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Renewable Energy Generation and Management Systems for Sustainable Development

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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 3796

Special Issue Editors


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Guest Editor
School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK
Interests: adsorption; biomass conversion technolgies; biofuels and bioenergy; hydrochar; pollutant control; water quality analysis
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK
Interests: conversion of biomass and wet wastes into bioenergy and bioproducts; algal biotechnology; waste to energy; energy and nutrient cycling; thermochemical and biological processing of biomass
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of renewable and sustainable energy sources is considered a solution for reducing environmental pollution and mitigating climate change, which is critical in achieving the United Nations' sustainable development goals. Hence, an in-depth understanding of engineering management of renewable energy systems is vital towards evaluating sustainable energy developments and achievements, in terms of optimal design, operational sustainable, economic feasibility, and environmental sustainability.   

This Special Issue aims to collect research papers aimed at a wide range of renewable energy topics: a systems analysis approach on sustainability, renewable and sustainable energy systems, hydrogen-based energy systems, energy storage, biofuels and bioenergy, solar energy, wind energy, geothermal energy, tidal energy, and wave energy. Contributions describing novel and significant knowledge, scientific results, and advanced applications in the fields of clean energy, clean technologies, environmental sustainability engineering, engineering management, renewable energy, renewable energy, and sustainable development are welcome.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the keywords presented below.

We look forward to receiving your contributions.

Dr. Eric Danso-Boateng
Dr. Andrew Ross
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • biomass energy
  • solar energy
  • wind energy
  • geothermal energy
  • tidal and wave energy
  • energy storage
  • renewable energy systems
  • sustainable energy systems
  • hydrogen technology
  • energy storage

Published Papers (3 papers)

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Research

22 pages, 2040 KiB  
Article
Optimal Design of the Proton-Exchange Membrane Fuel Cell Connected to the Network Utilizing an Improved Version of the Metaheuristic Algorithm
by Xuanxia Guo and Noradin Ghadimi
Sustainability 2023, 15(18), 13877; https://doi.org/10.3390/su151813877 - 18 Sep 2023
Cited by 19 | Viewed by 905
Abstract
Fuel cells are a newly developed source for generating electric energy. These cells produce electricity through a chemical reaction between oxygen and hydrogen, which releases electrons. In recent years, extensive research has been conducted in this field, leading to the emergence of high-power [...] Read more.
Fuel cells are a newly developed source for generating electric energy. These cells produce electricity through a chemical reaction between oxygen and hydrogen, which releases electrons. In recent years, extensive research has been conducted in this field, leading to the emergence of high-power batteries. This study introduces a novel technique to enhance the power quality of grid-connected proton-exchange membrane (PEM) fuel cells. The proposed approach uses an inverter following a buck converter that reduces voltage. A modified pelican optimization (MPO) algorithm optimizes the controller firing. A comparison is made between the controller’s performance, based on the recommended MPO algorithm and various other recent approaches, demonstrating the superior efficiency of the MPO algorithm. The study’s findings indicate that the current–voltage relationship in proton-exchange membrane fuel cells (PEMFCs) follows a logarithmic pattern, but becomes linear in the presence of ohmic overvoltage. Furthermore, the PEMFC operates at an impressive efficiency of 60.43% when running at 8 A, and it can deliver a significant power output under specific operating conditions. The MPO algorithm surpasses other strategies in terms of efficiency and reduction in voltage deviation, highlighting its effectiveness in managing the voltage stability, and improving the overall performance. Even during a 0.2 sagging event, the MPO-based controller successfully maintains the fuel cell voltage near its rated value, showcasing the robustness of the optimized regulators. The suggested MPO algorithm also achieves a superior accuracy in maintaining the voltage stability across various operating conditions. Full article
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13 pages, 1661 KiB  
Article
Optimisation of Anaerobic Digestate and Chemical Fertiliser Application to Enhance Rice Yield—A Machine-Learning Approach
by Binoy Kumar Show, Suraj Panja, Richik GhoshThakur, Aman Basu, Apurba Koley, Anudeb Ghosh, Kalipada Pramanik, Shibani Chaudhury, Amit Kumar Hazra, Narottam Dey, Andrew B. Ross and Srinivasan Balachandran
Sustainability 2023, 15(18), 13706; https://doi.org/10.3390/su151813706 - 14 Sep 2023
Cited by 2 | Viewed by 1158
Abstract
The present study evaluates the synergistic application of an anaerobic digestate for enhanced rice yield. The study utilised the digestate as a fertiliser with various inoculum-to-substrate (IS) ratios of anaerobic digestion from cow dung and water hyacinth (CW–BF) with combinations of NPK (16-22-22) [...] Read more.
The present study evaluates the synergistic application of an anaerobic digestate for enhanced rice yield. The study utilised the digestate as a fertiliser with various inoculum-to-substrate (IS) ratios of anaerobic digestion from cow dung and water hyacinth (CW–BF) with combinations of NPK (16-22-22) fertiliser for rice yield optimisation. The outcome of the combined digestate and fertiliser application on rice cultivation was observed in terms of parameters such as the number of tillers, panicle number, panicle length, fertile panicles, and 1000-grain weight. The digestate combination of CW–BF:NPK (3:1:1) resulted in the highest grain yield (7521 kg/hectare) with increased panicle length, test weight, and more filled grains than the other combinations. Moreover, various machine-learning approaches were used to study the efficacy of the different combinations of applied fertiliser (cow dung, water hyacinth, and NPK). The gradient-boosting machine-learning model was appropriate for predicting the modelling based on the measured data. Principal component analysis revealed NPK as the first principal component with high loading values and the digestate as the second principal component, which indicates its crucial role in fertiliser preparation. Therefore, deploying such hybridised fertilisers using the proper statistical analysis and machine-learning approaches can improve rice yield, which would be essential for the socio-economic uplifting of marginal rice farmers. Full article
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15 pages, 1571 KiB  
Article
Designing and Analysing a PV/Battery System via New Resilience Indicators
by S M Mezbahul Amin, Abul Hasnat and Nazia Hossain
Sustainability 2023, 15(13), 10328; https://doi.org/10.3390/su151310328 - 29 Jun 2023
Cited by 1 | Viewed by 994
Abstract
The increasing frequency of natural disasters in refugee camps has highlighted the urgent need for a dependable power source. In humanitarian camps, a reliable power supply is essential for meeting the basic daily needs of the residents. However, the conventional power systems in [...] Read more.
The increasing frequency of natural disasters in refugee camps has highlighted the urgent need for a dependable power source. In humanitarian camps, a reliable power supply is essential for meeting the basic daily needs of the residents. However, the conventional power systems in these camps often experience interruptions. To address this issue, microgrids have emerged as a viable solution. Although several studies have recognized the resilience benefits of microgrids, their application in refugee camps has been relatively limited. Hence, this study presents a grid-tied microgrid that combines photovoltaic and battery systems, designed using REopt lite web version software, to fulfill the energy requirements of Rohingya refugees in a selected camp located in Ukhia, Cox’s Bazar. Additionally, this study introduces four new indicators of resilience to evaluate the performance of the designed system. The findings reveal that the proposed microgrid consists of 5685 kW of photovoltaic capacity and 9011 kWh of battery capacity, enabling it to handle a 15 h power outage and resulting in substantial life-cycle savings of USD 2,956,737. The payback period for this resilient system is calculated to be 6.37 years, with an internal rate of return (IRR) of 12.2%. Furthermore, the system emits fewer emissions compared to other analysed modes in resilient operation, emphasizing its sustainability. In conclusion, the designed microgrid successfully enhances the reliability of the power supply in refugee camps. Full article
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