Ancillary services and electric vehicles: An overview from charging clusters and chargers technology perspectives

Sevdari, Kristian; Calearo, Lisa; Andersen, Peter Bach; Marinelli, Mattia

doi:10.1016/j.rser.2022.112666

Cited by 52 publications

(29 citation statements)

References 155 publications

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“…The authors of [14] explain three control possibilities: i) centralized; ii) decentralized; and iii) distributed. Due to the implementation simplicity, the early stage of smart chargers belongs to the centralized control approach [12]. However, recent initiatives follow the distributed control approach introduced in [15].…”

Section: Control Architecture a Smart Chargers State-of-the-artmentioning

confidence: 99%

“…This paper does not intend to be exhaustive on the grid service front but rather evaluates some important well-researched features such as peak-shaving, valley-filling, and phase-balancing actions. Based on previous work [12], [17], we take as state-of-the-art representatives for the centralized control approach the Zaptec charger, while the charger developed in the ACDC project for the distributed control approach from [15].…”

Section: Control Architecture a Smart Chargers State-of-the-artmentioning

confidence: 99%

“…Especially beneficial is the coupling of residential flexibility for the safe operation of the grid with economic and environmental benefits for the EV owner [11]. Previously, smart charger was defined as "a device offering communication, protection and at minimum scheduling or at maximum modulation and phase curtailment for the charging process" [12]. Therefore, by focusing on smart chargers, the main contributions of this paper are as follows:…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Power Modulation and Phase Switching Testing of Smart Charger and Electric Vehicle Pairs

Sevdari

Striani

Andersen

et al. 2022

2022 57th International Universities Power Engineering Conference (UPEC)

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De-coupling transport sector from the use of petroleum is giving way to the rise of electric mobility. As compromising the user's comfort is not an option managing the power system becomes a tall challenge, especially during peak hours. Thus, having a smart connection to the power system, such as an electric vehicle (EV) smart charger, is considered part of the solution. This paper focuses on assessing the capabilities of smart chargers in the context of helping the electrical network without compromising the user's comfort. By using a Tesla Model S P85, Renault Zoe, and Nissan LEAF, the paper first evaluates differently controlled (centralized and distributed) smart chargers against the IEC 61851 standard. Second, it tests smart features such as peak-shaving, valley-filling, and phase balancing. Being representatives of the state-of-the-art, both chargers exceed standard requirements and offer new grid service possibilities. However, the bottleneck for providing faster grid services remains the EV on-board charger. The results from this article can help to better simulate the dynamic charging behaviors of EVs.

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Section: Control Architecture a Smart Chargers State-of-the-artmentioning

confidence: 99%

Section: Control Architecture a Smart Chargers State-of-the-artmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Power Modulation and Phase Switching Testing of Smart Charger and Electric Vehicle Pairs

Sevdari

Striani

Andersen

et al. 2022

2022 57th International Universities Power Engineering Conference (UPEC)

View full text Add to dashboard Cite

show abstract

“…For example, peak load management [2], voltage and frequency support [3], and spinning reserves [4]. An overview of different ancillary services provided by EVs to distribution networks can be found in [5] and [6]. Therefore, the penetration of EVs has increased across the globe and it is expected to further increase in the coming future [7].…”

Section: Introductionmentioning

confidence: 99%

A Decentralized Dynamic Pricing Model for Demand Management of Electric Vehicles

2023

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Transportation electrification is considered a green alternative to internal combustion vehicles. However, higher penetration of electric vehicles (EVs) can cause several technical challenges to the power systems, including local equipment overloading. This is especially challenging for distribution systems due to the direct connection of EVs with them. To mitigate equipment overloading, by managing EV loads locally, a dynamic pricing model is proposed in this study. First, a satisfaction function is devised for EVs considering the sensitivity of different EV owners to the battery state of charge and urgency of recharge. Then, a welfare function is developed for the EV fleet operator (EFO) considering the net load of EVs and the electricity price of the upstream grid. To this end, a welfare maximization problem is formulated considering the welfare of EVs and EFO. The problem is then decomposed into the EFO subproblem and EV sub-problem to preserve privacy. Finally, a distributed mechanism is developed to solve the sub-problems iteratively without revealing private information. The performance of the proposed method is analyzed for a residential apartment complex in terms of load management and convergence for different day types (working days and holidays). Simulation results have shown the efficacy of the proposed method in mitigating the overloading of transformers during peak load hours. INDEX TERMSDemand management, dynamic pricing, electric vehicle, equipment overload, pricing model, satisfaction and welfare NOMENCLATURE ABBREVIATIONS VARIABLES BO Building operator , nt x Amount of power charged to EV n at time t CDF Cumulative density function , soc nt Hak-Man Kim (SM'15) received his first Ph.D.

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“…Inside a VPP, EVs are able to provide wind power production matching [11]. In this context autonomous control of electric vehicles is deployed within multiple parking lots for the provision of FTM services [12]. This study focuses on the global control architecture and on its application to a simulated virtual power plant scenario.…”

Section: Introductionmentioning

confidence: 99%

Wind Based Charging via Autonomously Controlled EV Chargers under Grid Constraints

Striani

Sevdari

Marinelli

et al. 2022

2022 57th International Universities Power Engineering Conference (UPEC)

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Smart charging has a strong potential to mitigate the challenges in security of supply caused by the increasing reliance on renewable energy sources (RESs) and electric vehicles (EVs). This paper describes the performances of an autonomous distributed control for coordinating the charge of four parking lots as part of a virtual power plant. The virtual power plant consists of a wind farm and four parking lots located in different areas of the grid and connected to two different feeders. The control architecture is applied to a 24-hour simulation with input data from a wind park, the loading data of two feeders, and user behavior from 68 EVs. The objectives of the architecture are: maximization of the wind power usage to charge the EVs; minimization of feeders overloading; minimization of energy imported from the grid; assurance of sufficient charging fulfillment; wind power variability mitigation. Under simulated conditions, the control architecture keeps the feeder loading below 80% by reducing the power allowance to the parking lot during peak demand. Nonetheless the four parking lots guarantee an energy charged of 10.7 kWh for all EVs starting the charging session with less than 60% state of charge (SOC). The total energy produced by the wind power plant is 4.36 MWh, of which 1.34 MWh is used to charge EVs. The remaining 3.07 MWh is exported to the grid, and only 92 kWh is imported from the grid for charging. Further investigation is needed regarding the wind power variability mitigation, as its reduction is only marginal under simulated conditions.

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Ancillary services and electric vehicles: An overview from charging clusters and chargers technology perspectives

Cited by 52 publications

References 155 publications

Power Modulation and Phase Switching Testing of Smart Charger and Electric Vehicle Pairs

Power Modulation and Phase Switching Testing of Smart Charger and Electric Vehicle Pairs

A Decentralized Dynamic Pricing Model for Demand Management of Electric Vehicles

Wind Based Charging via Autonomously Controlled EV Chargers under Grid Constraints

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