LUO Ke, GU Yanxun, LIAO Shijiang, et al. Multi-agent shared planning of offshore wind power transmission infrastructure based on cooperative game theory[J]. 2026, 59(7): 169-178.
LUO Ke, GU Yanxun, LIAO Shijiang, et al. Multi-agent shared planning of offshore wind power transmission infrastructure based on cooperative game theory[J]. 2026, 59(7): 169-178.DOI: 10.11930/j.issn.1004-9649.202602045.
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.