Utilisation of more than one energy source in the electric vehicle (EV) ensures the reliable riding of the vehicle without range anxieties. Solar PV, battery and ultra-capacitor are viable sources to power the EV. A novel dual input-dual output dc-dc converter is proposed for the integration of the above sources for the EV application. The converter can be used to transfer power between the input sources and loads/utility grid/other EVs. The proposed converter can be operated in ten different modes using the same structure by controlling the appropriate switches. The equivalent circuits with the analytical waveforms of significant modes of operation of the converter are discussed in this study. The output equations of all ten modes are derived. The theoretical analysis of the converter is verified experimentally using a 1 kW laboratory prototype and the observed experimental results are shown in the study. A strategy for selecting a mode according to the status of the vehicle, grid, battery etc. is developed. The loss breakdown analysis and efficiency profile of the converter are presented. Finally, the performance comparisons of the proposed converter with the reported converters are carried out in terms of component counts, a number of operating modes etc.

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The utility company enforces a limit on the amount of energy injected into the utility grid from residential renewable plants due to the stability/protection concerns caused by the reverse power flow. Under this scenario, a proper load scheduling at the consumer end is necessary to ensure maximum renewable energy utilization during the surplus generation. This article proposes a novel objective function to impart energy self-sufficiency for residential consumers who own electric vehicles and renewable energy power plants. The proposed objective function aims to promote the consumers to utilize the local sources such as the battery of an electric vehicle, solar PV, wind, etc., effectively through load scheduling. A dedicated program in MATLAB platform is developed for load scheduling, and an experimental case study is conducted using the forecasted demand and generation profiles collected from 10 typical residential consumers. Three new techno-economic parameters namely, aggregate daily exchanged energy, daily average discharged energy, and daily average self-sufficiency hours are proposed to conduct the comparative study. An Average Rank ranking method is introduced to evaluate the effectiveness of the proposed and conventional objective functions statistically. The result analysis proves that load scheduling using the proposed objective function secure the best Average Rank of 2.02 compared to the conventional objective functions.