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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 2023) | Viewed by 28426

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Special Issue Editors

Dr. Ayman Al-Quraan

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Guest Editor

Electrical Power Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan
Interests: wind energy; renewable energy; solar energy; PV systems
Special Issues, Collections and Topics in MDPI journals

Dr. Ahmad M. A. Malkawi

E-Mail Website
Guest Editor

Mechatronics Engineering Department, School of Engineering, The University of Jordan, Amman 11942, Jordan
Interests: power electronics and drive; renewable energy systems; micro-grid and smart-grids; hybrid energy storage systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

All nations are realizing the growing environmental and economic significance of renewable energy sources like sunlight, wind, water currents, and geothermal heat. Many different renewable energy technologies have already achieved commercial success, and most governments view them as emerging industries. International organizations, such as the United Nations, have extensive programs to support the development of new renewable resource technologies. According to specific statistics, between 2011 and 2021, the share of renewable energy in the world's electrical supply increased from 20% to 28%, while the share of fossil and nuclear energy decreased from 68% to 62%. Hydropower's proportion dropped from 16% to 15%, while solar and wind energy's share rose from 2% to 10%. Geothermal energy increased from 2% to 3%, as did biomass. Since we believe that renewable energy is distinct and needs specialized attention, we emphasize the scientific knowledge and analysis of renewable energy in this Special Issue.

We encourage researchers and colleagues to submit both their critical review papers and original, distinct works. These are just a few examples of possible topics:

The use of renewable energy;
Hybrid renewable energy systems using biomass and biofuel;
Energy systems;
Energy conservation;
Energy-saving technologies;
Applications of robotics in renewable energy systems in energy policy;
Electric automobiles;
Applications of power electronics in renewable energy;
Pollution of the atmosphere;
Solar systems;
Wind systems;
Artificial intelligence applications in the energy system;
Urban wind energy and its aerodynamic effect.

Dr. Ayman Al-Quraan
Dr. Ahmad M. A. Malkawi
Guest Editors

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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

renewable energy
solar energy
wind energy systems
biomass and biofuels
geothermal energy
tidal power
wave energy
photosynthetic process
hydro-power

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Published Papers (11 papers)

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Research

35 pages, 11123 KiB

Open AccessArticle

Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

by Ameer A. Kareim Al-Sahlawi, Shahrin Md. Ayob, Chee Wei Tan, Hussein Mohammed Ridha and Dhafer Manea Hachim

Sustainability 2024, 16(6), 2491; https://doi.org/10.3390/su16062491 - 17 Mar 2024

Cited by 10 | Viewed by 2791

Abstract

Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid (

E_{S O L D}

). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 ×

10^{- 2}

USD/kWh, the GCF is equal to 7.34 ×

10^{- 5}

kWh, and the

E_{S O L D}

is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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30 pages, 7572 KiB

Open AccessArticle

Velocity Augmentation Model for an Empty Concentrator-Diffuser-Augmented Wind Turbine and Optimisation of Geometrical Parameters Using Surface Response Methodology

by Ngwarai Shambira, Golden Makaka and Patrick Mukumba

Sustainability 2024, 16(4), 1707; https://doi.org/10.3390/su16041707 - 19 Feb 2024

Cited by 3 | Viewed by 1427

Abstract

Wind energy, renowned for cost-effectiveness and eco-friendliness, addresses global energy needs amid fossil fuel scarcity and environmental concerns. In low-wind speed regions, optimising wind turbine performance becomes vital and achievable by augmenting wind velocity at the turbine rotor using augmentation systems such as concentrators and diffusers. This study focuses on developing a velocity augmentation model that correctly predicts the throat velocity in an empty concentrator-diffuser-augmented wind turbine (CDaugWT) design and determines optimal geometrical parameters. Utilising response surface methodology (RSM) in Design Expert 13 and computational fluid dynamics (CFD) in ANSYS Fluent, 86 runs were analysed, optimising parameters such as diffuser and concentrator angles and lengths, throat length, and flange height. The ANOVA analysis confirmed the model’s significance (p < 0.05). Notably, the interaction between the concentrator’s length and the diffuser’s length had the highest impact on the throat velocity. The model showed a strong correlation (R² = 0.9581) and adequate precision (ratio value of 49.655). A low coefficient of variation (C.V.% = 0.1149) highlighted the model’s reliability. The findings revealed a 1.953-fold increase in inlet wind speed at the throat position. Optimal geometrical parameters for the CDaugWT included a diffuser angle of

