Abstract-This paper describes a new maximum-power-pointtracking method for a photovoltaic system based on the Lagrange Interpolation Formula and proposes the particle swarm optimization method. The proposed control scheme eliminates the problems of conventional methods by using only a simple numerical calculation to initialize the particles around the global maximum power point. Hence, the suggested scheme will utilize fewer iterations to reach the maximum power point.

Recently direct current (DC) microgrids have drawn more consideration because of the expanding use of direct current (DC) energy sources, energy storages, and loads in power systems. Design and analysis of a standalone solar photovoltaic (PV) system with DC microgrid has been proposed to supply power for both DC and alternating current (AC) loads. The proposed system comprises of a solar PV system with boost DC/DC converter, Incremental conductance (IncCond) maximum power point tracking (MPPT), bi-directional DC/DC converter (BDC), DC-AC inverter and batteries. The proposed bi-directional DC/DC converter (BDC) lessens the component losses and upsurges the efficiency of the complete system after many trials for its components’ selection. Additionally, the IncCond MPPT is replaced by Perturb & Observe (P&O) MPPT, and a particle swarm optimization (PSO) one. The three proposed techniques’ comparison shows the ranking of the best choice in terms of the achieved maximum power and fast—dynamic response. Furthermore, a stability analysis of the DC microgrid system is investigated with a boost converter and a bidirectional DC-DC converter with the Lyapunov function for the system has been proposed. The complete system is designed and executed in a MATLAB/SIMULINK environment and validated utilizing an OPAL real-time simulator.

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Abstract:In recent years, organic solar cells became more attractive due to their flexible power devices and the potential for low-cost manufacturing. Inkjet printing is a very potential manufacturing technique of organic solar cells because of its low material usage, flexibility, and large area formation. In this paper, we presented an overall review on the inkjet printing technology as well as advantages of inkjet-printing, comparison of inkjet printing with other printing technologies and its potential for organic solar cells (OSCs). Here we highlighted in more details about the viability of environment-friendly and cost-effective, non-halogenated indium tin oxide (ITO) free large scale roll to roll production of the OSC by inkjet printing technology. The challenges of inkjet printing like the viscosity limitations, nozzle clogging, coffee ring effect, and limitation of printability as well as dot spacing are also discussed. Lastly, some of the improvement strategies for getting the higher efficiency of the OSCs have been suggested.

Wind energy is particularly significant in the power system today since it is a cheap and clean power source. The unpredictability of wind speed leads to uncertainty in devolved power which increases the difficulty in wind energy system operation. This paper presents a stochastic optimal power flow (SCOPF) for obtaining the best scheduled power from wind farms while lowering total operational costs. A novel metaheuristics method called Aquila Optimizer (AO) is used to address the SCOPF problem due to its highly nonconvex and nonlinear nature. Wind speed is represented by the Weibull probability distribution function (PDF), which is used to anticipate the cost of wind-generated power from a wind farm based on scheduled power. Weibull parameters that provide the best match to wind data are estimated using the AO approach. The suggested wind generation cost model includes the opportunity costs of wind power underestimation and overestimation. Three IEEE systems (30, 57, and 118) are utilized to solve optimal power flow (OPF) using the AO method to prove the accuracy of this method, and results are compared with other metaheuristic methods. With six scenarios for the penalty and reverse cost coefficients, SCOPF is applied to a modified IEEE-30 bus system with two wind farms to obtain the optimal scheduled power from the two wind farms which reduces total operation cost.