Wind-solar-storage hybrid power plants represent a significant and growing share of new proposed projects in the United States. Their uptake is supported by increasing renewable energy market share, enhanced technical abilities for dispatch and control, and decreasing costs for wind energy, solar energy, and battery storage. Simultaneously, there is also increased use of generation and storage resources in distributed power systems. The diversification of energy resources through hybridization or spatial distribution provides an opportunity to enhance power system resilience (compared to single-source generation), addressing growing concerns about the reliability of the aging, transforming U.S. electric grid. The question of where to build hybrid plants for resilience value-rather than for bulk power supply-has not been fully explored in previous studies. Therefore, in this study we complete a national complementarity analysis to identify areas in the United States that are particularly suited for wind-solar hybrid power plant development. The authors show the importance of seasonal and diurnal patterns in assessing complementarity and identify that regions in the Great Plains, Midwest, and Southeast are particularly suited for hybrid power plants. We demonstrate the resilience value of hybridization for a reference system based near Memphis, Tennessee, and show optimal sizing of wind, solar, and storage assets given 1.0 and 0.9 critical load factors. Our results indicate that the pairing of wind and solar assets better meets constant load demand and reduces storage requirements compared to using only solar assets. These results will enable future work to integrate complementarity metrics with resilience frameworks. The results also indicate a need for more finely resolved data for local resources, demand, and hazards. v

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Abstract. Wind plant layout optimization is a difficult, complex problem with a large number of variables and many local minima. Layout optimization only becomes more difficult with the addition of solar generation. In this paper, we propose a parameterized approach to wind and solar hybrid power plant layout optimization that greatly reduces problem dimensionality while guaranteeing that the generated layouts have a desirable regular structure. Thus far, hybrid power plant optimization research has focused on system sizing. We go beyond sizing and present a practical approach to optimizing the physical layout of a wind–solar hybrid power plant. We argue that the evolution strategy class of derivative-free optimization methods is well-suited to the parameterized hybrid layout problem, and we demonstrate how hard layout constraints (e.g., placement restrictions) can be transformed into soft constraints that are amenable to optimization using evolution strategies. Next, we present experimental results on four test sites, demonstrating the viability, reliability, and effectiveness of the parameterized evolution strategy approach for generating optimized hybrid plant layouts. Completing the tool kit for parameterized layout generation, we include a brief tutorial describing how the parameterized evolutionary approach can be inspected, understood, and debugged when applied to hybrid plant layouts.

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