Sustainability

Research

14 pages, 3778 KiB

Open AccessArticle

Performance of Generator Translation and Rotation on Stroke Length Drive of the Two-Rod Mechanism in Renewable Energy Power Plant

by Hendra Hendra, Dhimas Satria, Hernadewita Hernadewita, Yozerizal Yozerizal, Frengki Hardian and Ahmed M. Galal

Sustainability 2023, 15(7), 5663; https://doi.org/10.3390/su15075663 - 23 Mar 2023

Viewed by 1727

Abstract

Generators are the main components in renewable energy power plants, especially in plants powered by ocean waves. The generator consists of two components of translational and rotational motion. Generators of translational and rotational motion can produce electric power from renewable energy sources such [...] Read more.

Generators are the main components in renewable energy power plants, especially in plants powered by ocean waves. The generator consists of two components of translational and rotational motion. Generators of translational and rotational motion can produce electric power from renewable energy sources such as water, wind, sea waves, biomass, and others. The voltage and electric power are the performance values of the translational and rotational generators which are affected by the type of magnet, the number of coil windings, the distance between the magnet and the coil winding and rotation, the geometry of the drive components, the type of drive, the length of the generator drive stroke, and so on. The types of translational and rotational generator drives can be found in the use of pneumatic motion mechanisms, two-rod motion, crankshaft motion, and others. A common problem in older power plants was that generator components were heavy, easy to break, less rigid, and had low rotation speed. Therefore, to overcome this problem, a generator with a two-rod mechanism is used in this research. In this paper, the generator drive step using a two-rod motion mechanism is used to run the generator. The length of the piston stroke is used to determine the performance of the generator, set at a length of 170–270 mm. The results show that the generator with two-rod motion mechanism rotating at 100–250 rpm can produce 30.9–55 volts at a frequency of 6.9–63.7 Hz with a maximum power of 0.377 w. By setting a piston stroke length of 170 mm, we obtained a rotation of 100–191 rpm and an electrical voltage of 30.9−35 volts. At a piston stroke length of 230 rpm, a rotation of 78–172 rpm is obtained with an electrical voltage of 47.7–55.5 volts. A piston stroke length of 270 mm produces a rotation of 172–256.5 rpm with a mains voltage of 39.9–55.5 volts. Testing the generators of translational and rotational motion using a two-rod motion mechanism in series and parallel with a stroke length of 270 mm produced a rotation from 179.2 to 242.3 rpm and an electric voltage from 57.4 to 79.5 volts and become constant at 35.6 volts by using a parallel mechanism. These results show that the generator translation and rotation motion can produce electric power by using renewable energy resources. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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13 pages, 3504 KiB

Open AccessArticle

Neural Network Based Approach for Steady-State Stability Assessment of Power Systems

by Tayo Uthman Badrudeen, Nnamdi I. Nwulu and Saheed Lekan Gbadamosi

Sustainability 2023, 15(2), 1667; https://doi.org/10.3390/su15021667 - 15 Jan 2023

Cited by 14 | Viewed by 3201

Abstract

The quest for an intelligence compliance system to solve power stability problems in real-time with high predictive accuracy, and efficiency has led to the discovery of deep learning (DL) techniques. This paper investigates the potency of several artificial neural network (ANN) techniques in [...] Read more.

The quest for an intelligence compliance system to solve power stability problems in real-time with high predictive accuracy, and efficiency has led to the discovery of deep learning (DL) techniques. This paper investigates the potency of several artificial neural network (ANN) techniques in assessing the steady-state stability of a power system. The new voltage stability pointer (NVSP) was employed to parameterize and reduce the input data to the neural network algorithms to predict the proximity of power systems to voltage instability. In this study, we consider five neural network algorithms viz. feedforward neural network (FFNN), cascade-forward neural network (CFNN), layer recurrent neural network (LRNN), linear layer neural network (LLNN), and Elman neural network (ENN). The evaluation is based on the predictability and accuracy of these techniques for dynamic stability in power systems. The neural network algorithms were trained to mimic the NVSP dataset using a Levenberg-Marquardt (LM) model. Similarly, the performance analyses of the neural network techniques were deduced from the regression learner algorithm (RLA) using a root-mean-squared error (rmse) and response plot graph. The effectiveness of these NN algorithms was demonstrated on the IEEE 30-bus system and the Nigerian power system. The simulation results show that the FFNN and the CFNN possess a relatively better performance in terms of accuracy and efficiency for the considered power networks. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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15 pages, 284 KiB

Open AccessArticle

Digital Transformation, Green Technology Innovation and Enterprise Financial Performance: Empirical Evidence from the Textual Analysis of the Annual Reports of Listed Renewable Energy Enterprises in China

by Yangjun Ren and Botang Li

Sustainability 2023, 15(1), 712; https://doi.org/10.3390/su15010712 - 30 Dec 2022

Cited by 22 | Viewed by 5177

Abstract

Digital transformation in renewable energy enterprises offers critical opportunities for China’s green orientation and sustainable growth. Based on a statistical data of Chinese A-share listed renewable energy companies, we explore the effects of digital transformation on a company’s financial performance and the mediating [...] Read more.

Digital transformation in renewable energy enterprises offers critical opportunities for China’s green orientation and sustainable growth. Based on a statistical data of Chinese A-share listed renewable energy companies, we explore the effects of digital transformation on a company’s financial performance and the mediating role of green technology innovation. The findings indicate that there is a driving effect of digital transformation on renewable energy companies’ financial performance. Our results remain valid after a series of robustness tests. Furthermore, a heterogeneous analysis indicates that enhancing digital transformation only positively affects the financial performance of state-owned firms and firms in the eastern area, and the driving effect of digital transformation is greater for large firms. In addition, green technology innovation plays a complete mediating role in digital transformation’s impact on renewable energy enterprises’ financial performance. Specifically, when a renewable energy company has digital transformation, it has better green technology innovation leading to better financial performance. Our results provide vital implications for promoting the effectiveness of digital transformation in the development of renewable energy enterprises. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

22 pages, 10416 KiB

Open AccessArticle

Power System Stability Improvement of FACTS Controller and PSS Design: A Time-Delay Approach

by Preeti Ranjan Sahu, Rajesh Kumar Lenka, Rajendra Kumar Khadanga, Prakash Kumar Hota, Sidhartha Panda and Taha Selim Ustun

Sustainability 2022, 14(21), 14649; https://doi.org/10.3390/su142114649 - 7 Nov 2022

Cited by 16 | Viewed by 2993

Abstract

The existence of low-frequency oscillations in power systems is the cause of power angle instability, limiting the transmission of maximum tie-line power. One of the effective ways to improve the stability limits is by installing a power system stabilizer and supplementary excitation control [...] Read more.

The existence of low-frequency oscillations in power systems is the cause of power angle instability, limiting the transmission of maximum tie-line power. One of the effective ways to improve the stability limits is by installing a power system stabilizer and supplementary excitation control to augment with an automatic voltage regulator (AVR) supplemental feedback stabilizing signal. This paper proposes a new strategy for simultaneously tuning the power system stabilizer (PSS) and FACTS controller, considering time delays. The design of the proposed controller is modeled as an optimization problem, and the parameters of the controller are optimized through the grasshopper optimization algorithm (GOA). The suggested controller’s efficacy is evaluated for both single-machine infinite bus systems and multi-machine power systems under various disturbances. It also investigated the performance of the proposed controller with variations in signal transmission delays. The results obtained from GOA optimized proposed controller are compared with those obtained from the differential evolution algorithm, genetic algorithm, and whale optimization algorithm. In this context, the proposed GOA optimized controller reduced the objective function value by 16.32%, 14.56%, and 13.72%, respectively, in the SMIB system and 1.41%, 9.98%, and 13.31%, respectively, for the multi-machine system compared with the recently published WOA, and the well-established GA and DE. Further, the proposed controller is found to be stable and effectively increases stability even under small disturbances. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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22 pages, 9604 KiB

