Novel operational strategies to maximize crop and electricity production in single-axis agrivoltaic systems based on light response curve and daily light integral

• Two novel solar tracking strategies proposed for agrivoltaics (DLIT and KPT). • Benchmarked against True Tracking (TT), Anti-Tracking (AT), and Scheduled Tracking (ST). • Barley selected as the reference crop for simulation-based evaluation. • DLIT showed performance close to in energy yield > 99 % and crop yield >89% when compared to the benchmarks TT and AT. • KPT provided a more balanced trade-off between crop yield and energy output with energy yield >86% and crop yield > 97.9%. Agrivoltaic (APV) systems require tracking strategies that reconcile crop light demand with electricity generation, yet conventional true tracking (TT) maximizes energy at the expense of ground irradiance. This study proposes two novel control strategies for single-axis APV systems: Daily Light Integral Tracking (DLIT) and Knee-Point Tracking (KPT). These strategies embed crop physiological requirements into tilt control using stage-dependent DLI profiles and temperature-sensitive light-response curves. A simulation framework combining solar geometry, ground irradiance modelling, LAI dynamics, and photosynthetic carbon assimilation was applied to barley under Swedish conditions and benchmarked against TT, anti-tracking (AT), and scheduled tracking (ST). Relative to TT, KPT increased biomass from 10.60 to 11.67 ton ha⁻¹ (+10.1%) while reducing energy yield from 937.74 to 804.72 kWh kWp⁻¹ (−14.2%). DLIT achieved near-optimal electricity production (933.94 kWh kWp⁻¹, −0.4% vs. TT) with a modest biomass gain to 10.76 ton ha⁻¹ (+1.5%), demonstrating its ability to prioritize energy production after meeting crop DLI targets. Smoothing of tilt trajectories reduced mechanical oscillations but affected strategies differently: biomass decreased by 22–24% across cases, while energy impacts varied (−8.5% TT, +19.6% AT, −7.5% DLIT, −0.6% KPT) due to distinct baseline tilt-angle dynamics. The results show that crop-informed tracking enhances land-use efficiency by dynamically balancing food and energy objectives. Although quantitative outcomes are crop- and site-specific, the DLIT and KPT frameworks are transferable to other crops when appropriate LAI development, DLI targets, and light-response parameters are provided, enabling scalable next-generation APV control.