Pregled bibliografske jedinice broj: 1011524
Model Predictive Control of Building HVAC System Employing Zone Thermal Energy Requests
Model Predictive Control of Building HVAC System Employing Zone Thermal Energy Requests // Proceedings of the 2019 22nd International Conference on Process Control (PC19) / Fikar, M. ; Kvasnica, M. (ur.).
Štrbské Pleso, Slovačka, 2019. str. 13-18 doi:10.1109/PC.2019.8815225 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1011524 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Model Predictive Control of Building HVAC System
Employing Zone Thermal Energy Requests
Autori
Hure, Nikola ; Martinčević, Anita ; Vašak, Mario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 2019 22nd International Conference on Process Control (PC19)
/ Fikar, M. ; Kvasnica, M. - , 2019, 13-18
Skup
22nd International Conference on Process Control
Mjesto i datum
Štrbské Pleso, Slovačka, 11.06.2019. - 14.06.2019
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
HVAC, cooling, chiller, COP model, zone energy requests, heat losses, demand response, model predictive control, SLP
Sažetak
Control in buildings has been a subject of research interest in the control community for some time. Various control methods have shown a potential for a significant savings in the building operation costs, whereas a large economic gain in the operation of a heating, ventilation and air conditioning (HVAC) system can be obtained by employing information about the building thermal model and the model of actuators, weather conditions, energy demand cost as well as the energy requests in the zones. This paper proposes a model predictive controller for a building chiller that exploits respective information to minimise the cost of cooling in the electricity market with volatile electrical energy prices, while ensuring comfort within the zones and respecting the power demand limitations. Obtained optimal control problem is nonlinear and the minimisation is performed by employing the successive linear programming algorithm within the feasibility region and the gradient algorithm for finding the initial feasible point. A case study HVAC system model is used to validate the performance of the proposed controller in the simulation scenario. Obtained controller minimises the cost of cooling while adhering to the imposed comfort constraints.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Temeljne tehničke znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
