Multi-objective optimization for capacity expansion of regional power-generation systems: Case study of far west Texas

High expansion of power demand is expected in the Upper Rio Grande region of far west Texas as a result of both electrical demand growth and decommissioning of installed capacity. On the supply side, a notable deployment of renewable power technologies can be projected owing to the recent legislation of a new energy policy in Texas, which attempts to reach 10,000 installed MWe of renewable capacity for 2025. Power generation fueled by natural gas might consistently expand due to the encouraged use of this fuel. In this context, the array of participating technologies can be optimized within a sustainability framework, which translates into a multi-objective optimization problem. In this paper, the problem is formulated and solved to determine supply shares for some chosen technologies based on both renewable power conversion and natural gas use. The exergetic and economic costs are established as primary competing factors. The deployment of renewable power technologies hypothetically follows the Gompertz growth model, which is constrained by exergetic self sustenance. The solution is given as a Pareto tradeoff front for arrays of optimal technologies and capacities. Additionally, the sustainability of these arrays is analyzed through indicators, and the current goal for renewable power technologies is discussed.