Article
Green & Sustainable Science & Technology
Ahmed Elnozahy, H. S. Ramadan, Farag K. Abo-Elyousr
Summary: The paper proposes four hybrid storage options, implements a probabilistic approach based on artificial neural networks, and combines them with comprehensive eco-techno-economic optimization studies. The effectiveness of the developed options and approach are validated through multi-objective optimization scenarios considering the Utopia point approach.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Energy & Fuels
Merel Enserink, Rudi Van Etteger, Sven Stremke
Summary: The current approach to developing renewable energy projects often faces local opposition and has been said to increase injustice. Addressing procedural justice by including local stakeholders in the design process can be difficult due to the technical complexities of solar power plants. However, using a full-scale prototype and engaged action research, this study found that participatory design processes can aid understanding and increase local support for the development of solar power plants.
Article
Green & Sustainable Science & Technology
Yi He, Su Guo, Jianxu Zhou, Jilei Ye, Jing Huang, Kun Zheng, Xinru Du
Summary: This paper proposes a wind-photovoltaic-battery-thermal energy storage hybrid power system and investigates its multi-objective planning-operation co-optimization. By introducing a novel coordinated operation strategy and a decision-making multi-objective evolutionary algorithm, the system achieves significant improvements in addressing the intermittency of renewable energy, enhancing economy, and ensuring reliability.
Article
Green & Sustainable Science & Technology
Saida Makhloufi, Smail Khennas, Sami Bouchaib, Amar Hadj Arab
Summary: This paper presents the most credible options to increase the share of renewable energy resource in the Algerian electricity power system by 2050, and uses the screening curve method and EnergyPlan tool for evaluation and estimation, while adopting the multi-objective cuckoo search algorithm to formulate the energy transition strategy.
Article
Green & Sustainable Science & Technology
J. Vergara-Zambrano, W. Kracht, Felipe A. Diaz-Alvarado
Summary: This paper proposes a methodology for designing a solar-biogas hybrid renewable energy system considering the integration of renewable energy's variability and its intermittency nature. The results indicate that solar energy and biogas are attractive options to supply the electrical requirements of a copper mining process, but a deeper environmental evaluation of the system is needed.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Energy & Fuels
Musik Park, Zhiyuan Wang, Lanyu Li, Xiaonan Wang
Summary: With increasing concerns over carbon dioxide emissions, the concept of Zero Energy Building (ZEB) and Electric Vehicles (EVs) have emerged to address environmental issues. This paper develops a new framework to find the optimal energy system design that meets EV charging demand and ZEB requirements, using machine learning models to predict charging demand and Genetic Algorithm and PROBID method to optimize costs and self-sufficiency ratio. The study finds that EV charging demand significantly affects energy system design, especially in small-size buildings.
Article
Environmental Studies
Sgouris Sgouridis, Christian Kimmich, Jordi Sole, Martin Cerny, Melf-Hinrich Ehlers, Christian Kerschner
Summary: This article discusses the importance and issues of Energy-Economy-Environment (E3) models in energy policy and climate mitigation planning. It argues that during energy transitions, it is better to develop a vision of the desired future energy system rather than relying on simple objective-based technoeconomic solutions. The article highlights biases in E3 models and warns against uncritical usage that may hinder radical transitions. It suggests prioritizing a clear articulation of the future vision and utilizing models as tools for evaluating interventions.
ENERGY RESEARCH & SOCIAL SCIENCE
(2022)
Article
Green & Sustainable Science & Technology
Xiuxing Yin, Zhigao Zhao, Weijia Yang
Summary: This study investigates the distributed production of green hydrogen using renewable energy sources and the power grid. By providing an overall modeling framework and an optimization method aided by ensemble learning, stable hydrogen production is achieved and wind farm power prediction errors are reduced.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Energy & Fuels
Shuangshuang Zhou, Juan Yang, Shiwei Yu
Summary: This article proposes a new model to optimize the power generation structure in China by considering the integration of variable renewables. The optimized results show that renewable power will account for more than 42% of total power in 2040, with solar photovoltaic power growing the most. The study also finds that renewable power exceeds thermal power in 14 provinces and the share of PV power increases in each region.
