Reza Fachrizal

Dr. Reza Fachrizal

Uppsala University
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2020 in eTransportation
Verified
Journal Article
Closed access
RFReza Fachrizal
Reza Fachrizal
MSMahmoud Shepero
Mahmoud Shepero
DMDennis van der Meer
Dennis van der Meer
JMJoakim Munkhammar
Joakim Munkhammar
JWJoakim Widén
Joakim Widén

1 February 2022 in Applied Energy
Verified
Journal Article
Open access
RFReza Fachrizal
Reza Fachrizal
MSMahmoud Shepero
Mahmoud Shepero
MÅMagnus Åberg
Magnus Åberg
Joakim MunkhammarJoakim Munkhammar
Joakim Munkhammar

1 June 2021 in Sustainable Energy, Grids and Networks
Verified
Journal Article
Open access
RFReza Fachrizal
Reza Fachrizal
URUmar Hanif Ramadhani
Umar Hanif Ramadhani
JMJoakim Munkhammar
Joakim Munkhammar
JWJoakim Widén
Joakim Widén

4 March 2020 in Energies
Verified
Journal Article
Open access
PDF file
RFReza Fachrizal
Reza Fachrizal
Joakim MunkhammarJoakim Munkhammar
Joakim Munkhammar
The integration of photovoltaic (PV) and electric vehicle (EV) charging in residential buildings has increased in recent years. At high latitudes, both pose new challenges to the residential power systems due to the negative correlation between household load and PV power production and the increase in household peak load by EV charging. EV smart charging schemes can be an option to overcome these challenges. This paper presents a distributed and a centralized EV smart charging scheme for residential buildings based on installed photovoltaic (PV) power output and household electricity consumption. The proposed smart charging schemes are designed to determine the optimal EV charging schedules with the objective to minimize the net load variability or to flatten the net load profile. Minimizing the net load variability implies both increasing the PV self-consumption and reducing the peak loads. The charging scheduling problems are formulated and solved with quadratic programming approaches. The departure and arrival time and the distance covered by vehicles in each trip are specifically modeled based on available statistical data from the Swedish travel survey. The schemes are applied on simulated typical Swedish detached houses without electric heating. Results show that both improved PV self-consumption and peak load reduction are achieved. The aggregation of distributed smart charging in multiple households is conducted, and the results are compared to the smart charging for a single household. On the community level, both results from distributed and centralized charging approaches are compared.

20 January 2024 in eTransportation
Verified
Journal Article
Open access
RFReza Fachrizal
Reza Fachrizal
KQKun Qian
Kun Qian
OLOskar Lindberg
Oskar Lindberg
MSMahmoud Shepero
Mahmoud Shepero
RARebecca Adam
Rebecca Adam
JMJoakim Munkhammar
Joakim Munkhammar

1 September 2021 in Sustainable Cities and Society
Verified
Journal Article
Open access
URUmar Hanif Ramadhani
Umar Hanif Ramadhani
RFReza Fachrizal
Reza Fachrizal
MSMahmoud Shepero
Mahmoud Shepero
JMJoakim Munkhammar
Joakim Munkhammar
JWJoakim Widén
Joakim Widén