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Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 42405

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Special Issue Editor

Dr. Muhammad Khalid

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Guest Editor

1. Electrical Engineering Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran 31261, Saudi Arabia
2. Center for Renewable Energy and Power Systems, KFUPM, Dhahran 31261, Saudi Arabia
3. SDAIA-KFUPM Joint Research Center for Artificial Intelligence, KFUPM, Dhahran 31261, Saudi Arabia
Interests: advanced control; distributed generation; energy storage systems; forecasting; micro grids; optimization techniques; renewable power systems; hydrogen systems; smart grids; artificial intelligence; machine learning
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Special Issue Information

Dear Colleagues,

The global transition towards renewable integration in the energy sector comes with unique challenges and opportunities. At present, many renewable technologies impose a power quality and stability threat that concurrently limits their commercialized deployment. The current developmental trend strives to establish renewable integration based on the concept of microgrid-using technologies such as forecasting, power electronics and energy management to ultimately formulate a deregulated and sustainable smart grid. The recent advancement in renewable technologies in combination with the growing need for optimal energy storage utilization consists of many research and knowledge gaps that require meticulous research initiatives and innovation.

In similar terms, the concept of an energy storage system as an energy buffer—that is, to store/supply abundant/deficit power—has proven to be a pivotal methodology for suitable growth in renewable integration. However, appropriate advancements are urgently required in the areas of constructional, conceptual, and power management to obviate contraptions focused on individual energy storage technologies. Accordingly, with the commercialization of electric vehicles, the concept of utilizing vehicular storage devices to enhance the techno-economic significance of multi-energy renewable systems encourages its potentiality for future sustainable power systems.

This Special Issue provides a unique platform to present state-of-the-art research findings in all fields of renewable energy integration and innovative solutions associated with the development and selection of renewable and energy storage technologies to overcome distinctive technical challenges related to sustainable power establishment. This Special Issue aims to facilitate and promote interdisciplinary researchers to provide multi-faced solutions related to renewable energy and energy storage systems.

Dr. Muhammad Khalid
Guest Editor

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Need for renewable energy, challenges, and opportunities
Impact of renewable technology on environment and climate change
Renewable energy policy
Emerging renewable and storage technologies
Global practices of commercial and residential renewable integration
Renewable energy economics (hydrogen economy, carbon accounting, carbon emission, regionalization and legislation of renewable installation)
Renewable process control (solar, wind, biomass, hydro, tidal geothermal, desalination, solar thermal, solar chimney, electrification of natural gas)
Electric vehicle (EV) technologies in renewable power system (peak shaving, load following, swappable storage stations)
Renewable power electronic converters: topology, structure, and optimization
Advancement and development in energy storage technologies that include, but are not limited to: electrochemical storage (e.g., lithium-ion, lead-acid, nickel-cadmium, sodium-sulfur), thermoelectric storages, electromechanical/mechanical storage, electromagnetic storage systems, thermal storage, chemical storage, flow batteries, supercapacitors, hybrid energy storage systems, hydrogen storage and mobility
Development and advancement in renewable and storage materials (organic materials, organic electrodes, nanomaterial, nanohybridization, functional nanomaterials, flexible batteries, electrochemical analysis, degradation)
Innovations in smart grids and microgrids
Renewable flexibility, reliability, and resilience
Self-healing renewable grids
Optimization, control and forecasting of renewable energy sources
Renewable and distributed system planning and operation
Output power smoothing of renewables and optimal power dispatch
Energy storage efficacy in renewable deployment
Load forecasting
Demand response and demand side management
Machine learning applications in renewable storage systems
Energy storage applicability in power quality, grid stability, and renewable flexibility

Published Papers (13 papers)

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Research

Jump to: Review

18 pages, 6268 KiB

Open AccessArticle

Maximum Power Point Tracking of a Grid Connected PV Based Fuel Cell System Using Optimal Control Technique

by Muhammad Majid Gulzar

Sustainability 2023, 15(5), 3980; https://0-doi-org.brum.beds.ac.uk/10.3390/su15053980 - 22 Feb 2023

Cited by 6 | Viewed by 1713

Abstract

The efficiency of renewable energy sources like PV and fuel cells is improving with advancements in technology. However, maximum power point (MPP) tracking remains the most important factor for a PV-based fuel cell power system to perform at its best. The MPP of a PV system mainly depends on irradiance and temperature, while the MPP of a fuel cell depends upon factors such as the temperature of a cell, membrane water content, and oxygen and hydrogen partial pressure. With a change in any of these factors, the output is changed, which is highly undesirable in real-life applications. Thus, an efficient tracking method is required to achieve MPP. In this research, an optimal salp swarm algorithm tuned fractional order PID technique is proposed, which tracks the MPP in both steady and dynamic environments. To put that technique to the test, a system was designed comprised of a grid-connected proton exchange membrane fuel cell together with PV system and a DC-DC boost converter along with the resistive load. The output from the controller was further tuned and PWM was generated which was fed to the switch of the converter. MATLAB/SIMULINK was used to simulate this model to study the results. The response of the system under different steady and dynamic conditions was compared with those of the conventionally used techniques to validate the competency of the proposed approach in terms of fast response with minimum oscillation. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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17 pages, 1693 KiB

Open AccessArticle

Coordinated Frequency Control of an Energy Storage System with a Generator for Frequency Regulation in a Power Plant

by Lateef Onaadepo Ibrahim, In-Young Chung, Juyoung Youn, Jae Woong Shim, Youl-Moon Sung, Minhan Yoon and Jaewan Suh

Sustainability 2022, 14(24), 16933; https://0-doi-org.brum.beds.ac.uk/10.3390/su142416933 - 16 Dec 2022

Cited by 2 | Viewed by 1737

Abstract

Considering the controllability and high responsiveness of an energy storage system (ESS) to changes in frequency, the inertial response (IR) and primary frequency response (PFR) enable its application in frequency regulation (FR) when system contingency occurs. This paper presents a coordinated control of an ESS with a generator for analyzing and stabilizing a power plant by controlling the grid frequency deviation, ESS output power response, equipment active power, and state of charge (SoC) limitation of the ESS in a power plant. The conventional generator and FR-ESS controllers were investigated and compared. To obtain the optimal frequency and power response, an ESS-based adaptive droop control method was proposed. The proposed control strategy was developed and implemented considering the changes and limitations of the dynamic characteristics of the system, FR requirements, and an ESS using the PSCAD/EMTDC software. The simulation results showed that the proposed method was more effective than the conventional droop-control-based FR-ESS, and the effectiveness of this method was validated. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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27 pages, 1219 KiB

Open AccessArticle

Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty

by Abdul Rauf, Mahmoud Kassas and Muhammad Khalid

Sustainability 2022, 14(17), 11002; https://0-doi-org.brum.beds.ac.uk/10.3390/su141711002 - 02 Sep 2022

Cited by 12 | Viewed by 2181

Abstract

A large-scale renewable-based sustainable power system requires multifaced techno-economic optimization and energy penetration. Due to the volatile and non-periodic nature of renewable energy, the uncertainty of renewables combined with load uncertainties significantly impacts the operational efficiency of renewable integration. The complexities in balancing demand, generation, and maintaining system reliability have introduced new challenges in the current distribution system. Most of the associated challenges can be effectively reduced by using a battery energy storage system (BESS) and the right techniques for handling uncertainties. In this paper, a distributionally robust optimization (DRO) technique with a linear decision rule is formulated for the unit commitment (UC) framework for optimal scheduling of a distribution network that consists of a wind farm, solar PV, a distributed generator (DG), and BESS. To cut the energy cost per unit, BESS plays an important role by storing energy at an off-peak time for on-peak-time use with relatively lower prices. For the all-time minimum overall systems cost, the distribution system requires an optimal size of the BESS to be connected to provide optimal scheduling of DGs. Three case studies are formulated using an IEEE 14 bus system (converted from MW to kW to match the BESS size available in the market) and solved with the proposed distributionally robust optimization technique to achieve the maximum operating point with an optimal capacity of BESS, i.e., wind, solar and hybrid. Each case study has its own optimal 30-min interval schedule for DGs along with the optimal capacity of BESS. The cost comparison with and without BESS and its impact on the start-up and shut down of DGs is reported with all the dynamic economic dispatch results, including the battery’s state-of-charge profile. The proposed technique can handle the uncertainties in renewables and allows economical energy dispatch and optimal BESS sizing with comparatively lower computational processing and complexities. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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29 pages, 984 KiB

Open AccessArticle

Robust Control for Optimized Islanded and Grid-Connected Operation of Solar/Wind/Battery Hybrid Energy

by Muhammad Maaruf, Khalid Khan and Muhammad Khalid

Sustainability 2022, 14(9), 5673; https://0-doi-org.brum.beds.ac.uk/10.3390/su14095673 - 08 May 2022

Cited by 19 | Viewed by 2266

Abstract

Wind and solar energy systems are among the most promising renewable energy technologies for electric power generations. Hybrid renewable energy systems (HRES) enable the incorporation of more than one renewable technology, allowing increased reliability and efficiency. Nevertheless, the introduction of variable generation sources in concurrence with the existing system load demand necessitates maintaining the power balance between the components of the HRES. Additionally, the efficiency of the hybrid power supply system is drastically affected by the number of converters interfacing its components. Therefore, to improve the performance of the HRES, this paper proposes a robust sliding mode control strategy for both standalone and grid-connected operation. The control strategy achieves maximum power point tracking for both the renewable energy sources and stabilizes the DC-bus and load voltages irrespective of the disturbances, change in load demand, variations of irradiance level, temperature, and wind speed ensuring an efficient energy management. Furthermore, the solar PV system is directly linked to the DC-bus obviating the need for redundant interfacing boost converters with decreased costs and reduced system losses. Lyapunov candidate function is used to prove the asymptotic stability and the convergence of the entire system. The robustness of the proposed control strategy is tested and validated under various conditions of HRES, demonstrating its efficacy and performance under various conditions of the HRES. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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14 pages, 4178 KiB

Open AccessArticle

Analysis of a Hybrid Wind/Photovoltaic Energy System Controlled by Brain Emotional Learning-Based Intelligent Controller

by Hani Albalawi, Mohamed E. El-Shimy, Hosam AbdelMeguid, Ahmed M. Kassem and Sherif A. Zaid

Sustainability 2022, 14(8), 4775; https://0-doi-org.brum.beds.ac.uk/10.3390/su14084775 - 15 Apr 2022

Cited by 7 | Viewed by 1881

Abstract

Recently, hybrid wind/PV microgrids have gained great attention all over the world. It has the merits of being environmentally friendly, reliable, sustainable, and efficient compared to its counterparts. Though there has been great development in this issue, the control and energy management of these systems still face challenges. The source of those challenges is the intermittent nature of both wind and PV energy. On the other hand, a new intelligent control technique called Brain Emotional Learning-Based Intelligent Controller (BELBIC) has garnered more interest. This paper proposes the control and energy management of hybrid wind/PV microgrids using a BELBIC controller. To design the system, simple power and energy analyses were proposed. The proposed microgrid was modeled and simulated using MATLAB. The responses of the energy system were tested under two different types of disturbances, namely step and ramp disturbances. These disturbances are applied to the wind speed, the irradiation level of the PV, and the load power. The results indicate that the AC load voltage and frequency are steady with negligible transients against the previous disturbance. In addition, the performance is better than that of the classical PI controller. Also, energy management acts perfectly to compensate for the intermittence and disturbances of the wind and PV energies. On the other hand, the system robustness against model parameters uncertainties in the microgrid parameters are studied. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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21 pages, 960 KiB

Open AccessArticle

Enhancing Transient Response and Voltage Stability of Renewable Integrated Microgrids

by Luay Elkhidir, Khalid Khan, Mohammad Al-Muhaini and Muhammad Khalid

Sustainability 2022, 14(7), 3710; https://0-doi-org.brum.beds.ac.uk/10.3390/su14073710 - 22 Mar 2022

Cited by 5 | Viewed by 1773

Abstract

Integration of renewable generation coupled with an energy storage system (ESS) in a power system increases the complexity of networks’ stability analysis and control. Therefore, an accurate stability assessment of power networks is expected to become a big challenge in the future. In this work, an effective approach to prevent power outage by controlling the source voltage of the power network is formulated to mitigate the effects of grid faults. Small signal stability studies are conducted on a renewable integrated IEEE 9 bus system as a case study with optimized size and allocation of ESS for reducing output power variability of renewables. An assessment is performed to study the effects of load-sharing devices on parallel generators under 6-cycle three-phase fault disturbances. The damping of the power network is increased at nominal and light loading conditions with 6-cycle three-phase fault disturbances through coordinated power system stabilizer (PSS) and static VAR compensator (SVC) at bus 9. The developed framework is extensively analyzed in steady-state conditions using a load flow program. Based on the results obtained, the proposed coordinated PSS-SVC device proves to possess comparatively better performance in terms of enhancing most of the system response rate under various load conditions with overall improved stability. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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13 pages, 2027 KiB

Open AccessArticle

Water-Energy-Food Nexus Approach to Assess Crop Trading in Saudi Arabia

by Mohammad Tamim Kashifi, Fahad Saleh Mohammed Al-Ismail, Shakhawat Chowdhury, Hassan M. Baaqeel, Md Shafiullah, Surya Prakash Tiwari and Syed Masiur Rahman

Sustainability 2022, 14(6), 3494; https://0-doi-org.brum.beds.ac.uk/10.3390/su14063494 - 16 Mar 2022

Cited by 5 | Viewed by 2585

Abstract

Water scarcity is a global challenge, especially in arid regions, including Middle Eastern and North African countries. The distribution of water around the earth is not even. Trading water in the form of an embedded commodity, known as the water footprint (WF), from water-abundant regions to water-scarce regions, is a viable solution to water scarcity problems. Agricultural products account for approximately 85% of the earth’s total WF, indicating that importing water-intense crops, such as cereal crops, can partially solve the local water scarcity problem. This study investigated water, energy, and food nexus dynamics for the trades of a few major crops, specifically considering Saudi Arabia. It analyzed the trade of crops and its impact on WF, energy, and carbon dioxide (CO₂) emission savings. The findings revealed that importing major cereal crops to Saudi Arabia could significantly reduce the local WF. The imports of wheat, maize, rice, and barley reduced approximately 24 billion m³ per year of consumable WF (i.e., blue and green water footprint) in the global scale. Similarly, the trade of major crops had a significant impact on energy and CO₂ emission savings. The energy savings from the wheat, maize, and barley trades in Saudi Arabia was estimated to be approximately 9 billion kWh. It also saved about 7 million tons per year of CO₂ emissions. The trades of cereal crops in Saudi Arabia reduced water consumption, energy usage, and CO₂ emissions significantly. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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19 pages, 1081 KiB

Open AccessArticle

Adaptive Nonsingular Fast Terminal Sliding Mode Control for Maximum Power Point Tracking of a WECS-PMSG

by Muhammad Maaruf, Md Shafiullah, Ali T. Al-Awami and Fahad S. Al-Ismail

Sustainability 2021, 13(23), 13427; https://0-doi-org.brum.beds.ac.uk/10.3390/su132313427 - 03 Dec 2021

Cited by 13 | Viewed by 2195

Abstract

This paper investigates maximum power extraction from a wind-energy-conversion system (WECS) with a permanent magnet synchronous generator (PMSG) operating in standalone mode. This was achieved by designing a robust adaptive nonsingular fast terminal sliding mode control (ANFTSMC) for the WECS-PMSG. The proposed scheme guaranteed optimal power generation and suppressed the system uncertainties with a rapid convergence rate. Moreover, it is independent of the upper bounds of the system uncertainties as an online adjustment algorithm was utilized to estimate and compensate them. Finally, four case studies were carried out, which manifested the remarkable performance of ANFTSMC in comparison to previous methods reported in the literature. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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22 pages, 6382 KiB

Open AccessArticle

A Machine Learning-Based Communication-Free PV Controller for Voltage Regulation

by Shabib Shahid, Saifullah Shafiq, Bilal Khan, Ali T. Al-Awami and Muhammad Omair Butt

Sustainability 2021, 13(21), 12208; https://0-doi-org.brum.beds.ac.uk/10.3390/su132112208 - 05 Nov 2021

Cited by 2 | Viewed by 1462

Abstract

Due to the recent advancements in the manufacturing process of solar photovoltaics (PVs) and electronic converters, solar PVs has emerged as a viable investment option for energy trading. However, distribution system with large-scale integration of rooftop PVs, would be subjected to voltage upper limit violations, unless properly controlled. Most of the traditional solutions introduced to address this problem do not ensure fairness amongst the on-line energy sources. In addition, other schemes assume the presence of communication linkages between these energy sources. This paper proposes a control scheme to mitigate the over-voltages in the distribution system without any communication between the distributed energy sources. The proposed approach is based on artificial neural networks that can utilize two locally obtainable inputs, namely, the nodal voltage and node voltage sensitivity and control the PV power. The controller is trained using extensive data generated for various loading conditions to include daily load variations. The control scheme was implemented and tested on a 12.47 kV feeder with 85 households connected on the 220 V distribution system. The results demonstrate the fair control of all the rooftop solar PVs mounted on various houses to ensure the system voltage are maintained within the allowed limits as defined by the ANSI C84.1-2016 standard. Furthermore, to verify the robustness of the proposed PV controller, it is tested during cloudy weather condition and the impact of integration of electric vehicles on the proposed controller is also analyzed. The results prove the efficacy of the proposed controller. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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21 pages, 3316 KiB

Open AccessArticle

PV/Wind-Integrated Low-Inertia System Frequency Control: PSO-Optimized Fractional-Order PI-Based SMES Approach

by Md Shafiul Alam, Fahad Saleh Al-Ismail and Mohammad Ali Abido

Sustainability 2021, 13(14), 7622; https://0-doi-org.brum.beds.ac.uk/10.3390/su13147622 - 07 Jul 2021

Cited by 25 | Viewed by 2760

Abstract

A paradigm shift in power engineering transforms conventional fossil fuel-based power systems gradually into more sustainable and environmentally friendly systems due to more renewable energy source (RES) integration. However, the control structure of high-level RES integrated system becomes complex, and the total system inertia is reduced due to the removal of conventional synchronous generators. Thus, such a system poses serious frequency instabilities due to the high rate of change of frequency (RoCoF). To handle this frequency instability issue, this work proposes an optimized fractional-order proportional integral (FOPI) controller-based superconducting magnetic energy storage (SMES) approach. The proposed FOPI-based SMES technique to support virtual inertia is superior to and more robust than the conventional technique. The FOPI parameters are optimized using the particle swarm optimization (PSO) technique. The SMES is modeled and integrated into the optimally designed FOPI to support the virtual inertia of the system. Fluctuating RESs are considered to show the effectiveness of the proposed approach. Extensive time-domain simulations were carried out in MATLAB Simulink with different load and generation mismatch levels. Systems with different inertia levels were simulated to guarantee the frequency stability of the system with the proposed FOPI-based SMES control technique. Several performance indices, such as overshoot, undershoot, and settling time, were considered in the analysis. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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0 pages, 1510 KiB

Open AccessArticle

A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment

by Sana Iqbal, Mohammad Sarfraz, Mohammad Ayyub, Mohd Tariq, Ripon K. Chakrabortty, Michael J. Ryan and Basem Alamri