Article
Economics
Pragyan Deb, Davide Furceri, Jonathan D. Ostry, Nour Tawk
Summary: Lockdowns during the COVID-19 pandemic led to a decrease in overall energy demand, but electricity generation from renewable sources remained strong. Recessions and crises result in a small, but permanent increase in energy efficiency and the share of renewables in total electricity generation. This effect is more significant in advanced economies and when combined with environment and energy policies, including market-based measures and non-market measures, to encourage the transition to renewable energy sources.
Article
Energy & Fuels
Bahman Ahmadi, Oguzhan Ceylan, Aydogan Ozdemir
Summary: Renewable distributed generation and energy storage systems have revolutionized energy supply by introducing a new approach which should be optimally planned and operated. The proposed multi-objective multiverse optimization method has been shown to outperform other algorithms in improving voltage profiles and reducing costs.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Chemistry, Physical
Prabhakar Sharma, Bibhuti B. Sahoo
Summary: This study investigates the use of a hybrid adaptive neuro-fuzzy inference system (ANFIS)-response surface methodology (RSM) to improve the performance of a syngas-powered engine. By analyzing engine load and syngas composition, the study aims to optimize efficiency and reduce pollutant emissions. The results show that the developed ANFIS model has a good correlation and low errors, demonstrating its superior forecasting abilities. The optimal engine load and syngas composition for maximum production were determined to be 67.99% load and a 72.4:27.6 H2:CO syngas mix.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Thermodynamics
Seyyed Ali Sadat, Jonathan Takahashi, Joshua M. Pearce
Summary: This paper introduces SAMA, an open-source microgrid optimization software designed to economically optimize hybrid energy systems using specific load configurations and meteorological data. The validation results show congruence between SAMA and Homer Pro. SAMA can be used for various applications and has unique features, while also allowing for customization according to user needs.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Thermodynamics
Seyed Farhad Zandrazavi, Cindy Paola Guzman, Alejandra Tabares Pozos, Jairo Quiros-Tortos, John Fredy Franco
Summary: A stochastic multi objective optimization model is proposed for grid-connected unbalanced microgrids to minimize total operational cost and voltage deviation. The epsilon-constraint method and fuzzy satisfying approach are used to solve the multi-objective optimization problem, considering uncertainties through the roulette wheel mechanism for scenario generation.
Article
Business
Patricia Tourais, Nuno Videira
Summary: The role and impact of businesses in transition processes depend on their strategic positioning for long-term sustainability goals. However, there is a lack of operational guidelines in previous literature to support organizations in navigating the complexities of wider sustainability transitions. This study explores the contribution of sustainability transitions research to strategic planning processes in a business context. A procedure is developed and tested in the Portuguese tourism sector to guide organizations in developing sustainability transition strategies. The results highlight the importance of participatory and long-term oriented approaches in supporting businesses' transformation processes, and identify improvement opportunities regarding stakeholder involvement and innovation integration.
CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Xiangyun Shi, Takanori Matsui, Takashi Machimura, Xiaoyu Gan, Ang Hu
Article
Green & Sustainable Science & Technology
Risper Nyairo, Takashi Machimura, Takanori Matsui
Article
Ecology
Chihiro Haga, Marimi Maeda, Wataru Hotta, Takahiro Inoue, Takanori Matsui, Takashi Machimura, Masahiro Nakaoka, Junko Morimoto, Hideaki Shibata, Shizuka Hashimoto, Osamu Saito
FRONTIERS IN ECOLOGY AND EVOLUTION
(2020)
Article
Green & Sustainable Science & Technology
Keiko Hori, Osamu Saito, Shizuka Hashimoto, Takanori Matsui, Rumana Akter, Kazuhiko Takeuchi
Summary: This study developed a projection model of future population distribution based on Japan's depopulation trend, and conducted scenario analyses of population compactification and dispersion. The results show significant spatial changes in population distribution by 2050, with some areas experiencing a near disappearance of population.
SUSTAINABILITY SCIENCE
(2021)
Article
Ecology
Yuko Maegawa, Yuji Ushigome, Masato Suzuki, Karen Taguchi, Keigo Kobayashi, Chihiro Haga, Takanori Matsui
Summary: This research proposes a new, efficient method for surveying raptors that is low-impact on the raptors themselves. The developed system achieved an overall accuracy of 97.0% and can classify different sounds across various locations and distances from nests. The survey method offers a way to judge whether an area is inhabited by goshawks and their approximate reproductive state based on environmental sounds, with minimal fieldwork required.
