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Pregled bibliografske jedinice broj: 1136885

Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques


Barukčić, Marinko; Varga, Toni; Jerković Štil, Vedrana; Benšić, Tin
Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques // Electronics, 10 (2021), 14; 1648, 25 doi:10.3390/electronics10141648 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1136885 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques

Autori
Barukčić, Marinko ; Varga, Toni ; Jerković Štil, Vedrana ; Benšić, Tin

Izvornik
Electronics (2079-9292) 10 (2021), 14; 1648, 25

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
co-simulation ; computational intelligence techniques ; distributed generation ; optimal allocation and control

Sažetak
The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non- controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co- simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekti:
UIP-2017-05-8572 - Razvoj postupaka kosimulacija programskih alata za primjenu mekog računarstva u elektroenergetici (COPESOC) (Barukčić, Marinko, HRZZ - 2017-05) ( POIROT)

Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Poveznice na cjeloviti tekst rada:

doi www.mdpi.com

Citiraj ovu publikaciju:

Barukčić, Marinko; Varga, Toni; Jerković Štil, Vedrana; Benšić, Tin
Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques // Electronics, 10 (2021), 14; 1648, 25 doi:10.3390/electronics10141648 (međunarodna recenzija, članak, znanstveni)
Barukčić, M., Varga, T., Jerković Štil, V. & Benšić, T. (2021) Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques. Electronics, 10 (14), 1648, 25 doi:10.3390/electronics10141648.
@article{article, author = {Baruk\v{c}i\'{c}, Marinko and Varga, Toni and Jerkovi\'{c} \v{S}til, Vedrana and Ben\v{s}i\'{c}, Tin}, year = {2021}, pages = {25}, DOI = {10.3390/electronics10141648}, chapter = {1648}, keywords = {co-simulation, computational intelligence techniques, distributed generation, optimal allocation and control}, journal = {Electronics}, doi = {10.3390/electronics10141648}, volume = {10}, number = {14}, issn = {2079-9292}, title = {Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques}, keyword = {co-simulation, computational intelligence techniques, distributed generation, optimal allocation and control}, chapternumber = {1648} }
@article{article, author = {Baruk\v{c}i\'{c}, Marinko and Varga, Toni and Jerkovi\'{c} \v{S}til, Vedrana and Ben\v{s}i\'{c}, Tin}, year = {2021}, pages = {25}, DOI = {10.3390/electronics10141648}, chapter = {1648}, keywords = {co-simulation, computational intelligence techniques, distributed generation, optimal allocation and control}, journal = {Electronics}, doi = {10.3390/electronics10141648}, volume = {10}, number = {14}, issn = {2079-9292}, title = {Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques}, keyword = {co-simulation, computational intelligence techniques, distributed generation, optimal allocation and control}, chapternumber = {1648} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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