Renewable Energy Sources Research Articles

Rechargeable Hydrogen Gas Batteries: Fundamentals, Principles, Materials, and Applications.

The growing demand for renewable energy sources has accelerated a boom in research on new battery chemistries. Despite decades of development for various battery types, including lithium-ion batteries, their suitability for grid-scale energy storage applications remains imperfect. In recent years, rechargeable hydrogen gas batteries (HGBs), utilizing hydrogen catalytic electrode as anode, have attracted extensive academic and industrial attention. HGBs, facilitated by appropriate catalysts, demonstrate notable attributes such as high power density, high capacity, excellent low-temperature performance, and ultralong cycle life. This review presents a comprehensive overview of four key aspects pertaining to HGBs: fundamentals, principles, materials, and applications. First, detailed insights are provided into hydrogen electrodes, encompassing electrochemical principles, hydrogen catalytic mechanisms, advancements in hydrogen catalytic materials, and structural considerations in hydrogen electrode design. Second, an examination and future prospects of cathode material compatibility, encompassing both current and potential materials, are summarized. Third, other components and engineering considerations of HGBs are elaborated, including cell stack design and pressure vessel design. Finally, a techno-economic analysis and outlook offers an overview of the current status and future prospects of HGBs, indicating their orientation for further research and application advancements.

Innovative Microgrid Services and Applications in Electric Grids: Enhancing Energy Management and Grid Integration

Currently, microgrids are a reliable solution for integrating distributed energy resources and managing demand on electricity grids, serving as a pathway towards a responsible energy transition. However, the evolving needs of the sector require specialized approaches to enhance grid flexibility and support the increasing penetration of renewable energy sources and their rising demand. This article explores and characterizes various advanced and innovative services offered by microgrids to improve the resilience, security, and reliability of electricity grids. It analyzes technical advances and novel control methodologies that demonstrate the potential for microgrids beyond mere energy provision. These include ancillary services, services aligned with demand response programs, and advanced asset management and energy resource optimization services. A global case study is conducted to provide a framework for the services that microgrids can provide. The case study validates the efficiency and reliability of electric grids with microgrids and addresses challenges related to their stability and resilience. This research provides a comprehensive perspective on the benefits of implementing microgrids and proposes new guidelines for the deployment of these systems in both urban and rural areas within the framework of energy communities in the Colombian electricity system, emphasizing the need for collaboration among stakeholders to ensure sustainable energy solutions.

Optimal operating strategy of hybrid heat pump − boiler systems with photovoltaics and battery storage

The growing need to reduce energy consumption and greenhouse gas emissions is driving the search for more efficient heating solutions in buildings. Hybrid heating systems, which combine air-to-water heat pumps (AWHP) with traditional gas boilers, are a common solution after refurbishment investments. However, managing these systems effectively, particularly when integrated with photovoltaic (PV) panels and battery energy storage systems (BESS), remains a complex task. For instance, heat pumps perform poorly in very cold conditions, making boilers a more efficient option; however, it might be advantageous to use it to increase electricity self-consumption. Optimal management depends on multiple factors, including future forecast data. In this paper, a daily optimization program is developed by means of a brute-force approach using forecast data. The core innovation of this paper is the use of an artificial neural network (ANN) that, trained on predictive optimization results, can determine the optimal solution in real-time without the need for future forecasts. The ANN achieved a 99.16% accuracy in new scenarios, successfully optimizing costs, CO2 emissions, and primary energy use. Results indicate up to 19% cost savings in colder cities, a 12% reduction in CO2 emissions, and a 3% decrease in primary energy consumption. This approach holds significant potential for enhancing the integration of renewable energy sources, contributing to long-term sustainability goals.

Multi-timescale modeling and order reduction towards stability analysis of isolated microgrids

Microgrids incorporate a significant proportion of renewable energy sources and power electronic converters in the energy conversion process, creating a sustainable and clean energy infrastructure. However, the multi-timescale dynamics of microgrids are interactively coupled under a nonlinear structure, which makes it difficult to gain insight into the instability mechanisms without a high-fidelity reduced-order model that preserves the main dynamic behaviors of the system. For the isolated AC microgrid dominated by voltage source inverters (VSI), a detailed state-space model of the system, including the inverter, network, and load, is first developed. Based on this model, the eigenvalue analysis is carried out, and a participation factor analysis tool is also utilized to identify the relevant dynamics that have a strong impact on the system's dominant mode. Furthermore, to simplify the system modeling process without losing essential dynamic interactions, a novel multi-timescale coupled reduced-order model is proposed using a transfer function-based order reduction method, which retains the open-loop gain characteristics to preserve the critical couplings between fast inner loop dynamics and slow droop control dynamics. Finally, the accuracy of the reduced-order model is verified by comparing it with the detailed model and the conventional singular perturbation reduced-order model through eigenvalue distribution and time-domain simulation analysis.

Optimizing Multi-Channel Green Supply Chain Dynamics with Renewable Energy Integration and Emissions Reduction

In response to the global imperative of mitigating greenhouse gas emissions (GHGs) and the shifting landscape of business models toward multi-channel structures, this study delves into the intricacies of a green supply chain. Operating through both online and traditional channels with uncertain demands, the producer’s distribution strategy prompts an exploration of supply chain dynamics. Utilizing an integer programming model, this study calculates optimal prices, optimizes total profit, and minimizes transportation costs to curtail carbon dioxide emissions, depending on the transportation mode. Additionally, this study incorporates renewable energy sources into the production and transportation processes to further minimize carbon dioxide emissions. The integration of renewable energy not only supports environmental goals, but also contributes to the overall profitability of the supply chain by reducing energy costs. Employing a theoretical technique for linearization, the model, resolved through the Jimenez and TH methods, demonstrates efficacy in reconciling economic and environmental goals. The Jimenez method enables the transformation of fuzzy parameters into deterministic equivalents, allowing for a more reliable optimization during uncertainty, while the TH method provides an interactive fuzzy multi-objective approach, aligning the model’s dual objectives for both economic and environmental goals. Notably, when transportation costs to both markets are equal, the model prioritizes devices with a lower environmental impact, showcasing adaptability. Furthermore, the proposed solution empowers decision makers to influence pricing and enhance the entire supply chain’s profitability. In conclusion, this research offers nuanced insights, strategically aligning economic viability with environmental sustainability in the discourse on green supply chains.

Synthesis of SrTiO3 nanoparticles for photocatalytic applications

Due to the heightened emphasis on environmental protection and the escalating demand for renewable energy sources, the potential applications of strontium titanate (SrTiO3) nanoparticles in photocatalysis have shown remarkable promise. With rapid advancements in technological capabilities, the standards for SrTiO3 photocatalytic materials have soared. Researchers have relentlessly delved into and innovated techniques for preparing strontium titanate powders, striving to yield nanocrystalline SrTiO3 that exhibits specific morphologies, high purity, superior dispersibility, and exceptional photocatalytic efficiency, while continually refining the properties of these powders. The paper encapsulates the advancements in preparation methodologies and photocatalytic attributes of perovskite SrTiO3 nanoparticles, encompassing diverse synthetic routes such as hydrothermal synthesis, sol-gel process, chemical precipitation, solid-state reaction, sonochemical technique, and composite modification strategies. The characteristics, merits, demerits, and prevailing challenges associated with each synthesis technique are thoroughly and analyzed. Ultimately, this review serves as a valuable reference and foundation for the synthesis, modification, and application of SrTiO3 nanoparticle photocatalysts, fostering their development and practical implementation in environmental remediation and renewable energy technologies.

Coordinated planning for offshore wind and electricity–hydrogen system based on SDDP: A case study of coastal provinces in China

The coordinated development of offshore wind and electricity–hydrogen systems (OW-EHS) has the potential to enhance the utilization of renewable energy sources and achieve carbon neutrality. This article presents a case study of nine coastal provinces in China and designs four scenarios to analyze the economic benefits and potential hydrogen production capacity of OW-EHS. A multi-stage stochastic dual dynamic programming based approach is proposed for integrating OW-EHS, exploring offshore wind energy as both a primary electricity source for coastal regions and a clean, sustainable energy source for electrolyzers. It accounts for variations in hydrogen demand, wind uncertainty, load profiles, and electricity price dynamics, offering a holistic perspective on the feasibility and benefits of collaborative offshore wind and electricity–hydrogen systems. A comparative analysis highlights the effectiveness of the proposed planning approach, demonstrating its capacity to maximize the overall system benefits, encompassing both the optimal levelized cost of energy and hydrogen production. The new discoveries elucidate the unique attributes and advantages of each coastal province in OW-EHS. This research provides a tailored blueprint for coastal provinces in China to harness their offshore wind potential and accelerate progress towards carbon neutrality.

Financial mechanisms for energy transitions: review article

PurposeThe transition from fossil fuel-based energy systems to renewable energy sources, commonly referred to as the energy transition, is essential for combating climate change. However, comprehensive studies that thoroughly examine the financial mechanisms involved in this process are lacking. Despite the availability of various financial tools, there is a notable absence of extensive research that synthesizes and categorizes these mechanisms into broad groups.Design/methodology/approachA systematic literature review is used to explore a comprehensive framework for financial mechanisms related to the energy transition and their application across six stages of the process.FindingsThe framework of financial mechanisms for energy transition encompasses these six factors: public financing mechanisms, private financing mechanisms, market-based mechanisms, innovative financing mechanisms, risk mitigation instruments and institutional support and capacity building.Originality/valueThis is the first study that thoroughly reviewed the financial mechanisms involved in the energy transition process.

Influence of the Conditions of Alkaline Pretreatment of Vegetable Raw Material before Hydrolysis in a Rotor Pulsation Device on the Cellulose Conversion

Introduction. The growing global energy demand, limited fossil fuel resources, and increasing greenhouse gasemissions highlight the need for expanded use of renewable energy sources, particularly biomass.Problem Statement. A significant drawback in the production of bioethanol is its high cost, primarily due tothe presence of hemicellulose and lignin.Purpose. This study aims to determine the effect of treating an alkaline suspension of wheat straw in a rotary pulsation device on the degree of cellulose conversion during enzymatic hydrolysis, a critical step in the productionof fuel ethanol.Materials and Methods. The raw material is pre-crushed wheat straw. The experiments have been conductedwith the use of a rotary pulsation device in an experimental plant.Results. It has been found that the combined physical effects of the discrete pulse energy input method andreduced straw particle size significantly increase the lignin extraction, from 40.0% at an average particle size of2—1 mm to 62.0% at an average particle size of 0.4—0.1 mm. Additionally, the treatment of an alkaline suspension of wheat straw at 90 оC for one hour, at alkali concentrations ranging from 1 to 4% (wt./wt.), results in anincrease in the cellulose conversion during enzymatic hydrolysis from 38% to 65.8%. Additionally, a corresponding decrease in the lignin content, from 17.1% to 3.16% has been reported.Conclusions. Increasing alkali concentration during the alkaline pretreatment of wheat straw using the discrete-pulse energy input method in a rotary pulsation device enhances the rate of cellulose conversion duringsubsequent enzymatic hydrolysis.

Evaluation of a Peer-To-Peer Smart Grid Using Digital Twins: A Case Study of a Remote European Island

Decarbonization of the built environment by electrifying energy systems and decarbonizing the electrical grid coupled with the digitization of these systems is a central strategy implemented by the European Commission (EC) to meet carbon reduction policies. The proliferation of technologies such as renewable energy sources (RES) and demand-side management (DSM) systems can be improved by using digital twins to predict and optimize their integration with existing systems. Digital twins in the built environment have been used for multiple purposes, such as predicting the performance of a system before its inception or optimizing its operation during use. To this end, a novel application of a combination of these technologies towards optimized DSM is peer-to-peer (P2P) energy trading, which can improve the local use of RES in the built environment. This paper investigates the potential of P2P energy trading in optimizing local RES of a remote island, Inishmore, Republic of Ireland, using a combination of data-driven and predictive digital twins towards the island’s journey to net zero. Data-driven digital twins are used to evaluate the current energy use at the pilot site. Predictive digital twins are applied to estimate the impact of applying P2P in the future and its influence on RES consumption at the pilot site. The findings show that in scenarios with limited RES coverage, P2P can significantly increase the local consumption of excess RES energy, reducing the risk of transmission or curtailment losses. However, P2P is limited in scenarios with widespread RES installation without storage or behavioral change to shift energy loads.

Impact of Natural Disasters on House Prices: A Global Analysis and Policy Implications

This study addresses the limited research on how natural disasters affect house prices by analyzing data from 117 countries between 2000 and 2018, using a panel regression approach to assess these impacts. The results reveal that natural disasters tend to decrease house prices, a finding that holds strong across multiple robustness checks. Specifically, geological disasters are found to have the most significant negative impact on property values. The study also distinguishes between the effects of small and large disasters, with both showing a clear downward effect on house prices. These insights carry important implications for policymakers and investors, as lower house prices in disaster-prone areas may indicate reduced consumption and investment due to the wealth effect, potentially leading to wider economic downturns. To support these regions, economic policymakers might consider measures such as low-tax policies or quantitative easing. The findings also highlight the urgent need for governments to address climate change impacts on the housing market by adopting sustainable technologies and renewable energy sources. Keywords Natural Disasters, House Pricing, Climate Change, Statistical model

Modeling of Hydrogen Combustion from a 0D/1D Analysis to Complete 3D-CFD Engine Simulations

Hydrogen and its unique properties pose major challenges to the development of innovative combustion engines, while it represents a viable alternative when it is based on renewable energy sources. The present paper deals with the holistic approach of hydrogen combustion modeling from a 0D/1D reactor evaluation with Cantera up to complete engine simulations in the 3D-CFD tool QuickSim. The obtained results are referenced to the current literature and calibrated with experimental data. In particular, the engine simulations are validated against measurements of a single-cylinder research engine, which was specifically adapted for lean hydrogen operation and equipped with port fuel injection and a passive pre-chamber system. Special attention is hereby given to the influence of different engine loads and varying lambda operation. The focus of this work is the complementary numerical investigation of the hydrogen flame speed and its self-ignition resistance under the consideration of various reaction mechanisms. A detailed transfer from laminar propagation under laboratory conditions to turbulent flame development within the single-cylinder engine is hereby carried out. It is found that the relatively simple reaction kinetics of hydrogen can lead to acceptable results for all mechanisms, but there are particular effects with regard to the engine behavior. The laminar flame speed and induction time vary greatly with the inner cylinder conditions and significantly affect the entire engine’s operation. The 3D-CFD environment offers the opportunity to analyze the interactions between mixture formation and combustion progress, which are indispensable to evaluate advanced operating strategies and optimize the performance and efficiency, as well as the reliability, of the engine.

Robust Distributed Load Frequency Control for Multi-Area Power Systems with Photovoltaic and Battery Energy Storage System

The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs.

Renewable Solar Energy Facilities in South America—The Road to a Low-Carbon Sustainable Energy Matrix: A Systematic Review

South America is a place on the planet that stands out with enormous potential linked to renewable energies. Countries in this region have developed private investment projects to carry out an energy transition from fossil energies to clean energies and contribute to climate change mitigation. The sun resource is one of the more abundant sources of renewable energies that stands out in South America, especially in the Atacama Desert. In this context, South American countries are developing sustainable actions/strategies linked to implementing solar photovoltaic (PV) and concentrated solar power (CSP) facilities and achieving carbon neutrality for the year 2050. As a result, this systematic review presents the progress, new trends, and the road to a sustainable paradigm with disruptive innovations like artificial intelligence, robots, and unmanned aerial vehicles (UAVs) for solar energy facilities in the region. According to the findings, solar energy infrastructure was applied in South America during the global climate change crisis era. Different levels of implementation in solar photovoltaic (PV) facilities have been reached in each country, with the region being a worldwide research and development (R&D) hotspot. Also, high potential exists for concentrated solar power (CSP) facilities considering the technology evolution, and for the implementation of the hybridization of solar photovoltaic (PV) facilities with onshore wind farm infrastructures, decreasing the capital/operation costs of the projects. Finally, synergy between solar energy infrastructures with emerging technologies linked with low-carbon economies like battery energy storage systems (BESSs) and the use of floating solar PV plants looks like a promising sustainable solution.

Techno-economic feasibility study of ammonia recovery from sewage sludge digestate in wastewater treatment plants

Wastewater treatment plants play a vital role in resource recovery, particularly through biogas production, a key renewable energy source. Beyond biogas, the digestate from anaerobic digestion is rich in nutrients like ammonia. This study explored the feasibility of recovering ammonia from sewage sludge digestate using air stripping. The process was modeled using Aspen Plus® software, utilizing real data from As-Samra WWTP in Jordan. Various operational parameters, such as digestate feed flow, air flow rate, temperature, and pressure, were analyzed to optimize ammonia recovery. The results showed that with a feed flow rate between 10,000 and 30,000 kg/hr, ammonia recovery reached 85%, with production exceeding 100 kg/hr, where the effect of the flow rate appears mostly at elevated feeding temperatures. Increased air flow rates significantly boosted recovery, achieving 90% efficiency at 60 °C with 50,000 kg/h as air flow. Flashing pressure peaked at 1.5 bar, with 85% efficiency at 95 °C, while higher pressures yielded diminishing returns, stabilizing production around 106 kg/hr. The NaOH feed rate also influenced output, rising from 100 kg/hr at a 50 kg/hr feed rate to 107 kg/hr at 750 kg/hr, with recovery efficiency exceeding 85%. The economic analysis showed that the project had a payback period of 6.07 years, reflecting a reasonable recovery of the initial investment. The net present value was 122,924 USD over 15 years, with 8% amortization rate, indicating that the project created value beyond the initial cost. The internal rate of return was 14.23%, surpassing the discount rate and highlighting the project's financial attractiveness.

Social factors influence on energy efficiency management and development of renewable energy sources

Current issues of increasing energy efficiency in the conditions of new industrialization are considered. The article analyzes social factors that affect the effectiveness of energy efficiency management and the development of renewable energy sources, including social awareness of the population, state support, the role of business and social responsibility of enterprises. The study shows that social aspects play a critical role in the implementation of energy-saving technologies and the achievement of sustainable development goals. A comprehensive approach was used, which includes theoretical analysis, questionnaires, expert interviews and statistical analysis to identify key social factors and their impact on energy efficiency management. The results of the study can be useful for developing recommendations for improving energy efficiency management systems taking into account social aspects, as well as for forming a strategy for the development of renewable energy sources in Ukraine and a hydrogen strategy.In the process of researching the impact of social factors on energy efficiency management and the development of renewable energy sources, several unresolved aspects were identified that require additional analysis. Firstly, the insufficiency of research that would reveal the relationship between the social awareness of the population regarding energy efficiency and the level of implementation of energysaving technologies and energy storage technologies using hydrogen was revealed.Sociocultural factors such as educational attainment, cultural stereotypes and values remain understudied. Secondly, the role of social responsibility of business in the implementation of energy-efficient solutions needs a deeper study, since questions about the impact of social initiatives on these processes still remain open. Thirdly, the study of the impact of public policy on the social aspects of energy efficiency is also an underdeveloped direction, particularly in the context of how public programs take into account social factors, such as the adoption of new technologies by the population and the impact on social groups with different income levels.And fourthly, how does Ukraine maintain the level of awareness and understanding of hydrogen technologies. These aspects require further scientific analysis to improve the efficiency of energy efficiency management and the development of renewable energy sources.

