The Impact of Integrating Variable Renewable Energy Sources into Grid-Connected Power Systems: Challenges, Mitigation Strategies, and Prospects

Abstract

Although the impact of integrating solar and wind sources into the power system has been studied in the past, the chaos caused by wind and solar energy generation has not yet had broader mitigation solutions notwithstanding their rapid deployment. Many research efforts in using prediction models have developed real-time monitoring of variability and machine learning predictive algorithms in contrast to the conventional methods of studying variability. This study focused on the causes and types of variability, challenges, and mitigation strategies used to minimize variability in grids worldwide. A summary of the top ten cases of countries that have successfully managed variability in their electrical power grids has been presented. Review shows that most of the success cases embraced advanced energy storage, grid upgrading, and flexible energy mix as key technological and economic strategies. A seven-point conceptual framework involving all energy stakeholders for managing variability in power system networks and increasing variable renewable energy (VRE)-grid integration has been proposed. Long-duration energy storage, virtual power plants (VPPs), smart grid infrastructure, cross-border interconnection, power-to-X, and grid flexibility are the key takeaways in achieving a reliable, resilient, and stable grid. This review provides a useful summary of up-to-date research information for researchers and industries investing in a renewable energy-intensive grid.

1. Introduction

Integrating VRE sources, like wind and solar into grid-connected power systems, offers considerable opportunities alongside notable challenges. As the global transition to clean energy accelerates, the growing proportion of VRE in electricity generation can minimize greenhouse gas emissions and strengthen energy security. Nevertheless, the intermittent and variable nature of VRE sources poses significant obstacles to grid stability, reliability, and efficient energy distribution [1,2]. These hurdles include variations in power output, matching supply with demand, and maintaining grid frequency and voltage. To mitigate these issues, various techno-economic and policy-related strategies such as energy storage systems, sophisticated forecasting methods, demand response initiatives, and the enhancement of grid infrastructure through smart grid technologies have been conceived and implemented in some countries around the world. These approaches are designed to enhance grid flexibility and reliability while accommodating increased VRE integration. Moreover, advancements in technology, supportive policies, and innovative market solutions are essential in further incorporating VRE into grid-connected systems, paving the way for less polluting and more eco-friendly energy prospects [3].

In recent years, the number of VRE installations and wind/PV-grid-connected systems has been on an exponential increase in various regions; however, the impact of the variability of these renewable energy sources (sun and wind) has received modest attention compared to its proliferation. This study steps in to examine the variability impact of integrating solar and wind into conventional power grids, the strategies, and conceptual frameworks that could mitigate the challenges that arise, and the scalability prospects.

Variation in renewable energy is contained with ease when demand and supply are matched, both rising and falling simultaneously. When demand and renewable supplies move in opposite directions, the cost of balancing can rise considerably [4]. The innovations in VRE-fed power grids today present a new shift of difficulties making the issue of variability more evident in networks. Also, RE systems exhibit a notably weak correlation with the power demand, creating a negative effect on the grid [5]. Both variability and uncertainty in solar and wind energy happen across numerous time scales posing issues to the grid, but the injection of small quantities of renewable energy on the power grid can be smoothly interconnected. Injecting high values beyond 30% starts causing chaos and will need new methods to deal with expanding and operating the grid [4,6].

Although significant progress has been made in the integration of VRE sources into grid-connected power systems, there are still challenges in maximizing their efficiencies, grid stability, energy storage, and supply-demand balancing in the present networks. The unpredictable nature, seasonal variations, and intrinsic fluctuations associated with solar and wind energy generation pose difficulties in smoothly integrating renewables into traditional electrical power networks. Ultimately, the study evaluates the prospects of VRE integration in achieving sustainable, reliable, and resilient power systems. This paper addresses the impacts of wind/solar variability in power systems and proposes methodical solutions. It specifically addresses the following research objectives:

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To examine the techno-economic difficulties in incorporating VRE into grid-connected power systems, focusing on issues like intermittency, frequency regulation, voltage violations, power quality, and ancillary services.

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To identify mitigating strategies that can improve grid stability and reliability, including advanced forecasting techniques, energy storage options, and demand response mechanisms.

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To review the role of grid modernization and adaptable infrastructure in supporting the high proportions of renewable energy while ensuring optimal grid performance.

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To present a survey of 10 successful cases of well-managed variability worldwide and propose a conceptual framework that can be followed to minimize variability in line with the day-to-day technological advancements, policy frameworks, and market trends.

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To explore the long-term prospects of VRE integration in fostering a sustainable and resilient power grid.

The paper starts with an introduction and proceeds with reviewing the literature on previous studies to set the pace for this study. Thereafter, the methodology is presented and followed by a comprehensive outline of variability in power systems. A discussion section is presented before the perspectives. The overall structure of the paper is shown in Figure 1.

2. Review of Related Literature

Integrating high portions of variable renewable energy sources into conventional energy networks has become a leading method. Also, the need to fulfill the net zero emission (NZE) agreement of COP28 by 2050 has come along with pressing grid challenges [7,8,9]. Although advancements have been made in literature, ongoing research remains crucial for creating effective and scalable solutions that facilitate the smooth incorporation of VRE into current power grids.

The authors in [10] investigated optimal power system flexibility for the integration of VRE. The survey examined the baseline scenario and the investment scenario, their report revealed challenges such as aging infrastructure, inadequate generation capacity, frequent power outages, and minimal renewable energy production (1.9%), accompanied by a substantial loss of load. The study falls short of data gaps and inconsistency, with limited stakeholder participation of only 25% of companies responding to targeted entities. Policy application complexity is another limitation of the investigation, the study did not treat the obstacles that decision-makers might encounter. The study affirms the technical shortcomings of accuracy in data collection and model constraints which need to be improved for the effectiveness of the suggested solutions to VRE integration.

In the research work presented in [11], wind and solar energy were explored as the major sources of variable renewable energy and as integration into the power system grid as a means to strengthen grid robustness using data analysis. The authors focus on methods to enhance the incorporation of wind and sun energy into the power grid while improving the grid’s resilience. Using a comprehensive four-year dataset from Spain that comprised energy consumption, generation, pricing, and weather conditions. The study applied advanced statistical analyses, regression models, and optimization techniques. The findings indicate that solar energy exhibits seasonal patterns, whereas wind energy is characterized by variability, significantly influenced by weather conditions. The study fell short of data variability considerations, for not using data from the previous five years to analyze long-term variability. This may have limited the trends and anomalies in power generation and consumption which are critical for VRE grid-connected systems demand and supply side management. The study goes further to point out unequal energy demand and supply, citing seasonal variability and intermittency as the major threats to grid stability which need further findings.

The review in [12] examines the distinct effects of photovoltaic systems (PVs) and electric vehicle (EV) integration on electrical grids. It stresses the adverse collective impact of PV-EV integration on the stability of the power system which causes serious chaos; voltage violations, continual rotor angle oscillation, frequency regulation, loss of loads, energy shifting, losses, and harmonic distortion. The survey suggested coordinated operations to eliminate the challenges associated with the individual integration of PV and EV, indicating that limited research has been conducted on the combined effects of these systems on power quality and economic factors. This literature exposes the following gaps: the need to investigate the collective impact of integrating PVs and EVs and the need for a specific control mechanism or framework that could manage fluctuations in the grid system (PV/EV integration). This study is limited by the fact that it did not show the most effective strategies for managing the interaction between RE sources and electric vehicle charging. An in-depth examination of harmonics generated using PV systems and EVs is essential to propose suitable power electronics-driven converters.

The research conducted by the authors in [13] on large-scale solar penetration in the Nigerian electrical grid identified voltage instability and the aged shunt reactors as key challenges associated with the integration of variable renewable energy (VRE). The study examined two scenarios: one involving centralized large-scale PV generation at critical bus locations and the other focusing on dispersed large-scale PV installations across less robust buses within the grid. To evaluate the impact of PV integration, the critical voltage-reactive power ratio (CVQR) index was employed, derived from P-V and Q-V analyses. The results indicated that in the case of centralized PV generation, the maximum bus voltage could remain within acceptable thresholds at a penetration level of 26.29% (1000 MW), whereas the dispersed PV scenario achieved this at a penetration level of 21.44% (800 MW). The limited scope of the case study may not wholly mirror the challenges and dynamics of other weak national networks such that the result could be applied to other regions facing similar situations. With a major emphasis on voltage stability enhancement, critical factors such as the environmental impacts of large-scale wind and solar integration, economic feasibility, and grid flexibility may have been left out. A more holistic approach could provide a broader understanding of the implications of large-scale PV integration. The scarcity of prior research papers mentioned in the work may limit the depth of comparison and validation of the findings presented in the report.

The research in [14] examines the impact of rooftop solar energy on distribution networks. It emphasizes power loss, and voltage instability resulting from photovoltaic integration as the key challenges posed by VRE to power grids. The analysis employed ETAP (version 19) software to conduct simulations. The authors suggest reactive power compensation and load tap adjustments to stabilize the voltage and minimize power losses. Identified gaps for future research include the need for studies on independent measurements for photovoltaic sources and consumption loads and the need for output unit commitment in forecasting power generation capacity trends. Monitoring solutions for the quality of electricity from various grid-connected inverters need to be put in place by research. Furthermore, the substantial investment associated with the installation of discrete measurement devices impedes efficient data collection for forecasting purposes.

A rigorous scrutiny of existing literature on temporal variability evaluation and forecasting methods for solar, wind, wave, and tidal energy resources was presented in [15]. The authors identified research gaps like the pertinent need for more coherent studies that explore variability and forecasting comparatively, using data with the same temporal and spatial resolution. The survey compares various forecasting approaches and variability evaluation strategies used for renewable energy sources. The comparison is essential for understanding the strengths and weaknesses of existing approaches and for establishing best practices in the field. Emphasis was laid on temporal variability not just in terms of resource availability but also in terms of actual power generation. The work encourages more research into the filtering effect and total variability in the renewable energy mix and integration issues.

Other studies have investigated the spatial and temporal fluctuations of VRE, highlighting the complementary nature of solar and wind generation patterns. This characteristic allows for the management of their variability through strategic planning and optimization of the grid [16]. The reference [1] adds that power system flexibility is a necessary complementarity in sub-Saharan Africa, through the coupling of wind and solar to hydro plants in boosting VRE hybrid grid penetration.

The research [17] examined approaches for interpretable machine learning (ML) in weather and climate prediction, including post-hoc techniques such as additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME) that improve model transparency. The findings indicate enhanced forecast accuracy, which will help in the management of VRE variability. However, shortcomings include the complexity of atmospheric data and the necessity for tailor-made explicable approaches to meteorological challenges. The research recommends further surveys to establish domain-specific methodologies and incorporate explicability into the model development lifecycle to improve prediction, reliability, and physical consistency. This method will improve model interpretability while also ensuring that stakeholders can make informed decisions based on realistic climate forecasts.

Grid-scale solar farm systems achieve profitability, primarily when solar power generation can be accurately predicted and controlled within a 15-min timeframe for the customer. Advanced deep learning models, grounded in computational finance, can enhance prediction accuracy and mitigate financial risks. Essential strategies employed in deep learning-based solar power models encompass a wide array of hyper-parameters across diverse ranges, an extensive set of historical predictors, and the utilization of assembly models that integrate various deep learning approaches to bolster prediction accuracy [18].

An evaluation of the implementation of wind and solar plants and integration into an existing grid was carried out to trace the path for renewable energy advancements and the associated challenges. The study highlights challenges that may emerge from the integration of VRE technologies into the existing power system infrastructure, citing voltage instability, voltage rise, reverse power flow, unplanned islanding, frequency variation, and harmonic distortions which jeopardize the reliability and quality of electricity delivered to consumers [19,20]. The paper outlined a framework for evaluating potential energy output from wind and solar power plants using raw data obtained from meteorological stations. The authors propose the aggregation of wind and solar energy outputs, FACTS devices, and adaptive, and AI-based algorithms as remedial strategies to enhance power generation and eliminate grid instability. The paper’s drawbacks include a narrow emphasis on battery storage solutions and a lack of real-world case studies, which may limit its practical application. The authors recommend that prospective studies should look at developing technologies, extensive control methods, and localized studies to improve the efficacy of VRE integration into different grid topologies.

Another study emphasized the inability to maintain grid reliability as the amount of VRE grows. The authors highlight the main grid-related issues to be; frequency regulation, voltage control, and power quality [21]. The researchers add that traditional grid infrastructure often designed for centralized and predictable power sources needs to be modernized to accommodate the decentralized, fluctuating nature of renewable generation and electric vehicles. The study fell short of investigating the enhancement methodologies and establishing strong strategies for the effective integration of EVs and RES in the power grid.

A state-of-the-art literature review on the number of published papers and research focus in recent years (2019–2024) is summarized in

Table 1. Summary of published paper and focus in recent years.

Author/Reference	Year	Topic	Focus
Juma et al. [1]	2023	Power System Flexibility: A Necessary Complement to Variable Renewable Energy Optimal Capacity Configuration	Impacts of intermittency on grid stability and efficient energy distribution.
Xu et al. [2]	2022	The implementation limitation of variable renewable energies and its impacts on the public power grid.	Impacts of variability on demand and supply, stability, and voltage fluctuations.
Zaheb et al. [10]	2023	Optimal Grid Flexibility Assessment for Integration of Variable Renewable-Based Electricity Generation.	Aging infrastructure, inadequate generation, power outages, minimal RE production, and loss of loads.
Ahmad et al. [12]	2020	Impacts of grid integration of Solar PV and Electric Vehicle on grid stability, power quality, and Energy Economics.	The collective adverse impact of PV-EV integration on the stability of the power system.
R. Yang et al. [17]	2024	Interpretable machine learning for weather and climate prediction.	Two approaches for interpretable machine learning in weather and climate prediction techniques.
S. Y. Jang et al. [18]	2024	A Deep Learning-Based Solar Power Generation Forecasting Method Applicable to Multiple Sites.	Advanced deep learning models, grounded in computation and prediction accuracy, mitigate variability risks.
C. A. Cárdenas [20]	2023	Analysis of the Impact of Integrating Variable Renewable Energy into the Power System in the Colombian Caribbean Region.	Comparison of the impact of adding VRE on the Colombian grid; the present 2023 grid to the grid of 2033.
J. Dimnik et al. [22]	2024	Impacts of High PV Penetration on Slovenia’s Electricity Grid: Energy Modeling and Life Cycle Assessment.	PV Variability integration, impact analysis of life cycle evaluation of technical, and environmental aspects of grid penetration.
A. sIung et al. [23]	2023	A Review on Modeling Variable Renewable Energy: Complementarity and Spatial-Temporal Dependence.	A systematic review, providing an overview of applied methodologies and methods to address reliance and complementarity.
Magaña-González et al. [24]	2023	Analysis of seasonal variability and complementarity of wind and solar resources in Mexico.	Focused on wind and solar resources’ local and regional complementarity using experimental and ERA5 data in Mexico.
Chang-Gi Min [25]	2019	Analyzing the Impact of Variability and Uncertainty on Power System Flexibility.	Variability and uncertainty to determine which is more impactful on flexibility, using flexibility index, ramping capability shortage probability (RSP), to quantify the effect on power system flexibility.
R. Singh et al. [26]	2024	Machine learning-based energy management and power forecasting in grid-connected microgrids with multiple distributed energy sources.	Proposal of a support vector regression algorithm model that accurately forecasts power generation, and improves grid stability, mitigating the variability and intermittency of VRES.
Mohit et al. [27]	2023	Institutional Framework of Variable Renewable Energy Forecasting in India.	Review of institutional frameworks for VRE forecasting that advocate large-scale integration in India by applying the best practices. Presents 6 methods of enhancing the VRE forecasting framework in India.
M. Shafiullah et al. [28]	2022	Grid Integration Challenges and Solution Strategies for Solar PV Systems.	Focused on the challenges and solutions of integrating PV into grid-connected systems; addressing technical, operational, and market problems while emphasizing methods like ESS and advanced control as solutions to variability.
Han et al. [29]	2021	Real-Time Load Variability Control Using Energy Storage System for Demand-Side Management in South Korea.	The control of fluctuation in customers’ load profiles in real-time DSM using consumer’s installed batteries, optimizing the reserved capacity. Proposal of a hybrid method of estimating variability every 15 min, and, in turn, reserve ESSs.
Gonçalves et al. [30]	2024	Extreme weather events on energy systems: a comprehensive review on impacts, mitigation, and adaptation measures.	Reviewed mitigation strategies, and analyzed them to reduce the impact of bad weather conditions on RE-grid systems. Examines grid protection, and adapts the systems’ resilience.
IEA [31]	2023	Managing Seasonal and Inter-annual Variability of Renewables.	Strategies of dealing with short-term and long-term variability in VRE sources.
L. Göransson et al. [32]	2021	Management of Wind Power Variations in Electricity System Investment Models: A Parallel Computing Strategy.	Evaluated the Hours-to-Decades model on an approach to account for strategies to manage variations in the electricity system covering several days, with an interest in wind power variation management.
P. Hirschorn [33]	2021	Rising to the Challenges of Integrating Solar and Wind at Scale.	Focused on the challenges of injecting VRE in great quantities and the solutions to congestion, uncertainty, and scalability for power grid stability.
Basit et al. [34]	2020	Limitations, challenges, and solution approaches in grid-connected renewable energy systems.	Grid integrated-RESs challenges: power quality problems, network instability, harmonics, oscillations. Proposing ESSs as solution to intermittency form RESs.
C.Medinal et al. [35]	2022	Transmission Grids to Foster High Penetration of Large-Scale Variable Renewable Energy Sources—A Review of Challenges, Problems, and Solutions	Focused on transmission infrastructure’s role in minimizing variability effect in grid power quality (voltage sag, swell, transient, frequency fluctuation,)
J. Heptonstall and Gross [36]	2020	A systematic review of the costs and impacts of integrating variable renewables into power grids.	The effect of additional expenditure stemming from variability and its impact on the grid.
R. Sadiq et al. [37]	2021	A review of static synchronous compensator control for stability enhancement of power systems with wind/PV penetration: Existing research and future scope.	The study focused on control strategies for managing stability in networks integrated with VRESs, addressing rotor angle, voltage, and resonance stability hurdles due to increased power electronics in grids.
Cho et al. [38]	2024	Global Residual Demand Analysis in a Deep Variable Renewable Energy Penetration Scenario for Replacing Coal: A Study of 42 Countries.	Analyzes the residual demand curves of 42 nations under 5 scenarios with varying variable renewable energy (VRE) levels to see if the replacement of coal with VRE can change the demand curve.
Latifa A. et al. [39]	2023	Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions	VRE management AI techniques for optimized power generation, forecasting, power demand forecasting, energy storage, and optimal integration.
Y. Fang et al. [40]	2024	Electric energy system planning considering chronological renewable generation variability and uncertainty.	Proposal on grid expansion-planning model that integrates operational flexibility constraints addressing both long and short-term variability and uncertainty for high VRE penetration.

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From the review, we observe that the latest studies concerning grid stability and the incorporation of VRE sources highlight the remarkable challenges arising from the variability and intermittency associated with renewable energy sources, particularly wind and solar. Generally, they have underscored the necessity for innovative grid infrastructure, enhanced forecasting methods, and real-time monitoring systems to maintain reliable functioning as the proportion of renewable energy grows. The majority of grids reviewed in these studies are either hypothetical or lack practical cases that help other scholars replicate these studies. Also, most of the studies treated the challenges caused by variability as an entity (globalizing its impacts) without disintegrating them to identify the individual sources of variability. The incorporation of VRE sources (sun and wind) with conventional power grids (thermal, coal, hydrogen gas, hydro) results in multiple sources of chaos. The need to investigate supportive regulatory policies and strategies that foster grid stability and reliability in the face of variability is inevitable [41]. This study fills the gaps in the strategic management of variability in VRE power grids and proposes an all-inclusive policy framework in relation to the shortcomings found in the literature, like in [22,42,43]. The research contributions of this study are summarized as follows:

• An up-to-date comprehensive literature review on the impacts of the variability of renewable energy integration into power grids, the chaos caused, and the different successful mitigation methods applied in some ten selected countries’ grids worldwide.
• A review of the key technological, economic, and policy mitigation strategies; analytical, and data-driven, machine learning methods for managing variability from both the demand and supply side.
• A seven-point proposed conceptual policy framework for smoothing out variability in VRE grid-connected power systems involving all energy stakeholders, with lessons drawn from the successful cases has been presented.
• The work highlights the essentiality of long-duration energy storage, grid-forming inverters, virtual power plants, smart grid/infrastructure, and incentivizing support as key takeaways for reliable, resilient, and carbon-free grids.

This work is different in that it focuses on a holistic review of VRE sources and their impacts on power systems grids, providing useful insights concerning the challenges, mitigation strategies, frameworks, and prospects over a broad scale including the technological, economic, and policy aspects. A clear understanding of the inherent variability of solar and wind resources integration from this study will serve as a lift from the pitfall of some VRE grid-connected projects around the globe, paving the way for efficient grid decarbonization.

3. Methodology Adopted

This survey provides a theoretical framework for the effects of incorporating variable renewable energy sources (VRE) sources into power systems. We followed a systematic approach to assemble materials for this paper. Firstly, we carried out an exhaustive sorting of 552 papers related to the study on grid integration of VRESs utilizing well-known scientific databases such as Scopus, Google Scholar, ScienceDirect, SpringerLink, Web of Science, and scientific journal websites. The following keywords were used: variability, power system stability, energy storage, grid flexibility, renewable energy integration, variable renewable energy, mitigation strategies, and countries’ grid reports. This review focused on the solar and wind sources because of their high unpredictability excluding energy sources that vary seasonally and can be predictable like hydro, tidal, and ocean power. During the search, the main literature sample was extracted from the Science Direct database using the following Boolean expressions: ((“variable renewable energy” OR “intermittent renewable energy”) AND (“solar PV” OR “wind power”) AND (“grid integration” OR “power system”) NOT “hydro” NOT “tidal” NOT “waste”) and (“grid-connected” AND (“power system stability” OR “voltage regulation” OR “ energy storage” AND (“challenges” OR “mitigation strategies” OR Policies”)) NOT “modeling “NOT “Simulation”). Studies focused on modeling and simulations were excluded as they often address a single challenge. Likewise, studies dealing with price and tariff analyses and waste management were excluded as indicated by the search query. Meanwhile, some theoretical and empirical studies were included to ensure a balanced conceptual framework with practical applications and real-world case studies.

Secondly, emphasis was placed on prioritizing recent publications of the last 5 years between 2019 and 2024 to address the current state-of-the-art research in renewable energy (RE) variability. However, despite the stringent restrictions on the publication timeframe, major seminal works outside this timeframe that have significantly influenced the field and continue to be widely cited were included. We systematically reviewed over 130 review publications for clarity of the ideas on variability in renewable energy sources and grid integration, as well as over 70 technical studies, before selecting 105 papers and reports. Based on these investigations, we assessed key publications to determine the methods used, challenges, mitigation strategies, and prospects of VRESs to grid integration.

Furthermore, it is critical to understand how some governments’ policies handled earlier related issues. Following this phase, the most relevant articles were sorted, giving us a foundation with which to develop this research paper. We were able to grasp the evolution of variable energy sources as well as new technologies that have recently gained attention. Also, technical publications provided a more in-depth understanding of applications and cost-effective policies for developing VRE sources, as well as opportunities and barriers. Through the results of these investigations, we have demonstrated through a proposed framework, the key roles played by government policies, techno-economic changes, or advancements in the development and management of variable renewable energy to grid integration. Also, we have taken advantage of the opportunities that these sectors present to suggest the best solutions and recommendations to scale up the benefits of VRE integration. Figure 1 shows the structure of this paper. All publications relevant to the subject were sorted and divided into two categories: technical papers and peer-reviewed papers. A methodology was established based on these papers and the structure of the paper was defined.

According to the systematic review approach presented by the authors in [23,44], we developed a step-by-step method for sorting the peer-reviewed papers and relevant reports used in writing this paper. The review used the PRISMA 2020 flow diagram for screening the number of papers referenced and a checklist for organizing the different articles [45]. A synthesis of the selection criteria is outlined here.

• Identification process

The global number of studies identified from databases such as Scopus, Google Scholar, Web of Science, and Science Direct was 552 research works.

2.

Screening approach

The number of studies after double occurrences were extracted was considered 181 from the total number of studies.

A number of studies were excluded after examining the titles and reading the abstract. For example, the studies on tidal, biomass, hydro, modeling, and simulation researches, 147 of them were exempted.

3.

Eligibility

The number of full-text research processed to be eligible was 130 reviewed studies, and the number of full-text research works and technical reports reviewed and found irrelevant to our study was 31 investigations. These were excluded. The exclusion of some studies was due to the following reasons:

• Because the studies focused on biomass energy and other energy sources.
• Because the studies were out of the publications’ time frame (2019–2024) defined for our review.
• Because the studies concentrated on modeling and simulation of a specific aspect.

4.

Inclusion

The final number of studies included in the review writing was made up of peer-reviewed, conference papers, and technical reports were 106. More details are highlighted on the PRISMA flow diagram of Figure 2 below.

From the methodology and flow diagram presented above, the planning and systematic review process followed specific and well-structured guidelines summarized in the PRISMA checklist

Table 2. PRISMA checklist.

Item	Section	Description	How It’s Addressed in Your Paper
1	Title	Identifying the systematic review or the meta-analysis in the title.	“Systematic Review of Grid Integration of Variable Renewable Energy Sources”
2	Abstract	A structured abstract consists of a background, objectives, eligibility criteria, participants, intervention, and outcomes.	Structured abstract summarizing the framework for integrating VRE sources, eligibility criteria, and key findings.
3	Rationale	Explanation of the reason for the systematic review.	Motivation for investigating VRE integration to improve power system stability and grid flexibility.
4	Objectives	A clear statement of the review objectives.	The objective was to assess the impact of VRE sources (solar and wind) on grid integration, system stability, and mitigation strategies.
5	Eligibility Criteria	Peculiar inclusion and exclusion criteria for the studies.	Studies focused on solar and wind power sources. Excluding tidal, biomass, hydro, and ocean energy sources. Also excluded modeling and simulation studies.
6	Information Sources	Databases, registers, and other information sources were used to find information for the review.	Databases: Scopus, ScienceDirect, Web of Science, SpringerLink, etc.
7	Search Strategy	Detailed search method including keywords, Boolean operators, and date range.	Keywords: “variable renewable energy” solar PV” Grid integration” “wind power”. Time frame: 2019–2024, with inclusion of seminal studies.
8	Study selection	Process of selecting studies, including screening.	The studies were screened based on the abstract and titles, followed by a full-text review respecting the exclusion/inclusion criteria.
9	Data Extraction	Information extracted from studies.	Major themes on methods, challenges, mitigation strategies, government policies, and enhanced technology in VRE integration.
10	Risk of bias	Risk of bias in included studies.	Potential bias may be acknowledged in the discussion section.
11	Synthesis of Results	Synthesis method: quantitative or qualitative.	A qualitative analysis of the key challenges, mitigation strategies, technological, and policy strategies made.

below.

4. An Overview of Global VRE Installations

Variable renewable energy sources consist of energy technologies that produce electricity through natural processes that vary over different time scales. The major VRE sources are wind and solar.

The fluctuations of other renewables like hydro, ocean energy, and tidal power are insignificant, and their variations are mostly seasonal. VRE sources, mainly solar and wind, are distinguished by their variability and reliance on meteorological conditions. The output from VRE can vary significantly in seconds, minutes, hours, throughout the day, or across seasons, resulting in unpredictability. Solar energy generation depends on sunlight availability, whereas wind energy production is influenced by wind speed and patterns. These fluctuations present challenges in maintaining grid stability and effective energy management. Nevertheless, VRE sources are sustainable, carbon dioxide-free, and are becoming more economically viable [24]. Their incorporation into power systems networks is crucial for minimizing carbon emissions and a smooth shift towards cleaner energy alternatives. The International Energy Agency (IEA), in its October 2023 reports [46], revealed that in a scenario where countries meet their nationally pledged energy and climate targets on schedule, wind and solar PV will account for more than 80% of the total growth in global power capacity over the next two decades, compared to less than 40% in the previous two decades. In line with the IEA report, other authors have added that wind and solar power are responsible for about 90% of the increase in Net Zero Emissions in the 2050 Scenario. Solar energy is at the forefront of the energy transition, contributing more than double the amount of new electricity compared to coal in 2023 and the first half of 2024 [47]. In the EU zone, coal generation in the first half of 2024 witnessed a major decline of 24% compared to the same period in 2023, which corresponds to a reduction of 39 TWh. This decline accounted for more than half of the global decrease of 71 TWh in fossil fuel generation. Wind and solar grew 13% (+45 TWh). This meant that their share of EU electricity generation increased from 27% in the first half of 2023 to 30% in 2024, an all-time high [48]. During the same year, global solar generation increased by 307 TWh, representing a growth rate of 23%, surpassing the growth of wind energy, which saw an increase of 206 TWh, or 9.8%. In 2023, solar accounted for 5.5% of the global electricity mix, totaling 1631 TWh [49]. Solar photovoltaic (PV) systems will require an increase of just 35% in 2029 and 2030, whereas wind energy will need a two-fold increase. Forecasts indicate that photovoltaic (PV) capacity is expected to expand to an estimated 10 TW by 2030 in the most optimistic scenario [50].

Exploiting wind as a source of energy began quite many years ago. Presently, power-generating wind turbines are multiplying all over the planet; and China, the U.S, and Germany are the main wind energy farmers. The global installed capacity in GW of wind versus solar PV capacity has started to fall short by 2021 reaching about 30% less installed capacity. However, the wind turbine capacity factor remains significantly better than that of PV, despite the improvement of both (with a ratio of about 2:1 between them) [35]. The wind industry attained an unprecedented height in achievements in 2023, a year marked by a 50% increase in installations compared to the previous year. Although the world had fully reopened following the global health crisis triggered by COVID-19, 2023 was characterized by a unique set of challenges, including a difficult macroeconomic landscape, ongoing conflicts, the Red Sea crisis, and persistent supply chain issues that originated during the Russia–Ukraine conflict. The connection of 117 GW of wind power capacity to the electricity grid within a year. This not only highlights the exceptional resilience and adaptability of the wind sector but also indicates global efforts to address climate change toward a positive path [46]. Market overview: with the addition of 117 GW in new wind power installations, the total global wind power capacity surpassed the 1 TW milestone in 2023, reflecting a year-on-year growth of 13%. In the onshore wind sector, 106 GW was integrated into the grid last year, achieving a year-on-year growth rate of 54%. Major markets have all witnessed a rise and sharp emission reductions from electricity generation [7]. The historical and projected solar PV and wind power capacity in the renewable 2023 main case (2024–2028) and Net Zero Emission by 2050 scenario (2018–2030) are shown in Figure 3 below.

At the national level, China and the United States remain the biggest markets for onshore wind installations, followed by Brazil, Germany, and India. These top five countries accounted for 82% of the global new installations in 2023, constituting a combined surge of 9% compared to the previous year. After two years of modest growth, onshore wind installations in China surged in 2023, recording over 69 GW commissioned. In the US, developers installed more new wind plants leading to a total addition of just 6.4 GW of onshore wind capacity, marking the lowest figure since 2014 [51].

5. Variability in Power Systems

Contextually, variability in the electrical power grid refers to short or long-term changes in the generation and consumption of electrical energy due to load variation, weather patterns, and the sporadic nature of renewable energy sources like sun and wind [3]. Because renewable energy sources rely on climatic factors like sunshine and wind speed, they are intrinsically variable compared to conventional power plants that can produce steady outputs. The researchers in [25] define variability as the degree to which data values are spread out or dispersed concerning statistics. Variability renders the task difficult for grid operators to ensure reliability, network stability, and power supply and demand balance. The fluctuation associated with VRE sources presents significant challenges for their incorporation into power grids. Recent research works are geared towards grasping and measuring variability to create more efficient strategies for grid management. The natural intermittency of wind and solar energy generation leads to considerable changes in power supply, thereby complicating grid stability, particularly in electrical networks constituting more shares of renewable energy [52]. A proposed finite-time correlation could boost large voltage angle variations in power systems if well-articulated [53]. The authors in [26] proposed a support vector regression algorithm model that can be used to monitor generation, outages, detailed weather patterns, and dynamic grid conditions to predict energy production for efficient and dependable power plants. Furthermore, several novel technological cost-effective approaches such as AI-forecasting models, long-duration energy storage systems (LDESs), and inter-continental grid connections provide promising mitigating answers as summarized in Section 5 below.

Intermittency and variability are challenges that arise during grid penetration with renewables such as solar and wind into electrical power systems. Some regions/nations around the globe have succeeded in effectively curbing the chaos caused by VRE grid coupling, using various methods such as energy storage systems, cross-border interconnections, demand-side management, network flexibility, supply and demand balancing strategies, etc. [54]. In the meantime, these strides have ensured the reliability and stable functioning of the networks.

Grid-forming inverters, large-scale battery storage, and real-time predictive modeling, smart grids are vital strategies for maintaining grid equilibrium in the integration of VRESs [10,55]. Many countries in the world are making remarkable progress in overcoming the issues VRE sources have introduced into the grid. Leading nations that have succeeded in managing variability issues are summarized in

Table 3. Top 10 successful cases of well-managed variability in some power grids around the world.

Nation/Region	Grid Project (Case)	Major Hallmark	Method/Success Factor	References
Denmark	Energy Island (Bornholm)	Supply of the entire Island with 100% renewable, solar and wind energy	High wind capacity, flexible network, interconnected with neighboring nations such as Germany and Sweden	[27,55,56,57]
Germany	Energiewende	High share grid integration with solar and wind energy	Demand response, Energy Storage System (ESS), Smart grids, and decongested power production	[22,23,25]
Spain	The Spanish power system network	Large-scale renewable energy integration with over 40% in 2020	Dynamic power grid management, grid interconnections with nearby countries, peak storage capacity (e.g., pumped-hydro storage system)	[58,59]
California-United States of America	California Independent System Operator (CAISO)	High integration of solar and wind power	Power grid innovations, VRE forecasting models, energy storage, demand response programs	[27,28,60]
South Australia (Australia)	South Australia’s Renewable Transition	60% variable renewable energy incorporated into the grid from solar and wind plants	Battery storage (e.g., the Hornsdale Power Reserve), smart grid-forming inverters, Virtual power plants, and Rigorous regulatory aids	[41,61,62]
United Kingdom	National Grid Electricity System Operator’s energy transition	Injection of offshore wind, interconnections with Europe	Use of advanced forecasting, flexible demand, battery storage, and grid stability measures	[60,63,64]
Norway	Norway’s Hydroelectric Power Integration	Supplying 98% of its electricity from hydropower plants	Interconnecting with nearby nations (e.g., Denmark, and Sweden), hydropower for adaptability	[63,65,66]
China	Established 12th and 13th five–year energy plan.	A speedy expansion of solar and wind power	Integration of large-scale wind, solar, and hydro, use of ultra-high voltage transmission lines to balance variability	[6,24,32]
Iceland	Hydropower mix and Geothermal exploit	100% renewable energy from geothermal and hydroelectric plants	Using stable and dispatchable sources of renewable energy (hydropower and geothermal) to balance fluctuations in demand	[67,68]
TX, USA	ERCOT (Electric Reliability Council of Texas)	High share grid integration of wind and solar energy; with over 30% renewable injected in 2020	Dynamic market-oriented balancing, enhanced forecasting models, and high amounts of power sharing with nearby grids	[27,69,70]

.

The above-presented practical cases of variability ride-through is an illustration of how solutions like energy storage, cross-border interconnections, and adaptive management systems can go a long way to minimize variability and the necessity for more research and development in this area.

5.1. Causes of Variability

Variability in electrical power systems can result from diverse sources directly or indirectly. Variations in energy supply and demand are the major sources of variability in power system networks. Power system grid instability and fluctuation can also be amplified by technical issues including transmission losses, grid congestion, and equipment breakdowns. Some of the various root causes of variability in renewable energy-coupled power systems are examined below.

• Fluctuations in power demand

Changes in electrical grid loads can originate from unpredictable changes in demand resulting from factors such as weather, economic activity, and time of day. Climate patterns, industrial activities, consumer load behavior, and peak power demand change diurnally, weekly, or annually, and induce significant alterations in grid functioning [29].

• Power plant outages

Sudden power failure in power stations resulting from plant maintenance, equipment breakdown, or fuel supply problems may lead to abrupt changes in production capacity [29].

• Transmission line losses

Losses in transmission lines occur when power is conveyed over long distances, thereby bringing changes (variability) to the power system network. Load fluctuations or distant supplies to consumer centers heighten energy loss, which negatively affects grid stability.

• Environmental factors, weather, and intermittency of renewables

Power production from wind and solar relies heavily on natural environmental factors. These factors affect power plants’ output negatively. Geographical factors like temperature, precipitation, tropical cyclones, wind speeds, storms, and seasons determine wind or solar yields in a specific location. For example, cloud cover reduces solar output and demand patterns [30]. Variable renewable energy is generally characterized by its sporadic nature, moving at very irregular intervals. This intermittency causes chaos in the power systems’ network as a whole, thereby bringing disequilibrium in the operation of grid components. The solar and wind renewable resources depend totally on wind strength and sun irradiance, which follow metrological conditions for their output.

• Variable fuel availability

Traditional fuel-based grids could witness changes due to corresponding changes in fossil fuel supply, price fluctuation, or perturbations in transport, which indirectly affect energy production and supply.

• Limited energy storage capacity

Batteries and pumped hydro storage systems are major causes of variability in the power grid due to their rate of charge and discharge; their limited efficiencies introduce changes in the network specifically when the amount of energy in the power bank is exhausted [71].

• System frequency variability

To achieve the stable functioning of grids, the network frequency must be kept within specific intervals. Changes in energy production and energy requirements can lead to frequency deviations necessitating rapid action to restore equilibrium [72].

• Inter-regional energy exchange

Energy exchange between countries gives room for nations to bring in and send out electricity with the goal of balancing variability. The presence of external energy sources does vary and introduces more fluctuation in the conventional network [73].

• System communication and control delays

Setbacks in the grid control and communication can induce variation. Delayed reaction to supply and demand or failure to sense real-time problems may worsen the network stability [74].

Variability causes presented above show the seriousness of the difficulties encountered by grid operators to ensure reliability and equilibrium as renewable energy integration projects sprout.

5.2. Types of Variability

Generally, variability is categorized into three major classes: (i) short-term variability, (ii) long-term variability, and (iii) spatial and temporal correlation. Variability in renewable energy grid-integrated systems has been broken down into sub-categories looking from the demand-side and the supply-side viewpoint. Power system grids that accommodate VRESs face variations from two ends (the generation end, and the consumer end). The major reason for the need for short-term flexibility is to account for daily variations in demand and VRE output. Steeper ramps and more frequent intervals of negative net load necessitate quick supply changes in networks with significant solar PV penetration to preserve grid stability [23]. Sharp changes in the output of PV generators are caused by variability in solar irradiance on cloud-cover days in contrast to clear sunny days. Wind speed on the other hand varies hourly on each given day, causing corresponding changes in wind output energy.

5.2.1. Types of Supply-Side Variability

• Temporal variability

Daily variability: Renewable energy production changes depending on the time of the day. Sun intensity in the case of solar energy is not always the same throughout the different hours of the day. A similar thing happens to wind power production that follows wind patterns throughout the day and night.

Seasonal variability: For example, wind source generation is often at its peak production in the winter months, while the solar source output is optimal during the summer months depending on the location and region [31].

ii.

Weather-reliant variability

Solar variability: Solar generation of energy relies much on weather conditions. Cloudy days may reduce PV output, and clear days might give an increase in output.

Wind variability: Strong windy days result in high yields of wind power production, while calm days with little or no wind lead to low power production. Localized weather activities can affect power generation since wind patterns are stochastic [32].

iii.

Topographical variability

Renewable energy production varies according to site location. For instance, wind power production yields are greater at seashores or mountainous sites, while solar may be efficient in zones closer to the equator.

iv.

Inter-annual variability:

Long-term variability can span from one year to another causing solar and wind resources to change due to prolonged climate change. Thus, impacting the power supply scenarios [31].

v.

Spatial Variability

Renewable energy (RE) production in the same region or nation often varies because of zonal humidity, distribution of renewable energy resources, or land characteristics.

5.2.2. Types of Demand-Side Variability

• Grid Frequency Variability and Voltage Variability

Frequency instability: Sharp variations (ramping) in renewable energy injections could result in unstable grid frequency which may decrease or increase depending on the regional frequency limits (50 Hz or 60 Hz).

Voltage instability: Solar and wind energy sources are often integrated at various bus bars on the grids and can lead to voltage fluctuation if the voltage stability analysis studies are not effective [75].

ii.

Energy Storage and Dispatch Variability

Energy storage intermittency: Storage systems in VRE are effective mitigation strategies for variability in power systems’ networks; however, they become types of variability due to their charging and discharging cycles. They introduce variations in the grid based on the quantity of energy in stock.

Energy Dispatch variability: Renewables are fundamentally non-dispatchable. Meeting demand stresses the network, and balancing demand with supply introduces variability, particularly during periods of low production [76].

iii.

Transmission and Distribution Variability

Transmission congestion: Variations in renewable energy (RE) generation could result in congestion when there is optimum production from the sources but insufficient transmission infrastructure to manage the available excess power. This situation leads to instability, energy loss, and network deficiency [33].

Voltage Regulation in the Distributed System: In zones or regions with a proliferation of rooftop installations, the distributed system of power production could have voltage regulation challenges, especially whenever solar yields go above load demand and reverse power flow back into the network.

The types of variability surveyed in the previous sub-section have led to a lot of chaos in grids around the world, some of which are presented in the next section.

5.3. Chaos Caused by Variability in Some Grids in the World

Variability in renewable energy power systems has brought about chaos, which has grown into a significant problem as electrical grids adapt to sophisticated technologies. This study emphasizes the intricacy of chaos in the electrical grids which manifest in many forms. The authors in [77] stressed that it is imperative to consider harmonic distortion, voltage imbalance, the capacity of transmission/distribution equipment, overvoltage, flickering, and undervoltage as some of the chaos resulting from stochastic loads and generation that create negative impacts on power quality and should be eliminated.

The reference [78] reports that variability causes transient chaos, which has been a phenomenon of multi-stability witnessed on the British power grid and is characterized by the presence of multiple coexisting attractors that result in unpredictable reactions to disturbances. This intricate behavior is shaped by the topological configurations of the network, especially in areas featuring complex basin landscapes.

Another case of chaos is that of the Texas grid where variability has led to operational failures as a result of forecasting errors in energy production. The electricity system had experienced the effects of randomness and variability due to emerging stochastic assets [79]. The authors proposed a probabilistic steady-state analysis driven by inspirations from statistical worst-case circuit analysis to assess the likelihood of operational violations originating from stochastic resources.

The variability inherent in RE production, such as fluctuations in wind velocity or changes in solar irradiance, introduces considerable uncertainty in terms of the output power. Consequently, power systems operators are often required to sustain a reasonable quantity reserve of backup generation capacity to ensure system stability amid these variations in renewable energy output. For instance, in the case of Denmark and the United Kingdom, where wind power plays a pivotal role in electricity generation, the grid must maintain some reserves to accommodate rapid variations in wind conditions, thereby complicating operational management and huge costs incurred for standby generators. Furthermore, variability in these cases has increased the demand for reserves, leading to a dependency on fuel-based reserves, which risk elevating carbon emissions [80].

5.4. Variability Management in VRE Grid-Connected Power Systems

The production and integration of VRES into power grids pose some real-time operational challenges to system operators, system designers, and researchers. These challenges span from technology, economics, and to governmental energy policies. Generally, current VRE resources utilize power electronic devices or inverters to interface with the network rather than synchronous generators [81]. At a point when a greater proportion of VRE injected goes above 50%, the system functions as an inverter-controlled network and such a system has exceptional qualities that change the operation of the grid components [82]. The key challenge confronting policymakers and the energy markets is to install and maintain reliable carbon-free power grids that accommodate variable renewables while limiting holistic cost upgrading security and unwavering quality. This section summarizes some of the key challenges and attempts to provide technological, economic, and policy-related solutions as shown in

Table 4. Mitigation strategies of variability in power systems.

Challenges	Mitigation Strategy (Solution)	Category	References
Variability and uncertainty	- Deploying accurate innovative forecasting models or platforms - Installation of energy storage system	Technological	[33,60]
	- Implementing five-minute dispatch and greater balancing norms as in California and Germany - Curtailing of excess energy from VRE generation as in China and Germany - Dispersed installation of RE resources	Policy	[22,23]
	Solutions to Chaos Caused by Variability
Reverse current flow	- Installation of under-current detectors (relays) to signal grid inverters in case of current flow violations - The dynamic line rating (DLR) method is used on the Italian grid	Technological	[82,83]
Non-synchronization	- Use smart inverters (SI) to transfer maximum unsheathed power to the grid regardless of frequency, amplitude, and phase variation - Use of PI/PLL controllers	Technological	[84,85]
Frequency instability	- Installation of smart inverters (SI) to eliminate frequency tripping - Reduction of active power close loop regulation - Use of virtual synchronous machines - Five-minute energy dispatching	Technological	[34,86,87]
Generator rotor instability	- Use of fault ride-through criteria with quality time variation.	Technological	[83]
Voltage instability (swell, sag, or dip)	- Installation of SIs to eliminate voltage tripping - Use of smart transformers (ST) techniques to link DC storage battery plans. - Use of OLTCs to shape voltage profiles - Running of synchronous condensers - Grid reconfiguration especially transmission lines disposition - Use of dynamic voltage restorer (DVR)	Technological	[35,72,86,88]
Grid protection	- Installation of smart protective relays	Technological	[19,89]
	- Use of adaptive protective systems (APS) as in the Canadian distribution network
Low level of inertia	- Least quota of synchronous generators in a traditional grid (Virtual Synchronous Machine) - Running synchronous condensers - Use of smart grid-forming inverters - Superconducting magnetic energy storage (SMES)	Technological	[90]
	- Contracting for more faster-operating reserves	Economic	[36]
Transient issues	- Introduction of Distributed Flexible AC Transmission (DFACT) devices at the point of common coupling (PCC) - Use of thyristor-controlled series capacitor (TCSC) - Fast valving (turbine FACT solution)	Technological	[19,33,91,92]
Harmonic distortion	- Use of DFACTs - Active Power Filter - Smart converter control	Technological	[37,93]

.

The technological strategies proposed in Table 3 refer to techniques that employ novel components or systems such as smart meters, relays, inverters, smart transformers, and so on. The economic strategies touch on methods of power grid management or monetary incentives such as contractual reserves, price-oriented balancing, and energy consumption. Policy approaches are decisions in line with norms and regulatory structures such as grid modernization guidelines, balancing requirements, etc.

6. Discussion

A plethora of strategies found in literature could in one way or another help in managing variability and power system integration issues around the world; however, one solution cannot suit every grid and location, since climatic conditions and the realities of each grid differ. Nevertheless, there exist some key adaptive solutions and experiences that could be reflections of similar issues faced in other grids. A summary of some promising strategies for mitigating variability and what it takes to scale up are discussed here.

Grid flexibility and demand response: Most countries worldwide such as Germany and China have succeeded in managing variability in their electrical power networks due to the understanding and application of flexibility and demand response strategies. Their grids have been upgraded to adapt to power fluctuations from intermittent renewable energy sources, and consumers have been sensitized on adjusting their electricity usage to real-time supply conditions such as increasing loads when wind and solar energy production is abundant and decreasing loads during moments of low yields from the renewable sources [29]. The authors in [38] highlighted the relevance of proper load-following plants for efficiently managing VRE intermittency. Scaling up such strategies entails implementing the smart grid concept and adopting widespread advanced metering infrastructure (AMI) for customer engagement in demand response programs [94]. Furthermore, the use of conventional standby power plants such as natural gas may rapidly ramp up or down in response to variations from RE ensuring trustworthiness [95]. China now has a strong fleet of coal plants that can accommodate seasonal changes in demand and VRE supply, providing long-term flexibility. Also, dispatchable hydro capacity provides long-duration flexibility in today’s grids [46].

Flexibility is noted as a key factor in managing grid variabilities in real-time and is helping grid operators provide customers with a more predictable and steady power supply, lessening the need for more expensive and pollution-peaking power plants. To further facilitate the more effective use of the electrical networks, flexibility companies might temporarily alter how they produce, store, or consume power in response to demands (e.g., for congestion services and inertia capacity acquisition), as well as setting up the best regulatory frameworks and defining the most productive operational procedures, including data transfer protocols, compensation, and penalties. This would require effective coordination among key stakeholders, such as regulators, grid operators, and flexibility services providers [96].

Energy Storage Systems (ESS): Storing extra energy while renewable output is high and releasing it when demand exceeds supply or renewable generation drops has proven to be a promising strategy for power grids. Battery energy storage in particular aids in balancing supply and demand scenarios [77]. Short-time variability and grid instability can be mitigated through large-scale storage systems. Scaling this strategy will require significant investments in advanced storage technologies, and wide-scale financing models and policy support are the key ingredients for the economic viability of this strategy [97]. Energy storage systems are recognized as highly effective solutions for balancing electricity supply and demand, particularly in power systems that integrate high amounts of VRESs [55,98]. The range of energy storage technologies includes various approaches, such as electrical, electromagnetic, mechanical, thermal, hydrological, and electrochemical systems. Furthermore, the functionality of energy storage systems can be enhanced through the integration of power-to-X technologies, including power-to-gas (hydrogen) and power-to-heat solutions [56,99]. A key feature of energy storage systems that contributes to climate resilience is their ability to be distributed. A distributed energy storage system is noted for its significant spatiotemporal flexibility and quick response abilities and is a vital element in power systems dominated by renewable energy sources. Sophisticated forecasting and predictive analytics; accurate forecast and predictive models for solar and wind energy are one of the surest solutions to managing VRE integration, achieved by the deployment of machine-learning models, AI algorithms, and top-notch weather data collecting systems [39,100]. Real-time data flow and analytic mechanisms are crucial in achieving this solution.

Grid-forming inverters and advanced power electronics: These allow the integration of solar and wind energy sources into grids with minimal variation and have proven hopeful in enhancing grid stability, helping the weak and isolated networks to function without necessarily depending on the traditional rotating machines. This technological solution permits grid penetration with high shares of renewable energy without sacrificing voltage quality and frequency [101]. Smart power electronics components are emerging especially in the area of renewable energy to reduce the impact of low inertia in VRE sources, and smart inverters have proven to be lasting solutions in frequency and voltage control.

Virtual Power Plants (VPPs): This strategy has encouraged the clustering of decentralized energy sources being remote-controlled as a single dispatchable resource. VPPs help to mitigate variability by combining generation and energy storage to stabilize power grids. Bolstering this strategy will require high-level communication technologies in grids such as robust remote management platforms and real-time information analytics to guarantee cybersecurity and interoperability of equipment [102]. Virtual power plants can engage in energy markets, permitting a self-scheduling of renewable energy sources, promoting energy trading and sharing, and providing supplementary services for demand-side frequency regulation to increase system stability. More investigative studies on VPPs have gained prominence in recent energy research, aiming to mitigate the uncertainties associated with the distribution of VRE sources within the electrical network and to advance technologies aligned with energy control systems [103].

Sector coupling (Power-to-X): Sector coupling is a promising strategy for handling variation in renewable energy by integrating renewables with other sectors like heat pumps, and electric vehicles. The power-to-X strategy allows for the use of renewables in other forms of energy [104]. Other key strategies that could be used in mitigating fluctuations in VRE integration include energy systems decentralization, market mechanisms, and flexible markets.

An innovative expansion planning model that incorporates operational flexibility constraints can also be introduced to effectively handle both long-term and short-term chronological variability and uncertainty, hence optimizing investment alternatives for production and transmission infrastructure to ease the targeted integration of RESs.

The constraints integrated into such a model encompass clustered unit commitment designed to address the variability associated with renewable energy sources, as well as robust re-dispatch operating parameters [40].

The key takeaways from this survey are that despite the numerous challenges posed by the integration of VRESs into power systems networks, we identified many mitigation strategies, models, machine learning languages, and AI tools that are developed in literature and industries to help control the chaos introduced by solar and wind energy sources. However, many of the grids in some regions around the world are outdated and need modernization or total transformation to cope with the fast-growing technologies and economic policies of the energy industry. To effectively mitigate the impacts of variability in solar-wind integration into power grids, it is imperative to consider the following factors:

-

Investing in technologies like energy storage, forecasting tools, and grid infrastructure alongside advanced communication systems.

-

Adherence to regulatory frameworks like the one proposed in Table 4 below.

-

Cross-sector collaboration, e.g., the transport industry, to enhance global energy flexibility.

-

Functional coordination among generation, transmission, storage, and demand response which is critical in managing variability in large-scale systems.

Solar and wind integration into power systems in developed and developing countries presents both golden and challenging opportunities. Driven by the need to install cost-effective, eco-friendly energy systems, and the accomplishment of nationally determined contributions (NDC), nations are pushed to the forefront in the search for mitigating methods to challenges posed by VRE sources [68,105].

However, the inherent variability and intermittency of VRE need tailored strategies that will guarantee resilient, stable grids, and sustainable power grids. This is in line with a conceptual framework for the efficient integration of VRE that has been proposed. The theoretical framework must consider factors such as grid modernization, infrastructural development, policy and regulatory support, financing schemes, and capacity building as elaborated in the

Table 5. A proposed conceptual framework for boosting VRE integration into the grids.

SN	Policy	Concept	Application Note
1	Policy and regulatory support	Develop a clear policy framework	Governments clear long-term energy policies prioritizing integrating renewables and providing stability for investors and utility companies.
		Offer Incentives for VRE investments	Funding programs for renewable energy, such as feed-in tariffs, tax breaks, and subsidies should be promoted to motivate private sector investments in VRE.
		Access to Grids and tariffs	Flexible laws on grid access by VRE producers should be put in place and implemented to support tariff structures on energy sales and transmission projects.
		Implementation of grid code	Countries’ grid codes should be revisited to incorporate the variability of VRE, emphasizing grid stability, frequency variation, and grid flexibility.
2	Infrastructural development	Reinforcing grid infrastructure	Transmission and distribution structures should be upgraded to accommodate the variable nature of VRE, building smart grids, storage systems, and high-voltage lines.
		Installation of Energy Storage Systems (ESS)	Scaling up investment in storage technologies, e.g., batteries and pumped hydro, which mitigates variation in VRE and stabilizes grid functioning.
		Innovative grid management technologies	Practical application of continuous surveillance, smart grid technology, and automated management systems to improve network adaptiveness to VRE intermittency and incorporate distributed generation.
3	Capacity building and transfer of technical know-how	Skills development and training avenues	Training sessions and workshops should be organized for technicians, engineers, and policymakers, to equip them with technical knowledge in RE investment and management.
		Sharing knowledge through platforms	The exchange of ideas about the success stories of other countries or organizations well advanced in VRE integration will bolster local capacities and prowess.
		Collaborating with international organizations	Working together with international financial and technical organizations such as the World Bank, UNDP, IEA, IMF, and WEC will enhance know-how and resource mobilization.
4	Investing in research and innovation	Promote localize research	Research and development of renewable energy technologies and grid solutions best suited for regional geographic, climatic, and economic situations should be motivated.
		Building financing models	Lofty financial schemes such as microfinancing, multi-sourcing, and green bonds will help decentralize RE projects, especially in rural or isolated grid zones.
		Pilot projects	Commissioning pilot projects permits the testing of diverse VRE-incorporated technologies and methods, issuing important data for scaling up strides.
5	Power system flexibility and systems integration	Hybrid power system	Installation of hybrid grids that constitute VRE and traditional generation/or other renewables for the efficient matching of demand and supply.
		Demand-side management	Running demand-side management programs such as time-of-use (ToU) tariffs, to displace power demand to correspond to renewable energy availability and cut down dependency on fossil fuels.
		Cross-border energy market	Collaboration among regions and international energy sales helps mitigate variability in RE availability via grid interconnections with nearby nations.
6	Public sensitization and stakeholder involvement	Public awareness campaigns	Organizing VRE sensitization campaigns increases awareness of carbon-free energy sources and fosters sustainable development (SG7).
		Community involvement	Engaging local communities in RE planning and decision-making guarantees their needs are met and promotes universal acceptance of VRE projects.
		Involving the private sector	Join task forces with private companies will stimulate research, innovation, and the deployment of renewable technologies to meet local and country needs.
7	Monitoring evaluation and constant upgrading	Develop performance metrics	Establishing parameters to trace the path covered by VRE integration projects, with emphasis on reducing CO2 emission, grid reliability, and cost-effective energy strategies.
		Adaptive management	Establish assessment loops for evaluating renewable energy policies, technologies, and infrastructure, and fine-tune strategies to mitigate integration challenges.
		Data-driven decision	Design and invest in real-time monitoring data analytic systems to obtain reliable information for decision-making, optimization of VRE efficiency, and grid robustness.

below.

The above framework presents policies, concepts, and practical strategies that could help scale up variable renewable energy integration, especially in developing countries whose power system networks are yet to meet today’s advancement in grid standards as illustrated by the top ten nations depicted in Table 3.

7. Conclusions and Future Perspectives

7.1. Conclusions

A review of variability of variable renewable energy integration into the grids has been presented, focusing on solar and wind energy resources as the major sources of variability on the supply side, while the loads on the power system entirely were considered as the origin of variations on the demand side. The study investigated the major causes of variability issues and how it has been managed technologically, economically, and policy-wise in some of the top ten energy-emergent countries in the world, notably, China, Germany, Australia, Spain, the United Kingdom, and the United States, etc. A summary of the challenges caused by variability and the successful mitigation strategies used as found in the literature has been presented. The research followed the descriptive analysis approach with a stringent method of selecting peer-reviewed publications and other most cited technical reports. We used the Boolean expressions exclusion method in databases to select papers for this review, with 80% emphasis on publications from 2019 to 2024. The survey revealed many variability issues faced by different grids around the world and their experiences in handling the hurdles. From the diverse mitigation strategies presented in Section 6, a seven-point conceptual policy framework involving all energy stakeholders for smoothing out variability in power system networks and increasing VRE grid integration was outlined. Long-duration energy storage, virtual power plants (VPPs), smart grid infrastructure, cross-border interconnection, Power-to-X (sector coupling), supportive financial schemes, market mechanisms, and grid flexibility are the key takeaways in achieving reliable, resilient, and stable grids. The work ends with research prospects. This review provides a useful summary of up-to-date research information for researchers and industries investing in energy-mixed grid installation and management issues.

7.2. Prospects

The integration of VRE source (solar and wind) technologies into grid-connected electrical networks introduces a range of challenges as well as considerable opportunities. The first challenge stems from the intermittent and variable nature of solar and wind energy generation, which impacts grid stability and reliability. Nonetheless, the shift towards high shares of renewable energy offers avenues for modernization and advanced sustainability and guarantees energy security. In guaranteeing the power system’s “grids of the future” major technological initiatives and feasible policies must be implemented by governments worldwide in response to the challenges emanating from the integration of VRE sources in conventional grids. Some prospects of the promising technologies and policies in scaling renewable grid integration are presented here.

The successful integration of variable renewable energy is fundamentally dependent on enhancing the flexibility of the electrical grid. Innovations such as smart grid technologies, demand–response mechanisms, and sophisticated grid management systems will ease the real-time balancing of supply and demand and subdue the inherent variability of VRE generation. Furthermore, the application of AI in forecasting and predictive analytics will significantly improve the capacity of grid operators to anticipate RE production and optimize the global operation of grids.

Energy storage, particularly in the form of battery technology, is expected to advance significantly and will become crucial in addressing the fluctuations associated with VRE. The progress in long-duration energy storage solutions, including flow batteries and solid-state batteries, will facilitate the storing of surplus RE for use during times of peak demand or low generation.

Putting in place market mechanisms that encourage flexibility, energy storage, and the integration of VRE sources is crucial. Innovative market frameworks, including flexibility markets, can offer financial rewards for resources that help in balancing supply and demand, particularly during times of significant variability in VRE generation.

The extensive integration of VRE presents major prospects for diminishing greenhouse gas emissions, slashing reliance on fossil fuels, and carbon-free energy. Nations are poised to use variable renewable energy to achieve global climate objectives as outlined in the Paris Agreement by leading the decarbonization process in the energy sector.

Increasing the implementation of microgrids and VPPs is noted as these systems aggregate and decentralize energy resources like solar PV, batteries, and demand-side management technologies. They offer specific solutions for the integration of VRE and are capable of operating to function autonomously or in conjunction with the entire electrical network.

In today’s grids, flexibility is one of the major means of managing variable renewable energy penetration issues. Therefore, government policies such as grid modernization and infrastructural developments should be promoted for power system grids of the future to enhance their standards and flexibility. These will involve financial investments in transmission systems that can better host the dispersed nature of fluctuating energy sources and decongest power flow in the grids [33].

Capacity Mechanisms and Market Integration. Capacity mechanisms preserve system reliability by ensuring enough generation capacity, even when renewable energy generation is low. Market integration policies allow the flow of renewable energy between regions to balance fluctuating generation over broader geographical areas.

The Renewable Portfolio Standards and Feed-in-Tariffs (FITs) policy are critical in rewarding the implementation of variable renewable energy projects, driving the widespread VRE mixed in countries like the USA, Germany, and China. For instance, FITs offer ensured transactions for renewable energy production, encouraging investment and bolstering curtailment issues.

The technological advancements in storage technology, AI-driven forecasting, and across-border grid alliance all point to a promising future for integrating VRE sources into grid-connected power systems. When combined with supporting policies such as carbon pricing and grid upgrading, these technologies will increase both the techno-economic and regulatory viability of VRE integration, leading to cleaner and more resilient energy prospects [106].

7.3. Future Study

This research paper cannot say that every aspect has been fully treated, hence the need for future work directives. Further research needs to be carried out on AI incorporation in grids, exploring the use of AI to optimize digital twins for autonomous energy management, forecasting of VRE intermittency, and predictive maintenance in variable renewable energy grid-connected systems, where robust cyber-security system models can also be developed to secure digital twins from potential attacks in the smart grids. In the same light, user training programs need to be created for all stakeholders to be trained on how to use AI-assisted models and accurately interpret data obtained from digital twins during their lifecycle, following the policies proposed in Table 5.

Research on AI-powered models for hyper-local, short-term, or ultra-long-term renewable energy forecasting needs to be investigated for efficient and reliable weather forecast data which is essential for tracking wind and sun variability.

Future research can focus on developing super grids that connect regions or continents, allowing for the sharing of renewable energy from locations with complementary generation profiles and variability effects (e.g., sun during the day and wind at night). The study can aim at optimal efficiency, minimal curtailment, and enhanced grid stability using variable renewable grid-connected networks over wide geographic regions.

Also, an in-depth survey could be conducted to address the political, institutional, regulatory, and technical barriers to global renewable energy trade and their impact on grid flexibility.