ECOLOGICAL INFORMATICS
(2021)
Article
Forestry
Junko Morimoto, Masahiro Aiba, Flavio Furukawa, Yoshio Mishima, Nobuhiko Yoshimura, Sridhara Nayak, Tetsuya Takemi, Haga Chihiro, Takanori Matsui, Futoshi Nakamura
Summary: Using machine learning, a study assessed the disturbance risk to cool-temperate forests by typhoons in northern Japan in late August 2016. It identified damage features caused by typhoons accompanied by heavy precipitation and found that precipitation increased the probability of disturbance in forest stands based on species composition.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Junya Kumagai, Mihoko Wakamatsu, Shizuka Hashimoto, Osamu Saito, Takehito Yoshida, Takehisa Yamakita, Keiko Hori, Takanori Matsui, Michio Oguro, Masahiro Aiba, Rei Shibata, Tohru Nakashizuka, Shunsuke Managi
Summary: In recent years, the value of natural capital has become a topic of interest in Japan, with researchers and policymakers conducting surveys to investigate the perceived values of terrestrial and marine natural capital. The study found that certain explanatory variables and sociodemographic characteristics are significant drivers of willingness to pay (WTP) for the maintenance of natural capital aspects. Furthermore, future predictions of Japan's terrestrial and marine natural capital suggest that a population-dispersed scenario should be followed for sustainable management up to 2050.
SUSTAINABILITY SCIENCE
(2022)
Article
Ecology
Keigo Kobayashi, Keisuke Masuda, Chihiro Haga, Takanori Matsui, Dai Fukui, Takashi Machimura
Summary: This paper proposes a bat species identifier method based on the analysis of echolocation calls, aiming to improve the accuracy of bat species identification. By analyzing these calls, a deep learning-based bat species identifier achieved 98.1% accuracy using convolutional neural networks, outperforming previous studies. Future perspectives include changing the deep learning algorithm to object detection and applying the identifier to evaluate the feasibility of estimating bat fauna and spatial activity distribution.
ECOLOGICAL INFORMATICS
(2021)
Article
Environmental Sciences
Tomohiro Oda, Chihiro Haga, Kotaro Hosomi, Takanori Matsui, Rostyslav Bun
Summary: The study investigates the impact of COVID-19 on traffic CO2 emissions in Japan during the first half of 2020, showing a significant decrease in emissions during the state of emergency. The use of unconventional activity data for estimating emissions may provide near-real-time results but could introduce larger errors and uncertainties compared to traditional inventory estimates. The study highlights the challenges of repurposing data with limited traceability for assessing environmental impacts and emphasizes the importance of thorough error and uncertainty assessment before using such data for policy applications.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Green & Sustainable Science & Technology
Xiangyun Shi, Takanori Matsui, Chihiro Haga, Takashi Machimura, Shizuka Hashimoto, Osamu Saito
Summary: The study used a spatial downscaling framework to explore possible land-use patterns in the Guangdong-Hong Kong-Macao Greater Bay Area, combining global SSPs scenarios with local land planning policies to model land-use changes. The results showed significant urban expansion under all six future scenarios, with varying decreases in cropland and forest areas, impacting local biocapacity and carbon emissions.
SUSTAINABILITY SCIENCE
(2021)
Article
Forestry
Wataru Hotta, Junko Morimoto, Chihiro Haga, Satoshi N. Suzuki, Takahiro Inoue, Takanori Matsui, Toshiaki Owari, Hideaki Shibata, Futoshi Nakamura
Summary: This study focused on hemiboreal forests in northern Japan, incorporating a regeneration process on downed logs into a forest landscape model to evaluate the long-term effects of post-windthrow management on tree species composition and biomass recovery. The results suggest that avoiding salvage logging and scarification can help conserve the species composition and aboveground biomass of hemiboreal forests.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Takanori Matsui, Kanoko Suzuki, Kyota Ando, Yuya Kitai, Chihiro Haga, Naoki Masuhara, Shun Kawakubo
Summary: This study utilized a BERT model to build a classifier for semantic mapping of practices and issues related to the SDGs. It also developed a visualizing method to show the co-occurrence of SDGs and a matchmaking process for local issues and initiatives. The intelligent information system aims to assist stakeholders in taking action towards achieving the sustainable development goals.
SUSTAINABILITY SCIENCE
(2022)
Article
Ecology
Chihiro Haga, Wataru Hotta, Takahiro Inoue, Takanori Matsui, Masahiro Aiba, Toshiaki Owari, Satoshi N. Suzuki, Hideaki Shibata, Junko Morimoto
Summary: This study explores management options for recovering above-ground biomass (AGB) and tree species composition after windthrow damage in forests under climate change. The results show that salvage logging and planting can successfully recover AGB by 2050 regardless of the climate change scenario. Leaving fallen trees or only conducting salvage logging does not facilitate AGB recovery. The study also found that the warmer climate condition promotes the recovery of certain tree species.
ECOLOGICAL MODELLING
(2022)
Article
Ecology
Wataru Hotta, Chihiro Haga, Junko Morimoto, Satoshi N. Suzuki, Takanori Matsui, Toshiaki Owari, Hideaki Shibata, Futoshi Nakamura
Summary: Forest management practices are required to conserve biodiversity and maximize carbon sequestration under climate change. Although post-windthrow salvage logging and scarification can reduce CO2 emissions, they may greatly impact species composition and increase CO2 emissions based on cradle-to-grave analysis. Leaving downed logs and advanced seedlings is recommended to conserve boreal conifers and carbon sinks and maximize net CO2 absorption under climate change.
Article
Green & Sustainable Science & Technology
Shu Ishida, Takanori Matsui, Chihiro Haga, Keiko Hori, Shizuka Hashimoto, Osamu Saito
Summary: The recent rates of global change in nature are unprecedented. The IPBES has proposed a framework for transformative change, involving recognizing values, making inclusive decisions, restructuring policies, and transforming social norms and goals. This study examines the unique perspective of the Japanese community on biodiversity, using Twitter data to identify interest and concern and comparing it with the IPBES framework.
Article
Green & Sustainable Science & Technology
Cameron Bracken, Nathalie Voisin, Casey D. Burleyson, Allison M. Campbell, Z. Jason Hou, Daniel Broman
Summary: This study presents a methodology and dataset for examining compound wind and solar energy droughts, as well as the first standardized benchmark of energy droughts across the Continental United States (CONUS) for a 2020 infrastructure. The results show that compound wind and solar droughts have distinct spatial and temporal patterns across the CONUS, and the characteristics of energy droughts are regional. The study also finds that compound high load events occur more often during compound wind and solar droughts than expected.
Article
Green & Sustainable Science & Technology
Ning Zhang, Yanghao Yu, Jiawei Wu, Ershun Du, Shuming Zhang, Jinyu Xiao
Summary: This paper provides insights into the optimal configuration of CSP plants with different penetrations of wind power by proposing an unconstrained optimization model. The results suggest that large solar multiples and TES are preferred in order to maximize profit, especially when combined with high penetrations of wind and photovoltaic plants. Additionally, the study demonstrates the economy and feasibility of installing electric heaters (EH) in CSP plants, which show a linear correlation with the penetration of variable energy resources.
Article
Green & Sustainable Science & Technology
M. Szubel, K. Papis-Fraczek, S. Podlasek
Article
Green & Sustainable Science & Technology
J. Silva, J. C. Goncalves, C. Rocha, J. Vilaca, L. M. Madeira
Summary: This study investigated the methanation of CO2 in biogas and compared two different methanation reactors. The results showed that the cooled reactor without CO2 separation achieved a CO2 conversion rate of 91.8%, while the adiabatic reactors achieved conversion rates of 59.6% and 67.2%, resulting in an overall conversion rate of 93.0%. Economic analysis revealed negative net present worth values, indicating the need for government monetary incentives.
Article
Green & Sustainable Science & Technology
Yang Liu, Yonglan Xi, Xiaomei Ye, Yingpeng Zhang, Chengcheng Wang, Zhaoyan Jia, Chunhui Cao, Ting Han, Jing Du, Xiangping Kong, Zhongbing Chen
Summary: This study investigated the effect of using nanofiber membrane composites containing Prussian blue-like compound nanoparticles (PNPs) to relieve ammonia nitrogen inhibition of rural organic household waste during high-solid anaerobic digestion and increase methane production. The results showed that adding NMCs with 15% PNPs can lower the concentrations of volatile fatty acids and ammonia nitrogen, and increase methane yield.
