论文标题
天然气短期操作问题与动态:一种最小化方法
Natural Gas Short-Term Operation Problem with Dynamics: A Rank Minimization Approach
论文作者
论文摘要
天然气发电的发电单元可以对冲在不确定的可再生生成中的波动,这可能在很短的时间内发生。使用能够正确捕获气体燃气单元需求引起的天然气网络动力学的模型至关重要。韦茅斯方程在文献中通常实现,以避免处理求解天然气动力学的原始管理微分方程的数学并发症。但是,本文表明,这种方法在短期操作问题中并不可靠。在这里,将非凸线瞬态模型的优点与简化的Weymouth方程进行了比较,并说明了采用Weymouth方程的缺点。结果表明,如何通过调整管道内的压力而不是天然气供应商的输出来满足天然气需求的变化。这项工作为具有动力学的原始非线性和非凸天然气流动方程提供了一种凸松弛方案,并采用了秩最小化方法来确保紧密度。所提出的方法呈现出一个计算高效的框架,该框架可以准确地解决非凸线非线性气体操作问题并准确捕获其动力学。同样,结果表明,与原始的非线性非凸模型相比,提出的模型改善了解决方案最优性和解决方案时间。最后,在案例研究中验证了所提出的方法的可伸缩性。
Natural gas-fired generation units can hedge against the volatility in the uncertain renewable generation, which may occur during very short periods. It is crucial to utilize models capable of correctly capturing the natural gas network dynamics induced by the volatile demand of gas-fired units. The Weymouth equation is commonly implemented in literature to avoid dealing with the mathematical complications of solving the original governing differential equations of the natural gas dynamics. However, it is shown in this paper that this approach is not reliable in the short-term operation problem. Here, the merit of the non-convex transient model is compared with the simplified Weymouth equation, and the drawbacks of employing the Weymouth equation are illustrated. The results demonstrate how changes in the natural gas demand are met by adjustment in the pressure within pipelines rather than the output of natural gas suppliers. This work presents a convex relaxation scheme for the original non-linear and non-convex natural gas flow equations with dynamics, utilizing a rank minimization approach to ensure the tightness. The proposed method renders a computationally efficient framework that can accurately solve the non-convex non-linear gas operation problem and accurately capture its dynamics. Also, the results suggest that the proposed model improves the solution optimality and solution time compared to the original non-linear non-convex model. Finally, the scalability of the proposed approach is verified in the case study.