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Hybrid energy system (HES) is considered a solution to the energy supply issue, particularly in rural areas to achieve their sustainable development goals. The rise in energy consumption has increased the appeal of renewable resources, because of their potential to supply consumers with competitive, carbon-free electricity. This paper suggests strategies for managing energy and the most recently published optimizers for designing a stand-alone HES positioned in a remote region of southwest Egypt. This HES includes two green energy sources (wind and solar) and a storage system for energy (battery) as the first backup in addition to a second backup (diesel). The most recent sizing techniques employing the Chernobyl disaster optimizer, dynamic control cuckoo search (DCCS), and gold rush optimizer have been suggested to obtain the optimal design of the utilized HES. Furthermore, an in-depth evaluation of the applied optimization approaches has been achieved based on a comparative study. A detailed analysis of the studied algorithms aims to identify the optimum algorithm that provides the lowest possible cost at the highest level of reliability for the proposed HES. The simulation results verified that, the DCCS algorithm outperformed other algorithms, indicating its potential for achieving promising solutions. [ABSTRACT FROM AUTHOR]

In the present day, there is widespread acceptance of autonomous hybrid power systems (AHPSs) that rely on renewable energy sources (RESs), owing to their minimal adverse effects on the environment. This paper evaluates and compares three various AHPS configurations comprising photovoltaic (PV) modules, wind turbines (WTs), batteries, and diesel generators (DGs), using a recent optimization approach. A new optimizer 'Dandelion-Optimizer' (DO) is applied to tackle design problems. Real-time meteorological data from Siwa Oasis in northwest Egypt was utilized to determine an optimum design of system components for the purpose of providing sustainable power to this remote region. The system configurations are effectively modelled and optimized to achieve the minimum cost of energy (COE), while also minimizing the loss of power supply probability (LPSP) and carbon dioxide (CO2) emissions. As per the results, the last configuration (PV with both backup equipment) is the most optimal one in terms of the lowest cost, whereas the first configuration (PV and WT with both types of backup equipment) is the most optimal one with regards to the lowest carbon emissions. [ABSTRACT FROM AUTHOR]

The static charges and induced voltages from extra-high-voltage alternating current transmission lines (EHVACTLs) on parallel oil pipelines (POPLs) raise the risk levels for people and animals. Thus, the objective of this paper was to reduce and/or mitigate the electric field which is concentrated on POPLs by using grounded shield wires under EHVACTLs. Three techniques are employed to reduce the electric field effects on POPLs of two distinct types of transmission lines (TLs), 500 kV and 220 kV. The first technique involves raising the tower's height to improve the clearance space between the POPLs and the TL conductors. The second technique is increasing the horizontal distance between the POPLs and the nearest stressed conductors of the TL. The third technique involves placing shield wires beneath the stressed conductors of the EHVACTLs. The electric field under the EHVACTLs is calculated with and without the grounded shield wires using charge simulation method. The results of the first technique revealed that with increasing the tower height from 10 m to 15, 20, 25, and 30 m, the electric field decreased by 43.75%, 62.5%, 68.75%, and 75%, respectively. Herein, employing the second technique, the electric field intensity is reduced by 20% and 21% depending on the POPL placed at a distance from the right stressed conductor equal to the horizontal clearance between conductors of 500 kV and 220 kV, respectively. Besides, the results of the third technique proved that the shield wires under the EHVACTLs reduced the electric field intensity on the POPLs by 17.65% and 24.71% for 500-kV and 220-kV TLs, respectively. [ABSTRACT FROM AUTHOR]

The main objective of this research study is to improve the performance of a standalone hybrid power system (SHPS) that consists of photovoltaic modules (PVMs), wind turbines (WTs), battery system (BS), and diesel engine (DE). The emphasis is on optimizing the system's design by incorporating demand response strategies (DRSs). Incorporating these strategies into the system can enhance system performance, stability, and profitability while also reducing the capacity of SHPS components and, consequently, lowering consumers' bills. To achieve this objective, the sizing model incorporates a novel indicator called the load variation factor (LVF). This paper assesses and contrasts various scenarios, including SHPS without DRS, with DRS, and with DRS but no DE. In this article, interruptible/curtailable (I/C) as one of the DRSs is incorporated into the model used for sizing issues. A newly developed optimization algorithm called the mountain gazelle optimizer (MGO) is utilized for the multi-objective design of the proposed SHPS. The utilization of MGO will facilitate achieving the lowest possible values for each of the following: cost of energy (COE), loss of power supply probability (LPSP), and carbon dioxide (CO2) emissions. This work introduces a mathematical model for the entire system, which is subsequently simulated using MATLAB software. The results reveal that among all the scenarios analysed, scenario iii — which has an LVF of 30% — is the most cost-effective. It has the lowest COE, at 0.2334 $/kWh, hence the lowest net present cost (NPC), at 6,836,445.5 $. [ABSTRACT FROM AUTHOR]

• The optimal allocation of PV and DSTATCOM. • Cost minimization and net saving maximization. • Applying the two recent optimization algorithms for solving the studied optimization problem. • Determining the candidate losses based on sensitivity analysis. • Studying the annual total cost reduction at different penetration levels. This paper introduces an efficient two-stage procedure for assigning the optimal sites and sizes of the photovoltaic-based distributed generator (PV-DG) and distribution static synchronous compensator (DSTATCOM). This procedure is applied for radial distribution network (RDN) under seasonal variations of irradiance and load demand. In the first stage, the voltage loss sensitivity index (VLSI) is utilized to identify the high potential buses for integration of the PV-DG and DSTATCOM while in the second stage, two recent optimization algorithms including the lightning attachment procedure optimization (LAPO) and the equilibrium optimizer (EO) are utilized to identify the best sizes and locations of the PV-DG and DSTATCOM from the candidate nodes. The proposed algorithms are tested on a 118-bus distribution system and the obtained results are compared with the Whale optimization algorithm (WOA) and sine cosine algorithm (SCA). The computational study shows the superiority of the application of the new optimization techniques (LAPO and EO) compared with WOA and SCA. [Display omitted] [ABSTRACT FROM AUTHOR]

As a key portion of renewable energy resources (RESs), wind energy penetration is rapidly deployed. The effects of grid faults on grid-connected wind turbines (WTs) are causing problems for wind energy producers. To meet the necessary requirements, additional resources and technical interventions are needed. One of these requirements is low voltage ride-through (LVRT) of doubly fed induction generator (DFIG)-based WTs. This means that DFIG-WTs must stay connected to the grid during transient grid faults and supply active and reactive power after the fault is cleared. Many techniques for improving the LVRT capability of DFIG-WTs have been developed and this paper examines them. The paper also evaluates how well they align with grid codes, and offers case studies and simulations of the selected key techniques. Lastly, this paper provides guidelines and suggested designs for the LVRT techniques for DFIG-WTs to ensure they meet local grid codes. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the allocation of a hybrid system that includes PV‐DG and DSTATCOM. The planning problem considers the variations of load demand and solar irradiance under deterministic and probabilistic conditions. An efficient optimization algorithm called MPA is implemented to assign the optimal placement and ratings of the hybrid PV‐DG and DSTATCOM. The considered objective function is a multi‐objective function that includes the annual cost reduction, improvement of voltage profiles, and system stability improvement. The assessment is accomplished with the inclusion of a single and two‐hybrid system on a large 94‐bus system. For validating the effectiveness of the MPA, the yielded results are compared with the PSO, which is considered a commonly used algorithm. In deterministic conditions, the hourly variations of the load demand and solar radiation are considered in four yearly seasons, while in probabilistic conditions, 3 years of hourly historical data of solar irradiance and load demand are utilized to describe the uncertainties of the load demand and solar irradiance. The simulation results demonstrate that the optimal inclusion of a single‐hybrid PV‐DG and DSTATCOM system can enhance the system's technical performance (the voltage profile, the voltage stability) and enhance the economic scheme (total annual cost reduction). In addition, the inclusion of two‐hybrid systems is superior compared with the inclusion of a single‐hybrid system in terms of the considered objective functions, as well as the proposed technique is more efficient for solving the allocation problem of the hybrid system. [ABSTRACT FROM AUTHOR]