Open AccessArticle

Design and Implementation of a Real-Time Smart Home Management System Considering Energy Saving

by Mahmoud H. Elkholy, Tomonobu Senjyu, Mohammed Elsayed Lotfy, Abdelrahman Elgarhy, Nehad S. Ali and Tamer S. Gaafar

Sustainability 2022, 14(21), 13840; https://doi.org/10.3390/su142113840 - 25 Oct 2022

Cited by 23 | Viewed by 13147

Abstract

One of the most challenging problems related to the operation of smart microgrids is the optimal home energy management scheme with multiple and conflicting objectives. Moreover, there is a noticeable increase in homes equipped with renewable energy sources (RESs), where the coordination of [...] Read more.

One of the most challenging problems related to the operation of smart microgrids is the optimal home energy management scheme with multiple and conflicting objectives. Moreover, there is a noticeable increase in homes equipped with renewable energy sources (RESs), where the coordination of loads and generation can achieve extra savings and minimize peak loads. In this paper, a solar-powered smart home with optimal energy management is designed in an affordable and secure manner, allowing the owner to control the home from remote and local sites using their smartphones and PCs. The Raspberry Pi 4 B is used as the brain of the proposed smart home automation management system (HAMS). It is used to collect the data from the existing sensors and store them, and then take the decision. The home is monitored using a graphical interface that monitors room temperature, humidity, smoke, and lighting through a set of sensors, as well as PIR sensors to monitor the people movement. This action enables remote control of all home appliances in a safe and emission-free manner. This target is reached using Cayenne, which is an IoT platform, in addition to building some codes related to some appliances and sensors not supported in Cayenne from scratch. Convenience for people with disabilities is considered by using the Amazon Echo Dot (Alexa) to control home appliances and the charging point by voice, implementing the associated code for connecting the Raspberry pi with Alexa from scratch, and simulating the system on LabVIEW. To reach the optimal operation and reduce the operating costs, an optimization framework for the home energy management system (HEMS) is proposed. The operating costs for the day amounted to approximately 16.039 €. There is a decrease in the operating costs by about 23.13%. The consumption decreased after using the smart HAMS by 18.161 kWh. The results of the optimization also show that the least area that can be used to install solar panels to produce the desired energy with the lowest cost is about 118.1039 m², which is about 23.62% of the total surface area of the home in which the study was conducted. The obtained results prove the effectiveness of the proposed system in terms of automation, security, safety, and low operating costs. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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22 pages, 5691 KiB

Open AccessArticle

Converting Offshore Oil and Gas Infrastructures into Renewable Energy Generation Plants: An Economic and Technical Analysis of the Decommissioning Delay in the Brazilian Case

by Jime Braga, Thauan Santos, Milad Shadman, Corbiniano Silva, Luiz Filipe Assis Tavares and Segen Estefen

Sustainability 2022, 14(21), 13783; https://doi.org/10.3390/su142113783 - 24 Oct 2022

Cited by 8 | Viewed by 5736

Abstract

The offshore harnessing of oil and gas resources is made possible by massive infrastructures installed at sea. At the end-of-life stage, in the absence of new uses for offshore installations, decommissioning proceedings usually take place, requiring the removal and final disposal of all [...] Read more.

The offshore harnessing of oil and gas resources is made possible by massive infrastructures installed at sea. At the end-of-life stage, in the absence of new uses for offshore installations, decommissioning proceedings usually take place, requiring the removal and final disposal of all materials. In Brazilian waters, decommissioning is hampered by high costs. The offshore wind-power sector has arisen as a new clean power source, in line with worldwide de-carbonization initiatives. In this context, we propose an innovative approach suggesting offshore wind power projects as an alternative to the removal and final disposal of infrastructures, a potential solution to Brazilian offshore decommissioning. In this article we report on the assessment of structures at the end of their lifecycle along with decommissioning cost estimation. Then, we explore wind turbine installation viability along the Brazilian coast and estimate the levelized cost of energy for each wind turbine. Finally, the results allow us to conduct a critical analysis of customary decommissioning versus the repurposing of infrastructures as offshore wind power project sites in two scenarios involving site repurposing. Our main results indicate that the CapEx discount rate of wind power projects offsetting decommissioning is considerable, as are the benefits of delaying decommissioning in terms of reduced carbon emissions and the social effects of increased local employment rates, through the repurposing of offshore oil and gas infrastructures. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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20 pages, 5253 KiB

Open AccessArticle

Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique

by Mahmoud M. Gamil, Soichirou Ueda, Akito Nakadomari, Keifa Vamba Konneh, Tomonobu Senjyu, Ashraf M. Hemeida and Mohammed Elsayed Lotfy

Sustainability 2022, 14(21), 13709; https://doi.org/10.3390/su142113709 - 22 Oct 2022

Cited by 3 | Viewed by 2179

Abstract

Microgrid optimization is one of the most promising solutions to power system issues and new city electrification. This paper presents a strategy for optimal power scheduling of a residential microgrid depending on renewable generating sources and hydrogen power. Five scenarios of the microgrid [...] Read more.

Microgrid optimization is one of the most promising solutions to power system issues and new city electrification. This paper presents a strategy for optimal power scheduling of a residential microgrid depending on renewable generating sources and hydrogen power. Five scenarios of the microgrid are introduced to show the effect of using biomass energy and a seawater electrolyzer on microgrid cost and CO

_{2}

emissions. Time of use demand response is applied to reshape the electric load demand and decrease the dependence on grid power. The obtained results from the multi-objective optimization verify that biomass has a significant role in minimizing the cost and CO

_{2}

emissions; the cost is decreased by 37.9% when comparing scenarios with and without biomass. Besides, the FC integration with seawater electrolyzer and tanks reduces the microgrid emissions by around 40%. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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23 pages, 9247 KiB

Open AccessArticle

Modeling and Simulation of Multipumping Photovoltaic Irrigation Systems

by Javier R. Ledesma, Rita H. Almeida and Luis Narvarte

Sustainability 2022, 14(15), 9318; https://doi.org/10.3390/su14159318 - 29 Jul 2022

Cited by 3 | Viewed by 1810

Abstract

The growing market of large-power photovoltaic irrigation systems (PVISs)—made of systems with different and several motor pumps working in parallel—needs simulation tools capable to estimate their energy and water productivity. The objective of this paper is to present the simulation models developed for [...] Read more.

The growing market of large-power photovoltaic irrigation systems (PVISs)—made of systems with different and several motor pumps working in parallel—needs simulation tools capable to estimate their energy and water productivity. The objective of this paper is to present the simulation models developed for parallel multipump PVISs fed by a single PV generator. These models seek to maximize the instantaneous water flow rate according to the available PV power and were developed for the typical configurations of large-power irrigation facilities. The models present some advantages when compared with the current state of the art (in which a single motor pump connected to a 1/N fraction of the PV generator is simulated and the result is multiplied by N): in the case of negligible hydraulic friction losses, the use of the multipump model shows gains with respect to the state of the art; in the case of appreciable friction losses, the current state of the art overestimates the productivity of the systems. Then, the ability of these models to compare different multipump designs is shown: two groups of pumps working at variable frequencies show better performance than a group working at a variable frequency and a group at a nominal frequency—an 8% increase in the water pumped is seen. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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19 pages, 1367 KiB

Open AccessArticle

A Yearly Based Multiobjective Park-and-Ride Control Approach Simulation Using Photovoltaic and Battery Energy Storage Systems: Fuxin, China Case Study

by Liu Pai and Tomonobu Senjyu

Sustainability 2022, 14(14), 8655; https://doi.org/10.3390/su14148655 - 15 Jul 2022

Cited by 3 | Viewed by 2068

Abstract

This paper presents a modern yearly based park-and-ride management scheme. The electric vehicles’ owners are encouraged to keep their cars away from the crowded areas in cities and use the public facilities such as bus, train, and metro. This action will help the [...] Read more.

This paper presents a modern yearly based park-and-ride management scheme. The electric vehicles’ owners are encouraged to keep their cars away from the crowded areas in cities and use the public facilities such as bus, train, and metro. This action will help the owners to reach their work on time inside these crowded cities. Electric vehicle charging stations are designed to charge 1000 electric vehicles using the proposed park-and-ride control approach. A case study of Fuxin, China is considered. The electric vehicle charging stations demand is met using renewable energy sources, namely photovoltaic and battery energy storage systems. Meeting the load demand and minimizing the total life cycle cost are considered two objective functions to formulate a multiobjective approach. The optimal sizes of the photovoltaic and battery energy storage systems are obtained using a multiobjective genetic algorithm and

ε

-MOGA. The robustness and effectiveness of the proposed control methodology are verified by detailed analysis and comparison using MATLAB^®. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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15 pages, 5340 KiB

Open AccessArticle

An Experimental Demonstration of the Effective Application of Thermal Energy Storage in a Particle-Based CSP System

by Shaker Alaqel, Nader S. Saleh, Rageh S. Saeed, Eldwin Djajadiwinata, Abdulelah Alswaiyd, Muhammad Sarfraz, Hany Al-Ansary, Abdelrahman El-Leathy, Zeyad Al-Suhaibani, Syed Danish, Sheldon Jeter and Zeyad Almutairi

Sustainability 2022, 14(9), 5316; https://doi.org/10.3390/su14095316 - 28 Apr 2022

Cited by 8 | Viewed by 2020

Abstract

Tests were performed at the particle-based CSP test facility at King Saud University to demonstrate a viable solution to overcome the limitations of using molten salt as a working medium in power plants. The KSU facility is composed of a heliostat field, particle [...] Read more.

Tests were performed at the particle-based CSP test facility at King Saud University to demonstrate a viable solution to overcome the limitations of using molten salt as a working medium in power plants. The KSU facility is composed of a heliostat field, particle heating receiver (PHR) at the top of a tower, thermal energy storage (TES) bin, a particle-to-working fluid heat exchanger (PWFHX), power cycle (microturbine), and a particle lift. During pre-commissioning, a substantial portion of the collected solar energy was lost during particle flow through the TES bin. The entrained air is shown to be the primary cause of such heat loss. The results show that the particle temperature at the PHR outlet can reach 720 °C after mitigating the entrained air issue. Additionally, during on-sun testing, a higher temperature of the air exiting the PWFHX than that of the air entering is observed, which indicates the effective solar contribution. Half-hour plant operation through stored energy was demonstrated after heliostat defocusing. Lastly, a sealable TES bin configuration for 1.3 MWe pre-commercial demonstration unit to be built in Saudi Arabia by Saudi Electric Company (SEC) is presented. This design modification has addressed the heat loss, pressure build-up, and contamination issues during TES charging. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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18 pages, 3991 KiB

Open AccessArticle

Robust Design of Power System Stabilizers Using Improved Harris Hawk Optimizer for Interconnected Power System

by Lakhdar Chaib, Abdelghani Choucha, Salem Arif, Hatim G. Zaini, Attia El-Fergany and Sherif S. M. Ghoneim

Sustainability 2021, 13(21), 11776; https://doi.org/10.3390/su132111776 - 25 Oct 2021

Cited by 19 | Viewed by 2286

Abstract

In this present work, a new metaheuristic method called a Harris hawk optimizer (HHO) is applied to achieve the optimal design of a power system stabilizer (PSS) in a multimachine power system. Several well-known chaos maps are incorporated into the HHO to form [...] Read more.

