In recent modern power systems, the number of renewable energy systems (RESs) and nonlinear loads have become more prevalent. When these systems are connected to the electricity grid, they may face new difficulties and issues such as harmonics and non-standard voltage. The proposed study suggests the application of a whale optimization algorithm (WOA) based on a fractional-order proportional-integral controller (FOPIC) for unified power quality conditioner (UPQC) and STATCOM tools. These operate best with the help of their improved control system, to increase the system’s reliability and fast dynamic response, and to decrease the total harmonic distortion (THD) for enhancing the power quality (PQ). In this article, three different configurations are studied and assessed, namely: (C₁) WOA-based FOPIC for UPQC, (C₂) WOA-based FOPIC for STATCOM, and (C₃) system without FACTS, i.e., base case, to mitigate the mentioned drawbacks. C₃ is also considered as a base case to highlight the main benefits of C₁ and C₂ in improving the PQ by reducing the %THD of the voltage and current system and improving the systems’ voltage waveforms. With C₂, voltage fluctuation is decreased by 98%, but it nearly disappears in C₁ during normal conditions. Additionally, during the fault period, voltage distortion is reduced by 95% and 100% with C₂ and C₁, respectively. Furthermore, when comparing C₁ to C₂ and C₃ under regular conditions, the percentage reduction in THD is remarkable. In addition, C₁ eliminates the need for voltage sag, and harmonic and current harmonic detectors, and it helps to streamline the control approach and boost control precision. The modeling and simulation of the prepared system are performed by MATLAB/Simulink. Finally, it can be concluded that the acquired results are very interesting and helpful in the recovery to the steady state of wind systems and nonlinear loads, thereby increasing their grid connection capabilities.

Electric vehicles (EVs) have emerged as a promising solution for sustainable transportation. The high energy density, long cycle life, and low self-discharge rate of lithium-ion batteries make them an ideal choice for EVs. Recently, these batteries have been prone to faster decay in life span, leading to sudden failure of the battery. To avoid uncertainty among EV users with sudden battery failures, a robust health monitoring and prediction scheme is required for the EV battery management system. In this regard, the Unscented Kalman Filter (UKF)-based technique has been developed for accurate and reliable prediction of battery health status. The UKF approximates nonlinearity using a set of sigma points and propagates them via the nonlinear function to enhance battery health estimation accuracy. Furthermore, the UKF-based health estimation scheme considers the state of charge (SOC) and internal resistance of the battery. Here, the UKF-based health prediction technique is compared with the Extended Kalman filter (EKF) scheme. The robustness of the UKF and EKF-based health prognostic techniques were studied under varying initial SOC values. Under these abrupt changing conditions, the proposed UKF technique performed effectively in terms of state of health (SOH) prediction. Accurate SOH determination can help EV users to decide when the battery needs to be replaced or if adjustments need to be made to extend its life. Ultimately, accurate and reliable battery health estimation is essential in vehicular applications and plays a pivotal role in ensuring lithium-ion battery sustainability and minimizing environmental impacts.

A deregulated electricity market provides open access to all market players. In an open-access power market, the system operator is responsible for ensuring that all contracted power is dispatched. However, if this results in line flows that exceed their acceptable range, then it could threaten the system’s security. Therefore, the system operator checks for congestion as the line flow exceeds its limit. For congestion management, the system operator applies different curtailment strategies to limit the requested transaction. Therefore, in this work, an optimal power dispatch model has been presented in order to reduce the curtailment of requested power. A modified moth flame optimization technique has been implemented to frame this OPD model. The impact of congestion management on power dispatch has been analyzed, considering bilateral and multilateral dispatch in an electricity market. In addition, the effect of FACTS devices on reducing congestion and curtailing power is studied. Verification studies showed that the proposed solution reduces congestion costs by 27.14% and 29.4% in 14- and 30-bus systems, respectively. It has been verified that the MMFO approach with the FACTS device improves transaction deviations and ensures that the deregulated system provides secure energy with less cost reflected on the customers.

The rapid depletion of fossil fuel motivates researchers and policymakers to switch from the internal combustion engine (ICE) to plug-in electric vehicles (PEVs). However, the electric power distribution networks are congested, which lowers the accommodation of PEVs and produces higher power losses. Therefore, the study proposes an effective deterministic methodology to maximize the accommodation of PEVs and percentage power loss reduction (%PLR) in radial distribution networks (RDNs). In the first stage, the PEVs are allocated to the best bus, which is chosen based on the loading capacity to power loss index (LCPLI), and the accommodation profile of PEVs is developed based on varying states of charge (SoC) and battery capacities (BCs). In the second stage, the power losses are minimized in PEV integrated networks with the allocation of DG units using a recently developed parallel-operated arithmetic optimization algorithm salp swarm algorithm (AOASSA). In the third stage, the charging and discharging ratios of PEVs are optimized analytically to minimize power losses after planning PEVs and DGs. The outcomes reveal that bus-2 is the most optimal bus for accommodation of PEVs, as it has the highest level of LCPLI, which is 9.81 in the 33-bus system and 28.24 in the 69-bus system. The optimal bus can safely accommodate the largest number of electric vehicles, with a capacity of 31,988 units in the 33-bus system and 92,519 units in the 69-bus system. Additionally, the parallel-operated AOASSA mechanism leads to a reduction in power losses of at least 0.09% and 0.25% compared with other algorithms that have been previously applied to the 33-bus and 69-bus systems, respectively. Moreover, with an optimal charging and discharging ratio of PEVs in the IEEE-33-bus radial distribution network (RDN), the %PLR further improved by 3.08%, 4.19%, and 2.29% in the presence of the optimal allocation of one, two and three DG units, respectively. In the IEEE-69-bus RDN, the %PLR further improved by 0.09%, 0.09%, and 0.08% with optimal charge and discharge ratios in the presence of one, two, and three DG units, respectively. The proposed study intends to help the local power distribution companies to maximize accommodation of PEV units and minimize power losses in RDNs.

A static synchronous compensator (STATCOM) is a powerful mechanism for balancing reactive power and uplift voltage stability in a transmission system. Nowadays, the desire to save energy by reducing losses is prioritized as an essential target instead of increasing the power generation for the sustainability of any nation’s growth plans. As a result, power-electronics-based converters are more significant for power savings in transmission systems. STATCOM based on voltage source converters (VSC) are operated to improve on stable performance conditions as well as to minimize the harmonic distortions in a power system. Hence, this paper explores low harmonic distortions of fifteen-level VSC structured STACOM using only one DC-link voltage to balance the reactive power and to manage the voltage profile in large power transmission systems. STATCOM consisting of H-bridge type VSCs and binary weighted transformers was utilized to maintain an AC system voltage at 132 kV, 50 Hz. The three stages of VSCs were operated with meticulous firing angles based on converter levels for controlling THD (total harmonic distortion) and providing system improvement. The proposed model of the fifteen-level H-bridge type voltage source converters with fuzzy logic decoupled control algorithm based STATCOM can be used for large power range applications with a small number of switches. This model attained stable operation of the system with a low harmonic deviation at any dynamical conditions. The simulation results using MATLAB showed that the system’s operation was enhanced, with a smoother response and improved steady state performance.

The Kingdom of Saudi Arabia (KSA) is committed to transition its fossil fuel-driven electricity generation to that from renewable energy technologies, such as solar photovoltaic (PV) and wind. The need to reduce greenhouse gas emissions has led it to announce an ambitious target of 40 GW of PV power capacity by 2030. The deployment of such a capacity needs to be augmented with analyses to overcome the challenges faced in terms of the technical capability of the country. This work contributes to this goal by investigating the utilisation of solar photovoltaic PV systems to supply medium-size entities such as universities with clean power, displacing the current fossil fuel power supply. Currently, such considerations are not fully addressed in KSA. The study used the University of Jeddah campus electrical load profile, taking into account future power needs. The methodology encompassed modelling the installation of multi-MW PV systems for the university by considering weather conditions, actual university consumption, load segregation, and economics under different development scenarios informed by surveys with decision makers at the university. The results showed that air conditioning loads alone were responsible for 79% of the campus electrical load and that a 4.5 MW PV system is able to supply half of the total campus annual electrical energy consumption of the year of 2019. The optimum scenario showed that utilising grid-connected PVs would decrease the total cost of electricity over the next two decades by 28 to 35 percent and would result in halving the current campus carbon emissions. The analysis concludes that the business-as-usual case is no longer the cheapest option for the campus.