10^{°}

, concentrator angle of

20^{°}

, concentrator length of 375 mm (0.62

R_{t h}

), diffuser length of 975 mm (1.61

R_{t h}

), throat length of 70 mm (0.12

R_{t h}

), and flange height of 100 mm (0.17

R_{t h}

) where

R_{t h}

is the throat radius. A desirability value of 0.9, close to 1, showed a successful optimisation. CFD simulations and RSM reduced calculation cost and time when determining optimal geometrical parameters for the CDaugWT design. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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21 pages, 5583 KiB

Open AccessArticle

The Optimization of PEM Fuel-Cell Operating Parameters with the Design of a Multiport High-Gain DC–DC Converter for Hybrid Electric Vehicle Application

by B. Karthikeyan, Palanisamy Ramasamy, M. Pandi Maharajan, N. Padmamalini, J. Sivakumar, Subhashree Choudhury and George Fernandez Savari

Sustainability 2024, 16(2), 872; https://doi.org/10.3390/su16020872 - 19 Jan 2024

Cited by 5 | Viewed by 2365

Abstract

The fossil fuel crisis is a major concern across the globe, and fossil fuels are being exhausted day by day. It is essential to promptly change from fossil fuels to renewable energy resources for transportation applications as they make a major contribution to fossil fuel consumption. Among the available energy resources, a fuel cell is the most affordable for transportation applications because of such advantages as moderate operating temperature, high energy density, and scalable size. It is a challenging task to optimize PEMFC operating parameters for the enhancement of performance. This paper provides a detailed study on the optimization of PEMFC operating parameters using a multilayer feed-forward neural network, a genetic algorithm, and the design of a multiport high-gain DC–DC converter for hybrid electric vehicle application, which is capable of handling both a 6 kW PEMFC and an 80 AH 12 V heavy-duty battery. To trace the maximum power from the PEMFC, the most recent SFO-based MPPT control technique is implemented in this research work. Initially, a multilayer feed-forward neural network is trained using a back-propagation algorithm with experimental data. Then, the optimization phase is separately carried out in a neural-power software environment using a genetic algorithm (GA). The simulation study was carried out using the MATLAB/R2022a platform to verify the converter performance along with the SFO-based MPPT controller. To validate the real-time test bench results, a 0.2 kW prototype model was constructed in the laboratory, and the results were verified. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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18 pages, 2709 KiB

Open AccessArticle

Optimizing a Single-Slope Solar Still for Fresh-Water Production in the Deserts of Arid Regions: An Experimental and Numerical Approach

by Ibrahim M. Al-Helal, Abdullah Alsadon, Samy Marey, Abdullah Ibrahim and Mohamed R. Shady

Sustainability 2024, 16(2), 800; https://doi.org/10.3390/su16020800 - 17 Jan 2024

Cited by 3 | Viewed by 1254

Abstract

Solar desalination is a promising sustainable solution to overcome the scarcity of fresh water in the deserts of arid regions. The productivity of a solar still depends mainly on its design parameters and the meteorological conditions of its location (longitude and latitude angles). Therefore, this study aimed to optimize the main design parameters of a single-slope solar still for freshwater production in the arid climate of the central region of Saudi Arabia (24°4′ N, 32.89° E). Experiments were conducted on four identical solar stills, with the same basin surface area and air gap distances (d) of 14, 16, 18, and 20 cm, respectively. The stills operated using three basin water depths (h) of 0.5, 1, and 1.5 cm on clear sunny days. The performance and productivity of the four stills were evaluated. The results showed that reducing the air gap distance (d) and water depth (h) significantly enhanced the distillate freshwater yield, and the optimum ratio of the length/width is 2 and of the back/front wall height is 3.65. Specifically, at a low water depth (h) of 0.5 cm, the daily distillate yield of the solar still increased by about 11% when the air gap distance (d) decreased from 20 to 14 cm. For the lowest air gap distance (d) of 14 cm, the distillate yield increased by about 23% when h decreased from 1.5 to 0.5 cm. Using the measured parameters, several numerical correlations have been developed to estimate the desalination rate (m_c) as a function of the solar irradiance (I_s) and ambient temperature (T_am). The developed correlations can be used successfully to estimate the values of m_c instead of the prohibitive experimental measurements. The stills showed excellent performance in the arid climate and reduced water salinity from 31,250 to 495 ppm. This should encourage decision-makers to expand investment in solar desalination to sustainably develop the deserts of arid regions. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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15 pages, 6503 KiB

