that fully considers the effect of DG, and ESS units and uncertainty of CLPU. The proposed models are tested on the IEEE 33-node and 69-node test systems using the Advanced Grey Wolf Algorithm (AGWO). The simulation scenarios are designed to uncover optimal scheduling strategies for the restoration process corresponding to each Pareto solution of a previous study. The results are discussed for several distinct initial conditions. Moreover, a comparative evaluation is done, contrasting the outcomes achieved through the AGWO algorithm with those stemming from alternative heuristic methods. | en_US |
dc.description.sponsorship | EU [957682]; The Scientific and Technological Research Council of Turkey TUBITAK | en_US |
dc.description.sponsorship | The funding for this research is provided by the EU HORIZON 2020 project SERENE, grant agreement No 957682, and the "117E773 Advanced Evolutionary Computation for Smart Grid and Smart Community" project, conducted under the 1001 Project framework organized by "The Scientific and Technological Research Council of Turkey TUBITAK". | en_US |
dc.description.woscitationindex | Science Citation Index Expanded | |
dc.identifier.doi | 10.1016/j.compeleceng.2025.110196 | |
dc.identifier.issn | 0045-7906 | |
dc.identifier.issn | 1879-0755 | |
dc.identifier.scopus | 2-s2.0-85218891617 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.uri | https://doi.org/10.1016/j.compeleceng.2025.110196 | |
dc.identifier.volume | 123 | en_US |
dc.identifier.wos | WOS:001435820400001 | |
dc.identifier.wosquality | Q2 | |
dc.language.iso | en | en_US |
dc.publisher | Pergamon-elsevier Science Ltd | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Large-Scale Blackout | en_US |
dc.subject | Power System Restoration | en_US |
dc.subject | Smart Grid | en_US |
dc.subject | Robust Optimization | en_US |
dc.subject | Self-Healing | en_US |
dc.title | Advanced Restoration Management Strategies in Smart Grids: the Role of Distributed Energy Resources and Load Priorities | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication |