Feasible Domain Solution for Industrial Park Power Based on Combination of Sampling and OPF

The development of load-side flexible regulation resources has emerged as a pivotal strategy to mitigate the declining source-side regulation capabilities in modern power systems. Among potential contributors, industrial parks-particularly those integrating large-scale electrolytic aluminum production and mineral heat furnace operations-exhibit substantial flexibility potential due to their controllable and high-capacity loads. However, effectively leveraging this potential is hindered by complex high-dimensional nonlinear coupling constraints, which arise from the intricate interactions of network current balance, load dynamics, and source-load characteristics within these parks. Accurately determining the power feasible region under these conditions is therefore a nontrivial challenge. To address this problem, this paper develops a comprehensive power feasible domain model tailored for industrial parks, explicitly incorporating the nonlinear coupling constraints between active and reactive power. A novel ray-emission-based sampling approach is proposed, which systematically explores the P-Q coupling plane by iteratively solving the optimal power flow (OPF) problem along multiple directions. This method efficiently identifies boundary points, enabling a precise and high-fidelity characterization of the feasible power region. The effectiveness and accuracy of the proposed modeling framework and sampling strategy are validated through a detailed case study on a five-node industrial park network. Results demonstrate that the approach not only captures the nonlinear interactions among loads and network constraints but also provides actionable insights for the real-time utilization of load-side flexibility. These findings underscore the potential of industrial park loads as a valuable resource for enhancing system regulation and operational resilience, paving the way for more adaptive and efficient power system management.