In this present work, a new metaheuristic method called a Harris hawk optimizer (HHO) is applied to achieve the optimal design of a power system stabilizer (PSS) in a multimachine power system. Several well-known chaos maps are incorporated into the HHO to form a chaotic HHO (CHHO) with the aim of improving static operators and enhancing global searching. To assess the CHHO performance, exhaustive comparison studies are made between anticipated chaotic maps in handling unconstrained mathematical problems. At this moment, The PSS design problem over a wide permutation of loading conditions is formulated as a non-linear optimization problem. The adopted objective function defines the damping ratio of lightly damped electromechanical modes subject to a set of constraints. The best PSS parameters are generated by the proposed CHHO. The applicability of the proposed CHHO based on PSS is examined and demonstrated on a 10-generator and 39-bus multimachine power system model. The performance assessments of the CHHO results are realized by a comparative study with HHO through extensive simulations along with further eigenvalue analysis to prove its efficacy. The simulation results convincingly demonstrate the high performance of the proposed CHHO-PSS under various operating scenarios. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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28 pages, 5781 KiB

Open AccessArticle

Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems

by Ahmed Ginidi, Sherif M. Ghoneim, Abdallah Elsayed, Ragab El-Sehiemy, Abdullah Shaheen and Attia El-Fergany

Sustainability 2021, 13(16), 9459; https://doi.org/10.3390/su13169459 - 23 Aug 2021

Cited by 89 | Viewed by 3784

Abstract

The extraction of parameters of solar photovoltaic generating systems is a difficult problem because of the complex nonlinear variables of current-voltage and power-voltage. In this article, a new implementation of the Gorilla Troops Optimization (GTO) technique for parameter extraction of several PV models [...] Read more.

The extraction of parameters of solar photovoltaic generating systems is a difficult problem because of the complex nonlinear variables of current-voltage and power-voltage. In this article, a new implementation of the Gorilla Troops Optimization (GTO) technique for parameter extraction of several PV models is created. GTO is inspired by gorilla group activities in which numerous strategies are imitated, including migration to an unknown area, moving to other gorillas, migration in the direction of a defined site, following the silverback, and competition for adult females. With numerical analyses of the Kyocera KC200GT PV and STM6-40/36 PV modules for the Single Diode (SD) and Double-Diode (DD), the validity of GTO is illustrated. Furthermore, the developed GTO is compared with the outcomes of recent algorithms in 2020, which are Forensic-Based Investigation Optimizer, Equilibrium Optimizer, Jellyfish Search Optimizer, HEAP Optimizer, Marine Predator Algorithm, and an upgraded MPA. GTO’s efficacy and superiority are expressed by calculating the standard deviations of the fitness values, which indicates that the SD and DD models are smaller than 1E−16, and 1E−6, respectively. In addition, validation of GTO for the KC200GT module is demonstrated with diverse irradiations and temperatures where great closeness between the emulated and experimental P-V and I-V curves is achieved under various operating conditions (temperatures and irradiations). Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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15 pages, 2883 KiB

Open AccessArticle

Cost Minimizations and Performance Enhancements of Power Systems Using Spherical Prune Differential Evolution Algorithm Including Modal Analysis

by Sherif S. M. Ghoneim, Mohamed F. Kotb, Hany M. Hasanien, Mosleh M. Alharthi and Attia A. El-Fergany

Sustainability 2021, 13(14), 8113; https://doi.org/10.3390/su13148113 - 20 Jul 2021

Cited by 8 | Viewed by 2281

Abstract

A novel application of the spherical prune differential evolution algorithm (SpDEA) to solve optimal power flow (OPF) problems in electric power systems is presented. The SpDEA has several merits, such as its high convergence speed, low number of parameters to be designed, and [...] Read more.

