Mitigating Voltage Instability in the Saudi Grid for a Decarbonized, Fully Solar Power System

The integration of renewable energy sources (RESs) has become more attractive to provide electricity to rural and remote areas, which increases the reliability and sustainability of the electrical system, particularly for areas where electricity extension is difficult. Despite this, the integration of hybrid RESs is accompanied by many problems as a result of the intermittent and unstable nature of RESs. The extant literature has discussed the integration of RESs, but it is not comprehensive enough to clarify all the factors that affect the integration of RESs. In this paper, a comprehensive review is made of the integration of RESs. This review includes various combinations of integrated systems, integration schemes, integration requirements, microgrid communication challenges, as well as artificial intelligence used in the integration. In addition, the review comprehensively presents the potential challenges arising from integrating renewable resources with the grid and the control strategies used. The classifications developed in this review facilitate the integration improvement process. This paper also discusses the various optimization techniques used to reduce the total cost of integrated energy sources. In addition, it examines the use of up-to-date methods to improve the performance of the electrical grid. A case study is conducted to analyze the impact of using artificial intelligence when integrating RESs. The results of the case study prove that the use of artificial intelligence helps to improve the accuracy of operation to provide effective and accurate prediction control of the integrated system. Various optimization techniques are combined with ANN to select the best hybrid model. PSO has the fast convergence rate for reaching to the minimum errors as the Normalized Mean Square Error (NMSE) percentage reaches 1.10% in 3367.50 s.

Stochastic flexible transmission operation for coordinated integration of plug-in electric vehicles and renewable energy sources

Increasing penetration of Renewable Energy Sources (RESs) such as wind, solar plants equipped with fast-acting control systems to the weak points of a power system could be concerned about the problem from classical voltage instability to control instability and control interactions. System strength is one of the important concerns in the integration of RES. Short circuit ratio (SCR) is often used as an index of the system strength. However, when RES are installed in an adjacent location, system strength can be lower than evaluation by SCR. Weighted Short Circuit Ratio (WSCR) is an index that reflects RESs interaction by assuming a 100% influence. This paper propose Inverter Interaction Level Short Circuit Ratio (IILSCR) method using inverter-based resource's output tracing. IILSCR can accurately estimate system strength which RESs are connected in adjacent spot by reflecting the interaction between RESs.

With the large scale grid integration of renewable energy sources(RES) such as photovoltaic(PV) and wind power stations, new energy has become one of the main power sources, which has brought a series of challenges to the security, reliability and operation scheduling of the power grid system. There is an urgent need that these RES, especially the PV power generation system with IGBT-based inverters, supports the rapid power control, based on which the power grid system stability control system(PSCS) can realize "two-way regulating instead of one-way tripping/switching off ". A new scheme of system stability control based on photovoltaic rapid power control technology, and a station rapid power control device was also designed, supported by fast communication and rapid power execution of inverters. The scheme has been applied and tested in power grid of China. The test and operation results verify the effectiveness and advancement of the technology.

A reactive scheduling and control framework for integration of renewable energy sources with a reformer-based fuel cell system and an energy storage device

Increase in generating electricity using fossil fuel, nuclear power, coal and natural gas greatly affects human health and causes climate changes or global warming. Integration of renewable energy sources with power grid can help to overcome these challenging problems. This approach together with smarter techniques is referred to smart grid as it promises to provide an affordable electrical environment. It is noted that neither a standalone photovoltaic system, nor a wind energy system can provide a supply of energy continuously due to seasonal and periodic variations. This paper analyses an approach of integrating a solar-battery system with an existing power grid. This paper also provides an energy efficient methodology to control and optimize the energy consumption and usage from the power grid. This leads to a smart grid platform which can help not only to increase the efficiency, security, reliability but also to reduce the impact on health problems and environmental effects. Simulation studies were carried out and the simulation results ensure the advantages of this energy management approach. It is showed that the introduction of battery storage to the solar system achieves a more stabilized power supply which helps to reduce electricity bill by reducing power grid usage and increase the usage of renewable energy.

This paper introduces a Modified Reptile Search Algorithm (MRSA) designed to optimize the operation of distribution networks (DNs) considering the growing integration of renewable energy sources (RESs). The integration of RESs‐based Distributed Generation (DG) systems, such as wind turbines (WTs) and photovoltaics (PVs), presents a complex challenge due to its significant impact on DN operations and planning, particularly considering uncertainties related to solar irradiance, temperature, wind speed, consumption, and energy prices. The primary objective is cost reduction, encompassing electricity acquisition, PV and WTs unit costs, and annual energy losses. The proposed MRSA incorporates two strategies: the fitness‐distance balance method and Levy flight motion, enhancing its searching capabilities beyond standard Reptile Search Algorithm and mitigating local optima issues. The uncertainties in load demand, energy prices, and renewable energy generation are represented through probability density functions and simulated using Monte Carlo methods. Evaluation involves typical bentchmark functions and a real 112‐bus Algerian DN, comparing MRSA's efficacy with other optimization techniques. Results indicate that the proposed DN optimization program with WTs and PVs integration reduces annual costs by 21.43%, from 6.2715E + 06 to 4.9270E + 06 USD, reduce voltage deviations by 21.67%, from 77.1022 to 60.4007 USD, and enhance system stability by 2.59%, from 2.3699E + 03 to 2.4314E + 03 USD, compared with the base case.

