Penetration rates of intermittent renewables increase in smart grid due to environmental issues. As a significant part of smart grid, distributed microgrids (DMGs) have huge application prospects for its flexibility, high efficiency and fast recovery ability. In order to improve the effective penetration of renewable energy in distributed microgrids at low cost, we proposed a dynamic model-based configuration and scheduling coupling optimization method in this study. We established the multi-domain joint simulation model for DMGs based on the Modelica acausal modeling language to realize the coupling of distributed generation (DG), energy conversion/storage components and user loads with multiscale time-varying characteristics, and validated its accuracy by using the measured data. On the basis of the model established above, branch and bound method and meta-heuristic algorithm are used to optimize the double layer configuration and scheduling of microgrids in four typical scenarios. Moreover, a novel evaluating indicator, the effective penetration of renewable energy (EPRE), is proposed to improve the system self-utilization rate of renewable energy. Study results show that by using the newly developed model-based optimization method with the new indicator, the self-utilization rate in DMGs can be increased up to 58.05% and the average daily interactive power of electricity fed back to the regional grid is reduced significantly.

由于环境问题，智能电网中间歇性可再生能源的渗透率增加。分布式微电网（DMG）作为智能电网的重要组成部分，其灵活性，高效性和快速恢复能力具有广阔的应用前景。为了以低成本提高可再生能源在分布式微电网中的有效渗透，我们提出了一种基于动态模型的配置与调度耦合优化方法。我们基于Modelica非因果建模语言建立了DMG的多域联合仿真模型，以实现分布式发电（DG），能量转换/存储组件和具有多尺度时变特性的用户负载的耦合，并通过使用验证了其准确性。测量数据。根据以上建立的模型，在四种典型情况下，使用分支定界方法和元启发式算法优化微电网的双层配置和调度。此外，提出了一种新的评价指标，即可再生能源的有效渗透率（EPRE），以提高可再生能源的系统自利用率。研究结果表明，通过使用新开发的基于模型的优化方法和新指标，DMG中的自用率可以提高到58.05％，并且显着降低反馈到区域电网的平均每日互动电力。提出提高可再生能源系统的自利用率。研究结果表明，通过使用新开发的基于模型的优化方法和新指标，DMG中的自用率可以提高到58.05％，并且显着降低反馈到区域电网的平均每日互动电力。提出提高可再生能源系统的自利用率。研究结果表明，通过使用新开发的基于模型的优化方法和新指标，DMG中的自用率可以提高到58.05％，并且显着降低反馈到区域电网的平均每日互动电力。