UC Santa Barbara

Wind energy has been used by humans for thousands of years. Yet, the relatively low economic cost and availability of fossil fuels upstaged the use of wind power. Fossil fuel resources are not renewable and will decline until exhaustion in the future. At the same time, humans have become aware of the adverse effects on the environment caused by reliance on fossil fuel energy. Wind, on the other hand, is a renewable energy source with minimal adverse environmental impacts that does not involve greenhouse gas emissions. Agricultural irrigation systems use fossil fuel energy resources in various forms. Groundwater withdrawal is central to supplying agricultural water demand in arid and semi-arid regions. Such withdrawal is mostly based on water extraction with pumps powered by diesel, gasoline, or electricity (which is commonly produced by fossil fuels). This paper coupled the non-sorted genetic algorithm (NSGA-II) as the optimization tool to the mathematical formulation of the wind-powered groundwater production problem to determine the potential of wind energy for groundwater withdrawal in an arid area. The optimal safe yield and the optimal size of regulation reservoir are determined considering two objectives: (1) maximizing total extraction of groundwater and (2) minimizing the cost of reservoir construction. The safe yield and the two objectives are optimized for periods lasting 1, 2, 3, 4, and 6 months over a 1-year planning horizon. This paper's methodology is evaluated with groundwater and wind-power data pertinent to Eghlid, Iran. The optimal safe yield increases by increasing the period length. Specifically, increasing the period length from 1 to 6 months increases the safe yield from 12 to 29 m³. Application of the proposed NSGA-II-based optimization of groundwater production identifies the best design and operational variables with computational efficiency and accuracy.