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21 pages, 392 KiB

Open AccessArticle

Decarbonizing Public Transportation: A Multi-Criteria Comparative Analysis of Battery Electric Buses and Fuel Cell Electric Buses

by Afnan Fayez Eliyan, Mohamed Haouari and Ahmad Sleiti

Sustainability 2024, 16(21), 9354; https://doi.org/10.3390/su16219354 - 28 Oct 2024

Viewed by 887

Abstract

To combat global warming, many industrialized countries have announced plans to ban vehicles powered by fossil fuel in the near future. In alignment with this global initiative, many countries across the globe are committed to decarbonizing their public transportation sector, which significantly contributes [...] Read more.

To combat global warming, many industrialized countries have announced plans to ban vehicles powered by fossil fuel in the near future. In alignment with this global initiative, many countries across the globe are committed to decarbonizing their public transportation sector, which significantly contributes to increased greenhouse gas emissions. A promising strategy to achieve this goal is the adoption of electric buses, specifically battery electric buses and fuel cell electric buses. Each technology offers distinct advantages and drawbacks, making the decision-making process complex. This research aims to answer two critical questions: What is the optimal choice for decarbonizing the bus transportation sector—electric battery buses or fuel cell electric buses? And what are the best energy carrier pathways for charging or refueling these buses? We propose a methodological framework based on multi-criteria decision-making to address these questions comprehensively. This framework utilizes the entropy weighting and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) methodologies to rank alternative bus technologies along with energy carrier pathways. The framework evaluates a range of criteria, including economic viability, energy demand, and environmental aspects. To illustrate the framework, we considered Qatar as a case study. Our results indicate that, with respect to economic viability and energy consumption, the operation of battery electric buses is favored over fuel cell electric buses, regardless of the energy pathway utilized during both the energy production and bus operation phases. However, from an environmental perspective, operating both bus alternatives using energy from green sources provides superior performance compared to when these buses are powered by natural gas sources. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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21 pages, 1922 KiB

Open AccessArticle

A Two-Stage Evaluation of China’s New Energy Industrial Policy Package

by Qiao Wang, Shiyun Chen and Hongtao Yi

Sustainability 2024, 16(18), 8264; https://doi.org/10.3390/su16188264 - 23 Sep 2024

Viewed by 781

Abstract

Energy structural transformation plays a strategically important role in achieving the dual-carbon reduction goals. Among the various approaches to carbon reduction, the Chinese government regards the growth of the new energy industry as an essential means. Considering that the government policy support determines [...] Read more.

Energy structural transformation plays a strategically important role in achieving the dual-carbon reduction goals. Among the various approaches to carbon reduction, the Chinese government regards the growth of the new energy industry as an essential means. Considering that the government policy support determines the long-term growth of the new energy industry, how to improve and optimize the policy support system has always been the core issue. Based on the fact that policy evaluation is a prerequisite, and the new energy industrial development requires the government to promote solutions in the form of a policy package rather than just individual policies, we investigate whether the implementation of the new energy industry policy package (NEIPP) is effective through an empirical case study of Shanghai. A two-stage evaluation method, which integrates the content analysis method (CAM) and synthetic control method (SCM), was used to empirically evaluate the actual effect of the NEIPP. At Stage One, four policy goals were summarized. SCM was used to identify the pure multi-effect of the NEIPP. The results showed that the NEIPP had a significant positive effect on green economic growth and industrial structure, while having a negative effect on carbon emissions. The NEIPP had no impact on the promotion of technological innovation. Several policy implications were drawn from this study. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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22 pages, 635 KiB

Open AccessArticle

Cold Chain Distribution Route Optimization for Mixed Vehicle Types of Fresh Agricultural Products Considering Carbon Emissions: A Study Based on a Survey in China

by Shuangli Pan, Huiyu Liao, Guijun Zheng, Qian Huang and Maozhuo Shan

Sustainability 2024, 16(18), 8207; https://doi.org/10.3390/su16188207 - 20 Sep 2024

Viewed by 800

Abstract

With the improvement of people’s living standards and the widening of circulation channels, the demand for fresh agricultural products continues to increase. The increase in demand will lead to an increase in delivery vehicles, costs, and carbon emissions, among which the increase in [...] Read more.