Open AccessArticle

Grid-Forming Inverter Control for Power Sharing in Microgrids Based on P/f and Q/V Droop Characteristics

by Qusay Salem, Rafat Aljarrah, Mazaher Karimi and Ayman Al-Quraan

Sustainability 2023, 15(15), 11712; https://doi.org/10.3390/su151511712 - 28 Jul 2023

Cited by 5 | Viewed by 4446

Abstract

Grid-forming inverters are anticipated to be integrated more into future smart microgrids commencing the function of traditional power generators. The grid-forming inverter can generate a reference frequency and voltage itself without assistance from the main grid. This paper comprehensively investigates grid-forming inverter modelling and control methodology. A decentralized method employing an active power versus frequency P − f droop and a reactive power versus voltage Q − V droop is exploited to drive the operation of the grid-forming inverter. This decentralized method ensures balancing the supply and demand beside the power-sharing task between two or more inverters. The performance of the grid-forming inverter is examined by monitoring the frequency and RMS voltage of the inverter bus for three different periods of a varying PQ load. In addition, the performance of the resultant droop is compared with the assumed droop to validate the effectiveness of the proposed method. Finally, two grid-forming inverters equipped with the same droop characteristics are connected to a single load to observe the power-sharing concept among them. All simulations are implemented and executed using Matlab/Simulink version R2014b. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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25 pages, 5567 KiB

Open AccessArticle

A Droop-Controlled Interlink Converter for a Dual DC Bus Nanogrid with Decentralized Control

by Ahmad M. A. Malkawi, Ayman AL-Quraan and Luiz A. C. Lopes

Sustainability 2023, 15(13), 10394; https://doi.org/10.3390/su151310394 - 30 Jun 2023

Cited by 1 | Viewed by 1148

Abstract

This paper proposed a dual DC bus nanogrid with 380 V and 48 V buses and allows the integration of distributed energy resources on two buses. The proposed system employs an interlink converter to enable power sharing between the buses. The integration of distributed energy resources has been found to enhance the reliability of the low-voltage bus in comparison to those that lack such integration. The integration process requires the introduction of a new V-I curve for the interlink converter within a DC nanogrid controlled by DC bus signaling and droop control. Furthermore, selecting a power electronics converter for the interlink converter is essential. This paper employs a dual active bridge with galvanic isolation as an interlink converter and proposes a control strategy for the converter that relies on DC bus signaling and droop control. Moreover, this control methodology serves the purpose of preventing any detrimental impact of the interlink converter on the DC buses through the reprogramming of the V-I curve. Subsequently, the suggested control methodology underwent simulation testing via MATLAB/Simulink, which included two different test categories. Initially, the DAB was evaluated as an interlink converter, followed by a comprehensive assessment of the interlink converter in a complete dual DC bus nanogrid. The results indicate that the DAB has the potential to function as an interlink converter while the suggested control approach effectively manages the power sharing between the two buses. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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25 pages, 4056 KiB

Open AccessArticle

A Cost-Effective Multi-Verse Optimization Algorithm for Efficient Power Generation in a Microgrid

by Upasana Lakhina, Irraivan Elamvazuthi, Nasreen Badruddin, Ajay Jangra, Bao-Huy Truong and Joseph M. Guerrero

Sustainability 2023, 15(8), 6358; https://doi.org/10.3390/su15086358 - 7 Apr 2023

