Optimal Allocation of Renewable Energy Generation and Storage Systems

There is an increasing demand for renewable power capacity in Texas due to the growing population statewide. However, increasing the amount of power supplied to the grid through renewable technologies can place stresses on the food, energy and water resources in the area. The aim of this research project is to model and optimize the allocation of renewable energy generation and storage technologies considering various objectives, such as cost and environmental impact, and scenarios, such as varying energy demands and land and water use constraints. Detailed high fidelity modeling of various energy generating processes, including solar farms, wind farms, and biomass, was performed. Nonlinear optimization was then used to obtain the energy output profiles of the various renewable energy generation technologies. The derived profiles were then used as inputs to a linear optimization program to obtain the optimal allocation for each scenario through mixed-integer linear optimization. The results of this model indicate that varying the restrictions placed on the model, such as limiting land area or water availability, can greatly affect the optimum energy production and storage methods. The proposed methodology has been adopted for a water-stressed region in south-central Texas. The outcomes of this research stress the significance of geographic factors, the energy demand profiles and resource availability, such as water and land, on the transition towards renewable energy generation.