Pregled bibliografske jedinice broj: 665919
Receding horizon model predictive control for smart management of microgrids under the day-ahead electricity market.
Receding horizon model predictive control for smart management of microgrids under the day-ahead electricity market. // Digital Proceedings of 8th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES Conference / Ban, Marko .... [et al.] (ur.). - Zagreb : University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture , 2013.
Dubrovnik, Hrvatska, 2013. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Receding horizon model predictive control for smart management of microgrids under the day-ahead electricity market.
Autori
Perković, Luka ; Ban, Marko ; Krajačić, Goran ; Duić, Neven
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Digital Proceedings of 8th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES Conference / Ban, Marko .... [et al.] (ur.). - Zagreb : University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture , 2013.
/ - , 2013
Skup
8th Conference on Sustainable Development of Energy, Water and Environment Systems – SDEWES Conference
Mjesto i datum
Dubrovnik, Hrvatska, 22.09.2013. - 27.09.2013
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Model Predictive Control (MPC); Microgrids; Energy Storage; Renewable Energy Sources (RES)
Sažetak
In this paper a Model Predictive Control is applied for investigating the management of grid- connected microgrid consisting of renewable energy sources, unit demand, unit storage and plug-in vehicles. The method optimizes the behaviour of the microgrid system for a predefined time horizon but applies only the solution for the first hour. This procedure is repeated for each hour of microgrid operation. The objective is to maximize the net profit for the system owner. Optimization procedure is under the influence of environment (state) variables, which are generally unknown, but predictable. These are: wind speed, solar insolation and consumer needs for electricity and mobility. Applicability of the method is directly related to uncertainty in input data. Optimization is performed in stochastic programming framework. Input of market electricity price is assumed to be deterministic under day-ahead market. The proposed method is verified for a hypothetical case study. Results are showing potential benefits in optimization of the microgrid management with the proposed method.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Projekti:
120-1201918-1920 - Racionalno skladištenje energije za održivi razvoj energetike (Duić, Neven, MZOS ) ( CroRIS)
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb
