Range anxiety of electric vehicles in energy management of microgrids with controllable loads

Esmaili, Masoud; Shafiee, H.; Aghaei, Jamshid

doi:10.1016/j.est.2018.08.023

Cited by 46 publications

(15 citation statements)

References 27 publications

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“…Figure 3a pictures the module assembly of the 24p1s connection as an example. The cells (1) are stacked between two steel jigs (2) and connected in parallel on their positive tab via an aluminium bus bar (3). Figure 3b shows the complete experiment set-up with the module assembly (4) from Figure 3a, a pneumatic cylinder working as a nail penetration trigger mechanism at the first cell (5) and the thermally insulated wires (6) leading from the negative cell tab to the current measurement box.…”

Section: Methodsmentioning

confidence: 99%

“…The ongoing triumphal procession of plug-in hybrid electric vehicles and all-electric vehicles (EV) is accompanied and made possible by the spread of lithium-ion cells and their rapidly falling costs [1]. Range anxiety being still a major concern of customers deciding to acquire an EV [2,3] drives manufacturers to build batteries with higher and higher capacity. This can be done in two ways, either by using a small number of large capacity cells (e.g., BMW i3, Mitsubishi iMiEV) or a greater number of lower capacity cells connected in parallel (e.g., Tesla Model S, VW e-Golf and Nissan Leaf) [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Discharge by Short Circuit Currents of Parallel-Connected Lithium-Ion Cells in Thermal Propagation

et al. 2019

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The increasing need for high capacity batteries in plug-in hybrids and all-electric vehicles gives rise to the question of whether these batteries should be equipped with a few large capacity cells or rather many low capacity cells in parallel. This article demonstrates the possible benefits of smaller cells connected in parallel because of discharge effects. Measurements have been conducted proving the beneficial influence of a lower SoC on the thermal runaway behaviour of lithium-ion cells.A second test series examines the short circuit currents during an ongoing thermal propagation in parallel-connected cells. With the help of a developed equivalent circuit model and the results of the test series two major system parameters, the ohmic resistance of a cell during thermal runaway R tr and the resistance post thermal runaway R ptr are extracted for the test set-up. A further developed equivalent circuit model and its analytical description are presented and illustrate the great impact of R ptr on the overall discharged capacity. According to the model, cells with a capacity of no more than C cell = 10-15 Ah and a parallel-connection of 24 cells show the most potential to discharge a significant amount.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discharge by Short Circuit Currents of Parallel-Connected Lithium-Ion Cells in Thermal Propagation

et al. 2019

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“…Also, many research works used electric vehicles (EVs) as a favorable strategy to meet the increasing environmental concerns and energy storage in MGs. For instance, Esmaili et al [36] presented an approach to minimize the operation cost and energy loss of a grid-connected MG, considering the range anxiety of EVs in energy management with different types of controllable loads to enhance the benefits. Igualada [37] formulated a MILP model to manage a residential MG, including a charging spot with a vehicle-to-grid system and renewable energy sources.…”

Section: Grid−tmentioning

confidence: 99%

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

et al. 2020

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This paper presents the economic analysis and optimal energy management of a grid-connected MG that comprises renewable energy resources and different battery storage technologies with different characteristics such as initial charge, depth of discharge, and the number of charging/discharging cycles to minimize the total operating cost of the system by maximizing the benefits of BSS, minimizing the investment and replacement cost of BSS, and minimizing the operation and maintenance cost of DGs. Several constraints are considered, such as the output power limits of the distributed generators, the limits of power imported from or exported to the grid, load balance, and other sets of battery storage constraints. The general algebraic modeling system (GAMS) is used to solve the deterministic optimization problem. Second, stochastic optimization is used to solve the deterministic problem with market price uncertainty. Third, robust optimization using the information gap decision theory is presented to model the electric load uncertainty. The validity and effectiveness of the proposed solution are explained by comparing the results obtained by GAMS to the results obtained by other optimization techniques presented in the literature.

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“…While the KSIGALNS algorithm that they developed to solve their bi-level integer programming model was proven to be very effective compared to standard and previous solutions approaches, the analysis of range anxiety as a parameter shows that it is an essential factor to the location strategy of the CS network. Other interesting computational studies exist in the context of range anxiety, such as the one by Esmaili et al [31], where the authors examine EVs as distributed energy storage units and their potential contribution to microgrids when vehicle-to-grid service is considered. An interesting result that emerges from the solution of their Mixed-Integer Linear Programming (MILP) model is that when range anxiety, as modelled in their mathematical optimization program, is in higher levels, then the average State of Charge of the EV drivers rises and, as a result, the total cost of the microgrid is higher, too.…”

Section: Literature Reviewmentioning

confidence: 99%

A Method for the Optimization of Daily Activity Chains Including Electric Vehicles

Rizopoulos

Esztergár-Kiss

2020

Energies

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The focus of this article is to introduce a method for the optimization of daily activity chains of travelers who use Electric Vehicles (EVs) in an urban environment. An approach has been developed based on activity-based modeling and the Genetic Algorithm (GA) framework to calculate a suitable schedule of activities, taking into account the locations of activities, modes of transport, and the time of attendance to each activity. The priorities of the travelers concerning the spatial and temporal flexibility were considered, as well as the constraints that are related to the limited range of the EVs, the availability of Charging Stations (CS), and the elevation of the road network. In order to model real travel behavior, two charging scenarios were realized. In the first case, the traveler stays in the EV at the CS, and in the second case, the traveler leaves the EV to charge at the CS while conducting another activity at a nearby location. Through a series of tests on synthetic activity chain data, we proved the suitability of the method elaborated for addressing the needs of travelers and being utilized as an optimization method for a modern Intelligent Transportation System (ITS).

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Range anxiety of electric vehicles in energy management of microgrids with controllable loads

Cited by 46 publications

References 27 publications

Discharge by Short Circuit Currents of Parallel-Connected Lithium-Ion Cells in Thermal Propagation

Discharge by Short Circuit Currents of Parallel-Connected Lithium-Ion Cells in Thermal Propagation

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

A Method for the Optimization of Daily Activity Chains Including Electric Vehicles

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