Pregled bibliografske jedinice broj: 1081214
Mathematical model of flexible multi-energy industrial prosumer under uncertainty
Mathematical model of flexible multi-energy industrial prosumer under uncertainty // 2020 International Conference on Smart Energy Systems and Technologies (SEST): Proceedings
Istanbul, Turska: Institute of Electrical and Electronics Engineers (IEEE), 2020. str. 1-6 doi:10.1109/sest48500.2020.9203240 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1081214 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Mathematical model of flexible multi-energy
industrial prosumer under uncertainty
Autori
Kostelac, Matija ; Pavić, Ivan ; Capuder, Tomislav
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2020 International Conference on Smart Energy Systems and Technologies (SEST): Proceedings
/ - : Institute of Electrical and Electronics Engineers (IEEE), 2020, 1-6
ISBN
978-1-7281-4701-7
Skup
2020 International Conference on Smart Energy Systems and Technologies (SEST)
Mjesto i datum
Istanbul, Turska, 07.09.2020. - 09.09.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
energy markets ; industrial prosumer ; MultiEnergy system ; stochastic optimization
Sažetak
In traditional power systems production always followed consumption, while nowadays consumers are incentivized to take active part in electricity markets. In energy intensive industry large portion of the product cost goes to energy expenses. Thus, optimizing operations based on market signals can create substantial benefits for industrial prosumers. Industries with more than one energy input vector, e.g. electricity and gas, both being bought from their respective day ahead markets are investigated in this paper. The paper introduces enthalpy modeling versus conventional mass flow which increases the scheduling efficiency. Proposed optimization model is based on stochastic mixed integer linear programming where prices of electricity are treated as stochastic process as oppose to deterministic approach usually used. Goal of optimization is to reduce overall energy cost. Also, it must provide bidding strategy for both day-ahead markets. Idea is to reduce market variability by proper device scheduling, utilizing flexibility between energy vectors and behind the meter production of electricity.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb