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This document is a compilation of research papers that explore the topics of Smart Cities and Positive Energy Districts (PEDs). The papers cover a range of subjects including energy efficiency, renewable energy communities, smart urban management, and financial schemes for sustainable neighborhoods. The findings emphasize the importance of energy renovation, potential energy and financial savings, and the need for collaborative approaches and policy direction to achieve sustainable urban development. The papers also provide insights into innovative solutions and technological advancements that can contribute to the realization of carbon-neutral and sustainable cities. This document serves as a valuable resource for library patrons conducting research on energy efficiency and sustainable building practices. [Extracted from the article]

Accurate short-term load forecasting (STLF) plays an essential role in sustainable energy development. Specifically, energy companies can efficiently plan and manage their generation capacity, lessening resource wastage and promoting the overall efficiency of power resource utilization. However, existing models cannot accurately capture the nonlinear features of electricity data, leading to a decline in the forecasting performance. To relieve this issue, this paper designs an innovative load forecasting method, named Prophet–CEEMDAN–ARBiLSTM, which consists of Prophet, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the residual Bidirectional Long Short-Term Memory (BiLSTM) network. Specifically, this paper firstly employs the Prophet method to learn cyclic and trend features from input data, aiming to discern the influence of these features on the short-term electricity load. Then, the paper adopts CEEMDAN to decompose the residual series and yield components with distinct modalities. In the end, this paper designs the advanced residual BiLSTM (ARBiLSTM) block as the input of the above extracted features to obtain the forecasting results. By conducting multiple experiments on the New England public dataset, it demonstrates that the Prophet–CEEMDAN–ARBiLSTM method can achieve better performance compared with the existing Prophet-based ones. [ABSTRACT FROM AUTHOR]

This paper addresses the challenges in forecasting electrical energy in the current era of renewable energy integration. It reviews advanced adaptive forecasting methodologies while also analyzing the evolution of research in this field through bibliometric analysis. The review highlights the key contributions and limitations of current models with an emphasis on the challenges of traditional methods. The analysis reveals that Long Short-Term Memory (LSTM) networks, optimization techniques, and deep learning have the potential to model the dynamic nature of energy consumption, but they also have higher computational demands and data requirements. This review aims to offer a balanced view of current advancements and challenges in forecasting methods, guiding researchers, policymakers, and industry experts. It advocates for collaborative innovation in adaptive methodologies to enhance forecasting accuracy and support the development of resilient, sustainable energy systems. [ABSTRACT FROM AUTHOR]

As a key project of China's western development, the West-East Natural Gas Transmission Project (WENGT) has effectively alleviated China's uneven energy distribution and supply-demand issues. It has promoted the optimization of China's energy structure and sustainable development in the new era, helping to achieve the goal of "double carbon". Based on pollution data from Chinese industrial enterprises from 2000 to 2012, this paper analyzes the impact of the West-East Natural Gas Pipeline Project on the air pollution emissions of industrial enterprises using a difference-in-difference model and explores the moderating role of local government environmental regulations. The findings indicate that the project significantly reduced air pollutant emissions from industrial enterprises in cities along the route, with a more pronounced reduction effect in areas with higher environmental regulation intensity. Additionally, the emission reduction effect varied among different types of enterprises and regions, with private enterprises showing the smallest reduction impact and the eastern coastal region exhibiting the most significant effect. This paper delves into the relationship between sustainable cross-regional energy development and air pollution emissions from industrial enterprises, providing a theoretical basis for energy conservation and emission reduction policies in China. [ABSTRACT FROM AUTHOR]

The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and the port loads with large fluctuations and fast changes. These factors can easily lead to the problem of the state of charge exceeding the limit of the energy storage system. To distribute the fluctuating power in the green port multi-energy microgrid system reasonably and maintain the state of charge (SOC) of the hybrid energy storage system in an moderate range, an energy management strategy (EMS) based on dual-stage fuzzy control with a low pass-filter algorithm is proposed in this paper. First, the mathematical model of a green port multi-energy microgrid system is established. Then, fuzzy rules are designed, and the dual-stage fuzzy controller is used to change the time constant of the low-pass filter (LPF) and modify the initial power distribution by an LPF algorithm. Finally, simulation models are built in Matlab 2016a/Simulink. The simulation results demonstrate that, compared with other algorithms under the control of the EMS proposed in this paper, the high-frequency component in the flywheel power is smaller, and the SOC of the supercapacitor is maintained in a reasonable range of 34–78%, which extends the lifespan of the flywheel and supercapacitor. Additionally, it has a faster automatic adjustment ability for the state of charge of the energy storage system, which is conducive to better maintaining the stable operation of green port multi-energy microgrid systems. [ABSTRACT FROM AUTHOR]

Electric vehicles can reduce the dependence on limited resources such as oil, which is conducive to the development of clean energy. An accurate battery state of health (SOH) is beneficial for the safety of electric vehicles. A multi-feature and Convolutional Neural Network–Bidirectional Long Short-Term Memory–Multi-head Attention (CNN-BiLSTM-MHA)-based lithium-ion battery SOH estimation method is proposed in this paper. First, the voltage, energy, and temperature data of the battery in the constant current charging phase are measured. Then, based on the voltage and energy data, the incremental energy analysis (IEA) is performed to calculate the incremental energy (IE) curve. The IE curve features including IE, peak value, average value, and standard deviation are extracted and combined with the thermal features of the battery to form a complete multi-feature sequence. A CNN-BiLSTM-MHA model is set up to map the features to the battery SOH. Experiments were conducted using batteries with different charging currents, and the results showed that even if the nonlinearity of battery SOH degradation is significant, this method can still achieve a fast and accurate estimation of the battery SOH. The Mean Absolute Error (MAE) is 0.1982%, 0.1873%, 0.1652%, and 0.1968%, and the Root-Mean-Square Error (RMSE) is 0.2921%, 0.2997%, 0.2130%, and 0.2625%, respectively. The average Coefficient of Determination (R2) is above 96%. Compared to the BiLSTM model, the training time is reduced by an average of about 36%. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive bibliometric review and visualization of smart and sustainable energy consumption, delving into the challenges and opportunities of developing renewable and non-renewable energy sources. The study examines research trends and emerging themes about integrating smart solutions and sustainable energy resource consumption. The analytical methods used involve thoroughly analyzing empirical data, case studies, and review papers to map the research landscape. The results highlight dominant research topics, influential authors, and publication timelines in this field. The review identifies the key challenges in harnessing renewable and non-renewable energy sources, including the need for reliable energy sources, energy storage systems, and smart grid technologies. The paper concludes with insights into the most effective practices for promoting smart and energy-efficient methods while emphasizing the complexity of sustainable energy solutions. [ABSTRACT FROM AUTHOR]

Sustainable energy projects can help societies reduce climate change's negative impacts. In the present paper, published studies regarding European community energy schemes (CESs) were analysed to investigate CESs' barriers and drivers towards including community members and, more specifically, vulnerable groups. This review followed the PRISMA guidelines to ensure transparency. Exclusion and inclusion criteria were defined to select the proper articles and books that were aligned with the scope of this review. A total of 143 publications from 2019 to February 2024 were considered and selected. Content analysis was used to outline the various definitions of energy poverty, vulnerable groups, and CESs as well as the different strategies and approaches followed by European countries to tackle energy poverty and increase public engagement in CESs. This research suggests that environmental citizenship is a concept that can bring individuals and society together to promote changes in energy-related behaviours. The outcome reveals factors that enhance community energy acceptance and social cohesion such as providing energy education or education for sustainability to community members, financial support, increased prosocial culture, and the participation of vulnerable groups in CESs. This can be achieved through various interventions to help community members, including vulnerable groups, understand sustainable energy behaviour and thus reduce energy poverty. [ABSTRACT FROM AUTHOR]

In advancing the transition of the energy sector toward heightened sustainability and environmental friendliness, biopolymers have emerged as key elements in the construction of triboelectric nanogenerators (TENGs) due to their renewable sources and excellent biodegradability. The development of these TENG devices is of significant importance to the next generation of renewable and sustainable energy technologies based on carbon-neutral materials. This paper introduces the working principles, material sources, and wide-ranging applications of biopolymer-based triboelectric nanogenerators (BP-TENGs). It focuses on the various categories of biopolymers, ranging from natural sources to microbial and chemical synthesis, showcasing their significant potential in enhancing TENG performance and expanding their application scope, while emphasizing their notable advantages in biocompatibility and environmental sustainability. To gain deeper insights into future trends, we discuss the practical applications of BP-TENG in different fields, categorizing them into energy harvesting, healthcare, and environmental monitoring. Finally, the paper reveals the shortcomings, challenges, and possible solutions of BP-TENG, aiming to promote the advancement and application of biopolymer-based TENG technology. We hope this review will inspire the further development of BP-TENG towards more efficient energy conversion and broader applications. [ABSTRACT FROM AUTHOR]

The excessive use of energy from fossil fuels, which corresponds to population, industrialisation, and unsustainable economic growth, is the cause of carbon dioxide production and climate change. The Water–Energy–Food (WEF) nexus is an applicable conceptual framework that helps manage the balance between human development and natural resource constraints, and it becomes a valuable tool to address the challenges of resource depletion and clean energy. This article aims to analyse the relationship between the WEF nexus and clean energy through a statistical analysis and a systematic review of knowledge on energy sustainability. The methodology involves the selection of bibliographic information databases such as Scopus and Web of Science (WoS), a statistical analysis, specifically the Scientometrics applied to the information obtained, and the identification of 179 scientific publications related to the study variables through a screening process called Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The interaction of green energy and sustainability with the WEF nexus has been approached mainly by developed countries such as China (10%), the United States (9.49%), India (7.26%), and Brazil (5.02%). The review of 55 scientific papers identified strategies that balance economic growth and environmental impact, applying clean energy systems (e.g., solar and wind), and the importance of adaptation to the subsystems of the WEF nexus. This study also highlights adaptability to climate change in rural and urban communities. Therefore, it is consistent with the four pillars of sustainable development (Economic: 7 papers, Environmental: 22, Social: 18, and Cultural: 8). This study highlights the following: (a) the importance of the use of renewable energy either in mixed systems and consumption, energy storage, and seeking energy efficiency in systems adapted to diverse environments and (b) the relevance of community participation in the decision-making process for the use of clean energy, such as a strategy for climate change adaptation. [ABSTRACT FROM AUTHOR]

The article discusses the process of biomass pyrolysis and the importance of kinetic modeling in understanding and optimizing this process. Pyrolysis is a thermal conversion method that can produce solid and liquid biofuels, as well as raw materials for bio-based products. The distribution and quality of the products depend on the properties of the biomass and the thermal conditions used. However, there are challenges in accurately determining the kinetics of pyrolysis reactions due to factors such as the variability of biomass composition and the presence of catalysts. The article also provides an overview of nine research papers published in a special issue of the journal Processes, which cover topics such as the devolatilization behavior of different biomass feedstocks, the effects of torrefaction pretreatment, and the influence of catalysts on conversion dynamics. [Extracted from the article]

This paper introduces a new hybrid DC–DC converter with enhanced voltage gain and synchronized multiple output capabilities, specifically tailored for smart grid applications. The proposed converter is based on the integration of non-isolated Zeta and Mahafzah converters, comprising a single controlled switch, two diodes, three inductors, and two coupling capacitors. The primary objective of this novel hybrid converter is to improve voltage gain as compared to conventional Zeta and Mahafzah topologies. By achieving higher voltage gain at lower duty cycles, the converter effectively reduces voltage stress on semiconductor switches and output diodes, thereby enhancing overall performance and reliability. A comprehensive examination of the hybrid converter's operating principle is presented, along with detailed calculations of duty cycle and switching losses. The paper also explores the converter's application in smart grids, specifically in the context of renewable energy systems and electric vehicles. Two distinct scenarios are analyzed to evaluate the converter's efficacy. Firstly, the converter is assessed as a DC–DC converter for renewable energy systems, highlighting its relevance in sustainable energy applications. Secondly, the converter is evaluated as an electric vehicle adapter, showcasing its potential in the transportation sector. To validate the converter's performance, extensive simulations are carried out using MATLAB/SIMULINK with parameters set at 25 kW, 200 V, and 130 A. The simulation results demonstrate the converter's ability to efficiently supply multiple loads with opposing energy flows, making it a promising technology for optimized grid management and energy distribution. Moreover, the paper investigates the total harmonic distortion (THD) of the grid current, focusing on its impact in smart grid environments. Notably, the new hybrid converter topology achieves a THD of 21.11% for the grid current, indicating its ability to effectively mitigate harmonics and improve power quality. Overall, this research introduces a cutting-edge hybrid DC–DC converter that enhances voltage gain and synchronizes multiple outputs, specifically catering to the requirements of smart grid applications. The findings underscore the converter's potential to significantly contribute to the advancement of efficient and resilient power conversion technologies for smart grids, enabling seamless integration of renewable energy systems and electric vehicles into the grid. [ABSTRACT FROM AUTHOR]

This paper introduces a groundbreaking approach to demand response management, aiming to empower consumers through innovative strategies. The key contribution is the concept of "acquiring flexibility rights", wherein consumers engage with power aggregators to curtail energy usage during peak-load periods, receiving incentives in return. A flexibility right coefficient is introduced, allowing consumers to tailor their participation in demand response programs, ensuring their well-being. Additionally, a lighting intensity control system is developed to enhance residential lighting network efficiency. The study demonstrates that high-energy consumers, adopting a satisfaction factor of 10, can achieve over 61% in electricity cost savings by combining the lighting control system and active participation in demand response programs. This not only reduces expenses but also generates income through the sale of flexibility rights. Conversely, low-energy consumers can fully offset their expenses and accumulate over USD 33 in earnings through the installation of solar panels. This paper formulates an optimization problem considering flexibility rights, lighting control, and time-of-use tariff rates. An algorithm is proposed for a distributed solution, and a sensitivity analysis is conducted for evaluation. The proposed method showcases significant benefits, including cost savings and income generation for consumers, while contributing to grid stability and reduced blackout occurrences. Real data from a residential district in Tehran validates the method's effectiveness. This study concludes that this approach holds promise for demand response management in smart grids, emphasizing the importance of consumer empowerment and sustainable energy practices. [ABSTRACT FROM AUTHOR]

The primary objective of this paper focuses on developing a control approach to improve the operational performance of a three-level neutral point clamped (3LNPC) shunt active power filter (SAPF) within a grid-tied PV system configuration. Indeed, this developed control approach, based on the used 3LNPC-SAPF topology, aims to ensure the seamless integration of a photovoltaic system into the three-phase four-wire grid while effectively mitigating grid harmonics, grid current unbalance, ensuring grid unit power factor by compensating the load reactive power, and allowing power sharing with the grid in case of an excess of generated power from the PV system, leading to overall high power quality at the grid side. This developed approach is based initially on the application of the four-wire instantaneous p-q theory for the identification of the reference currents that have to be injected by the 3LNPC-SAPF in the grid point of common coupling (PCC). Whereas, the 3LNPC is controlled based on using the finite control set model predictive control (FCS-MPC), which can be accomplished by determining the convenient set of switch states leading to the voltage vector, which is the most suitable to ensure the minimization of the selected cost function. Furthermore, the used topology requires a constant DC-link voltage and balanced split-capacitor voltages at the input side of the 3LNPN. Hence, the cost function is adjusted by the addition of another term with a selected weighting factor related to these voltages to ensure their precise control following the required reference values. However, due to the random changes in solar irradiance and, furthermore, to ensure efficient operation of the proposed topology, the PV system is connected to the 3LNPN-SAPF via a DC/DC boost converter to ensure the stability of the 3LNPN input voltage within the reference value, which is achieved in this paper based on the use of the maximum power point tracking (MPPT) technique. For the validation of the proposed control technique and the functionality of the used topology, a set of simulations has been presented and investigated in this paper following different irradiance profile scenarios such as a constant irradiance profile and a variables irradiance profile where the main aim is to prove the effectiveness and flexibility of the proposed approach under variable irradiance conditions. The obtained results based on the simulations carried out in this study demonstrate that the proposed control approach with the used topology under different loads such as linear, non-linear, and unbalanced can effectively reduce the harmonics, eliminating the unbalance in the currents and compensating for the reactive component contained in the grid side. The obtained results prove also that the proposed control ensures a consistent flow of power based on the sharing principle between the grid and the PV system as well as enabling the efficient satisfaction of the load demand. It can be said that the proposal presented in this paper has been proven to have many dominant features such as the ability to accurately estimate the power sharing between the grid and the PV system for ensuring the harmonics elimination, the reactive power compensation, and the elimination of the neutral current based on the zero-sequence component compensation, even under variable irradiance conditions. This feature makes the used topology and the developed control a valuable tool for power quality improvement and grid stability enhancement with low cost and under clean energy. [ABSTRACT FROM AUTHOR]

As the understanding of natural gas hydrates as a vast potential resource deepens, their importance as a future clean energy source becomes increasingly evident. However, natural gas hydrates trend towards secondary generation during extraction and transportation, leading to safety issues such as pipeline blockages. Consequently, developing new and efficient natural gas hydrate inhibitors has become a focal point in hydrate research. Kinetic hydrate inhibitors (KHIs) offer an effective solution by disrupting the nucleation and growth processes of hydrates without altering their thermodynamic equilibrium conditions. This paper systematically reviews the latest research progress and development trends in KHIs for natural gas hydrates, covering their development history, classification, and inhibition mechanisms. It particularly focuses on the chemical properties, inhibition effects, and mechanisms of polymer inhibitors such as polyvinylpyrrolidone (PVP) and polyvinylcaprolactam (PVCap). Studies indicate that these polymer inhibitors provide an economical and efficient solution due to their low dosage and environmental friendliness. Additionally, this paper explores the environmental impact and biodegradability of these inhibitors, offering guidance for future research, including the development, optimization, and environmental assessment of new inhibitors. Through a comprehensive analysis of existing research, this work aims to provide a theoretical foundation and technical reference for the commercial development of natural gas hydrates, promoting their safe and efficient use as a clean energy resource. [ABSTRACT FROM AUTHOR]

The development of offshore wind farms is an important step toward increasing the share of green energy in Poland's energy mix, offering promising prospects for the energy industry. However, in addition to numerous benefits, such investments also carry potential risks for the marine environment, including the risk of spills of hazardous substances such as gear oils, hydraulic oils, and lubricants. This paper analyses the potential impact of oil spills from offshore wind farms on the marine ecosystems of the Baltic Sea, taking into account hydrometeorological factors, particularly protected areas (such as Natura 2000 sites) and the intensity of ship traffic in the area of the planned farms. Simulations of spill scenarios are also presented to assess the potential extent of pollution and its impact on the environment. This paper emphasises the importance of advanced monitoring and safety systems in minimising the risk of accidents and responding quickly to possible incidents. The development of offshore wind farms in Poland presents itself as a key element in a sustainable energy development strategy, combining advanced technology with environmental concerns. [ABSTRACT FROM AUTHOR]

Renewable energy has emerged as a promising solution to address the challenges of climate change, energy security, and socio-economic development. South Africa, with its abundant renewable energy resources, has made significant strides in the utilization of renewable energy over the past decade. This paper provides a comprehensive review of the progress of renewable energy advancement in South Africa, examining the policies, initiatives, and achievements in various renewable energy sectors. This study explores the country's transition from a heavily coal-dependent energy system to a diversified and sustainable energy mix. It analyses the growth of renewable energy technologies, such as wind power and solar photovoltaic (PV), highlighting the key milestones, challenges, and opportunities. Furthermore, this paper discusses the role of government support, regulatory frameworks, and private sector investments in driving renewable energy deployment in South Africa. Finally, it identifies the prospects and potential areas for further advancement in the renewable energy sector. This review aims to contribute to the understanding of South Africa's renewable energy journey and provides valuable insights for policy-makers, researchers, and stakeholders involved in the sustainable energy transition. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of optimal energy community design, leveraging time-of-use pricing mechanisms and techno-economic parameters. Focusing on a case study of Valongo, Portugal, this study explores the intricate interplay between energy infrastructure planning, economic considerations, and pricing dynamics. Through a systematic approach, various factors, such as renewable energy integration, demand–response strategies, and investment costs, are evaluated to formulate an efficient and sustainable energy community model. Time-of-use pricing schemes are incorporated to reflect the dynamic nature of energy markets and consumer behavior. By integrating techno-economic analyses, this study aims to optimize energy resource allocation while ensuring cost-effectiveness and environmental sustainability. The influence of optimized sizes of photovoltaics (PV), battery storage, and electrical vehicles (EVs) on self-sufficiency rates, self-consumption rates and CO2 savings is analyzed. The findings offer valuable insights into the design and implementation of energy communities in urban settings, highlighting the importance of adaptive strategies in the transition towards a resilient and low-carbon energy future. The novelty of this paper lies in its comprehensive approach to energy community design, which integrates time-of-use pricing mechanisms with techno-economic parameters. By focusing on the specific case of Valongo, Portugal, it addresses the unique challenges and opportunities present in urban settings. Additionally, the analysis considers the interaction between renewable energy production, demand profiles and investment costs, providing valuable insights for optimizing resource allocation and achieving both cost-effectiveness and environmental sustainability. [ABSTRACT FROM AUTHOR]

The efficient development and widespread utilization of clean energy hold global significance, particularly for developing countries like China, which has committed to carbon peak and neutrality targets. In this context, the financial sector plays a crucial role in supporting the renewable energy industry, ensuring a reliable energy supply for economic growth. To statistically assess the impact of financial characteristics—such as financial efficiency, financial size, and green finance—this paper employs a panel vector autoregressive (PVAR) model with province-level data from China spanning the period 1991 to 2018. The key findings demonstrate that (1) financial factors significantly contribute to the development of clean energy in China, and among these factors, financial scale has a greater impact than financial efficiency and green finance; (2) there are distinct regional variations in how financial development affects the clean energy sector, and the role of financial scale is particularly pronounced in the central and western regions of China while the impact of financial efficiency on the clean energy industry is not significant across all regions; and (3) other drivers—including industrial structure, financial expenditure, and technological advancements—also spur the growth of the clean energy industry. However, due to diminishing marginal effects, the forces driving its growth may gradually diminish. Therefore, the article proposes critical policy suggestions for promoting clean energy development in China. These policies should consider the regional context and address both financial and non-financial aspects. Understanding the interplay between finance, regional dynamics, and clean energy development is crucial for achieving sustainable and resilient energy systems in China. [ABSTRACT FROM AUTHOR]

Solar cells represent a promising innovation in energy storage, offering not only exceptional cleanliness and low cost but also a high degree of flexibility, rendering them widely applicable. In recent years, scientists have dedicated substantial efforts to enhancing the performance of solar cells, aiming to drive sustainable development and promote clean energy applications. One approach that has garnered significant attention is strain engineering, which involves the adjustment of material microstructure and organization through mechanical tensile or compressive strain, ultimately serving to enhance the mechanical properties and performance stability of materials. This paper aims to provide a comprehensive review of the latest advancements in the application of strain engineering in solar cells, focused on the current hot research area—perovskite solar cells. Specifically, it delves into the origins and characterization of strain in solar cells, the impact of strain on solar cell performance, and the methods for regulating stable strain. Furthermore, it outlines strategies for enhancing the power conversion efficiency (PCE) and stability of solar cells through strain engineering. Finally, the paper conducts an analysis of the challenges encountered in the development process and presents a forward-looking perspective on further enhancing the performance of solar cells through strain engineering. [ABSTRACT FROM AUTHOR]

Due to the extensive use of fossil fuels, energy conservation and sustainable transportation have become hot topics. Electric vehicles (EVs), renowned for their clean and eco-friendly attributes, have garnered considerable global attention and are progressively being embraced worldwide. However, disorganized EV charging not only reduces charging station efficiency but also threatens power grid stability. In this low-carbon era, photovoltaic storage charging stations offer a solution that accommodates future EV growth. However, due to the significant instability in both the charging load and photovoltaic power generation within charging stations, it is critical to maximize local photovoltaic power consumption and minimize the impact of disorganized EV charging on the power grid. This paper formulates an intelligent scheduling strategy for electric heavy trucks within charging stations based on typical photovoltaic output data. The study focuses on a photovoltaic storage charging station in an industrial zone in Xinjiang. While considering the electricity procurement cost of the charging station, the aim is to minimize fluctuations in the electricity procurement load. A simulation analysis was conducted using MATLAB 2021a software, and the results indicated that, compared to an uncoordinated charging strategy for electric heavy trucks, the proposed strategy reduced electricity procurement costs by CNY 1348.25, decreased load fluctuations by 169.45, and improved the utilization efficiency of photovoltaic energy by 30%. A statistical analysis was also used to support the reduction in electricity procurement costs and load variations. Finally, a sensitivity analysis of the weight factors in the objective function was performed, proving that the proposed strategy effectively reduces electricity procurement costs and improves the utilization efficiency of photovoltaic energy. [ABSTRACT FROM AUTHOR]

In the context of sustainability, the integration of renewable energy into industrial processes not only minimizes dependence on fossil fuels but also contributes to the efficient management of industrial waste. By transforming organic waste, including agri-food and urban waste, into biogas, green energy can be generated, thus reducing the impact on the environment and closing the loop of material used in the economic circuit. Thus, a sustainable system can be promoted, where resources are continuously reused and exploited. Statistical methods and a decision tree with the Classification and Regression Trees (CRT) algorithm were employed to analyze data. The paper focuses on the importance of industrial waste and biogas for the generation, transformation, and consumption of energy in the EU (European Union)-27 countries. To provide a thorough analysis, we have divided these countries based on real gross domestic product (GDP) per capita, grouping them above/below the annual average for the period 2012–2021/2022. Descriptive statistics revealed observable differences between the two groups, but the paper aimed to provide evidence regarding the existence of these differences as statistically significant. Using the Kolmogorov–Smirnov test, the non-normal distribution of the data was confirmed, requiring non-parametric inferential methods. The Mann–Whitney U test revealed statistically significant differences between the two groups for all the studied variables. This comprehensive approach highlights the distinct energy-related characteristics influenced by economic development in the EU-27. [ABSTRACT FROM AUTHOR]

Batteries play a crucial role in the domain of energy storage systems and electric vehicles by enabling energy resilience, promoting renewable integration, and driving the advancement of eco-friendly mobility. However, the degradation of batteries over time remains a significant challenge. This paper presents a comprehensive review aimed at investigating the intricate phenomenon of battery degradation within the realm of sustainable energy storage systems and electric vehicles (EVs). This review consolidates current knowledge on the diverse array of factors influencing battery degradation mechanisms, encompassing thermal stresses, cycling patterns, chemical reactions, and environmental conditions. The key degradation factors of lithium-ion batteries such as electrolyte breakdown, cycling, temperature, calendar aging, and depth of discharge are thoroughly discussed. Along with the key degradation factor, the impacts of these factors on lithium-ion batteries including capacity fade, reduction in energy density, increase in internal resistance, and reduction in overall efficiency have also been highlighted throughout the paper. Additionally, the data-driven approaches of battery degradation estimation have taken into consideration. Furthermore, this paper delves into the multifaceted impacts of battery degradation on the performance, longevity, and overall sustainability of energy storage systems and EVs. Finally, the main drawbacks, issues and challenges related to the lifespan of batteries are addressed. Recommendations, best practices, and future directions are also provided to overcome the battery degradation issues towards sustainable energy storage system. [ABSTRACT FROM AUTHOR]

Accelerating the transition to a cleaner global energy system is essential for tackling the climate crisis, and green hydrogen energy systems hold significant promise for integrating renewable energy sources. This paper offers a thorough evaluation of green hydrogen's potential as a groundbreaking alternative to achieve near-zero greenhouse gas (GHG) emissions within a renewable energy framework. The paper explores current technological options and assesses the industry's present status alongside future challenges. It also includes an economic analysis to gauge the feasibility of integrating green hydrogen, providing a critical review of the current and future expectations for the levelized cost of hydrogen (LCOH). Depending on the geographic location and the technology employed, the LCOH for green hydrogen can range from as low as EUR 1.12/kg to as high as EUR 16.06/kg. Nonetheless, the findings suggest that green hydrogen could play a crucial role in reducing GHG emissions, particularly in hard-to-decarbonize sectors. A target LCOH of approximately EUR 1/kg by 2050 seems attainable, in some geographies. However, there are still significant hurdles to overcome before green hydrogen can become a cost-competitive alternative. Key challenges include the need for further technological advancements and the establishment of hydrogen policies to achieve cost reductions in electrolyzers, which are vital for green hydrogen production. [ABSTRACT FROM AUTHOR]

The coupling between modern electric power physical and cyber systems is deepening. An increasing number of users are gradually participating in power operation and control, engaging in bidirectional interactions with the grid. The evolving new power system is transforming into a highly intelligent socio–cyber–physical system, featuring increasingly intricate and expansive architectures. Demands for stable system operation are becoming more specific and rigorous. The new power system confronts significant challenges in areas like planning, dispatching, and operational maintenance. Hence, this paper aims to comprehensively explore potential synergies among various power system components from multiple viewpoints. It analyzes numerous core elements and key technologies to fully unlock the efficiency of this coupling. Our objective is to establish a solid theoretical foundation and practical strategies for the precise implementation of integrated planning and operation dispatching of source–grid–load–storage systems. Based on this, the paper first delves into the theoretical concepts of source, grid, load, and storage, comprehensively exploring new developments and emerging changes in each domain within the new power system context. Secondly, it summarizes pivotal technologies such as data acquisition, collaborative planning, and security measures, while presenting reasonable prospects for their future advancement. Finally, the paper extensively discusses the immense value and potential applications of the integrated planning and operation dispatching concept in source–grid–load–storage systems. This includes its assistance in regards to large-scale engineering projects such as extreme disaster management, facilitating green energy development in desertification regions, and promoting the construction of zero-carbon parks. [ABSTRACT FROM AUTHOR]

The development and utilization of clean energy is becoming more extensive, and wind power generation is one of the key points of this. Occasionally, wind turbines are faced with various extreme environmental impacts such as icing, lightning strikes and so on. In particular, the icing of wind turbines increases icing–wind loads, and results in a reduced power output. And blades broken down lead to large-area shutdown accidents caused by high-speed rotating, which seriously affects the reliability and equipment safety of wind power generation. Relevant institutions and researchers at home and abroad have carried out a lot of research on this. This paper summarizes the formation and influencing factors of wind turbine icing, the influence of icing on wind power generation, and defense technologies. First, it introduces the formation conditions and mechanisms of icing in wind farm regions and the relationship between meteorological and climatic characteristics and icing, and analyzes the key influence factors on icing. Then, the impact of icing on wind turbines is explained from the aspects of mechanical operation, the power curve, jeopardies and economic benefits. And then the monitoring and safety status of wind turbines icing is analyzed, which involves collecting the relevant research on anti-de-icing in wind power generation, introducing various anti/de-icing technologies, and analyzing the principle of icing defense. Finally, this paper summarizes wind turbine icing and its defense technologies, and puts forward the future research direction based on the existing problems of wind power generation icing. [ABSTRACT FROM AUTHOR]

Microbial fuel cells (MFCs) are sustainable energy recovery systems because they use organic waste as biofuel. Using critical raw materials (CRMs), like platinum-group metals, at the cathode side threatens MFC technology's sustainability and raises costs. By developing an efficient electrode design for MFC performance enhancement, CRM-based cathodic catalysts should be replaced with CRM-free materials. This work proposes developing and optimizing iron-based air cathodes for enhancing oxygen reduction in MFCs. By subjecting iron phthalocyanine and carbon black pearls to controlled thermal treatments, we obtained Fe-based electrocatalysts combining high surface area (628 m2 g−1) and catalytic activity for O2 reduction at near-neutral pH. The electrocatalysts were integrated on carbon cloth and carbon paper to obtain gas diffusion electrodes whose architecture was optimized to maximize MFC performance. Excellent cell performance was achieved with the carbon-paper-based cathode modified with the Fe-based electrocatalysts (maximum power density-PDmax = 1028 mWm−2) compared to a traditional electrode design based on carbon cloth (619 mWm−2), indicating the optimized cathodes as promising electrodes for energy recovery in an MFC application. [ABSTRACT FROM AUTHOR]

Cultural institutions hold a unique position of influence, serving as hubs of education and knowledge dissemination for the people they serve. Embracing sustainable energy use in buildings in zoos and botanical gardens is a commitment to environmental responsibility that reinforces these institutions as trusted sources of information and community leaders on climate change, one of the most vital issues of our time. Sustainable energy solutions can synergize operations with educational missions, allowing zoos and botanical gardens to lead by example and inspire visitors to adopt eco-friendly practices in their own lives. In this opinion paper, Phipps Conservatory and Botanical Gardens President and CEO Richard Piacentini discusses key elements in developing a sustainable building energy plan, reviews potential barriers to implementation, and makes a case for adopting regenerative thinking and new metrics for measuring success—citing example cases from Phipps' Center for Sustainable Landscapes (CSL) project. Additionally, the paper demonstrates how green building certification systems and peer-based resource networks like The Climate Toolkit can help guide institutions in the process. [ABSTRACT FROM AUTHOR]

In light of growing concerns regarding greenhouse gas emissions and the increasingly severe impacts of climate change, the global situation demands immediate action to transition towards sustainable energy solutions. In this sense, hydrogen could play a fundamental role in the energy transition, offering a potential clean and versatile energy carrier. This paper reviews the recent results of Life Cycle Assessment studies of different hydrogen production pathways, which are trying to define the routes that can guarantee the least environmental burdens. Steam methane reforming was considered as the benchmark for Global Warming Potential, with an average emission of 11 kgCO2eq/kgH2. Hydrogen produced from water electrolysis powered by renewable energy (green H2) or nuclear energy (pink H2) showed the average lowest impacts, with mean values of 2.02 kgCO2eq/kgH2 and 0.41 kgCO2eq/kgH2, respectively. The use of grid electricity to power the electrolyzer (yellow H2) raised the mean carbon footprint up to 17.2 kgCO2eq/kgH2, with a peak of 41.4 kgCO2eq/kgH2 in the case of countries with low renewable energy production. Waste pyrolysis and/or gasification presented average emissions three times higher than steam methane reforming, while the recourse to residual biomass and biowaste significantly lowered greenhouse gas emissions. The acidification potential presents comparable results for all the technologies studied, except for biomass gasification which showed significantly higher and more scattered values. Regarding the abiotic depletion potential (mineral), the main issue is the lack of an established recycling strategy, especially for electrolysis technologies that hamper the inclusion of the End of Life stage in LCA computation. Whenever data were available, hotspots for each hydrogen production process were identified. [ABSTRACT FROM AUTHOR]

Inland areas have been affected by demographic and economic decline over the past decades. New economic models, which are more focused on a humane quality of life, encourage a revival of these territories as newer, healthier places for living. This paper focuses on minor centers, rethought as energy communities and how these can sustain themselves and become new places of living. The first part of the research critically analyzes current strategies of SECAPs (Sustainable Energy and Climate Action Plans) in smaller historic urban centers. The second part of the paper starts with the typological, morphological, and technological interscalar analysis of two case studies, testing a repeatable expeditious knowledge collection and an intervention method on them. For urban environments, the hypothesized interventions include the management of energy production from renewable sources that are compatible with the presence and value of urban and built heritage; concerning rural territories, an agro-energy park is proposed. The document aims to provide a repeatable method for planning strategic actions within SECAPs in smaller urban centers with a high historical connotation. The case studies show that energy self-sufficiency can be an opportunity to valorize the urban center while favoring environmental sustainability and local development. [ABSTRACT FROM AUTHOR]

As the demand for sustainable energy solutions grows, there is a critical requirement for continuous innovation to optimize the performance and safety of renewable energy systems (RESs). Closed-loop digital twins (CLDTs)—synchronized virtual replicas embedded with real-time data and control loops to mirror the behavior of physical systems—have emerged as a promising tool for achieving this goal. This paper presents a systematic literature review on the application of digital twin (DT) technology in the context of RESs with an emphasis on the impact of DTs on the efficiency, performance, and safety assurance of RESs. It explores the concept of CLDTs, highlighting their key functionalities and potential benefits for various renewable energy technologies. However, their effective implementation requires a structured approach to integrate observation, orientation, decision, and action (OODA) processes. This study presents a novel OODA framework specifically designed for CLDTs to systematically identify and manage their key components. These components include real-time monitoring, decision-making, and actuation. The comparison is carried out against the capabilities of DT utilizing the OODA framework. By analyzing the current literature, this review explores how DT empowers RESs with enhanced efficiency, reduced risks, and improved safety assurance. [ABSTRACT FROM AUTHOR]

The concept of sustainability introduced in 1987 has characterised the world of research in the AEC (Architecture, Engineering, and Construction) sector, directing it to try to tackle the problems inherent to the impacts of climate change on buildings. In addition, the advent of COVID-19, disrupting the world and people's habits, has obviously also strongly affected the academic world. Indeed, this paper aims to analyse the changes and differences between the pre- and post-pandemic periods through a two-stage hybrid literature review. First, through a systematic literature review, 90 articles were selected, filtered through different keywords (sustainability, climate, architecture, and buildings). Once the reasoned selection of papers had been made, it was possible to proceed to the second phase, which involved a thematic analysis according to the three classic macro themes of sustainability (Environment, Social, and Economic) and the inclusion of a fourth macro theme (Management and Development), which made it possible to reintroduce a holistic view of the problem. The results of this literature review revealed the presence of a growing interest in the topic analysed and a more homogenous distribution across all continents, with no distinction between developed and developing countries. Economic sustainability interests emerge post-COVID-19 through the deepening of the themes of clean energy and direct control of consumption. At the level of Environmental sustainability, on the other hand, COVID-19 replaced the house at the centre of people's lives. In addition, the Management and Development macro theme highlighted the need for an integrated view of the problem and the unexpected return of researchers preferring new constructions, which, despite alternative green approaches and renovations, can guarantee better performance. [ABSTRACT FROM AUTHOR]

This research paper presents a comprehensive review of the literature on microgrid development in the UAE, focusing on the socio-economic costs and benefits, policy frameworks, market dynamics, and environmental implications. The analysis encompasses publications from 2011 to 2021, with a particular emphasis on the United Arab Emirates (UAE) and the Gulf Cooperation Council (GCC) countries. A total of 33 papers were identified and classified, revealing gaps in comprehensive valuation models, consideration of environmental and social governance factors, and research informing policy and investment decisions. The findings highlight the significance of microgrid technology in the UAE, its limited adoption and commercialization, and its predominant usage in remote areas and academic testbeds. The paper underscores the UAE's vision for net-zero emissions by 2050 and the potential of microgrids in supporting its realization. Recommendations include the development of a comprehensive valuation framework to drive effective investments in microgrid technology, aligning with the UAE's sustainable energy goals. The study contributes to the understanding of microgrid development in the UAE, offering insights into its socio-economic, policy, market, and environmental dimensions. [ABSTRACT FROM AUTHOR]

As the demand for electricity, electrification, and renewable energy rises, accurate forecasting and flexible energy management become imperative. Distribution network operators face capacity limits set by regional grids, risking economic penalties if exceeded. This study examined data-driven approaches of load forecasting to address these challenges on a city scale through a use case study of Eskilstuna, Sweden. Multiple Linear Regression was used to model electric load data, identifying key calendar and meteorological variables through a rolling origin validation process, using three years of historical data. Despite its low cost, Multiple Linear Regression outperforms the more expensive non-linear Light Gradient Boosting Machine, and both outperform the "weekly Naïve" benchmark with a relative Root Mean Square Errors of 32–34% and 39–40%, respectively. Best-practice hyperparameter settings were derived, and they emphasize frequent re-training, maximizing the training data size, and setting a lag size larger than or equal to the forecast horizon for improved accuracy. Combining both models into an ensemble could the enhance accuracy. This paper demonstrates that robust load forecasts can be achieved by leveraging domain knowledge and statistical analysis, utilizing readily available machine learning libraries. The methodology for achieving this is presented within the paper. These models have the potential for economic optimization and load-shifting strategies, offering valuable insights into sustainable energy management. [ABSTRACT FROM AUTHOR]

Modern research has made the search for high-performance, sustainable, and efficient energy storage technologies a main focus, especially in light of the growing environmental and energy-demanding issues. This review paper focuses on the pivotal role of biomass-derived carbon (BDC) materials in the development of high-performance metal-ion hybrid supercapacitors (MIHSCs), specifically targeting sodium (Na)-, potassium (K)-, aluminium (Al)-, and zinc (Zn)-ion-based systems. Due to their widespread availability, renewable nature, and exceptional physicochemical properties, BDC materials are ideal for supercapacitor electrodes, which perfectly balance environmental sustainability and technological advancement. This paper delves into the synthesis, functionalization, and structural engineering of advanced biomass-based carbon materials, highlighting the strategies to enhance their electrochemical performance. It elaborates on the unique characteristics of these carbons, such as high specific surface area, tuneable porosity, and heteroatom doping, which are pivotal in achieving superior capacitance, energy density, and cycling stability in Na-, K-, Al-, and Zn-ion hybrid supercapacitors. Furthermore, the compatibility of BDCs with metal-ion electrolytes and their role in facilitating ion transport and charge storage mechanisms are critically analysed. Novelty arises from a comprehensive comparison of these carbon materials across metal-ion systems, unveiling the synergistic effects of BDCs' structural attributes on the performance of each supercapacitor type. This review also casts light on the current challenges, such as scalability, cost-effectiveness, and performance consistency, offering insightful perspectives for future research. This review underscores the transformative potential of BDC materials in MIHSCs and paves the way for next-generation energy storage technologies that are both high-performing and ecologically friendly. It calls for continued innovation and interdisciplinary collaboration to explore these sustainable materials, thereby contributing to advancing green energy technologies. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the status and future prospects of fuel-cell electric vehicles (FC-EVs). As global concerns about emissions escalate, FC-EVs have emerged as a promising substitute for traditional internal combustion engine vehicles. This paper discusses the fundamentals of fuel-cell technology considering the major types of fuel cells that have been researched and delves into the most suitable fuel cells for FC-EV applications, including comparisons with mainstream vehicle technologies. The present state of FC-EVs, ongoing research, and the challenges and opportunities that need to be accounted for are discussed. Furthermore, the comparison between promising proton-exchange membrane fuel cell (PEMFC) and solid oxide fuel cell (SOFC) technologies used in EVs provides valuable insights into their respective strengths and challenges. By synthesizing these aspects, the paper aims to provide a comprehensive understanding and facilitate decision-making for future advancements in sustainable FC-EV transportation, thereby contributing to the realization of a cleaner, greener, and more environmentally friendly future. [ABSTRACT FROM AUTHOR]

