Higher cost and stochastic nature of intermittent renewable energy (RE) resources complicate their planning, integration and operation of electric power system. Therefore, it is critical to determine the appropriate sizes of RE sources and associated energy storage for efficient, economic and reliable operation of electric power system. In this study, two constraintbased iterative search algorithms are proposed for optimal sizing of the wind turbine (WT), solar photovoltaic (PV) and the battery energy storage system (BESS) in the grid-connected configuration of a microgrid. The first algorithm, named as sources sizing algorithm, determines the optimal sizes of RE sources while the second algorithm, called as battery sizing algorithm, determines the optimal capacity of BESS. These algorithms are mainly based upon two key essentials, i.e. maximum reliability and minimum cost. The proposed methodology aims to avoid over-and under-sizing by searching every possible solution in the given search space. Moreover, it considers the forced outage rates of PV, WT and utilisation factor of BESS which makes it more realistic. Simulation results depict the effectiveness of the proposed approach. S space search space SV solution vector Δp instantaneous error between generation and demand ΔP cumulative error between generation and demand v wind speed

No abstract

No abstract

No abstract

The rising concerns over global climate change and depleting fossil fuel reserves are two of the main reasons for the ongoing efforts towards the electrification of the transportation sector. While greenhouse gases (GHGs) emissions from other sectors are generally falling, emissions from the road transport have increased over the past few decades, with both full electric vehicles (FEVs) and plug-in hybrid electric vehicles (PHEVs) being recognized as potential alternatives to combat climate change and reduce GHG emissions. However, widespread integration of FEVs and PHEVs will substantially increase the load on the power system which will eventually affect the reliability of existing power systems. In this paper, a probabilistic model for integrating FEVs and PHEVs with existing power grids is proposed that incorporates important FEV and PHEV characteristics, such as battery capacity, charge depleting distance, and charging rates. In addition, user behavior is taken into account through time of recharging, arrival and departure times, and daily miles driven. Furthermore, different charging strategies, i.e., opportunistic charging and controlled charging with and without vehicle-to-grid (V2G) scheme have been considered to evaluate the impact of FEVs and PHEVs on the composite power system. IEEE-RTS-79 system is used to examine the proposed probabilistic technique considering different FEV and PHEV penetration levels as well as charging strategies. Simulation results show that even a relatively low penetration level of FEVs or PHEVs might have a significant impact on the system reliability unless a proper charging and/or discharging schemes are utilized.