With the improvement of people’s living standards and the widening of circulation channels, the demand for fresh agricultural products continues to increase. The increase in demand will lead to an increase in delivery vehicles, costs, and carbon emissions, among which the increase in carbon emissions will aggravate pollution and is not conducive to sustainable development. Therefore, it is very important to balance economic and environmental benefits in the distribution of fresh agricultural products. Based on the analysis of the distribution characteristics of fresh agricultural products, this paper studies the optimization of the cold chain distribution route of fresh agricultural products considering carbon emission. Firstly, the cold chain distribution route planning of fresh agricultural products was investigated and analyzed by the interview method, and the basis for establishing the model objective and constraint conditions was obtained. Then, taking the minimum total cost including carbon emission cost as the optimization goal, the cold chain distribution route optimization model for mixed vehicle types is established considering electric refrigerated vehicles, gasoline refrigerated vehicles, and so on. Genetic algorithm was used to solve the model, and MATLAB2018b was used to substitute specific case data for simulation analysis. The analysis results show that increasing the consideration of carbon emission and mixed vehicle types in the distribution route of fresh agricultural products can not only reduce the distribution cost but also reduce the carbon emission. To some extent, the research content of this paper can provide a reference for enterprises in planning cold chain distribution routes of fresh agricultural products. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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24 pages, 4384 KiB

Open AccessArticle

Optimisation of Process Parameters to Maximise the Oil Yield from Pyrolysis of Mixed Waste Plastics

by Farjana Faisal, Mohammad Golam Rasul, Ashfaque Ahmed Chowdhury and Md Islam Jahirul

Sustainability 2024, 16(7), 2619; https://doi.org/10.3390/su16072619 - 22 Mar 2024

Cited by 1 | Viewed by 2251

Abstract

The study sought to optimise process parameters of thermal pyrolysis of mixed waste plastic (MWP) to maximise pyrolytic oil yield. High-density polyethylene (HDPE), polypropylene (PP), and polystyrene (PS) were used as feedstocks for pyrolysis. Response surface methodology (RSM) and Box–Behnken design (BBD) were [...] Read more.

The study sought to optimise process parameters of thermal pyrolysis of mixed waste plastic (MWP) to maximise pyrolytic oil yield. High-density polyethylene (HDPE), polypropylene (PP), and polystyrene (PS) were used as feedstocks for pyrolysis. Response surface methodology (RSM) and Box–Behnken design (BBD) were used to optimise the pyrolysis process. The optimisation was carried out by varying three independent variables, namely, reaction temperature (460–540 °C), residence time (30–150 min), and size of MWP feedstock (5–45 mm), to increase the liquid oil yield. A BBD matrix was used to generate the design of the experiments, and 15 experiments were conducted. The highest liquid oil yield of 75.14 wt% was obtained by optimising the operating parameters, which were a reaction temperature of 535.96 °C, a reaction time of 150 min, and a feedstock particle size of 23.99 mm. A model was developed to determine the relationships among the independent variables, and analysis of variance (ANOVA) was used to investigate their impact on maximising oil yield. ANOVA results showed that the temperature and residence time had the maximum impact on oil yield, followed by feedstock size. Physicochemical analysis of the properties of the plastic pyrolytic oil (PPO) revealed that the crude PPO obtained from the MWP had higher water (0.125 wt%) and sulfur content (5.12 mg/kg) and lower flash point (<20 °C) and cetane index (32), which makes it unsuitable for use as an automobile fuel. However, these issues can be resolved by upgrading the PPO using different posttreatment techniques, such as distillation and hydrotreatment. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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19 pages, 3721 KiB

Open AccessArticle

System Design, Optimization and 2nd Law Analysis of a 100 MWe Double Reheat s-CO₂ Power Plant at Full Load and Part Loads

by Sreekanth Manavalla, Feroskhan M., Joseph Daniel, Sivakumar Ramasamy, T. M. Yunus Khan, Rahmath Ulla Baig, Naif Almakayeel and Bhanu Kiran Voddin Tirumalapur

Sustainability 2023, 15(20), 14677; https://doi.org/10.3390/su152014677 - 10 Oct 2023

Viewed by 1071

Abstract

Super-critical Carbon dioxide (s-CO₂) power plants are considered to be efficient and environmentally friendly compared to the traditional Rankine cycle-based steam power plants and Brayton cycle-based gas turbine power plants. In this work, the system design of a coal-fired 100 MWe [...] Read more.

