Pregled bibliografske jedinice broj: 744046
Stochastic Model Predictive Control for Optimal Economic Operation of a Residential DC Microgrid
Stochastic Model Predictive Control for Optimal Economic Operation of a Residential DC Microgrid // Proceedings of the 2015 IEEE International Conference on Industrial Technology, ICIT 2015
Sevilla, Španjolska, 2015. str. 505-510 doi:10.1109/ICIT.2015.7125149 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Stochastic Model Predictive Control for Optimal
Economic Operation of a Residential DC Microgrid
Autori
Gulin, Marko ; Matuško, Jadranko ; Vašak, Mario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 2015 IEEE International Conference on Industrial Technology, ICIT 2015
/ - , 2015, 505-510
ISBN
978-1-4799-7799-4
Skup
IEEE International Conference on Industrial Technology, ICIT 2015
Mjesto i datum
Sevilla, Španjolska, 17.03.2015. - 19.03.2015
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Microgrid ; Stochastic Model Predictive Control ; Linear Program ; Power Flow Optimization ; Chance Constraints
(microgrid ; stochastic model predictive control ; linear program ; power flow optimization ; chance constraints)
Sažetak
In this paper we present power flow optimization of a residential DC microgrid that consists of photovoltaic array, batteries stack and fuel cells stack with electrolyser, and is connected to the grid via bidirectional power converter. The optimization problem aims to minimize microgrid operating costs and is formulated using a linear program that takes into account the storages charge and discharge efficiency. To account for power predictions uncertainty, optimization problem is defined in a stochastic framework by using chance constraints. Since we assume that the error in realization of power predictions will be compensated by utility grid, chance constraints are defined for power exchange between the microgrid and the utility grid. Finally, we investigate a stochastic model predictive control for the closed-loop power management in the microgrid. Performance verification of the proposed approach is performed on simulations for two-month period.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Temeljne tehničke znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb