Keywords
System dynamics
Policy effectiveness
Grey wolf algorithm
Offshore photovoltaic
How to Cite
Abstract
To address the impact of photovoltaic (PV) policies on the expansion of offshore PV installed capacity, this study proposes a prediction model based on system dynamics (SD) theory. This model quantifies policy types and practical situations, and the scoring results reflect the policy's influence effectiveness. The Grey Wolf Optimizer (GWO) is employed to optimize the influence coefficients of supportive, guiding, and developmental policy effectiveness within the model, thereby improving the model's precision and accuracy. First, a system dynamics model was constructed to analyze the relationships among PV power generation costs, revenues, installation willingness, and installed capacity. Then, the policy implementation effect was integrated into the SD model in the form of policy effectiveness, and a policy effectiveness evaluation system was established. Finally, simulation prediction and analysis were conducted. Predicted values of offshore PV installed capacity in Jiangsu Province from 2021 to 2024 were compared with actual data to verify the effectiveness of the model. Subsequently, offshore PV installed capacity and investment costs from 2025 to 2030 were simulated and analyzed. Case study results indicate that the predictions of the proposed model are consistent with industry development trends and provide valuable references.
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