Pregled bibliografske jedinice broj: 899959
Quadratic Programming-based Electric Vehicle Charging Optimisation combining Charging Cost and Grid Power Peak Minimisation
Quadratic Programming-based Electric Vehicle Charging Optimisation combining Charging Cost and Grid Power Peak Minimisation // 12th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES)
Dubrovnik, Hrvatska, 2017. str. 1-19 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 899959 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Quadratic Programming-based Electric Vehicle Charging Optimisation combining Charging Cost and Grid Power Peak Minimisation
Autori
Škugor, Branimir ; Topić, Jakov ; Deur, Joško
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Skup
12th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES)
Mjesto i datum
Dubrovnik, Hrvatska, 04.10.2017. - 08.10.2017
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Load levelling, charging cost minimisation, linear/quadratic programing, modelling, electric vehicle fleet, isolated energy system
Sažetak
This paper deals with charging optimisation of an electric vehicle (EV) fleet, which is aimed at real-time applications which includes both charging cost and peak power minimisation. It is shown that the optimal charging problem which includes these two criteria can be modelled as a quadratic optimisation problem, and can, thus, be solved with widely available and computationally efficient quadratic programming solvers. The corresponding quadratic cost function is extended with a single, free parameter, in order to enable tuning of relative significance of charging cost- and peak power-related sub-cost functions. The functionality of the proposed charging optimisation approach is demonstrated for the case of an isolated electrical energy system and hypothetical EV fleet of the National park Mljet. The time distributions, needed as inputs for charging optimisation, are obtained by using appropriate EV models and available driving cycles and related schedules of the particular fleet. Finally, benefits of using the presented charging optimisation method are presented based on comparison with respect to uncontrolled charging (charge when connected) results in terms of charging cost and peak power values.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb