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This chapter presents a three-cell flying capacitor converter photovoltaic (PV) system. This system consists of a DC-DC boost power converter connected in series with a multicell inverter. The perturb and observe MPPT technique has been used to extract the maximum power from the solar panel and generate the duty signal to control the switch of the DC-DC converter. The three-cell flying capacitor inverter ensures the conversion of the output voltage of the boost chopper to the alternative voltage. This topology is made up of hybrid association of commutation cells, which makes it possible to share the voltage constraint on several switches. A closed loop control based on PWM has been proposed to control the capacitor voltages of the inverter. The output current is controlled using a PI regulator. The aim of the proposed three cell inverter is to produce an approximate sinusoidal output current with a very low THD. The simulation results assess the effectiveness of the control.

This paper presents deep learning neural network models for photovoltaic output current prediction. The proposed models are long short-term memory and gated recurrent unit neural networks. The proposed models can predict photovoltaic output current for each second for a week time by using global solar radiation and ambient temperature values as inputs. These models can predict the output current of the photovoltaic system for the upcoming seven days after being trained by half-day data only. Python environment is used to develop the proposed models, and experimental data of a 1.4 kWp PV system are used to train, validate and test the proposed models. Highly uncertain data with steps in seconds are used in this research. Results show that the proposed models can accurately predict photovoltaic output current whereas the average values of the root mean square error of the predicted values by the proposed LSTM and GRU are 0.28 A and 0.27 A (the maximum current of the system is 7.91 A). In addition, results show that GRU is slightly more accurate than LSTM for this purpose and utilises less processor capacity. Finally, a comparison with other similar methods is conducted so as to show the significance of the proposed models.

Governments around the world have acknowledged the importance of conserving ecological connectivity to help reverse the decline of biodiversity. In this study we employed recent methodological developments in circuit theory to conduct the first pan-Canadian analysis of multi-species connectivity for all terrestrial regions of the country, at a spatial grain sufficient to support local land-management decisions. We developed a movement cost surface with a limited number of thematic categories using the most recently updated land cover data available for the country. We divided the country into 17 tiles and used a wall-to-wall, omnidirectional mode of Circuitscape on each tile in order to assess ecological connectivity throughout entire landscapes as opposed to strictly among protected areas. The resulting raw current density map of Canada revealed heterogenous patterns of current density across the country, strongly influenced by geography, natural barriers, and human development. We included a validation analysis of the output current density map with independent wildlife data from across the country and found that mammal and herpetofauna locations were predicted by areas of high current density. We believe our current density map can be used to identify areas important for connectivity throughout Canada and thereby contribute to efforts to conserve biodiversity.

Current study explores the effect of selected process parameters i.e. wt.% of reinforcement (A), elevated temperature (B) and load (C) on wear characteristics of Mg-WC nanocomposites using Taguchi robust design concept. Ultrasonic treated stir casting is employed to synthesize nanocomposites. Three levels for every factor are taken into consideration and accordingly L27 orthogonal array (OA) is used for minimization of wear rate. Main effect plot is generated to investigate the important parameters and optimality is also predicted from the main effect plot. Optimal condition for minimum wear rate is 2wt.% of WC, 100°C temperature and 20N load (A3B1C1). Interaction plots are generated to scrutinize the interaction outcome between selected parameters. ANOVA study is executed to evaluate significant parameters and their effective handout on output. Current investigation reveals, Wt.% of WC is the most significant factor while temperature and load are moderately significant. Among the interacting parameters, interaction between wt.% of WC & temperature (A×B) has moderate significance. Wt.% of WC (A) has 43.135% contribution while temperature (B), load (C) and interaction between wt.% of WC & temperature (A×B) have 26.623%, 19.037% and 5.639% contribution respectively. Residual plots for wear rate are discussed and confirmation test finally helps to validate present experimental model. S/N ratio is improved by 4.411 dB (48.60%) than the initial condition.

In this paper, constant-frequency peak-current control is analyzed focusing on the operation above the subharmonic threshold limit. The analysis is performed by mixing analytical and numerical approaches. Two levels of normalization are introduced: on the converter level and on the switching cell level, resulting in unified analysis regardless of the converter type. A function that maps the inductor current value at the beginning of a switching period to its value at the end of the switching period is derived. The analysis is performed by iterating this mapping, leading to information of the inductor current periodicity and the switching cell averaged output current. It is shown that before reaching chaotic state a converter passes through a sequence of bifurcations involving discontinuous conduction modes characterized by higher order periodicity. Boundaries of the region where the higher order discontinuous conduction modes occur are derived. Obtained dependence of the switching cell output current average on the operating parameters is used to derive a small signal model. The model parameters expose huge variations in the areas of deep subharmonic operation. The results are experimentally verified.

Abstract Grid-connected group-series photovoltaic cluster inverter system will cause resonance, which will adversely affect the system. To suppress grid-connected resonance, the mathematical model, resonance mechanism and resonance characteristics of the cluster inverters are analyzed, and a global resonance suppression strategy based on hybrid damping is proposed. In the current loop of the inverter, capacitive current feedback and parallel voltage proportional feed-forward are introduced as active dampers to reduce the harmonics of the parallel current. On this basis, RLC type second-order resonance suppression circuit is added as passive damping to suppress system resonance, so that the output current of the inverters can meet the grid-connected conditions when the cluster is connected to the grid. The simulation and experimental results show that the total harmonic distortion of the grid-connected current decreases from 10.54% to 1.97% after three series photovoltaic cluster inverters adopt this strategy, which effectively suppresses the grid-connected resonance.

Abstract In order to further optimize the output current harmonic suppression effect of photovoltaic grid-connected inverters, a composite control strategy of LCL type photovoltaic grid-connected inverter output current is proposed. This strategy combines proportional complex integral (PCI) control and repetitive control (RC) in parallel, draws a composite control block diagram, introduces a transfer function, and designs PCI and RC control parameters. Prove that the compound control can reduce current harmonics, achieved the purpose of reducing the steady-state error of the fundamental frequency. And adopts a new PCI composite control strategy, which helps to save the cost of the control system. By building the MATLAB/Simulink simulation platform and establishing the PCI+RC composite control model of LCL photovoltaic grid-connected inverter, the comparison of the simulation results shows that compared with the PI+RC control strategy, the total harmonic distortion rate of the grid-connected current is reduced by 25.77. %, significantly improving the quality of grid-connected current.

<span lang="EN-US">This paper proposes a control method for new simplified cascade multiphase direct current-direct current (DC-DC) buck power converters used for low-voltage large-current applications such as cathodic protection. To control the proposed converter, a proportional-integral (PI) controller is used to regulate the output current of the converter. The control scheme analysis is carried out by linearizing the small-signal model of the proposed converter to form the output current transfer functions. This transfer function will be analyzed by using phase and gain margin approach to obtain the control parameters (Kp, Ki, and Ti). Simulation and experiment results are included to show the validity of the proposed concept.</span>

The calculated dependences for determining the deviation of the output current of the resonant power supply of the materials pulsed processing system from a given stabilized value are obtained. The inversely proportional dependence of the output current on the frequency at the input of the series resonant circuit is obtained. These dependencies can be applied for the frequency control of the inverter’s switches commutation which stabilizes the RMS value of the output current. At the close to short circuit modes, the deviation of the output current from the stabilized value does not exceed 2%, and therefore it can be ignored.