Super-critical Carbon dioxide (s-CO₂) power plants are considered to be efficient and environmentally friendly compared to the traditional Rankine cycle-based steam power plants and Brayton cycle-based gas turbine power plants. In this work, the system design of a coal-fired 100 MWe double reheat s-CO₂ power plant is presented. The system is also optimized for efficiency with turbine inlet pressures and the recompression ratio as the variables. The components needed, mass flow rates of various streams and their pressures at various locations in the system have been established. The plant has been studied based on 1st and 2nd laws at full load and at part loads of 80%, 60% and 40%. Operating parameters such as mass flow rate, pressure and temperature have considerably changed in comparison to full load operation. It was also observed that the 1st law efficiency is 53.96%, 53.93%, 52.63% and 50% while the 2nd law efficiency is 51.88%, 51.86%, 50.61% and 48.1% at 100%, 80%, 60% and 40% loads, respectively. The power plant demonstrated good performance even at part loads, especially at 80% load, while the performance deteriorated at lower loads. At full load, the highest amount of exergy destruction is found in the main heater (36.6%) and re-heaters (23.2% and 19.6%) followed by the high-temperature recuperator (5.7%) and cooler (4.1%). Similar trends were observed for the part load operation. It has been found that the recompression ratio should be kept high (>0.5) at lower loads in order to match the performance at higher loads. Combustion and heat exchange due to finite temperature differences are the main causes of exergy destruction, followed by pressure drop. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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13 pages, 2006 KiB

Open AccessArticle

Optimal Parameter Determination of Membrane Bioreactor to Boost Biohydrogen Production-Based Integration of ANFIS Modeling and Honey Badger Algorithm

by Hegazy Rezk, A. G. Olabi, Mohammad Ali Abdelkareem, Abdul Hai Alami and Enas Taha Sayed

Sustainability 2023, 15(2), 1589; https://doi.org/10.3390/su15021589 - 13 Jan 2023

Cited by 6 | Viewed by 1680

Abstract

Hydrogen is a new promising energy source. Three operating parameters, including inlet gas flow rate, pH and impeller speed, mainly determine the biohydrogen production from membrane bioreactor. The work aims to boost biohydrogen production by determining the optimal values of the control parameters. [...] Read more.

Hydrogen is a new promising energy source. Three operating parameters, including inlet gas flow rate, pH and impeller speed, mainly determine the biohydrogen production from membrane bioreactor. The work aims to boost biohydrogen production by determining the optimal values of the control parameters. The proposed methodology contains two parts: modeling and parameter estimation. A robust ANIFS model to simulate a membrane bioreactor has been constructed for the modeling stage. Compared with RMS, thanks to ANFIS, the RMSE decreased from 2.89 using ANOVA to 0.0183 using ANFIS. Capturing the proper correlation between the inputs and output of the membrane bioreactor process system encourages the constructed ANFIS model to predict the output performance exactly. Then, the optimal operating parameters were identified using the honey badger algorithm. During the optimization process, inlet gas flow rate, pH and impeller speed are used as decision variables, whereas the biohydrogen production is the objective function required to be maximum. The integration between ANFIS and HBA boosted the hydrogen production yield from 23.8 L to 25.52 L, increasing by 7.22%. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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22 pages, 11976 KiB

Open AccessArticle

A Comparison of Different Renewable-Based DC Microgrid Energy Management Strategies for Commercial Buildings Applications

by Hegazy Rezk, Rania M. Ghoniem, Seydali Ferahtia, Ahmed Fathy, Mohamed M. Ghoniem and Reem Alkanhel

Sustainability 2022, 14(24), 16656; https://doi.org/10.3390/su142416656 - 12 Dec 2022

Cited by 3 | Viewed by 1787

Abstract

DC microgrid systems allow commercial buildings to use locally generated energy and achieve an optimal economy efficiently. Economical and eco-friendly energy can be achieved by employing renewable energy sources. However, additional controllable sources, such as fuel cells, are required because of their reduced [...] Read more.

