Dynamic Economic Dispatch with High Photovoltaic Penetration Based on Quadratic Constrained Programming

This study proposes a Dynamic Economic Dispatch (DED) framework based on Quadratic Constrained Programming (QCP) to improve the operational efficiency of power systems with high photovoltaic (PV) penetration. The proposed DED model incorporates real-time system conditions and leverages QCP to accurately represent the non-linear nature of generation cost functions and operational constraints. This optimization strategy enables adaptive and precise scheduling of generation units while maintaining supply-demand balance and minimizing operational costs. The DED problem is formulated as a quadratic optimization model and solved using the CPLEX solver. To evaluate its performance, the model is applied over a 24-hour dispatch horizon on the IEEE 30-bus system under varying PV penetration levels of 0%, 10%, 20%, and 30%. The simulation scenarios reflect typical daily solar generation profiles and account for operational constraints such as generator ramp rates and load variability. Simulation results show that the proposed method not only achieves cost-effective dispatch under dynamic conditions but also enhances system flexibility and reliability in the presence of high PV penetration.