Distributed coordination of electric vehicles for conforming to an energy schedule

Karfopoulos, Evangelos; Hatziargyriou, Nikos D.

doi:10.1016/j.epsr.2017.05.018

Cited by 23 publications

(13 citation statements)

References 20 publications

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“…In [6]- [16], the charging of PEVs is managed only at the aggregator level. Analyses performed in these references include power flow calculation, transformer loss of life estimation, and network congestion assessment, among others.…”

Section: Pev Charging Strategiesmentioning

confidence: 99%

An Improved Methodology for the Hierarchical Coordination of PEV Charging

et al. 2019

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This paper proposes an improved methodology for the hierarchical coordination of daily Plugin Electric Vehicle (PEV) charging. The aim is to limit the power supplied by the primary distribution transformer (PDT) while minimizing the energy costs of the aggregators. This methodology consists of an iterative optimization of the total aggregated power at the PDT level, considering the local power constraints of the aggregators and the PEVs with a reduced number of decision variables and constraints which only depend on the number of time intervals. Moreover, it defines the energy boundaries of the optimization problem in each iteration through a proposed method for simulating early charging and delayed charging, considering the power constraints of the aggregators. Otherwise, it evenly distributes the total power among the aggregators, and the local power of each aggregator among the PEVs, maximizing the feasible region of the optimization problem. The proposed methodology is applied to two case studies. The uncertainties related to the charging scenarios are considered by means of Monte-Carlo simulations. The results obtained show that the total power profile is effectively limited, while the profits of the aggregators are not significantly affected by the coordinated approach that is expected to be performed by the Distribution System Operator (DSO). Additionally, to demonstrate the reduction of the impact of PEV charging on the distribution system, the voltage profile, the transformer loss of life and the power and energy losses are reported.

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Section: Pev Charging Strategiesmentioning

confidence: 99%

An Improved Methodology for the Hierarchical Coordination of PEV Charging

et al. 2019

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“…Smart RUE is studying the flexible coupling of power electronics configuration for coupling DER and storage systems; in order to do so, they can take advantage of their in‐house PV and wind systems . Additionally, EM lies within the focus of this institute as well as low‐voltage grids operated by multiagent systems . Smart grid controllers and other hardware are tested using their power‐hardware‐in‐the‐loop (PHIL) simulation environment and their controller‐hardware‐in‐the‐loop (CHIL) simulation environment …”

Section: Smart Grid Labs Descriptionmentioning

confidence: 99%

“…67 Additionally, EM lies within the focus of this institute as well as low-voltage grids operated by multiagent systems. 68 Smart grid controllers and other hardware are tested using their power-hardware-in-the-loop (PHIL) simulation environment and their controller-hardware-in-the-loop (CHIL) simulation environment. 69…”

Section: Greece 3111 Electric Energy Systems Lab National Technicamentioning

confidence: 99%

Smart grid lab research in Europe and beyond

et al. 2019

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Summary In this survey, the objective is to identify current trends in the smart grid research by exploring the work carried out in numerous smart grid labs worldwide. For this purpose, a large number of smart grid labs are identified, and a short description of their activities is given. Fifty‐eight out of the 75 identified labs are located in Europe. Smart grid research is divided into categories, which represent popular topics of research in the field. The predominant category of research is identified to be generation and distributed energy resources (Gen & DER) with 91% of the labs conducting research in this field. Aggregated information is presented regarding the labs, providing a clear idea of the topics of research carried out. Connections between different topics of research are presented, which reveal synergies or collaboration gaps among various smart grid topics. Grid management and Gen & DER and energy storage and Gen & DER have been found to be popular combinations of topics with 55 labs active in both, respectively. In addition, we provide insights on the entities at which research is targeted and consider the evolution of publications produced by the labs on the different categories. An overall increase in publications was observed over the past 11 years in virtually all categories of smart grid research with the most published scientific papers in Gen & DER and electromobility. Collaborations between research institutes have been analyzed, pointing out existing joint research conducted and the huge potential to explore synergies between institutes further. Our work is useful in order to identify the smart grid areas where research is focusing on. This gives a clear picture of potential synergies between labs for knowledge sharing and enhancing their research efforts.

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“…There are two main strategies for scheduling EV charging. The first one is distributed or decentralized strategy [12][13][14], which offers great flexibility to EV owners, allowing them to decide about when and how to charge their EVs. This may give rise to some security problems and overload in the power grid.…”

Section: Literature Reviewmentioning

confidence: 99%

Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm

et al. 2018

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Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem due to the physical structure and conditions of the charging station. In this paper, we tackle an EV’s charging scheduling problem derived from a charging station designed to be installed in community parking where each EV has its own parking lot. The main goals are to satisfy the user demands and at the same time to make the best use of the available power. To solve the problem, we propose an artificial bee colony (ABC) algorithm enhanced with local search and some mating strategies borrowed from genetic algorithms. The proposal is analyzed experimentally by simulation and compared with other methods previously proposed for the same problem. The results of the experimental study provided interesting insights about the problem and showed that the proposed algorithm is quite competitive with previous methods.

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Distributed coordination of electric vehicles for conforming to an energy schedule

Cited by 23 publications

References 20 publications

An Improved Methodology for the Hierarchical Coordination of PEV Charging

An Improved Methodology for the Hierarchical Coordination of PEV Charging

Smart grid lab research in Europe and beyond

Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm

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