An Innovative Two-Level Model for Electric Vehicle Parking Lots in Distribution Systems with Renewable Energy

Shafie‐khah, Miadreza; Siano, Pierluigi; Fitiwi, Desta Z.; Mahmoudi, Nadali; Catalào, João P. S.

doi:10.1109/pesgm.2018.8585937

Cited by 14 publications

(26 citation statements)

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“…In case of industrial and commercial lateral, it is assumed that EVs arrive at the parking lot in the morning and leave by the evening. In order to model uncertainties of an EV owner's behaviour for an industrial/commercial parking lot, a truncated normal distribution has been reported previously [24, 25]. Therefore, SOC, arrival and departure time for each vehicle are generated from truncated normal distribution with random variable x , mean

μ

and standard deviation

σ

.…”

Section: Energy Demand Of Evsmentioning

confidence: 99%

Electric vehicles reactive power management and reconfiguration of distribution system to minimise losses

Singh

Tiwari

2020

IET Generation Trans & Dist

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This study investigates the optimal operation of distribution feeder reconfiguration (DFR) strategy in smart distribution system integrated with electric vehicles (EVs) and wind power generation. A two‐stage framework is proposed for real and reactive power management and DFR. In the first stage, demand dispatch of EVs is coordinated to utilise available wind power and minimise the total load variations. In the second stage, a comprehensive problem formulation is developed to minimise the losses in the system with simultaneous EVs reactive power management and DFR. A genetic algorithm is used to solve this two‐stage optimisation problem. A case study of 33‐bus radial distribution system is presented to highlight the efficacy of proposed approach. The obtained results are quantitatively assessed in terms of losses and node voltages. A comparative benchmarking analysis is presented to substantiate the role of DFR and reactive power capability of EVs in improving the system performance.

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μ

and standard deviation

σ

.…”

Section: Energy Demand Of Evsmentioning

confidence: 99%

Electric vehicles reactive power management and reconfiguration of distribution system to minimise losses

Singh

Tiwari

2020

IET Generation Trans & Dist

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“…Moreover, a comparison between coordinated and uncoordinated charging was provided by the devised model. Shafie-Khah et al [18] propounded a two-level model for EVPLs in renewable-based distribution systems to minimise the overall cost from distribution system operator (DSO) point of view and maximising EVPL and the relevant aggregator profit. In [19], the power flow of EVs due to traffic flow was investigated, and EVPL's charging operations based on traffic pattern were explored.…”

Section: Relevant Literaturementioning

confidence: 99%

“…Therefore, Special Order Sets of Type 2 (SOS2), one of the most common linearisation methods in the literature, is used in order to obtain appropriate function and integrate into MILP framework. Equation (16) states the SOS2 variables while the power flow is approximated by using these variables and constraints in (17) and (18) (19). Similarly, the total charging power of aggregator n can be calculated by summation of every EVPLs' power need P r, n, k, v, s, t…”

Section: Objective Functionmentioning

confidence: 99%

Day‐ahead charging operation of electric vehicles with on‐site renewable energy resources in a mixed integer linear programming framework

Şengör¹,

Erenoğlu²,

Erdinç³

et al. 2020

IET Smart Grid

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The large-scale penetration of electric vehicles (EVs) into the power system will provoke new challenges needed to be handled by distribution system operators (DSOs). Demand response (DR) strategies play a key role in facilitating the integration of each new asset into the power system. With the aid of the smart grid paradigm, a day-ahead charging operation of large-scale penetration of EVs in different regions that include different aggregators and various EV parking lots (EVPLs) is propounded in this study. Moreover, the uncertainty of the related EV owners, such as the initial state-of-energy and the arrival time to the related EVPL, is taken into account. The stochasticity of PV generation is also investigated by using a scenariobased approach related to daily solar irradiation data. Last but not least, the operational flexibility is also taken into consideration by implementing peak load limitation (PLL) based DR strategies from the DSO point of view. To reveal the effectiveness of the devised scheduling model, it is performed under various case studies that have different levels of PLL, and for the cases with and without PV generation.

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“…However, the flexibility behaviour of end users is the same under shiftable load constraint. All end users provide positive energy flexibility as virtual energy producers in time steps 10,11,12,13,19,20, and 21 when they are peak hours of the system according to Table 1. Moreover, Fig.…”

Section: Agent-based Decision-making Evaluationmentioning

confidence: 99%

“…Also, there are several pieces of research to study the impacts of EVs – as green mobility vehicles in smart cities – on energy management problems in SGs [19]. In [20], a two‐level model for the EV parking lot operator has been proposed for empowering parking lot operator to provide energy and reserve in distribution markets. On the other, Shafie‐Khah et al in [21] presented a model to optimise the behaviour of EV aggregator considering its participation in energy and reserve markets.…”

Section: Introductionmentioning

confidence: 99%

Decentralised flexibility management for EVs

Gazafroudi

Keane²,

Soroudi³

2019

IET Renewable Power Generation

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In smart cities, the end users should play an active role to provide the flexibility services in demand response programmes of smart distribution grids. Moreover, electric vehicles (EVs), their main task being providing green transportation, can play an important role in providing distributed energy in smart cities. In this study, a stochastic problem is presented to manage flexibility of end users and charging operation of EVs in the distribution grid. Thus, the end-users, aggregators, and EVs are defined as players in the proposed problem. Additionally, three strategies are presented to manage energy centralised, decentralised, or pseudo-decentralised in the proposed stochastic problem. In the decentralised and pseudo-decentralised approaches, flexibility of consumers is managed autonomously. On the other hand, EVs are utilised independently by their corresponding owners only in the decentralised approach. Also, a 33-bus distribution network is considered to assess the performance of the proposed strategies regarding the expected costs of players and the impact of flexibility on transacted energy through aggregators, and the real-time market. On the basis of simulation results, it is concluded that decentralised strategy to manage energy flexibility and charging operation of EVs by the end users is the win-win strategy for end users and aggregators.

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An Innovative Two-Level Model for Electric Vehicle Parking Lots in Distribution Systems with Renewable Energy

Cited by 14 publications

References 0 publications

Electric vehicles reactive power management and reconfiguration of distribution system to minimise losses

Electric vehicles reactive power management and reconfiguration of distribution system to minimise losses

Day‐ahead charging operation of electric vehicles with on‐site renewable energy resources in a mixed integer linear programming framework

Decentralised flexibility management for EVs

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