Abstract-The market for battery powered and plug-in hybrid electric vehicles is currently limited, but this is expected to grow rapidly with the increased concern about the environment and advances in technology. Due to their high energy capacity, mass deployment of electrical vehicles will have significant impact on power networks. This impact will dictate the design of the electric vehicle interface devices and the way future power networks will be designed and controlled. This paper presents the results of an analysis of the impact of electric vehicles on existing power distribution networks. Evaluation of supply/demand matching and potential violations of statutory voltage limits, power quality and imbalance are presented.

Citation: Kamjoo, Azadeh, Maheri, Alireza, Dizqah, Arash and Putrus, Ghanim (2016) Multiobjective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming. International Journal of Electrical Power & Energy Systems, Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economicenvironmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services. Highlights  Optimisation of energy cost, battery degradation, grid utilisation and CO2 emission  The conflicts among objectives were addressed with multi-objective optimisation  A multi-criteria decision making process was tailored to the stakeholders

Uncontrolled charging of electric vehicles (EVs) is expected to cause problems for power distribution networks as existing vehicles are continually being replaced by electric. Therefore, smart charging algorithms that prevent such problems will become necessary as uptake of EVs increases and they become more popular. Smart EV charging is not only useful to provide the necessary charge (energy) required by the user but may also be used to support the grid and protect battery health, which is investigated in this paper. Factors that affect battery life are quantified and their impact on battery degradation and ability (of EV) to support the grid are analysed. Charging regimes that can meet the driver needs, provide grid support and protect the state of health of the battery are proposed in this paper. The analysis presented demonstrates that smart charging that involves charging before departure, less frequent charging and limited vehicle-to-grid can prolong battery life compared with providing the same EV charge in an uncontrolled way. Thus, grid power is supported and battery life protected by the proposed smart charging regimes.

Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) Abstract -Multiphase brushless direct current (BLDC) motors can meet the increasing demand for higher reliability in motor drives applicable in electric vehicles by integrating fault diagnosis to a faulttolerant (FT) control method. To achieve this goal, a modified FT finite control set model predictive control (FCS-MPC) is proposed in this paper. The dead beat control is used to predict the reference voltage applied by the inverter. A sensitivity analysis is done to show the effect of model uncertainty on the controller performance. In addition, a simple, fast and general open switch and short circuit fault detection (FD) method in voltage source inverter (VSI) is presented. The FD method is capable of detecting open switch, open phase, and short circuit faults without any auxiliary variable. Moreover, it is robust to both speed and load transients in a motor drive. To validate the presented theory, experimental results are conducted on a five-phase BLDC motor drive with outer rotor in wheel structure.

(2012) Generic maximum power point tracking controller for small-scale wind turbines. Renewable Energy, 44. pp. 72-79.

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Abstract-This paper provides an analysis of the experimental results available for lithium ion battery degradation which has been used to create a model of the effect of the identified parameters on the ageing of an EV battery. The parameters affecting degradation are generally accepted to be; state of charge, depth of discharge, charging rate and battery temperature. Values for each of these parameters have been found for three versions of a typical daily cycling scenario; uncontrolled charging, delayed charging and V2G. A comparison is made of the expected overall degradation using four different charging rates and different charging patterns based on the model. A link is made between the charging patterns and the effect on the power flow at the transformer of a typical section of LV network using a ADMD profile.The analysis shows that delayed charging and V2G slow down the rate of battery degradation. However, fast charging appears to accelerate battery degradation. Delayed charging also helps avoid excessive evening loading and thus will help delay distribution network asset upgrading. Uncontrolled charging increases evening loading and V2G can reduce it. However, the EV then needs more power for charging and the charging after V2G needs to be managed if it is not to create another spike in demand at a later time.Index Terms-Li ion battery, battery ageing, battery degradation, calendar life, cycle life, V2G