Article
Green & Sustainable Science & Technology
Zhong Ge, Xiaodong Wang, Jian Li, Jian Xu, Jianbin Xie, Zhiyong Xie, Ruiqu Ma
Summary: This study evaluates the thermodynamic, exergy, and economic performance of a double-stage organic flash cycle (DOFC) using ten eco-friendly hydrofluoroolefins. The influences of key parameters on performance are analyzed, and the advantages of DOFC over single-stage type are quantified.
Article
Green & Sustainable Science & Technology
Nicolas Kirchner-Bossi, Fernando Porte-Agel
Summary: This study investigates the optimization of power density in wind farms and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced to optimize power density and turbine layout. The results show that the PDGA-driven solutions significantly reduce the levelized cost of energy (LCOE) compared to the default layout, and exhibit a convex relationship between area and LCOE or power density.
Article
Green & Sustainable Science & Technology
Chunxiao Zhang, Dongdong Li, Lin Wang, Qingpo Yang, Yutao Guo, Wei Zhang, Chao Shen, Jihong Pu
Summary: In this study, a novel reversible liquid-filled energy-saving window that effectively regulates indoor solar radiation heat gain is proposed. Experimental results show that this window can effectively reduce indoor temperature during both summer and winter seasons, while having minimal impact on indoor illuminance.
Article
Green & Sustainable Science & Technology
Alessandro L. Aguiar, Martinho Marta-Almeida, Mauro Cirano, Janini Pereira, Leticia Cotrim da Cunha
Summary: This study analyzed the Brazilian Equatorial Shelf using a high-resolution ocean model and found significant tidal variations in the area. Several hypothetical barrages were proposed with higher annual power generation than existing barrages. The study also evaluated the installation effort of these barrages.
Article
Green & Sustainable Science & Technology
Francesco Superchi, Nathan Giovannini, Antonis Moustakis, George Pechlivanoglou, Alessandro Bianchini
Summary: This study focuses on the optimization of a hybrid power station on the Tilos island in Greece, aiming to increase energy export and revenue by optimizing energy fluxes. Different scenarios are proposed to examine the impact of different agreements with the grid operator on the optimal solution.
Article
Green & Sustainable Science & Technology
Peimaneh Shirazi, Amirmohammad Behzadi, Pouria Ahmadi, Sasan Sadrizadeh
Summary: This research presents two novel energy production/storage/usage systems to reduce energy consumption and environmental effects in buildings. A biomass-fired model and a solar-driven system integrated with photovoltaic thermal (PVT) panels and a heat pump were designed and assessed. The results indicate that the solar-based system has an acceptable energy cost and the PVT-based system with a heat pump is environmentally superior. The biomass-fired system shows excellent efficiency.
Article
Green & Sustainable Science & Technology
Zihao Qi, Yingling Cai, Yunxiang Cui
Summary: This study aims to investigate the operational characteristics of the solar-ground source heat pump system (SGSHPS) in Shanghai under different operation modes. It concludes that tandem operation mode 1 is the optimal mode for winter operation in terms of energy efficiency.
Article
Green & Sustainable Science & Technology
L. Bartolucci, S. Cordiner, A. Di Carlo, A. Gallifuoco, P. Mele, V. Mulone
Summary: Spent coffee grounds are a valuable biogenic waste that can be used as a source of biofuels and valuable chemicals through pyrolysis and solvent extraction processes. The study found that heavy organic bio-oil derived from coffee grounds can be used as a carbon-rich biofuel, while solvent extraction can extract xantines and p-benzoquinone, which are important chemicals for various industries. The results highlight the promising potential of solvent extraction in improving the economic viability of coffee grounds pyrolysis-based biorefineries.
Article
Green & Sustainable Science & Technology
Luiza de Queiroz Correa, Diego Bagnis, Pedro Rabelo Melo Franco, Esly Ferreira da Costa Junior, Andrea Oliveira Souza da Costa
Summary: Building-integrated photovoltaics, especially organic solar technology, are important for reducing greenhouse gas emissions in the building sector. This study analyzed the performance of organic panels laminated in glass in a vertical installation in Latin America. Results showed that glass lamination and vertical orientation preserved the panels' performance and led to higher energy generation in winter.
Article
Green & Sustainable Science & Technology
Zhipei Hu, Shuo Jiang, Zhigao Sun, Jun Li
Summary: This study proposes innovative fin arrangements to enhance the thermal performance of latent heat storage units. Through optimization of fin distribution and prediction of transient melting behaviors, it is found that fin structures significantly influence heat transfer characteristics and melting behaviors.
