Optimal sizing of photovoltaic-wind hybrid system for community living environment and smart grid interaction

With the depletion of fossil fuels and skyrocketing levels of CO₂ in the atmosphere, renewable energy sources continue to gain popularity as a long-term sustainable energy source. However, two major limitations exist that prevent widespread adoption: variability of electricity generated and cost of the equipment needed. A grid-tied photovoltaic (PV) / wind hybrid system with battery back-up can help mitigate the variability of a single source. PV and wind generation are both time dependent and variable but have a high degree of correlation, which makes them ideal for a dual-sourced PV-Wind hybrid energy system. This paper presents an optimization technique base on particle swarm optimization (PSO) which uses high temporal resolution insolation data taken at 10 second data rate instead of the more commonly used hourly data rate. When analyzed over an entire year, the increased temporal resolution data has been shown to minimize the sizing of the PV and required storage capacity compared to optimization techniques that only use hourly-sampled date. The result is a minimized baseline cost to meet supply requirements of the loads. The Life Cycle Costing with payback time and Levelized Cost of Energy (LCOE) with Net Metering are provided as part of the economics.