Cited by 7 | Viewed by 2311

Abstract

Renewable energy sources (RESs) are a great source of power generation for microgrids with expeditious urbanization and increase in demand in the energy sector. One of the significant challenges in deploying RESs with microgrids is efficient energy management. Optimizing the power allocation among various available generation units to serve the load is the best way to achieve efficient energy management. This paper proposes a cost-effective multi-verse optimizer algorithm (CMVO) to solve this optimization problem. CMVO focuses on the optimal sharing of generated power in a microgrid between different available sources to reduce the generation cost. The proposed algorithm is analyzed for two different scale microgrids (IEEE 37-node test system and IEEE 141-node test system) using IEEE test feeder standards to assess its performance. The results show that CMVO outperforms multi-verse optimizer (MVO), particle swarm optimization (PSO), artificial hummingbird algorithm (AHA), and genetic algorithm (GA). The simulation results emphasize the cost reduction and execution time improvement in both IEEE test systems compared with other meta-heuristic algorithms. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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24 pages, 384 KiB

Open AccessArticle

Mechanisms for Choosing PV Locations That Allow for the Most Sustainable Usage of Solar Energy

by Syed Hammad Mian, Khaja Moiduddin, Hisham Alkhalefah, Mustufa Haider Abidi, Faraz Ahmed and Faraz Hussain Hashmi

Sustainability 2023, 15(4), 3284; https://doi.org/10.3390/su15043284 - 10 Feb 2023

Cited by 11 | Viewed by 2274

Abstract

The electrical power need in the Kingdom of Saudi Arabia (KSA) has been escalating at a rapid rate of about 7.5% annually. It has the third highest usage rate in the world as stated by World Energy Council statistics. The rising energy demand has a significant impact on the country’s economy since oil is considered to be its mainstay. Additionally, conventional energy production using fossil fuels is a leading contributor to ecological degradation and adversely influences human health. As a result, Saudi Arabia has taken significant steps to shift from its current status of total reliance on oil to new frontiers of exploration of other kinds of renewable energies. Photovoltaic (PV) solar energy is the most preferred renewable energy to be harnessed in Saudi Arabia. In accordance with Vision 2030, the KSA intends to generate at least 9.5 GW of electricity from green sources, a significant portion of which will come from solar PV power. Since the site peculiarities have a huge influence on the project’s technical and economic dimensions, the scaled-up deployment of solar projects calls for a judicious selection of PV sites. Undoubtedly, performing a thorough solar site survey is the foremost step to establishing a financially viable and successful solar project. Multiple criterion decision-making (MCDM) strategies can be very helpful in making judgments, given that a number of criteria might influence PV site selection. The objective of this research is to provide valuable information on various MCDM approaches that can be utilized to select optimal locations for PV solar plants. A number of variables, including topography, air temperature, dust storms, solar radiation, etc., are considered in this analysis. This study has combined various MCDM techniques in order for the strengths of each method to outweigh the weaknesses of the others. It has been deduced from this analysis that the most crucial factors in choosing PV sites are solar radiation and sunshine hours. It has also been concluded that of the surveyed cities, Tabuk is the optimum location for the construction of a solar power plant due to its high GHI value of 5992 W/m²/day and abundant sunshine hours of 12.16 h/day. Additionally, the FAHP-VIKOR method is noted as being the most rigorous, whereas Entropy-GRA is the simplest method. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

29 pages, 39110 KiB

Open AccessArticle

Machine Learning Classification and Prediction of Wind Estimation Using Artificial Intelligence Techniques and Normal PDF

by Hiba H. Darwish and Ayman Al-Quraan

Sustainability 2023, 15(4), 3270; https://doi.org/10.3390/su15043270 - 10 Feb 2023

