2022 Annual Meeting

Modeling and Economic Optimization of Solar Power Plant Expansion in West Virginia Using the System Advisor Model (SAM)

West Virginia is currently highly dependent on fossil fuels for its energy production and consumption. However, the state presents a strong capability for renewable energy systems. To continue to expand the renewable energy infrastructure in West Virginia, the feasibility of these systems must be studied. Previously, research was conducted to determine the System Advisor Model’s (SAM) capabilities for modeling wind and solar energy systems [1]. By modeling renewable energy systems with SAM, feasibility of such systems can be determined with regard to performance and financial considerations as well as optimized for specific parameters. Building from this past research, this project is conceptualized to determine West Virginia’s ability to meet renewable energy demand targets through solar energy modeling in SAM and financial optimization in Python. In particular, the objective of this project is to model and optimize renewable energy expansion for solar power plants in West Virginia using SAM to ultimately determine the optimal capacity for the state, while maintaining positive financial metrics such as net present value (NPV).

In this study, West Virginia’s degraded land sites suitable for renewable energy expansion are studied [2] . Potential solar photovoltaic power plants in West Virginia are modeled. Relevant weather information from the National Solar Radiation Database and plant specifications are used to simulate plant operations in SAM. In particular, first SAM is used to design site specific photovoltaic layouts to maximize the capacity without considering profitability or other financial factors. This step serves as a benchmark for the subsequent financial constrained optimization carried out in the combined Python-SAM framework. The objective function in this proposed, combined framework is the maximization of the solar output, but with the constraint of maintaining a positive NPV. Ultimately, this optimization will aim to demonstrate the maximum feasible expansion of solar energy in the state. Due to the accuracy of these produced SAM models, such models could be combined with fossil fuel power plants to develop a real-time optimization framework for the local energy grid and provide realistic ramping rates for advanced control studies of fossil fuel power plants in the future.

[1] L. Bischof, R. Alexander, and F. V. Lima, “Modeling of Solar and Wind Power Plants in West Virginia Using System Advisor Model (SAM),” presented at the 2021 AIChE Annual Meeting, Nov. 2021.

[2] J. James and E. Hansen, “Prospects for Large-Scale Solar on Degraded Land in West Virginia,” Feb 21, 2017.