Multi-agent shared planning of offshore wind power transmission infrastructure based on cooperative game theory

With the large-scale development of offshore wind power, the independent construction of transmission facilities tends to cause excessive investment and resource waste. To address this issue, this paper proposes an integrated framework combining bi-level optimal planning and cooperative game theory, aiming to collaboratively solve the dilemmas of site selection and capacity allocation for shared offshore wind power transmission facilities, as well as benefit allocation among multiple stakeholders. Firstly, the physical topology of the system is constructed, and a bi-level optimization model is established. The upper level model optimizes the location and capacity configuration of converter stations with the objective of minimizing initial investment, while the lower-level aims to minimize the system operation, maintenance and power loss costs. Secondly, a bi-level genetic algorithm based on Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) is adopted to iteratively solve the nonlinear model and obtain the optimal life-cycle planning scheme. Finally, cooperative game theory is introduced, and the Shapley value is utilized to quantify the marginal contribution of each development participant to realize fair and reasonable benefit distribution. The case study results demonstrate that the proposed shared planning mode can significantly reduce the total life-cycle cost of the system, with the cost-saving rate of each stakeholder exceeding 25%, which demonstrates the effectiveness and practicality of the established model and method.