The photovoltaic (PV) system contemplated in the study displays multiple peaks on power-voltage (P-V) curve under partial shading condition (PSC) results in a complicated maximum power point tracking (MPPT) process. Conventional MPPT algorithms work in an effective manner under uniform irradiance conditions. However, these algorithms are unable to track the global peak effectively under different irradiance conditions. In this study, a velocity of particle swarm optimisation-based Levy flight (VPSO-LF) for Global MPPT of PV system under PSCs is proposed. For the changes in irradiance, when verified with VPSO-LF, tracking time and a number of iterations are fewer to reach the global peak of PV array. It also minimises the number of tuning parameters of the velocity of particle swarm optimisation (PSO). The proposed technique is simulated in MATLAB/ SIMULINK as well as experimentally validated. It is observed that the results obtained using VPSO-LF is superior to conventional PSO and hill-climbing algorithm under different patterns of PV array. 2 PV system modelling For modelling and simulating PV system used a single-diode PV cell is shown in Fig. 1. It is implemented in MATLAB/SIMULINK environment based on the steps given in [31].
SummaryIn the study of photovoltaic (PV) system, power‐voltage (P‐V) curves exposed to view several peaks under partial shaded condition (PSC), which brings about muddled and most extreme maximum power point tracking (MPPT) process. Under uniform weather conditions, regular MPPT algorithms such as perturb and observe (P&O), hill climbing (HC), and incremental conductance (INC) work in an effective manner. However, these conventional methods are unable to track global peak successfully under PSC. In this context, the evolutionary algorithms such as grey wolf optimization (GWO) perform better than conventional algorithms. However, the conventional GWO is not sufficient for exploration point of view to locate global best particles; and moreover, GWO deteriorates the convergence process. To overcome these drawbacks, a modified GWO (MGWO) is proposed in this paper to track global best particle, which improves the convergence process under static condition and as well as re‐initialization of parameters under dynamic conditions. The proposed method is verified using simulations as well as using experimental results. The obtained results demonstrate superiority compared to conventional GWO and HC methods under partial shaded patterns of PV array.
This research article proposes a powerful fractional-order PI controller to mitigate the subsynchronous oscillations in turbine-generator shaft due to subsynchronous resonance (SSR) with flexible AC transmission system devices such as static synchronous compensator (STATCOM) and unified power flow controller (UPFC). The diminution of SSR is achieved by the raising of network damping at those frequencies which are proximate to the torsional mode frequency of the turbine-generator shaft. The increase of network damping is obtained with the injection of subsynchronous frequency component of current and both current and voltage into the line. The subsynchronous component of current and voltage are derived from the measured signal of the system and further the same amount of shunt current is injected with STATCOM and simultaneous injection of current and voltage with UPFC into the transmission line to make the subsynchronous current to zero which is the prime source of turbine shaft oscillations. The insertion and proper tuning of Fractional-order PI controller in the control scheme, the subsynchronous oscillations are reduced to 92 % in case of STATCOM and 98 % in case of UPFC as compared to without controller and 14 % as compared with the results of conventional PI controller. The IEEE first benchmark model has adopted for analyze the effectiveness and speed of the proposed control scheme using MATLAB-Simulink and the corresponding results illustrates the precision and robustness of the proposed controller.
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