Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid

Jian, Linni; Zheng, Yudian; Xiao, Xinping; Chan, C. C.

doi:10.1016/j.apenergy.2015.02.030

Cited by 158 publications

(49 citation statements)

References 51 publications

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“…The modelling methodology builds upon probabilistic and stochastic methods previously carried out [23][24][25] along with agent-based modelling [26,27], system dynamics approaches [28,29], linear and non-linear programming [30] and stochastic modelling [31,32]. Of note in the present work is its simulated and empirical data-driven approach, which utilises vehicle usage data, building demand, renewable energy generation and ancillary market data to simulate the economic potential of EVs with V2G.…”

Section: Methodsmentioning

confidence: 99%

Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage

et al. 2017

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Citation: GOUGH, R. ...et al., 2017. Vehicle-to-grid feasibility: A technoeconomic analysis of EV-based energy storage. Applied Energy, 192, Additional Information:• This paper was accepted for publication in the journal Ap- 1 Vehicle-to-Grid Feasibility: A Techno-economic Analysis of EV-based Energy StorageRebecca Gough*⁺ Abstract:The potential for electric vehicles to obtain income from energy supplied to a commercial building together with revenue accruing from specific ancillary service markets in the UK is evaluated in this work. A hybrid time-series/probabilistic simulation environment using real-world data is described, which is applied in the analysis of electricity trading with vehicle-to-grid to vehicles, buildings and markets. Key parameters are found to be the electric vehicle electricity sale price, battery degradation cost and infrastructure costs. Three vehicle-to-grid scenarios are evaluated using pool vehicle trip data, market pricing index data and half-hourly electricity demand for a commercial building. Results show that provision of energy to the wholesale electricity market with additional income from the capacity market results in the greatest projected return on investment, producing an individual vehicle net present value of ~£8,400. This is over 10 years for a vehicle supplying energy three times per week to the half-hour day-ahead market and includes the cost of installing the vehicle-to-grid infrastructure. The analysis also shows that net income generation is strongly dependent upon battery degradation costs associated with vehicle-to-grid cycling.

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Section: Methodsmentioning

confidence: 99%

Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage

et al. 2017

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“…The authors in [17] formulate the charging problem as an open-loop cost minimizing problem and an open-loop profit maximizing one. In [18] an event-triggered scheduling scheme for V2G operation is proposed that runs every time an EV connects or disconnects and in [19] an improved version of particle swarm optimization is used for optimal charging. Most of these approaches use a finite-horizon approach: this means that computational complexity is a crucial aspect, since the open-loop optimization routine has to run continuously, usually in a receding-horizon fashion.…”

Section: A Related Workmentioning

confidence: 99%

Adaptive Asymptotic Tracking Control of Uncertain Time-Driven Switched Linear Systems

Yuan

Schutter

2017

IEEE Trans. Automat. Contr.

116

104

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Abstract-Managing grid-connected charging stations for fleets of electric-vehicles leads to an optimal control problem where user preferences must be met with minimum energy costs (e.g. by exploiting lower electricity prices through the day, renewable energy production, stored energy of parked vehicles). Instead of state-of-the-art charging scheduling based on open-loop strategies that explicitly depend on initial operating conditions, this paper proposes an approximate dynamic programming feedback-based optimization method with continuous state space and action space, where the feedback action guarantees uniformity with respect to initial operating conditions, while price variations in the electricity and available solar energy are handled automatically in the optimization. The resulting control action is a multi-modal feedback which is shown to handle a wide range of operating regimes, via a set of controllers whose action that can be activated or deactivated depending on availability of solar energy and pricing model. Extensive simulations via a charging test case demonstrate the effectiveness of the approach.

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“…The ICT, ADA, control, advanced protection, PE, protection, and measurement technologies are inevitable, mainly for REG/DER integration connected to DN with PE converters and supported by energy storage systems (ESSs) [36][37][38][39][40][41][42][43][44][45][46]. The aforementioned technologies can be employed to address and possibly prevent undesired conditions [8], notably voltage instability (sag and swell) conditions, resulting in grid instabilities (voltage, frequency, and angular stability), faults and loss of DERs synchronization.…”

Section: Smooth Sgci Realization (Sgcir)mentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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Smart grids (SGs), as an emerging grid modernization concept, is spreading across diverse research areas for revolutionizing power systems. SGs realize new key concepts with intelligent technologies, maximizing achieved objectives and addressing critical issues that are limited in conventional grids. The SG modernization is more noticeable at the distribution grid level. Thus, the transformation of the traditional distribution network (DN) into an intelligent one, is a vital dimension of SG research. Since future DNs are expected to be interconnected in nature and operation, hence traditional planning methods and tools may no longer be applicable. In this paper, the smart distribution network (SDN) concept under the SG paradigm, has presented and reviewed from the planning perspective. Also, developments in the SDN planning process have been surveyed on the basis of SG package (SGP). The package presents a SDN planning foundation via major SG-enabling technologies (SGTF), anticipated functionalities (SGAF), new consumption models (MDC) as potential SDN candidates, associated policies and pilot projects and multi-objective planning (MOP) as a real-world optimization problem. In addition, the need for an aggregated SDN planning model has also been highlighted. The paper discusses recent notable related works, implementation activities, various issues/challenges and potential future research directions; all aiming at SDN planning.

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Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid

Cited by 158 publications

References 51 publications

Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage

Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage

Adaptive Asymptotic Tracking Control of Uncertain Time-Driven Switched Linear Systems

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

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