Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan.
School of Mechanical Engineering, Pusan National University, 2 Busandaehak-ro, Geumjeong-gu, Busan, 46241, Republic of Korea.
Sci Rep. 2022 Jul 20;12(1):12380. doi: 10.1038/s41598-022-15983-0.
This research aims to contribute in developing a mathematical model for the composite probabilistic energy emissions dispatch (CPEED) with renewable energy systems, and it proposes a novel framework, based on an existing astute black widow optimization (ABWO) algorithm. Renewable energy power generation technology has contributed to pollution reduction and sustainable development. Therefore, this research aims to explore the CPEED problem in the context of renewable energy generation systems to enhance the energy and climate benefits of the power systems. Five benchmark test systems, combined with conventional thermal power plants and renewable energy sources such as wind and solar, are considered herein to obtain the optimum solution for cost and pollutant emission by using the ABWO approach. The ascendancy is not limited to environmental impacts, but it also provides the diversification of energy supply and reduction of reliance on imported fuels. As a result, the research findings contribute in lowering the cost of fuel and pollutant emissions, correlated with electricity generation systems, while increasing the renewable energy usage and penetration. Finally, the performance and efficacy of the designed scheme have been fully validated by comprehensive experimental results and statistical analyses.
本研究旨在为包含可再生能源系统的复合概率能源排放调度（CPEED）开发数学模型，并提出了一种新的框架，基于现有的机敏黑寡妇优化（ABWO）算法。可再生能源发电技术为减少污染和可持续发展做出了贡献。因此，本研究旨在探索可再生能源发电系统背景下的 CPEED 问题，以提高电力系统的能源和气候效益。本研究考虑了五个基准测试系统，结合了传统的火力发电厂和可再生能源，如风能和太阳能，以使用 ABWO 方法获得成本和污染物排放的最佳解决方案。优势不仅限于环境影响，还提供了能源供应的多样化和减少对进口燃料的依赖。因此，研究结果有助于降低与发电系统相关的燃料成本和污染物排放，同时增加可再生能源的使用和渗透率。最后，通过全面的实验结果和统计分析充分验证了所设计方案的性能和效果。