Voltage source converters (VSCs) have emerged as the key components in modern power systems, facilitating efficient energy conversion and flexible power flow control. Understanding the fundamental circuit model of VSCs is essential for their accurate modeling and analysis in power system studies. A basic voltage source converter circuit model connected to an LC filter is essential because it lowers the harmonic distortions and enhances the overall power quality of the micro-grid. This guarantees a clean and steady power supply, which is necessary for the integration of multiple renewable energy sources and sensitive loads. A comprehensive methodology for developing a basic circuit model of VSCs, focusing on the key components and principals involved, is presented in this paper. The methodology includes the modeling of space vector pulse-width modulation (SVPWM) as well as the direct quadrature zero synchronous reference frame. Different design controls, including the design of current control loop in the S-domain, the design of the direct current (DC) bus voltage control loop in the S-domain, and the design of the alternating current (AC) voltage control loop in the S-domain, are explored to capture the dynamic behavior and control strategies of VSCs accurately. The proposed methodology provides a systematic framework for modeling VSCs, enabling engineers and researchers to analyze their performance and assess their impact on power system stability and operation. Future studies can be conducted by using case studies and simulation scenarios to show the efficiency and applicability of the developed models in analyzing VSC-based power electronics applications, including high-voltage direct current (HVDC) transmission systems and flexible alternating current transmission systems (FACTS). The significance of this work lies in its potential to advance the understanding and application of VSCs, contributing to more resilient and efficient power systems. By providing a solid foundation for future research and development, this study supports the ongoing integration of renewable energy sources and the advancement of modern electrical infrastructure.

Recently the growing demand for electricity has led to the increase of integrating renewable energy sources (RES) into the grid. This has proven to be an advantage for both power systems and environmental impacts. The introduction of RES has proven to be effective in minimizing power outages due to electricity shortage. Subsequently, this technology has been effective in preserving the atmosphere. However, RES integration has challenges which they bring into the power grid. In this paper, we analyzed the effect of connecting the wind turbine into the grid under fault conditions. From the results obtained, connecting RES increases the fault current which in-turn has the potential to increase the damages within the power grid.

This paper presents an adaptive load-frequency control scheme for a grid-connected solar PV system which supplies a load locally. The grid is meant to complement the solar Photo-Voltaic (PV) system ideally, but because of different loading conditions and intermittent nature of the solar PV system grid support becomes necessary. The PV system is integrated to the synchronous generator based grid via power electronic converters which extracts maximum power from solar PV based using Perturb and Observe (P&O) algorithm to get maximum benefit from the PV system. Integration of renewable energy sources tends to reduce the overall inertia of the grid and hence threaten its stability. Also, perturbations on the load side are known to affect the frequency negatively and now with increased penetration of intermittent renewable energy sources, the frequency problem is expected to be aggravated. The proposed frequency control scheme incorporates a Model Reference Adaptive Controller (MRAC) on the grid side to ensure that the grid frequency is restored within a much smaller time post small disturbances on either the load or the generation side. The proposed system is verified using MATLAB-SIMULINK under wide variation in system conditions.

The current level of electrification necessitates higher standards for electricity supply quality, highlighting the importance of the efficient organization, operation, and management of electricity systems. Addressing these challenges has become more complex with the increased integration of renewable energy sources (RES). This is particularly relevant for distribution power grids, which, due to their structural characteristics, are generally not adapted to accommodate fluctuating energy sources owing to insufficient network automation. This paper presents an approach based on an integral metric to evaluate the readiness of power grids to meet specific electricity supply requirements. The proposed metric is derived from an analysis of electricity supply quality within the context of accelerated RES development and power grid characteristics critical to quality performance. Such a metric is valuable for forming general strategies and solutions for grid development, particularly with respect to RES integration and the intellectualization of power systems. The integral indicator components are expressed as the probability that the operational mode aligns with an 'ideal' mode. This «Ideal» mode is determined using the least-impact principle and corresponds to a substitute network scheme based on the rscheme, thereby reducing subjectivity in assessments and subsequent decision-making.It is demonstrated that this approach to defining the integral indicator of power grid performance quality enables not only an assessment of current grid readiness but also consideration of specific consumer preferences in design decisions. The methodology outlined here details a progression from relative performance evaluations of grid components to cost assessments, ultimately allowing for technical and economic analyses. This approach facilitates targeted planning for measures aimed at improving grid performance quality and the reliability of power supply to consumers.

