Zobrazeno 1 - 10
of 210
pro vyhledávání: '"Pertti Järventausta"'
Publikováno v:
IET Generation, Transmission & Distribution, Vol 18, Iss 16, Pp 2688-2704 (2024)
Abstract Controlled electric vehicle (EV) charging at commercial locations has been seen as the key solution to mitigate the negative effects of uncontrolled charging on the power grid. In the scientific literature, EV users’ willingness to partici
Externí odkaz:
https://doaj.org/article/901c69ee2cb3440992a848b35905b8e4
Publikováno v:
Energies, Vol 17, Iss 13, p 3348 (2024)
The cost reflectivity of electricity distribution network tariffs has been debated in several countries, and various ways to enhance it have been investigated in recent years. However, the recent academic literature regarding the approach based on co
Externí odkaz:
https://doaj.org/article/0902347f460b435aa8049fc614163b33
Publikováno v:
IET Generation, Transmission & Distribution, Vol 17, Iss 14, Pp 3152-3167 (2023)
Abstract Smart electric vehicle (EV) charging is a widely studied topic, and multiple different solutions have been proposed in the scientific literature to execute various demand response objectives. However, most studies use assumptions and simplif
Externí odkaz:
https://doaj.org/article/f531fa9d22604e04aca3671fee5510b8
Autor:
Joel Seppälä, Pertti Järventausta
Publikováno v:
Energies, Vol 17, Iss 6, p 1451 (2024)
In support of the global green transition, numerous policies have been introduced to efficiently address the increasing demand for reliable electricity. However, the impacts of these policies have received limited attention, despite the potential for
Externí odkaz:
https://doaj.org/article/ddc6f39d25ce49e882791f88cf079626
Publikováno v:
IET Generation, Transmission & Distribution, Vol 16, Iss 15, Pp 3027-3035 (2022)
Abstract In the scientific literature, it has been a common assumption that electric vehicles (EVs) draw a constant current during the whole charging session. In reality, EV charging profiles are not linear, and the non‐linearities have recently ga
Externí odkaz:
https://doaj.org/article/c2ea1f7408e4419b9779f50eb8d67ccb
Publikováno v:
IET Generation, Transmission & Distribution, Vol 16, Iss 3, Pp 548-560 (2022)
Abstract The adaptive charging algorithms of today divide the available charging capacity of a charging site between the electric vehicles without knowing how much current each vehicle draws in reality. Thus, they are not able to detect deviations be
Externí odkaz:
https://doaj.org/article/18b3f9ac79ec484692ce2e83fa0df9a1
Publikováno v:
IET Electrical Systems in Transportation, Vol 11, Iss 4, Pp 310-321 (2021)
Abstract The inconvenient nature of non‐ideal charging characteristics is demonstrated from a power system point of view. A new adaptive charging algorithm that accounts for non‐ideal charging characteristics is introduced. The proposed algorithm
Externí odkaz:
https://doaj.org/article/78e7510e523544e397d4cdd1bced6050
Publikováno v:
IET Electrical Systems in Transportation, Vol 11, Iss 4, Pp 405-419 (2021)
Abstract This study assesses the performance of a multivariate multi‐step charging load prediction approach based on the long short‐term memory (LSTM) and commercial charging data. The major contribution of this study is to provide a comparison o
Externí odkaz:
https://doaj.org/article/3293c513ad3e450598f6f87aa7cfa374
Publikováno v:
IET Smart Grid, Vol 4, Iss 6, Pp 599-611 (2021)
Abstract As electric vehicles (EVs) are emerging, smart and adaptive charging algorithms have become necessary to ensure safe and efficient operation of the grid. In the scientific literature, most of the proposed charging control algorithms focus so
Externí odkaz:
https://doaj.org/article/3d9b9ec4839647daaff3d0e350dc9a2e
Publikováno v:
Electricity, Vol 2, Iss 3, Pp 225-243 (2021)
The sub-aggregation of electric vehicles provides significant potential to power systems in the form of ancillary services. This means with smart charging it is possible to shift loads from peak to off-peak hours. For the flexibility from privately o
Externí odkaz:
https://doaj.org/article/ccb418bc7d6f4f59b423208e70a74f1a