【目的】在考虑用户满意度和追求经济运行的同时，提出了弹性微电网优化模型，以研究系统在极端条件下的弹性。考虑到柔性负荷对用户满意度的影响，在优化经济调度的同时提高用户的满意度。【方法】该模型涉及用户满意度和寻求微电网经济运行和恢复力，考虑到灾前预防和灾后恢复，提出一种混合鹈鹕算法，其中包含惯性权重、莱维飞行、衰减因子和t分布多种策略。将多种策略混合，逐步提高鹈鹕算法的求解精度。【结果】在低概率高损害场景的仿真试验中，改进算法相比蝴蝶优化算法、粒子群优化算法、灰狼优化算法、人工蜂群优化算法及原始算法分别节省了26.7%、27.0%、26.1%、21.8%和6.7%的系统运行成本，性能优势显著。【结论】该模型可以在一定程度上提高用户的满意度，证明了所提算法在解决微电网的最优经济运行和恢复能力问题方面具有更强的优越性

[Objective] An optimisation model of a flexible microgrid is proposed to study the resilience of the system under extreme conditions while considering user satisfaction and pursuing economic operation. And the impact of flexible loads on user satisfaction is considered to improve user satisfaction while optimising economic dispatch. [Methods] This model integrated user satisfaction with microgrid economic operation and resilience enhancement, proposing a hybrid pelican optimization algorithm that simultaneously addresses pre-disaster prevention and post-disaster recovery strategies. A hybrid pelican algorithm was proposed, which contains multiple strategies of inertia weights, Lévy flights, attenuation factors and t-distribution. Mixing multiple strategies gradually improved the solution accuracy of the pelican algorithm. [Results] In simulation tests of low-probability high-impact scenarios, the proposed algorithm demonstrated significant performance advantages over butterfly optimization algorithm, particle swarm optimization algorithm, grey wolf optimization algorithm, artificial bee colony optimization algorithm, and the original algorithm, achieving system operational cost reductions of 26.7%, 27.0%, 26.1%, 21.8%, and 6.7% respectively, significant perpormance advantages. [Conclusion] The model can improve user satisfaction to a certain extent and proves that the proposed algorithm is more superior in solving the optimal economic operation and resilience problems of microgrids.