Purpose of the Study. The study aims to investigate various approaches to mitigating the impact of renewable energy sources on the stability of the power system and to determine the optimal combination of conventional and renewable energy sources to ensure stable and reliable energy supply. The effectiveness of different approaches to minimizing the impact of renewable energy on grid stability is evaluated. Materials and Methods. Methods of eigenvalue analysis and transient process modeling were used. Correlation and regression analysis methods were used to assess the impact of renewable energy sources (RES) on the stability of the energy system. Data from the system operator «Ukrenergo» were used, including power system load schedules (hourly, daily, seasonal). Data from the Ukrainian Hydrometeorological Center for the years 2023–2024 were used to model RES generation: data on solar radiation (hourly, daily) and wind speed (hourly, daily). Technical specifications of solar panels and wind turbines installed in Ukraine were also used. The QGIS software was utilized for geoinformation analysis. The study employed artificial neural network theory, optimization methods based on linear programming and logical production rules, as well as methods for assessing and regulating steady-state operating conditions of the system, taking into account energy storage devices. Results. The scientific novelty lies in the development of an innovative method for assessing the reduction of the impact of renewable energy sources on power system stability. The feasibility of using artificial neural networks to forecast wind and solar power generation was demonstrated, as well as the optimization of the model structure and parameters to improve forecasting accuracy. The optimal combination of conventional and renewable energy sources was determined to ensure stable and reliable operation of the power system. Practical Significance. Based on experimental and theoretical research, specific recommendations and solutions are provided aimed at ensuring the stability of the power system during the integration of renewable energy sources, including optimization of management, use of new technologies, and infrastructure development

Accurate modeling of photovoltaic systems for studying the transient effects of lightning strikes

The integration of renewable energy sources, such as photovoltaic (PV) and wind turbine generators (WTG), into the power systems of remote islands is an effective strategy to reduce carbon emissions and decrease dependence on diesel generators. By replacing diesel-generated electricity with PV-WTG hybrid energy, significant carbon emission reductions can be achieved. Given the diesel fuel emission factor of 2.68 kg CO2-eq per liter, the estimated annual emission reduction is 6,103 tons CO2-eq per year. The integration of PV and WTG into the local grid not only contributes to carbon reduction but also improves energy security and sustainability in remote areas. This research investigates the impact of a hybrid PV and WTG system on carbon emission reduction in Karimunjawa Island, Indonesia, using the Specific Fuel Consumption (SFC) Diesel method. The study proposes a research model involving 800 kWp solar PV and a 750 kW Goldwind WTG. Parameters include annual energy consumption, wind speed variations, and solar irradiance. Based on prior studies, hybrid systems have proven effective in reducing fuel consumption and emissions in island settings, but detailed evaluation on fuel savings and emission outcomes using actual system sizing remains limited. The proposed model simulates electricity generation from both PV and WTG based on local NASA satellite data and compares it against existing diesel-only generation. This study highlights the importance of transitioning to renewable energy sources in remote and off-grid island communities, reducing dependence on fossil fuels, and supporting Indonesia’s decarbonization goals. This study analyzes the impact of PV-WTG hybrid power plants on carbon emission reduction in Karimunjawa Island, using the Diesel Specific Fuel Consumption (SFC) approach. The annual energy consumption in Karimunjawa reaches 5,284,317.3 kWh, with an average SFC of 0.431 liters/kWh, resulting in an annual diesel fuel consumption of 2,277,640.69 liters.

The integration of renewable energy sources (RESs) such as solar photovoltaic (PV) and wind energy has become a promising solution as the world shifts toward clean energy. Solar PV and wind resources are increasingly replacing conventional synchronous generators, leading to reduced system inertia and increased vulnerability to frequency instability during disturbances. To address this challenge, this study proposes a novel synthetic inertia provision strategy using a battery energy storage system (BESS) integrated alongside solar PV. The proposed method dynamically compensates for the loss of inertia by considering the variability of solar PV output due to changes in irradiance and temperature. Simulation results obtained in MATLAB/Simulink demonstrate that the proposed strategy significantly improves system stability, with a reduction in the rate of change of frequency (RoCoF) by up to 86.6% and an improvement in frequency nadir by 0.91% under high PV penetration scenarios. These results confirm that incorporating synthetic inertia via BESS enhances the frequency response and resilience of low-inertia power systems with high renewable penetration.