Hazra Sunanda, Datta Dipanjan, Paul Chandan, Roy Provas Kumar, Sultana Sneha, Kumar Sajjan, Dutta Soham
Department of Electrical Engineering, Haldia Institute of Technology, Haldia, India.
ICA Edu Skills Pvt. Ltd, Kolkata, India.
Sci Rep. 2025 Apr 28;15(1):14888. doi: 10.1038/s41598-025-98594-9.
Incorporating electric vehicles (EVs) into the power grid significantly impacts its safe and reliable operation, while the unpredictable nature of wind power adds further complications. Solar power, though less efficient in converting sunlight to electricity compared to wind power, remains a popular renewable energy source. Combining wind and solar energy is advantageous because wind energy can be harnessed both day and night, unlike solar energy. Tidal energy also offers a reliable renewable option, although it has its own set of challenges. Consequently, the utilization of renewable energy sources (RESs) have become increasingly complex. Fossil fuels, on the other hand, are a major cause of severe pollution. This study addresses integration of wind, solar, tidal, and electric vehicles, using a unique moth-flame optimization technique, to solve the challenge of hydrothermal scheduling (HTS). The primary objective is to reduce power generation costs while adhering to various limitations, including transmission losses, thermal unit valve point effects, and RESs variability. In order to maximize energy management, several EVs are currently being built as virtual power plants (VPPs), utilizing sustainable energy sources. So, VPPs and combined renewable energy sources make the micro-grid more rigid. The objective is to minimize fuel expenditures by balancing load demand and transmission losses while satisfying all conditions. By evaluating the generation costs with MFO, this study demonstrates the effectiveness of the method and compares it with other advanced optimization techniques, highlighting its superior efficiency, utility and reliability. When the performance of normal HTS system, RES and EV based HTS system are observed, it is clearly observed that RESs based system has improved the results by 5.49% as compared to the conventional system using the suggested COMFO approach. The findings also show that EVs can effectively contribute to a hydro-thermal scheduling system with integrated renewable energy by using grid power.
将电动汽车（EV）并入电网会对其安全可靠运行产生重大影响，而风能的不可预测性则进一步增加了复杂性。太阳能虽然在将阳光转化为电能方面比风能效率低，但仍然是一种受欢迎的可再生能源。将风能和太阳能结合起来具有优势，因为与太阳能不同，风能在白天和晚上都可以利用。潮汐能也提供了一种可靠的可再生选择，尽管它有自己的一系列挑战。因此，可再生能源（RES）的利用变得越来越复杂。另一方面，化石燃料是严重污染的主要原因。本研究采用独特的 moth-flame 优化技术，解决水火电调度（HTS）的挑战，涉及风能、太阳能、潮汐能和电动汽车的整合。主要目标是在遵守各种限制条件（包括输电损耗、热力机组阀点效应和 RES 的可变性）的同时降低发电成本。为了实现能源管理的最大化，目前正在建造几辆电动汽车作为虚拟发电厂（VPP），利用可持续能源。因此，VPP 和组合可再生能源使微电网更加稳定。目标是通过平衡负荷需求和输电损耗，同时满足所有条件，将燃料支出降至最低。通过用 MFO 评估发电成本，本研究证明了该方法的有效性，并将其与其他先进的优化技术进行了比较，突出了其卓越的效率、实用性和可靠性。当观察正常 HTS 系统、基于 RES 和 EV 的 HTS 系统的性能时，可以清楚地看到，与使用建议的 COMFO 方法的传统系统相比，基于 RES 的系统使结果提高了 5.49%。研究结果还表明，电动汽车通过使用电网电力，可以有效地为具有综合可再生能源的水火电调度系统做出贡献。