A Review on Modular Multi-level Converter Based HVDC Systems

Modular Multilevel Converters (MMCs) have emerged as a promising technology for High Voltage Direct Current (HVDC) transmission systems, offering several advantages such as reduced harmonic distortion, high voltage capability and modularity. This paper presents a comprehensive review of MMC-based HVDC systems, focusing on their applications, control strategies and challenges. The paper begins by discussing the basic principles and structure of MMCs, highlighting their modular design and operation. The paper delves into the control strategies employed in MMC-HVDC systems, emphasizing the importance of coordinated control between the AC and DC sides to ensure stable and efficient operation. Furthermore, the paper addresses the challenges associated with MMC-HVDC systems, such as fault ride-through capability, harmonic interactions and grid integration. It highlights recent advancements in control techniques and technologies that are being developed to address these challenges. The paper provides a valuable overview of MMC-based HVDC systems, highlighting their potential benefits and the ongoing research efforts to overcome their challenges. As the demand for renewable energy sources and long-distance power transmission increases, MMC-HVDC systems are poised to play a crucial role in shaping the future of the power grid

Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response

AbstractDue to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII‐MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33‐node system with the DCDNs is validated under different scenarios. The hybrid NSGAII‐MOPSO performs better in obtaining the Pareto front than the NSGA‐II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.

Trends and opportunities in renewable energy investment in Saudi Arabia: Insights for achieving vision 2030 and enhancing environmental sustainability

Renewable energy has emerged as a critical alternative to traditional energy sources due to growing environmental concerns and the need for sustainable energy development. Saudi Arabia, driven by its Vision 2030, has strongly committed to shifting from fossil fuels to renewable energy sources such as solar, wind, and hydrogen. Despite significant progress, existing investment methods often focus narrowly on financial returns and do not adequately address the risks and uncertainties associated with renewable energy projects, such as policy changes, technological challenges, and fluctuating energy prices. This paper aims to highlight and compare the trends in renewable energy investments and incorporate a risk analysis matrix to address the economic, environmental, and social aspects of Saudi Arabia’s environment. The details used in the study are obtained from Kaggle, while the adopted analysis technique involves multi-criteria decision-making (MCDM). It provides a fresh qualitative approach that allows an all-sided assessment of the investment prospects by focusing on appropriate weight for different factors. The analysis results show that using the proposed framework can help effectively prioritize investment opportunities identifying major trends and risks in developing renewable energy sources in Saudi Arabia. Current investment trends have been reviewed systematically; experts have been interviewed; MCDM techniques have been employed, as the methodology effectiveness improves the comprehension of investment tendencies and contributes to strategic management in the renewable energy market stakeholder’s activity. The MCDM analysis results show that the solar energy system has the highest investment index in the Saudi Arabian cities; the first place belongs to Abha with an investment index of 0.93, the second place belongs to Jeddah with an investment index of 0.85, and the third place belongs to Dammam with an investment index of 0.75. From these outcomes, we can easily conclude that Abha is the best place to place a solar energy project, probably because of environmental and legal factors. The analysis underscores geographic factors in deploying renewable energy, directing investors and policymakers to cities with favourable solar power generation about sustainability and economic objectives. The results are expected to enhance investment awareness among local and international stakeholders, support the strategic goals of Vision 2030, and contribute to a more sustainable and diversified energy future for Saudi Arabia. This study provides a strategic framework for optimizing renewable energy investments, promoting sustainable development, and achieving long-term economic growth. Data AvailabilityData sharing is not applicable to this article as no data sets were generated during the current study.

Enhanced Frequency/Voltage Control in Multi-Source Power System Using CES and SSA-Optimized Cascade TID-FOPTID Controller

The stability and reliability of modern power systems, especially those with several renewable energy sources, strongly rely on load frequency control (LFC) and automatic voltage regulation (AVR) for frequency and voltage control under inconstant load demands. In this study, a new cascade tilt integral derivative-fractional order proportional tilt integral derivative (TID-FOPTID) controller is presented that is polished through the salp swarm algorithm (SSA) for LFC of a multi-area power system with AVR in all control areas. The system integrates capacitive energy storage (CES) and deals with governor dead-band and generation rate constraint nonlinear effects in a thermal-hydro-gas three-area multi-source power system (TAMSPS). The analysis of results, due to the SSA-based TID-FOPTID controller compared to TID-FOTID and TID-FOTID + 1 shows a positive outcome. Integrating CES brings additional improvement in the system performance, the overshoot/undershoot, and settling time are minimized. Finally, the sensitivity analysis reveals that the suggested controller will be effective and reliable for enhancing the frequency stability of the complex power system with a high RES integration level.