DC microgrid systems allow commercial buildings to use locally generated energy and achieve an optimal economy efficiently. Economical and eco-friendly energy can be achieved by employing renewable energy sources. However, additional controllable sources, such as fuel cells, are required because of their reduced efficiency and fluctuated nature. This microgrid can use energy storage systems to supply transient power and enhance stability. The functioning of the microgrid and its efficiency are related to the implemented energy management strategy. In this paper, a comparison of several reported energy management strategies is fulfilled. The considered EMSs include the fuzzy logic control (FLC) strategy, the state machine control (SMC) strategy, the equivalent consumption minimization strategy (ECMS), and external energy maximization strategy (EEMS). These strategies are compared in terms of power-saving, system efficiency, and power quality specifications. The overall results confirm the ability of EEMS (high efficiency of 84.91% and economic power-saving 6.11%) and SMC (efficiency of 84.18% with high power-saving 5.07%) for stationary applications, such as building commercial applications. These strategies provide other advantages, which are discussed in detail in this paper. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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25 pages, 9868 KiB

Open AccessArticle

A New Fractional-Order Load Frequency Control for Multi-Renewable Energy Interconnected Plants Using Skill Optimization Algorithm

by Ahmed Fathy, Hegazy Rezk, Seydali Ferahtia, Rania M. Ghoniem, Reem Alkanhel and Mohamed M. Ghoniem

Sustainability 2022, 14(22), 14999; https://doi.org/10.3390/su142214999 - 13 Nov 2022

Cited by 17 | Viewed by 2160

Abstract

Connection between electric power networks is essential to cover any deficit in the generation of power from any of them. The exchange powers of the plants during load disturbance should not be violated beyond their specified values. This can be achieved by installing [...] Read more.

Connection between electric power networks is essential to cover any deficit in the generation of power from any of them. The exchange powers of the plants during load disturbance should not be violated beyond their specified values. This can be achieved by installing load frequency control (LFC); therefore, this paper proposes a new metaheuristic-based approach using a skill optimization algorithm (SOA) to design a fractional-order proportional integral derivative (FOPID)-LFC approach with multi-interconnected systems. The target is minimizing the integral time absolute error (ITAE) of frequency and exchange power violations. Two power systems are investigated. The first one has two connected plants of photovoltaic (PV) and thermal units. The second system contains four plants, namely, PV, wind turbine, and two thermal plants, with governor dead-band (GDB) and generation rate constraints (GRC). Different load disturbances are analyzed in both considered systems. Extensive comparisons to the use of chef-based optimization algorithm (CBOA), jumping spider optimization algorithm (JSOA), Bonobo optimization (BO), Tasmanian devil optimization (TDO), and Atomic orbital search (AOS) are conducted. Moreover, statistical tests of Friedman ANOVA table, Wilcoxon rank test, Friedman rank test, and Kruskal Wallis test are implemented. Regarding the two interconnected areas, the proposed SOA achieved the minimum fitness value of 1.8779 pu during 10% disturbance on thermal plant. In addition, it outperformed all other approaches in the case of 1% disturbance on the first area as it achieved ITAE of 0.0327 pu. The obtained results proved the competence and reliability of the proposed SOA in designing an efficient FOPID-LFC in multi-interconnected power systems with multiple sources. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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13 pages, 3058 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Growth Rate and Biomass Productivity of Scenedesmus quadricauda and Chlorella vulgaris under Different LED Wavelengths and Photoperiods

by Ruth Chinyere Anyanwu, Cristina Rodriguez, Andy Durrant and Abdul Ghani Olabi

Sustainability 2022, 14(10), 6108; https://doi.org/10.3390/su14106108 - 17 May 2022

Cited by 16 | Viewed by 5513

Abstract

Cultivation has been identified as an essential stage for biofuel production. This research has examined two important parameters for the industrial production of microalgae, namely microalgae growth rate and biomass productivity. Chlorella vulgaris and Scenedesmusquadricauda were cultivated using a closed photobioreactor (PBR). [...] Read more.