Cited by 14 | Viewed by 2761

Abstract

Estimating wind energy at a specific wind site depends on how well the real wind data in that area can be represented using an appropriate distribution function. In fact, wind sites differ in the extent to which their wind data can be represented from one region to another, despite the widespread use of the Weibull function in representing the wind speed in various wind locations in the world. In this study, a new probability distribution model (normal PDF) was tested to implement wind speed at several wind locations in Jordan. The results show high compatibility between this model and the wind resources in Jordan. Therefore, this model was used to estimate the values of the wind energy and the extracted energy of wind turbines compared to those obtained by the Weibull PDF. Several artificial intelligence techniques were used (GA, BFOA, SA, and a neuro-fuzzy method) to estimate and predict the parameters of both the normal and Weibull PDFs that were reflected in conjunction with the actual observed data of wind probabilities. Afterward, the goodness of fit was decided with the aid of two performance indicators (RMSE and MAE). Surprisingly, in this study, the normal probability distribution function (PDF) outstripped the Weibull PDF, and interestingly, BFOA and SA were the most accurate methods. In the last stage, machine learning was used to classify and predict the error level between the actual probability and the estimated probability based on the trained and tested data of the PDF parameters. The proposed novel methodology aims to predict the most accurate parameters, as the subsequent energy calculation phases of wind depend on the proper selection of these parameters. Hence, 24 classifier algorithms were used in this study. The medium tree classifier shows the best performance from the accuracy and training time points of view, while the ensemble-boosted trees classifier shows poor performance regarding providing correct predictions. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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16 pages, 4943 KiB

Open AccessArticle

Real-Time Simulation and Energy Management Attainment of Microgrids

by Hani Muhsen, Asma Alkhraibat and Ala’aldeen Al-Halhouli

Sustainability 2023, 15(3), 2696; https://doi.org/10.3390/su15032696 - 2 Feb 2023

Cited by 2 | Viewed by 2357

Abstract

The rapid spread of Microgrid systems has led to the need for an intensive analysis of the system to avoid several challenges such as stability, reliability, power balance, and other aspects. In this context, real-time simulation plays a vital role in the overall system study before the actual implementation stage. This helps avoid many on-site problems of the Microgrid by simulating the system and studying different operation scenarios. This paper uses the OPAL-RT simulator to perform a real-time simulation of an MG case study. Furthermore, it examines the implementation of the Fault Ride Through technique to overcome the total disconnection of the PV system following unpredictable faults. Moreover, a Load curtailment solution method is proposed in this study, to meet the balance and stable operation of the MG. The results prove the effectiveness of both techniques, with FRT implementation reducing the losses by about 62%, and the Load curtailment algorithm maintaining the balance of the MG. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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20 pages, 4902 KiB

Open AccessArticle

Hybrid Tripping Characteristic-Based Protection Coordination Scheme for Photovoltaic Power Systems

by Feras Alasali, Abdelaziz Salah Saidi, Naser El-Naily, Mahmoud A. Smadi and William Holderbaum

Sustainability 2023, 15(2), 1540; https://doi.org/10.3390/su15021540 - 13 Jan 2023

Cited by 5 | Viewed by 2621

Abstract

Due to the high penetration of renewable energy sources into the electrical power network, overcurrent relays coordination with highly sensitive and selective protection systems are now two of the most important power protection concerns. In this research, an optimal coordination strategy utilising a new hybrid tripping scheme based on current–voltage characteristics has been devised for overcurrent relays in a power network coupled to a photovoltaic system. This research develops and proves a new optimal coordination scheme based on two optimisation methods, the vibrating particles system and particle swarm optimisation algorithms, in consideration of the impact of renewable sources on fault characteristics. The new optimal coordination approach aims to improve the sensitivity and dependability of the protection system by reducing the tripping time of the overcurrent relays by employing a new hybrid tripping scheme. A specific case study, Conseil International des Grands Réseaux Electriques (CIGRE) distribution network connected to two photovoltaic systems is constructed and presented utilising Industrial software (namely ETAP), and the outcomes of the proposed optimal coordination scheme are compared with standard and recent characteristics from the literature. The hybrid tripping scheme and optimisation techniques are evaluated using different fault and power network model scenarios. The results show that the optimal hybrid tripping scheme provided successfully decreases the overall operating time of the overcurrent relays and increases the sensitivity of the relay during all fault scenarios. The reduction in overall time for the proposed hybrid tripping scheme was 35% compared to the literature for the scenario of a power grid with and without photovoltaic systems. Full article

(This article belongs to the Special Issue Applications and Technologies of Renewable Energy)

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