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基于合作博弈的海上风电送出基础设施多主体共享规划

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

  • 摘要: 随着海上风电规模化开发,独立建设输电设施易出现投资冗余、资源浪费等问题。为此,提出融合双层优化规划与合作博弈理论的整体框架,协同解决海上风电共享输电设施的选址定容与多主体利益分配难题。首先构建系统物理拓扑,建立双层优化模型,上层以最小化初始投资为目标优化换流站选址与容量配置,下层最小化系统运行维护及损耗成本;其次采用基于非支配排序遗传算法二代(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)的双层遗传算法对非线性模型迭代求解,得到全寿命周期最优规划方案;最后引入合作博弈理论,通过Shapley值量化各开发主体的边际贡献,实现公平合理的利益分配。算例表明,该共享规划模式可显著降低系统全寿命周期成本,各风电开发主体成本节约率均超过25%,验证了模型与方法的有效性与实用性。

     

    Abstract: 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.

     

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