In the paper, an enhanced optimal technique is proposed for solving the optimal power flow (OPF) issues with uncertainties. An enhanced technique is the EHO calculation, which is roused bythe crowding conduct of elephant gathering. Originally, the OPF is examinedwith the (N-R) Newton-Raphson (N-R) approach after that, the wind and PV based power scheduling is performed. For the wind and PV analysis, the output power is determined from the Weibull PDF and Lognormal PDF. Initially, the objective functionis defined and analyzed the voltage deviation, power loss and generation cost. For the OPF analysis, multi-objective functions are considered under the uncertainty period. The activities are decided for various reasons depending on the variable costs of building photovoltaic and wind farms, radiation, discharge costs, transmission disturbances and voltage stability. The suggested procedure is tested with the IEEE 57 bus system and analyzed the corresponding emission coefficients, generation cost coefficients and etc.
Transportation electrification is happening at a rapid pace around the globe in response to the climate change mitigation measures taken by the regulatory agencies to curb tailpipe emissions. As the electric vehicle technology evolved, the size of on-board storage units has increased, which require charging from an external energy source. Renewable charging of electric vehicles is an attractive option to reduce the carbon footprint of an electric vehicle. The intermittent nature of the renewables necessitates a storage unit to provide continuous power. With a battery complementing solar generation, a power converter is deployed to interface these sources and storage units with the electric vehicle for charging. The converter shall now have to operate to quench the charging requirements by sourcing power from solar generation and storage elements. The converter also has to capture the generated solar power during the non-charging period and store it in the battery. All these functional requirements demand a robust energy management strategy to utilize all available sources and storage units efficiently without compromising load requirements. A Stateflow-based energy management algorithm for a three-port converter is proposed in this work. The proposed algorithm is implemented using OPAL-RT, and the real-time simulation results are presented.
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