EV Charging Schedule in Coupled Constrained Networks of Transportation and Power System

Sun, Yingyun; Chen, Zhengqi; Li, Zuyi; Tian, Wei; Shahidehpour, Mohammad

doi:10.1109/tsg.2018.2864258

Cited by 113 publications

(43 citation statements)

References 34 publications

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“…The coordinated large-scale PEV fleet as mobile storage and demand in the stochastic UC model considering wind energy, hourly demand, and behavior of EV's drivers uncertainty was developed in [19]. In [20], a stochastic UC model integrated with the traffic assignment of large-scale EVs with the high penetration of wind energy was proposed. The traffic network was modeled by EVs travels.…”

Section: B Literature Reviewmentioning

confidence: 99%

Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation

et al. 2020

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This paper proposes a two-stage robust-stochastic framework to evaluate the effect of the battery-based energy storage transport (BEST) system in a day-ahead market-clearing model. The model integrates the energy market-clearing process with a train routing problem, where a time-space network is used to describe the limitations of the rail transport network (RTN). Likewise, a price-sensitive shiftable (PSS) demand bidding approach is applied to increase the flexibility of the power grid operation and reduce carbon emissions in the system. The main objective of the proposed model is to determine the optimal hourly location, charge/discharge scheduling of the BEST system, power dispatch of thermal units, flexible loads scheduling as well as finding the locational marginal price (LMP) considering the daily carbon emission limit of thermal units. The proposed two-stage framework allows the market operator to differentiate between the risk level of all existing uncertainties and achieve a more flexible decision-making model. The operator can modify the conservatism degree of the market-clearing using a non-probabilistic method based on info-gap decision theory (IGDT), to reduce the effect of wind power fluctuations in realtime. In contrast, a risk-neutral-based stochastic technique is used to meet power demand uncertainty. The results of the proposed mixed-integer linear programming (MILP) problem, confirm the potential of BEST and PSS demand in decreasing the LMP, line congestion, carbon emission, and daily operation cost.

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Section: B Literature Reviewmentioning

confidence: 99%

Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation

et al. 2020

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“…By dualizing the inner SOCP, a bi-convex program arises, which is further transformed into an MISOCP. Reference [63] applies the interdependence model in the unit commitment problem, and proposes to use EV fleets as a battery storage unit.…”

Section: Coordinated Operationmentioning

confidence: 99%

Interdependence between transportation system and power distribution system: a comprehensive review on models and applications

Wei

et al. 2019

J. Mod. Power Syst. Clean Energy

110

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The rapidly increasing penetration of electric vehicles in modern metropolises has been witnessed during the past decade, inspired by financial subsidies as well as public awareness of climate change and environment protection. Integrating charging facilities, especially highpower chargers in fast charging stations, into power distribution systems remarkably alters the traditional load flow pattern, and thus imposes great challenges on the operation of distribution network in which controllable resources are rare. On the other hand, provided with appropriate incentives, the energy storage capability of electric vehicle offers a unique opportunity to facilitate the integration of distributed wind and solar power generation into power distribution system. The above trends call for thorough investigation and research on the interdependence between transportation system and power distribution system. This paper conducts a comprehensive survey on this line of research. The basic models of transportation system and power distribution system are introduced, especially the user equilibrium model, which describes the vehicular flow on each road segment and is not familiar to the readers in power system community. The modelling of interdependence across the two systems is highlighted. Taking into account such interdependence, applications ranging from long-term planning to short-term operation are reviewed with emphasis on comparing the description of traffic-power interdependence. Finally, an outlook of prospective directions and key technologies in future research is summarized.

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“…19,20 Cooperative model of PEV and wind power is developed and considered for SCUC with distribution patterns modeling of PEV trips in Shao et al 21 Similarly, stochastic SCUC has been formulated considering coupled power and traffic network for large-scale PEV integrations that provide optimal leaving time of EV fleets and hourly charge/discharge schedules with constraints on EV fleet charge/discharge, power transmission system, and thermal generating units. 22 Electric vehicle aggregator as market entity can coordinate with SO on behalf of the PEV owners and participate in the scheduling for optimally coordinating the charging and discharging of PEVs and gain revenue from the system to provide storage facility. 23 The literature shows works on stochastic SCUC with wind and PEVs integrations; however, the problem lacks the comprehensive formulation comprising the state of severe contingency that is based on N-1 contingency criteria and congestion management.…”

Section: Introductionmentioning

confidence: 99%

Optimal scheduling of electric vehicle in stochastic AC SCUC problem for large‐scale wind power penetration

Gupta

Jain

Sharma

et al. 2019

Int Trans Electr Energ Syst

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Summary Integration of highly volatile wind generation causes reliability and grid issues for system operator (SO). Plug‐in electric vehicles (PEVs) are mobile distributed source of active power that provides opportunity to use their battery storage for wind integration. The coordinated integration of wind volatility and PEVs fleet is studied under security‐constrained unit commitment (SCUC) model. In this regard, a stochastic SCUC with PEVs considering wind integration and line contingency is proposed. Wind volatility and PEVs driving behavior uncertainty is modeled through Monte Carlo simulations (MCS) of large number of scenarios with associated probabilities. This scenario has been reduced by Kantorovich distance (KD) matrix–based backward reduction technique. Moreover, pre‐line and post‐line contingency AC optimal power flow is used for network constraints in SCUC (AC SCUC). Due to consideration of N‐1 security criteria and wind power scenarios, the proposed model is mixed integer nonlinear programming (MINLP), which is computationally heavy and is thus solved by a two‐stage programming Benders decomposition (BD) approach. Different case studies are examined on modified IEEE reliability test system (RTS). Comparative analysis explores the impact on overall operational costs, PEV cost, wind curtailment, and locational marginal price (LMP) for congestion management. Simulation results validate that the proposed model is technoeconomically suitable for large‐scale wind power penetration.

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EV Charging Schedule in Coupled Constrained Networks of Transportation and Power System

Cited by 113 publications

References 34 publications

Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation

Two-Stage Robust-Stochastic Electricity Market Clearing Considering Mobile Energy Storage in Rail Transportation

Interdependence between transportation system and power distribution system: a comprehensive review on models and applications

Optimal scheduling of electric vehicle in stochastic AC SCUC problem for large‐scale wind power penetration

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