为实现“双碳”目标,缓解环境压力,综合能源系统(integrated energy system,IES)已成为能源转型的重要发展方向之一。考虑到电转气(power-to-gas,P2G)技术引入的氢气、合成天然气等多类型供气源混合的问题,传统的IES能量流计算已无法确...为实现“双碳”目标,缓解环境压力,综合能源系统(integrated energy system,IES)已成为能源转型的重要发展方向之一。考虑到电转气(power-to-gas,P2G)技术引入的氢气、合成天然气等多类型供气源混合的问题,传统的IES能量流计算已无法确定混合后的燃气品质是否达标,无法量化其对IES中的节点压力、电压等参数影响。为此,提出了一种计及气体成分变化的电-气-热综合能源系统能量流计算方法。首先,将气体相对密度和热值建模为迭代变量,给出了混合气体的相对密度和热值的节点偏差方程及求解流程,为IES中多种供气源及其混合问题提供了通用模型;其次,提出了扩展牛顿-拉夫逊求解方法,给出反映耦合关系的扩展雅可比矩阵,以实现更全面的能量流结果评估和运行分析;最后,通过算例验证了所提模型和方法可有效反映气体成分变化对耦合系统的影响。展开更多
In this paper,we investigate a parallel subspace correction framework for composite convex optimization.The variables are first divided into a few blocks based on certain rules.At each iteration,the algorithms solve a...In this paper,we investigate a parallel subspace correction framework for composite convex optimization.The variables are first divided into a few blocks based on certain rules.At each iteration,the algorithms solve a suitable subproblem on each block simultaneously,construct a search direction by combining their solutions on all blocks,then identify a new point along this direction using a step size satisfying the Armijo line search condition.They are called PSCLN and PSCLO,respectively,depending on whether there are overlapping regions between two imme-diately adjacent blocks of variables.Their convergence is established under mild assumptions.We compare PSCLN and PSCLO with the parallel version of the fast iterative thresholding algorithm and the fixed-point continuation method using the Barzilai-Borwein step size and the greedy coordinate block descent method for solving the l1-regularized minimization problems.Our numerical results showthatPSCLN andPSCLOcan run fast and return solutions notworse than those from the state-of-theart algorithms on most test problems.It is also observed that the overlapping domain decomposition scheme is helpful when the data of the problem has certain special structures.展开更多
文摘为实现“双碳”目标,缓解环境压力,综合能源系统(integrated energy system,IES)已成为能源转型的重要发展方向之一。考虑到电转气(power-to-gas,P2G)技术引入的氢气、合成天然气等多类型供气源混合的问题,传统的IES能量流计算已无法确定混合后的燃气品质是否达标,无法量化其对IES中的节点压力、电压等参数影响。为此,提出了一种计及气体成分变化的电-气-热综合能源系统能量流计算方法。首先,将气体相对密度和热值建模为迭代变量,给出了混合气体的相对密度和热值的节点偏差方程及求解流程,为IES中多种供气源及其混合问题提供了通用模型;其次,提出了扩展牛顿-拉夫逊求解方法,给出反映耦合关系的扩展雅可比矩阵,以实现更全面的能量流结果评估和运行分析;最后,通过算例验证了所提模型和方法可有效反映气体成分变化对耦合系统的影响。
基金Qian Dong was supported in part by the National Natural Science Foundation of China(Nos.11331012,11321061 and 11461161005)Xin Liu was supported in part by the National Natural Science Foundation of China(Nos.11101409,11331012,11471325 and 11461161005)+3 种基金China 863 Program(No.2013AA122902)the National Center for Mathematics and Interdisciplinary Sciences,Chinese Academy of SciencesZai-Wen Wen was supported in part by the National Natural Science Foundation of China(Nos.11322109 and 91330202)Ya-Xiang Yuan was supported in part by the National Natural Science Foundation of China(Nos.11331012,11321061 and 11461161005).
文摘In this paper,we investigate a parallel subspace correction framework for composite convex optimization.The variables are first divided into a few blocks based on certain rules.At each iteration,the algorithms solve a suitable subproblem on each block simultaneously,construct a search direction by combining their solutions on all blocks,then identify a new point along this direction using a step size satisfying the Armijo line search condition.They are called PSCLN and PSCLO,respectively,depending on whether there are overlapping regions between two imme-diately adjacent blocks of variables.Their convergence is established under mild assumptions.We compare PSCLN and PSCLO with the parallel version of the fast iterative thresholding algorithm and the fixed-point continuation method using the Barzilai-Borwein step size and the greedy coordinate block descent method for solving the l1-regularized minimization problems.Our numerical results showthatPSCLN andPSCLOcan run fast and return solutions notworse than those from the state-of-theart algorithms on most test problems.It is also observed that the overlapping domain decomposition scheme is helpful when the data of the problem has certain special structures.