Sustainability 2021, 13(13), 7170; https://0-doi-org.brum.beds.ac.uk/10.3390/su13137170 - 25 Jun 2021

Cited by 40 | Viewed by 4840

Abstract

The ever increasing demand for electricity and the rapid increase in the number of automatic electrical appliances have posed a critical energy management challenge for both utilities and consumers. Substantial work has been reported on the Home Energy Management System (HEMS) but to the best of our knowledge, there is no single review highlighting all recent and past developments on Demand Side Management (DSM) and HEMS altogether. The purpose of each study is to raise user comfort, load scheduling, energy minimization, or economic dispatch problem. Researchers have proposed different soft computing and optimization techniques to address the challenge, but still it seems to be a pressing issue. This paper presents a comprehensive review of research on DSM strategies to identify the challenging perspectives for future study. We have described DSM strategies, their deployment and communication technologies. The application of soft computing techniques such as Fuzzy Logic (FL), Artificial Neural Network (ANN), and Evolutionary Computation (EC) is discussed to deal with energy consumption minimization and scheduling problems. Different optimization-based DSM approaches are also reviewed. We have also reviewed the practical aspects of DSM implementation for smart energy management. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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Review

Jump to: Research

21 pages, 2177 KiB

Open AccessReview

A Review on Biohydrogen Sources, Production Routes, and Its Application as a Fuel Cell

by Antony V. Samrot, Deenadhayalan Rajalakshmi, Mahendran Sathiyasree, Subramanian Saigeetha, Kasirajan Kasipandian, Nachiyar Valli, Nellore Jayshree, Pandurangan Prakash and Nagarajan Shobana

Sustainability 2023, 15(16), 12641; https://0-doi-org.brum.beds.ac.uk/10.3390/su151612641 - 21 Aug 2023

Cited by 4 | Viewed by 2875

Abstract

More than 80% of the energy from fossil fuels is utilized in homes and industries. Increased use of fossil fuels not only depletes them but also contributes to global warming. By 2050, the usage of fossil fuels will be approximately lower than 80% than it is today. There is no yearly variation in the amount of CO₂ in the atmosphere due to soil and land plants. Therefore, an alternative source of energy is required to overcome these problems. Biohydrogen is considered to be a renewable source of energy, which is useful for electricity generation rather than relying on harmful fossil fuels. Hydrogen can be produced from a variety of sources and technologies and has numerous applications including electricity generation, being a clean energy carrier, and as an alternative fuel. In this review, a detailed elaboration about different kinds of sources involved in biohydrogen production, various biohydrogen production routes, and their applications in electricity generation is provided. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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18 pages, 3735 KiB

Open AccessReview

Recent Advances in Energy Storage Systems for Renewable Source Grid Integration: A Comprehensive Review

by Muhammed Y. Worku

Sustainability 2022, 14(10), 5985; https://0-doi-org.brum.beds.ac.uk/10.3390/su14105985 - 15 May 2022

Cited by 58 | Viewed by 11902

Abstract

The reduction of greenhouse gas emissions and strengthening the security of electric energy have gained enormous momentum recently. Integrating intermittent renewable energy sources (RESs) such as PV and wind into the existing grid has increased significantly in the last decade. However, this integration hampers the reliable and stable operation of the grid by posing many operational and control challenges. Generation uncertainty, voltage and angular stability, power quality issues, reactive power support and fault ride-through capability are some of the various challenges. The power generated from RESs fluctuates due to unpredictable weather conditions such as wind speed and sunshine. Energy storage systems (ESSs) play a vital role in mitigating the fluctuation by storing the excess generated power and then making it accessible on demand. This paper presents a review of energy storage systems covering several aspects including their main applications for grid integration, the type of storage technology and the power converters used to operate some of the energy storage technologies. This comprehensive review of energy storage systems will guide power utilities; the researchers select the best and the most recent energy storage device based on their effectiveness and economic feasibility. Full article

(This article belongs to the Special Issue Sustainable Energy Systems: Emerging Technologies and Practices in Renewable Energy Storage)

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