A significant fraction of the environmental emissions is due to the power generation sector and burning fossil fuels to produce electricity. Moreover, the transportation system with conventional fossil-fuel vehicles plays a key role in climate change. Accordingly, the generation sector has already changed its planning strategies to employ more renewable energies to supply the load demand, particularly at the distribution level. Besides, other alternatives have been being used in the transportation system to alleviate the pollution, caused by this sector, and plug-in hybrid electric vehicles (PHEVs) have grabbed attention. However, it should be noted that connecting a large number of PHEVs would impose a considerably high load demand on the distribution system, and may cause different problems. In this regard, this research study develops an effective day-ahead resource scheduling framework for a microgrid (MG), taking into account the PHEVs and renewable energy sources (RESs). The model has been defined for an MG, which is equipped with renewable and non-renewable energy-based distributed generation (DG) technologies, storage devices, and PHEVs. The proposed model addresses the uncertain parameters, relating to the hourly value of the load, the price of energy, procured by the upstream network, and renewable power generation, by deploying Monte-Carlo simulation (MCS). Furthermore, the nickel–metal hydride (Ni-MH) battery as a widely-used and reliable technology is employed in this study. The resource scheduling problem is introduced in the framework of an optimization problem with one objective function, intended to minimize the total cost of operation over a 24-hour horizon. Then, an efficient optimization method, named the hybrid whale optimization algorithm and pattern search (HWOA-PS), is utilized to cope with the mentioned optimization problem. The results, found by this approach would then be compared to the ones, obtained from other approaches to validate the results.

环境排放的很大一部分是由于发电部门和燃烧化石燃料来发电。此外，使用常规化石燃料车辆的运输系统在气候变化中起着关键作用。因此，发电部门已经改变了其计划策略，以使用更多的可再生能源来满足负荷需求，特别是在配电方面。此外，运输系统中还使用了其他替代方法来减轻该行业造成的污染，插电式混合动力汽车（PHEV）引起了人们的关注。然而，应当注意，连接大量的PHEV将对配电系统施加相当高的负载需求，并且可能引起不同的问题。在这方面，这项研究研究考虑到插电式混合动力汽车和可再生能源（RES），为微电网（MG）开发了有效的日前资源调度框架。该模型已为MG定义，该MG配备了可再生和不可再生基于能源的分布式发电（DG）技术，存储设备和PHEV。提出的模型通过部署蒙特卡洛模拟（MCS）解决了不确定参数，这些参数涉及负荷的小时值，上游网络采购的能源价格以及可再生能源发电。此外，本研究采用镍氢电池（Ni-MH）作为一种广泛使用的可靠技术。在具有一个目标函数的优化问题的框架中引入了资源调度问题，旨在最大程度地减少24小时的运营总成本。然后，使用一种有效的优化方法，即混合鲸鱼优化算法和模式搜索（HWOA-PS），来解决上述优化问题。然后将该方法找到的结果与从其他方法获得的结果进行比较，以验证结果。