A novel application of the spherical prune differential evolution algorithm (SpDEA) to solve optimal power flow (OPF) problems in electric power systems is presented. The SpDEA has several merits, such as its high convergence speed, low number of parameters to be designed, and low computational procedures. Four objectives, complete with their relevant operating constraints, are adopted to be optimized simultaneously. Various case studies of multiple objective scenarios are demonstrated under MATLAB environment. Static voltage stability index of lowest/weak bus using modal analysis is incorporated. The results generated by the SpDEA are investigated and compared to standard multi-objective differential evolution (MODE) to prove their viability. The best answer is chosen carefully among trade-off Pareto points by using the technique of fuzzy Pareto solution. Two power system networks such as IEEE 30-bus and 118-bus systems as large-scale optimization problems with 129 design control variables are utilized to point out the effectiveness of the SpDEA. The realized results among many independent runs indicate the robustness of the SpDEA-based approach on OPF methodology in optimizing the defined objectives simultaneously. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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11 pages, 2085 KiB

Open AccessArticle

Influence of Light Intensity and Photoperiod on the Photoautotrophic Growth and Lipid Content of the Microalgae Verrucodesmus verrucosus in a Photobioreactor

by Laura Vélez-Landa, Héctor Ricardo Hernández-De León, Yolanda Del Carmen Pérez-Luna, Sabino Velázquez-Trujillo, Joel Moreira-Acosta, Roberto Berrones-Hernández and Yazmin Sánchez-Roque

Sustainability 2021, 13(12), 6606; https://doi.org/10.3390/su13126606 - 10 Jun 2021

Cited by 17 | Viewed by 3473

Abstract

Microalgal biomass has the capacity to accumulate relatively large quantities of triacylglycerides (TAG) for the conversion of methyl esters of fatty acids (FAME) which has made microalgae a desirable alternative for the production of biofuels. In the present work Verrucodesmus verrucosus was evaluated [...] Read more.

Microalgal biomass has the capacity to accumulate relatively large quantities of triacylglycerides (TAG) for the conversion of methyl esters of fatty acids (FAME) which has made microalgae a desirable alternative for the production of biofuels. In the present work Verrucodesmus verrucosus was evaluated under autotrophic growth conditions as a suitable source of oil for biodiesel production. For this purpose BG11 media were evaluated in three different light:dark photoperiods (L:D; 16:08; 12:12; 24:0) and light intensities (1000, 2000 and 3000 Lux) in a photobioreactor with a capacity of three liters; the evaluation of the microalgal biomass was carried out through the cell count with the use of the Neubauer chamber followed by the evaluation of the kinetic growth parameters. So, the lipid accumulation was determined through the lipid extraction with a Soxhlet system. Finally, the fatty acid profile of the total pooled lipids was determined using gas chromatography-mass spectroscopy (GC-MS). The results demonstrate that the best conditions are a photoperiod of 12 light hours and 12 dark hours with BG11 medium in a 3 L tubular photobioreactor with 0.3% CO₂, 25 °C and 2000 Lux, allowing a lipid accumulation of 50.42%. Palmitic acid is identified as the most abundant fatty acid at 44.90%. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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14 pages, 722 KiB

Open AccessArticle

Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation

by Yongyi Huang, Atsushi Yona, Hiroshi Takahashi, Ashraf Mohamed Hemeida, Paras Mandal, Alexey Mikhaylov, Tomonobu Senjyu and Mohammed Elsayed Lotfy

Sustainability 2021, 13(11), 6163; https://doi.org/10.3390/su13116163 - 30 May 2021

Cited by 57 | Viewed by 4010

Abstract

Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce [...] Read more.

Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues. Full article

(This article belongs to the Special Issue Advanced Renewable Energy for Sustainability)

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