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Pregled bibliografske jedinice broj: 1210118

Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts


Čović, Nikolina; Badanjak, Domagoj; Šepetanc, Karlo; Pandžić, Hrvoje
Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts // 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)
Palermo, Italija, 2022. str. 860-865 doi:10.1109/MELECON53508.2022.9842933 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1210118 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts

Autori
Čović, Nikolina ; Badanjak, Domagoj ; Šepetanc, Karlo ; Pandžić, Hrvoje

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

ISBN
978-1-6654-4280-0

Skup
2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)

Mjesto i datum
Palermo, Italija, 14.06.2022. - 16.06.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
uncertainty ; model predictive control ; battery energy storage ; renewable energy sources

Sažetak
Addressing uncertainty has become a necessity when modeling modern power systems. Many state-of-the-art methods suffer from either poor uncertainty characterization or a high computational burden. This paper proposes a model that is easy to implement, fast to compute, and effective in addressing uncertainty. It is based on the model predictive control algorithm with the addition of uncertainty parameters optimization. For demonstration purposes, the model is applied to a microgrid consisting of a wind turbine, a local load, and battery energy storage. The model seeks to satisfy the local demand at the lowest cost by procuring energy from the battery energy storage, the wind turbine (in its portfolio), or the wholesale market, where wind power output, local demand, and market prices are uncertain parameters. In the presented case study, the upper bounds obtained using our model are close to the perfect information deterministic model values. Hence, this model has a great potential for practical use.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekti:
HRZZ-IP-2019-04-9164 - Aktivno sudjelovanje skupine kućanstava u energetskim tržištima (ANIMATION) (Pandžić, Hrvoje, HRZZ ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Poveznice na cjeloviti tekst rada:

doi ieeexplore.ieee.org

Citiraj ovu publikaciju:

Čović, Nikolina; Badanjak, Domagoj; Šepetanc, Karlo; Pandžić, Hrvoje
Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts // 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)
Palermo, Italija, 2022. str. 860-865 doi:10.1109/MELECON53508.2022.9842933 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Čović, N., Badanjak, D., Šepetanc, K. & Pandžić, H. (2022) Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts. U: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) doi:10.1109/MELECON53508.2022.9842933.
@article{article, author = {\v{C}ovi\'{c}, Nikolina and Badanjak, Domagoj and \v{S}epetanc, Karlo and Pand\v{z}i\'{c}, Hrvoje}, year = {2022}, pages = {860-865}, DOI = {10.1109/MELECON53508.2022.9842933}, keywords = {uncertainty, model predictive control, battery energy storage, renewable energy sources}, doi = {10.1109/MELECON53508.2022.9842933}, isbn = {978-1-6654-4280-0}, title = {Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts}, keyword = {uncertainty, model predictive control, battery energy storage, renewable energy sources}, publisherplace = {Palermo, Italija} }
@article{article, author = {\v{C}ovi\'{c}, Nikolina and Badanjak, Domagoj and \v{S}epetanc, Karlo and Pand\v{z}i\'{c}, Hrvoje}, year = {2022}, pages = {860-865}, DOI = {10.1109/MELECON53508.2022.9842933}, keywords = {uncertainty, model predictive control, battery energy storage, renewable energy sources}, doi = {10.1109/MELECON53508.2022.9842933}, isbn = {978-1-6654-4280-0}, title = {Cost Sensitivity Analysis to Uncertainty in Demand and Renewable Energy Sources Forecasts}, keyword = {uncertainty, model predictive control, battery energy storage, renewable energy sources}, publisherplace = {Palermo, Italija} }

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