The precise electrical modeling of photovoltaic (PV) module is crucial due to the large-scale permeation of PV power plants into electric power networks. Therefore, a triple-diode photovoltaic (TDPV) model is presented to address all PV losses. However, the TDPV is mathematically modelled by a nonlinear I-V behavior, including nine-parameters that cannot be directly determined from the PVs datasheet due to the lack data offered by the PV manufacturers. This article presents a new application of the marine predators algorithm (MPA) to properly extract the electrical parameters of the TDPV model of a PV panel. The validity of the MPA-based TDPV model is widely appraised by the numerical analyses, which are carried out under various temperatures and solar irradiations. The optimal nine-parameters achieved using the MPA are compared with that realized by different optimization approaches-based PV model. For a realistic study, the numerical results and the measured data are compared for the marketable Kyocera KC200GT and Solarex MSX-60 PV panels. The efficacy of the MPA-based TDPV model is properly executed by checking its current error with that obtained from various models. With the MPA technology, a highly accurate model of any marketable PV module can be attained, which represents a new contribution to the sector of PV power systems.

This paper proposes a new, metaheuristic optimization technique, Artificial Gorilla Troops Optimization (GTO), for a hybrid power system with photovoltaic (PV) and wind energy (WE) sources, solving the probabilistic optimum power flow (POPF) issue. First, the selected algorithm is developed and evaluated such that it applies to solve the classical optimum power flow (OPF) approach with the total fuel cost as the objective function. Second, the proposed algorithm is used for solving the POPF, including the PV and WE sources, considering the uncertainty of these renewable energy sources (RESs). The performance of the suggested algorithm was confirmed using the standard test systems IEEE 30-bus and 118-bus. Different scenarios involving different sets of the PV and WE sources and fixed and variable loads were considered in this study. The comparison of the obtained results from the suggested algorithm with other algorithms mentioned in this literature has confirmed the efficiency and performance of the proposed algorithm for providing optimal solutions for a hybrid power system. Furthermore, the results showed that the penetration of the PV and WE sources in the system significantly reduces the total cost of the system.

The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.

This paper addresses the problem of output feedback control for high voltage direct current (HVDC) systems based on voltage source converters (VSC). Specifically, the system under study consists of two power grids and two VSC stations connected via a long HVDC cable. The primary goal of this paper is to propose a different approach for the online estimation of the grid voltage placed at a great distance from the control unit which is considered generally known, moreover the proposed technique aims to online estimation of the grid pulsation and the HVDC cable states, generally considered available. A nonlinear observer is intended to address these concerns. Only the line current measurements are used to estimate all state variables. Furthermore, utilizing the estimation offered by the proposed observer, an output feedback control strategy is formulated, using the backstepping design technique, to meet the three control objectives: (i) tight output voltage regulation of the HVDC cable; (ii) ensuring a perfect power quality at both sides of the HVDC system; (iii) regulation of the active power at the inverter station. The high effectiveness of the proposed output feedback controller’s performance is highlighted via a semi-experimental platform that includes a Processor In the Loop (PIL) on the embedded board eZdsp. Extra numerical simulations show that The proposed output feedback performance enjoys additional robustness properties and meets all control objectives.

To avert climate change, there has been a rise in the usage of green energy sources that are also beneficial to the environment. To generate sustainable energy in a financially and technically efficient manner, our research attempts to close the gaps. The potential of green sources like photovoltaic (PV) and biomass for a rural community southwest of Sohag Al Gadida City, Sohag, Egypt, is examined in this research considering its techno-economic (TE) and eco-friendly feasibility. The HOMER Pro v3.14 package is used as a scaling and optimization instrument, to calculate the price of the PV/biomass setup and the size and characteristics of its parts. This is to estimate the corresponding electrical production and reduce the total annual cost for the customer. The suggested system structure is validated through the presentation of simulation outcomes and evaluations utilizing MATLAB/SIMULINK R2022a. In addition, a TE-environmental investigation of the optimized PV/biomass structure is performed. The optimum structure is carefully chosen from the best four configurations using the demand predilection by analogy to the perfect technique based on the generation cost, operation cost, energy production, and renewable fraction. The results also indicate that using hybrid PV/biomass is an attractive choice with the initial capital cost (ICC: USD 8.144), net present cost (NPC: USD 11,026), a low cost of energy (LCOE: 0.184 USD/kWh), and the high renewable fraction (RF: 99.9%) of the system. The annual CO₂ emission performance of a PV/biomass system is much better than that of the grid alone and PV/diesel. This method might be applied in rural areas in other developing countries.