Mohamed Emad A, Mostafa Mostafa H, Ali Ziad M, Abdel Aleem Shady H E
Department of Electrical Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al Kharj 16278, Saudi Arabia.
Electrical Department, Faculty of Engineering, Al Ryada University for Science and Technology, Sadat City 32897, Egypt.
PLoS One. 2025 Mar 18;20(3):e0319174. doi: 10.1371/journal.pone.0319174. eCollection 2025.
The escalating challenges posed by fossil fuel reliance, climate change, and increasing energy expenses have underscored the critical importance of optimizing energy systems. This paper addresses the economic dispatch (ED) challenge, which directs the optimization of the output of generation units to satisfy electricity and heat requirements while reducing operational expenses. In contrast to conventional economic dispatch methods, this research incorporates renewable energy sources (RESs), energy storage systems (ESSs), and combined heat and power (CHP) systems. This integrated strategy facilitates the concurrent optimization of electrical and thermal generation, culminating in a more comprehensive and efficient solution. A sophisticated scheduling model for combined heat, power, and electrical energy dispatch (CHPEED) has been devised, minimizing generation expenses. The suggested model accounts for practical constraints inherent in real-world power systems, such as prohibited operating regions, while also addressing the intricate relationships between heat and power generation in CHP units. Also, the nature of wind energy, photovoltaic systems, and load requirements within the realm of stochastic dynamic ED are considered. The general algebraic modeling system (GAMS) was utilized to solve the optimization problem. The cost without RES or ESS is $250,954.80, indicating a high reliance on costly energy sources. Integrating RES reduces costs to $247,616.42, highlighting savings through decreased fossil fuel dependency. The combination of RES and ESS achieves the lowest cost of $245,933.24, showcasing improvements in efficiency and supply-demand management via optimized energy utilization. Hence, the findings demonstrate the model's effectiveness in addressing uncertainties associated with renewable generation, ensuring reliability in meeting energy demands and validating the possible capability to enhance the sustainability and efficiency of energy systems.
对化石燃料的依赖、气候变化以及不断增加的能源成本所带来的挑战日益升级，这凸显了优化能源系统的至关重要性。本文探讨经济调度（ED）挑战，该挑战旨在优化发电机组的输出，以满足电力和热力需求，同时降低运营成本。与传统经济调度方法不同，本研究纳入了可再生能源（RES）、储能系统（ESS）以及热电联产（CHP）系统。这种综合策略有助于同时优化电力和热力发电，最终形成更全面、高效的解决方案。已设计出一种用于热电联产和电能调度的复杂调度模型（CHPEED），以最小化发电成本。所提出的模型考虑了实际电力系统中固有的实际约束条件，如禁止运行区域，同时还解决了CHP机组中热力和电力发电之间的复杂关系。此外，还考虑了随机动态经济调度领域中风能、光伏系统以及负荷需求的特性。利用通用代数建模系统（GAMS）来解决优化问题。不使用RES或ESS时的成本为250,954.80美元，这表明对成本高昂的能源来源高度依赖。整合RES可将成本降至247,616.42美元，突出了通过减少对化石燃料的依赖而实现的节约。RES和ESS的组合实现了最低成本245,933.24美元，展示了通过优化能源利用在效率和供需管理方面的提升。因此，研究结果证明了该模型在应对与可再生发电相关的不确定性、确保满足能源需求的可靠性以及验证提高能源系统可持续性和效率的潜在能力方面的有效性。