Cultivation has been identified as an essential stage for biofuel production. This research has examined two important parameters for the industrial production of microalgae, namely microalgae growth rate and biomass productivity. Chlorella vulgaris and Scenedesmusquadricauda were cultivated using a closed photobioreactor (PBR). A novel approach for cultivation and energy input reduction was developed by incorporating periods of darkness during cultivation, as would happen in nature. Three different LED light sources (white, red, and green) were used to determine the conditions that result in the highest growth rate and biomass productivity. C. vulgaris and S. quadricauda responded differently to lighting conditions. It was found that, depending on the LED source and light period, different growth rates and biomass productivities were obtained. Overall, experimental results obtained in this study indicated that a white LED is more effective than green or red LEDs in increasing microalgae growth rate and biomass productivity. A maximum growth rate of 3.41 d⁻¹ and a biomass productivity of 2.369 g L⁻¹d⁻¹ were achieved for S.quadricauda under a 19 h period of white light alternating with 5 h of darkness. For C. vulgaris the maximum growth rate of 3.49 d⁻¹ and maximum biomass productivity of 2.438 g L⁻¹d⁻¹ were achieved by continuous white light with no darkness period. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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27 pages, 13580 KiB

Open AccessArticle

Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads

by Amal A. Mohamed, Salah Kamel, Ali Selim, Tahir Khurshaid and Sang-Bong Rhee

Sustainability 2021, 13(8), 4447; https://doi.org/10.3390/su13084447 - 16 Apr 2021

Cited by 11 | Viewed by 1813

Abstract

The optimal location of renewable distributed generations (DGs) into a radial distribution system (RDS) has attracted major concerns from power system researchers in the present years. The main target of DG integration is to improve the overall system performance by minimizing power losses [...] Read more.

The optimal location of renewable distributed generations (DGs) into a radial distribution system (RDS) has attracted major concerns from power system researchers in the present years. The main target of DG integration is to improve the overall system performance by minimizing power losses and improving the voltage profile. Hence, this paper proposed a hybrid approach between an analytical and metaheuristic optimization technique for the optimal allocation of DG in RDS, considering different types of load. A simple analytical technique was developed in order to determine the sizes of different and multiple DGs, and a new efficient metaheuristic technique known as the Salp Swarm Algorithm (SSA) was suggested in order to choose the best buses in the system, proportionate to the sizes determined by the analytical technique, in order to obtain the minimum losses and the best voltage profile. To verify the power of the proposed hybrid technique on the incorporation of the DGs in RDS, it was applied to different types of static loads; constant power (CP), constant impedance (CZ), and constant current (CI). The performance of the proposed algorithm was validated using two standards RDSs—IEEE 33-bus and IEEE 69-bus systems—and was compared with other optimization techniques. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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Review

Jump to: Research

22 pages, 4742 KiB

Open AccessReview

Wind Energy Contribution to the Sustainable Development Goals: Case Study on London Array

by A. G. Olabi, Khaled Obaideen, Mohammad Ali Abdelkareem, Maryam Nooman AlMallahi, Nabila Shehata, Abdul Hai Alami, Ayman Mdallal, Asma Ali Murah Hassan and Enas Taha Sayed

Sustainability 2023, 15(5), 4641; https://doi.org/10.3390/su15054641 - 6 Mar 2023

Cited by 47 | Viewed by 23219

Abstract

Clean and safe energy sources are essential for the long-term growth of society. Wind energy is rapidly expanding and contributes to many countries’ efforts to decrease greenhouse gas emissions. In terms of sustainable development goals (SDGs), renewable energy development promotes energy security while [...] Read more.

Clean and safe energy sources are essential for the long-term growth of society. Wind energy is rapidly expanding and contributes to many countries’ efforts to decrease greenhouse gas emissions. In terms of sustainable development goals (SDGs), renewable energy development promotes energy security while also facilitating community development and environmental conservation on a global scale. In this context, the current article aims to investigate wind energy’s role within the SDGs. Furthermore, the present study highlights the role of the London Array wind farm in achieving the SDGs. Indeed, deploying clean and economical energy sources in place of conventional fossil fuel power plants provides vital insights into environmental impacts. The London Array operation is saving approximately 1 million tons of carbon dioxide (CO₂) equivalent. Furthermore, the London Array contributes to the achievement of multiple SDGs, including SDG 8: decent employment and economic growth; SDG 9: industry, innovation, and infrastructure; SDG 11: sustainable cities and communities; and SDG 15: life on land. To enhance the London Array’s contribution to the SDGs, a total of 77 indicators (key performance indicators) were proposed and compared to the current measurements that have been carried out. The results showed that the London Array used most of the suggested indicators without classifying them from the SDGs’ perspective. The proposed indicators will help cut operation costs, mitigate climate change and environmental damage, improve employee engagement and morale, reduce learning gaps, set goals and plans, and use resources efficiently. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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34 pages, 12871 KiB

