Duck Curve Mitigation through Optimal Orientation of Utility-Scale Solar Photovoltaics

The rapid growth of solar energy has intensified grid management challenges, particularly due to the “duck curve”-a pattern of midday overgeneration followed by steep evening ramps in net load. Traditional mitigation strategies such as fast-ramping gas generators, energy storage systems, and demand response require significant infrastructure investments and often conflict with decarbonization goals. This study presents a comple-mentary approach: optimizing the orientation (tilt and azimuth angles) of utility-scale photovoltaic (PV) modules to reshape the solar generation profile. We propose a two-stage stochastic optimization framework with detailed PV generation modeling that incorporates weather, load, and tariff uncertainties through scenario-based analysis The framework is evaluated using real-world datasets from the California Independent System Operator (CAISO), California Irrigation Management Information System (CIMIS), and utility tariff schedules. To manage computational complexity, a clustering-based aggregation method is employed to reduce the dimensionality of 783 utility-scale PV plants across California. Results demonstrate that optimal orientation shifts solar generation toward evening hours, achieving a 2.5%-6.6% reduction in net-load ramping and increasing revenue under time-of-use tariffs, despite only minor reductions (0.8%-4.3%) in total energy output. These findings illustrate the effectiveness of the PV orientation optimization as a complementary solution to existing strategies for duck-curve mitigation while maintaining profitability and paving the way for further integration of solar energy into the grid.