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Domain decomposition of the network conductance matrix is one of the efficient approaches to solve large-scale networks in parallel, wherein the most commonly-used non-iterative method is the Schur complement (SC) method. However, the SC method could not obtain the network conductance matrix inversion directly, and the computational cost will increase fast when the overlapping domain expands. In this work, a novel Linking-Domain Extraction (LDE) based decomposition method is proposed, in which the network matrix is expressed as the sum of a linking-domain matrix (LDM) and a diagonal block matrix (DBM) composed of multiple block matrices in diagonal. Through mathematical analysis over LDM, one lemma about the nature of LDM and its proof are proposed. Based on this lemma, the general formulation of the inverse matrix of the sum of LDM and DBM can be found using the Woodbury matrix identity, and based on the formulation the network matrix inversion can be directly computed in parallel to significantly accelerate the matrix inversion process. Test systems were implemented on both the FPGA and GPU parallel architectures, and the simulation results and speed-ups over the SC method and Gauss-Jordan elimination demonstrate the validity and efficiency of the proposed LDE method. [ABSTRACT FROM AUTHOR]

The existing economic dispatch (ED) control structures in power systems are based on solving a quadratic optimisation problem, which can only guarantee the optimal steady‐state performance. In this study, the authors formulate the real‐time ED problem for the transient operation of power systems as a dynamic model predictive control (MPC) optimisation problem. A novel MPC solving method, named backwards square completion (BSC) is thereby proposed to solve it with guaranteed transient economic performance. Meanwhile, it satisfies the input and state security constraints. Conventional linear MPC algorithms routinely involve with inverse matrix calculation, which is computationally expensive and may result in singularity. By contrast, BSC algorithm replaces the inverse matrix calculation by recursive receding horizon optimisation problem solving, which significantly reduces the computational complexity in terms of the control horizon. The proposed BSC‐MPC solution for real‐time ED is applied to an IEEE 39‐bus benchmark power network system to show its effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

The precise integration method proposed for linear time-invariant homogeneous dynamic systems can provide accurate numerical results that approach an exact solution at integration points. However, difficulties arise when the algorithm is used for non-homogeneous dynamic systems due to the inverse matrix calculation required. In this paper, the structural dynamic equalibrium equations are convened into a special form, the inverse matrix calculation is replaced by the Crout decomposition method to solve the dynamic equilibrium equations, and the precise integration method without the inverse matrix calculation is obtained. The new algorithm enhances the present precise integration method by improving both the computational accuracy and efficiency. Two numerical examples are given to demonstrate the validity and efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]