2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Syst 2017
DOI: 10.1109/eeeic.2017.7977472
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Provision of frequency regulation by a residential microgrid integrating PVs, energy storage and electric vehicle

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Cited by 7 publications
(4 citation statements)
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“…Since efficient EVs' chargers are available, the main objectives of EVs' charging management systems are to minimize peak loads, to avoid distribution network issues, 37 to regulate the voltage and the frequency of the systems, 38–40 and to reduce the charging EVs' energy costs, 41 peak load, 37 and load variations 42 . The main developed optimization techniques that have been based on linear and nonlinear programming, dynamic programming, and rule‐based methods, as well as metaheuristic methods, such as ant colony optimization, genetic algorithm, and PSO, 42 have been proposed to determine the optimal configuration of EVs' charging systems.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Since efficient EVs' chargers are available, the main objectives of EVs' charging management systems are to minimize peak loads, to avoid distribution network issues, 37 to regulate the voltage and the frequency of the systems, 38–40 and to reduce the charging EVs' energy costs, 41 peak load, 37 and load variations 42 . The main developed optimization techniques that have been based on linear and nonlinear programming, dynamic programming, and rule‐based methods, as well as metaheuristic methods, such as ant colony optimization, genetic algorithm, and PSO, 42 have been proposed to determine the optimal configuration of EVs' charging systems.…”
Section: Related Workmentioning
confidence: 99%
“…EVs are modeled as agents, which can (a) be charged, (b) be parked, or (c) travel 39 . The state of the EV agents is defined by the following parameters: The EV's index, providing information about the position of the charging EV in the low‐voltage system; The model of the EV, which includes the technical characteristics of the vehicles (battery capacity and ECPK); The battery SoC of the EV; The state of the EV, which declares if EV charges, is parked, or takes a trip; The EV's charging signal, declaring if the EV will be charged at a given time interval; The EV's charging delay time, declaring the time that the EV is waiting to be charged, but due to the technical constraints of the network cannot charge; The EV's charging power, in which the EV will be charged, at a given time interval. According to the states of the EVs, at each time step, the SoC of the battery: (a) can be increased, if EVs are charging; (b) can be decreased, if EVs are taking a trip; and (c) can remain the same, if EVs are parked.…”
Section: Description Of the Considered Multi‐agent Systemmentioning
confidence: 99%
“…However, its detailed presentation along with the equations governing its operation is beyond the scope of this paper but can be found in [19]. Furthermore, the MPPT technique chosen in this study is described thoroughly in [20].…”
Section: Description Of the Simulation Modelmentioning
confidence: 99%
“…66) , όπου ο λόγος των ρευμάτων δίνεται (για την περίπτωση του Flyback αντιστροφέα) από την ανάλυση της προηγούμενης ενότητας και την εξίσωση (5.61).Στη συνέχεια, παρατίθενται οι ενδεικτικές τιμές των μεγεθών Gain και � ,ℎ � ,1 Σχήμα 5.14β: Κανονικοποιημένη αρμονική παραμόρφωση της τάσης στο ΣΚΣ, � ,ℎ � ,1 � , συναρτήσει του λόγου ̂ℎ̂1 ⁄ με παράμετρο τον συντελεστή ποιότητας QL, αριστερά) h=2, δεξιά) h=3…”
unclassified