Open AccessReview

Solar Energy: Applications, Trends Analysis, Bibliometric Analysis and Research Contribution to Sustainable Development Goals (SDGs)

by Khaled Obaideen, Abdul Ghani Olabi, Yaser Al Swailmeen, Nabila Shehata, Mohammad Ali Abdelkareem, Abdul Hai Alami, Cristina Rodriguez and Enas Taha Sayed

Sustainability 2023, 15(2), 1418; https://doi.org/10.3390/su15021418 - 11 Jan 2023

Cited by 72 | Viewed by 10075

Abstract

Over the past decade, energy demand has witnessed a drastic increase, mainly due to huge development in the industry sector and growing populations. This has led to the global utilization of renewable energy resources and technologies to meet this high demand, as fossil [...] Read more.

Over the past decade, energy demand has witnessed a drastic increase, mainly due to huge development in the industry sector and growing populations. This has led to the global utilization of renewable energy resources and technologies to meet this high demand, as fossil fuels are bound to end and are causing harm to the environment. Solar PV (photovoltaic) systems are a renewable energy technology that allows the utilization of solar energy directly from the sun to meet electricity demands. Solar PV has the potential to create a reliable, clean and stable energy systems for the future. This paper discusses the different types and generations of solar PV technologies available, as well as several important applications of solar PV systems, which are “Large-Scale Solar PV”, “Residential Solar PV”, “Green Hydrogen”, “Water Desalination” and “Transportation”. This paper also provides research on the number of solar papers and their applications that relate to the Sustainable Development Goals (SDGs) in the years between 2011 and 2021. A total of 126,513 papers were analyzed. The results show that 72% of these papers are within SDG 7: Affordable and Clean Energy. This shows that there is a lack of research in solar energy regarding the SDGs, especially SDG 1: No Poverty, SDG 4: Quality Education, SDG 5: Gender Equality, SDG 9: Industry, Innovation and Infrastructure, SDG 10: Reduced Inequality and SDG 16: Peace, Justice and Strong Institutions. More research is needed in these fields to create a sustainable world with solar PV technologies. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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30 pages, 2097 KiB

Open AccessReview

Sustainable Approaches to Microalgal Pre-Treatment Techniques for Biodiesel Production: A Review

by Amarnath Krishnamoorthy, Cristina Rodriguez and Andy Durrant

Sustainability 2022, 14(16), 9953; https://doi.org/10.3390/su14169953 - 11 Aug 2022

Cited by 19 | Viewed by 3790

Abstract

Microalgae are a potential source of numerous nutritional products and biofuels. Their applications range from the food industry to the medical and fuel sectors and beyond. Recently, the conversion of biomass into biodiesel and other biofuels has received a lot of positive attention [...] Read more.

Microalgae are a potential source of numerous nutritional products and biofuels. Their applications range from the food industry to the medical and fuel sectors and beyond. Recently, the conversion of biomass into biodiesel and other biofuels has received a lot of positive attention within the fossil fuel arena. The objective of biorefineries is to focus on utilising biomass efficiently to produce quality biofuel products by minimising the input as well as to reduce the use of chemical or thermal pre-treatments. Pre-treatment processes in biorefineries involve cell disruption to obtain lipids. Cell disruption is a crucial part of bioconversion, as the structure and nature of microalgae cell walls are complex. In recent years, many research papers have shown various pre-treatment methods and their advantages. The objective of this paper was to provide a comprehensive in-depth review of various recent pre-treatment techniques that have been used for microalgal biodiesel production and to discuss their advantages, disadvantages, and how they are applied in algal biorefineries. Full article

(This article belongs to the Special Issue Renewable Energy and Utility System Optimization for Sustainable Industries)

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