PMSG‐based VS‐WECS for constant active power delivery to standalone load using direct matrix converter‐based SST with BESS

Abstract

This study presents a simplified control algorithm for constant active power delivery to a weak‐grid/standalone load from a variable speed‐wind energy conversion system (VS‐WECS). The proposed system consists of a permanent magnet synchronous generator (PMSG)‐based WECS connected to a weak‐grid/standalone through a direct matrix converter‐based solid‐state transformer (SST) along with a bidirectional buck–boost battery energy storage system (BESS). The power from the WECS is processed through the SST using Venturini‐based control algorithm together with the voltage‐oriented control scheme. This scheme effectively regulates active and reactive power as well as voltage gain of the SST. Wind turbines maximum power point tracking power curves are used to set reference for active power. While the reference for reactive power is taken as zero. The bidirectional buck–boost‐based BESS is used to smoothen the power generated by the PMSG‐based VS‐WECS. It absorbs the surplus power from the WECS during over generating period and delivers power back under power shortage period. To validate the performances of the proposed scheme, extensive simulation has been performed and exclusive hardware built by dSPACE1104 using MATLAB/Simulink.

Parameter identification of direct‐drive permanent magnet synchronous generator based on EDMPSO‐EKF

“…Under the principle of ensuring steady-state tracking and filtering without divergence, the initial matrix P, Q and R matrices are selected as follows: 6), R 1 = diag(0.08 0.08), P 2 = diag(10 0.01 0.01), Q 2 = diag(0.01 10 0.01), R 2 = diag(50 50). Optimized Q and R matrices: PSO-EKF:P 1 = diag(1 1 8 1), Q 1 = diag(1.5e-8 1.9e-8 1.3e-6 1.5e-6), R 1 = diag(0.6 1), P 2 = diag(10 0.01 0.01), Q 2 = diag(1e-5 6 0.81), R 2 = diag(0.08 0.08).…”

“…In the last decade, the direct-drive permeant magnet synchronous generator (D-PMSG) has been used in many industries, especially, for renewable energy applications [1][2][3], aircraft [4,5], and propulsion systems [6]. Normally, the stator resistance, d-q axis inductance, and permeant magnet flux linkage in the model of generator are constant by default, but in the actual operation process, the parameters of permeant magnet synchronous generator (PMSG) are affected by temperature, flux saturation, skin effect and so on, and these parameters are directly related to the performance of the controller.…”

Parameter estimation based on novel enhanced self‐learning particle swarm optimization algorithm with Levy flight for PMSG

“…Different from fossil fuel, wind energy is a renewable resource with abundant reserves and broad commercial prospects, and it has been widely applied to power generation [1]. Permanent magnet synchronous generator (PMSG) as the core equipment of power generation series, it has higher market acceptance for its better suitability for low wind speed, low energy consumption and lower subsequent maintenance cost [2,3]. Unfortunately, the parameters of PMSG are different under different operating conditions [4], and this will prevent the controller from working well and may even cause malfunctions, therefore, the precise estimation of the parameters is essential.…”