Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Robust optimization framework for dynamic distributed energy resources planning in distribution networks
This study relies on a dynamic reliability-based model for distributed energy resources (DER) planning in electric energy distribution networks (EEDN) with the aim of maximizing the profit of EEDN companies by increasing income and reducing costs. Load uncertainty is considered in the proposed planning model and the robust optimization (RO) approach is employed to cope with the uncertainty. The developed methodology is illustrated using real-world voltage-dependent load models, including residential, commercial and industrial types. These load models are used in evaluating the reliability cost and energy selling for customers. The reliability cost is calculated based on the total unsupplied load after an outage. Furthermore, a new modified harmony search algorithm is proposed to solve the formulated robust dynamic DER planning problem. The solution of the proposed optimization model provides the size, location, and power factor of DER. Furthermore, the need for transformers or lines upgrades and the best year for DER installation are other decision variables determined by the model. The effectiveness and capability of the developed model have been demonstrated with the aid of a case study based on a typical EEDN. The obtained results indicate that installing DER in EEDNs can relieve congestion on feeders; therefore, it can mitigate or defer upgrade investment. Moreover, if carefully planned, other benefits of DER integration such as reliability improvement and energy loss reduction can be achieved. ; fi=vertaisarvioitu|en=peerReviewed|
Robust optimization framework for dynamic distributed energy resources planning in distribution networks
This study relies on a dynamic reliability-based model for distributed energy resources (DER) planning in electric energy distribution networks (EEDN) with the aim of maximizing the profit of EEDN companies by increasing income and reducing costs. Load uncertainty is considered in the proposed planning model and the robust optimization (RO) approach is employed to cope with the uncertainty. The developed methodology is illustrated using real-world voltage-dependent load models, including residential, commercial and industrial types. These load models are used in evaluating the reliability cost and energy selling for customers. The reliability cost is calculated based on the total unsupplied load after an outage. Furthermore, a new modified harmony search algorithm is proposed to solve the formulated robust dynamic DER planning problem. The solution of the proposed optimization model provides the size, location, and power factor of DER. Furthermore, the need for transformers or lines upgrades and the best year for DER installation are other decision variables determined by the model. The effectiveness and capability of the developed model have been demonstrated with the aid of a case study based on a typical EEDN. The obtained results indicate that installing DER in EEDNs can relieve congestion on feeders; therefore, it can mitigate or defer upgrade investment. Moreover, if carefully planned, other benefits of DER integration such as reliability improvement and energy loss reduction can be achieved. ; fi=vertaisarvioitu|en=peerReviewed|
Robust optimization framework for dynamic distributed energy resources planning in distribution networks
Jeddi, Babak (Autor:in) / Vahidinasab, Vahid (Autor:in) / Ramezanpour, Parviz (Autor:in) / Aghaei, Jamshid (Autor:in) / Shafie-khah, Miadreza (Autor:in) / Catalão, João P.S. (Autor:in) / fi=Vaasan yliopisto|en=University of Vaasa| / orcid:0000-0003-1691-5355 / fi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations| / fi=Ei tutkimusalustaa|en=No platform|
01.09.2019
URN:NBN:fi-fe2019102835089
Scopus: 85063144652
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
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