Optimal grid design and logistic planning for wind and biomass based renewable electricity supply chains under uncertainties

In this work, the grid design and optimal allocation of wind and biomass resources for renewable electricity supply chains under uncertainties is studied. Due to wind intermittency, generation of wind electricity is not uniform and cannot be counted on to be readily available to meet the demand. Biomass represents a type of stored energy and is the only renewable resource that can be used for producing biofuels and generating electricity whenever required. However, amount of biomass resources are finite and might not be sufficient to meet the demand for electricity and biofuels. Potential of wind and biomass resources is therefore jointly analyzed for electricity generation. Policies are proposed and evaluated for optimal allocation of finite biomass resources for electricity generation. A stochastic programming model is proposed that optimally balances the electricity demand across the available supply from wind and biomass resources under uncertainties in wind speed and electricity sale price. A case study set in the American Midwest is presented to demonstrate the effectiveness of the proposed model by determining the optimal decisions for generation and transmission of renewable electricity. Sensitivity analysis shows that level of subsidy for renewable electricity production has a major impact on the decisions. - Highlights: • Stochastic optimization model for wind/biomass renewable electricity supply chain. • Multiple uncertainties in wind speeds and electricity sale price. • Proposed stochastic model outperforms the deterministic model under uncertainties. • Uncertainty affects grid connectivity and allocation of power generation capacity. • Location of wind farms is found to be insensitive to the stochastic environment