Electric vehicle (EV) adoption grows steadily on a global scale, yet there is no consistent experience for EV drivers to charge their vehicles, which hinders the important EV mass market adoption. The Open Charge Point Protocol (OCPP) is the solution to this challenge, as it provides standardization and open communication between EV infrastructure components. The interplay of the OCPP with open cross-functional communication standards boosters driver experience on the one hand, while the charging station itself is integrated into a renewable energy ecosystem. This paper presents a deep dive into the combination of the OCPP with the OpenADR protocol, the Open Smart Charging Protocol (OSCP), the ISO 15118, and eRoaming protocols to explore possibilities and limitations. Furthermore, we suggest LoRa communication as an alternative to IP-based communication for deep-in building applications. Hence, this paper reveals the next important steps towards a successful EV mass market transition powered by user-friendliness and green energy. [ABSTRACT FROM AUTHOR]

In the context of escalating energy demands and the quest for sustainable waste management solutions, this paper evaluates the efficacy of three machine learning methods—ElasticNet, Decision Trees, and Neural Networks—in predicting energy recovery from municipal waste across the European Union. As renewable energy sources increasingly dominate the energy production landscape, the integration of Waste-to-Energy (WTE) processes presents a dual advantage: enhancing waste management and contributing to the renewable energy mix. This study leverages a dataset incorporating economic and environmental indicators from 25 European countries, spanning 2013–2020, to compare the predictive capabilities of the three machine learning models. The analysis reveals that Neural Networks, with their intricate pattern recognition capabilities, outperform ElasticNet and Decision Trees in predicting energy recovery metrics, as evidenced by superior performance in key statistical indicators such as R-value, Mean Squared Error (MSE), and Mean Absolute Error (MAE). The comparative analysis not only demonstrates the effectiveness of each method but also suggests Neural Networks as a pivotal tool for informed decision-making in waste management and energy policy formulation. Through this investigation, the paper contributes to the sustainable energy and waste management discourse, emphasizing the critical intersection of advanced technologies, policy considerations, and environmental stewardship in addressing contemporary energy challenges. [ABSTRACT FROM AUTHOR]

Sustainable energy presently represents the energy of the future, which should be based on the application respecting the importance of energy priorities, increasing regional self-sufficiency, regional control of energy, and regulation of resource use. In the area of energy supply, the use of RES has been increasingly popular, mainly due to the instability in the energy market and the political situation worldwide. Paper's ambition is to evaluate the efficiency of the selected RES use in the specific conditions of Slovakia, with the aim to achieve the EU targets. This is important due to the increasing use of RES in Slovakia. The objective of this paper is achieved through an analysis of the energy profit of the RES system, comparing the costs of the proposed solutions. The evaluation is carried out by calculating the energy and economic efficiency of three possible buildings used in the research. Using the data obtained, the results show the most suitable alternative for each building. The resulting findings provide a valuable insight for governments in identifying the best projects for RES use. The result will be methodology creation as a base for local administration and communities to elaborate plans with a goal to extend RES use. [ABSTRACT FROM AUTHOR]

Microgrids are small power systems, often equipped with renewable energy sources, that are alternatives or supplementary to utility grids. Many studies have been conducted on the design and implementation of microgrids and their interconnects to utility grids, and investigations have been extended to the use of Internet of Things technology (IoT) to monitor and operate such power grids. However, the broad applications of the IoT technology itself also call for a green energy solution. This paper investigates how to power local IoT applications via an integration of a microgrid and the utility grid. Together, we call such a system an IoT microgrid. The goal of an IoT microgrid is to maintain the availability of IoT applications while saving energy costs, and this is achieved by sustaining IoT applications via local renewable energy from a microgrid and by mitigating the intermittent power supply using the utility grid. This paper characterizes the IoT microgrid and proposes a configurable cyber-physical testbed for its design and validation. The testbed incorporates the hardware-in-the-loop (HIL) approach, where real-time simulation is integrated with physical elements for quick prototyping of those components in an IoT microgrid. The paper concludes with an example implementation of the proposed testbed, which demonstrates its use for validating both an IoT microgrid and the IoT application it sustains. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive exploration of a hybrid energy system that integrates wind turbines with photovoltaics (PVs) to address the intermittent nature of electricity production from these sources. The necessity for such technology arises from the sporadic nature of electricity generated by PV cells and wind turbines. The envisioned outcome is an emissions-free, more efficient alternative to traditional energy sources. A variety of optimization techniques are utilized, specifically the Particle Swarm Optimization (PSO) algorithm and Electric Eel Foraging Optimization (EEFO), to achieve optimal power regulation and seamless integration with the public grid, as well as to mitigate anticipated loading issues. The employed mathematical modeling and simulation techniques are used to assess the effectiveness of EEFO in optimizing the operation of grid-connected PV and wind turbine hybrid systems. In this paper, the optimization methods applied to the system's architecture are described in detail, providing a clear understanding of the intricate nature of the approach. The efficacy of these optimization strategies is rigorously evaluated through simulations of diverse operating scenarios using MATLAB/SIMULINK. The results demonstrate that the proposed optimization strategies are not only capable of precisely and swiftly compensating for linked loads, but also effectively controlling the energy supply to maintain the load's power at the desired level. The findings underscore the potential of this hybrid energy system to offer a sustainable and reliable solution for meeting power demands, contributing to the advancement of clean and efficient energy technologies. The results demonstrate the capability of the proposed approach to improve system performance, maximize energy yield, and enhance grid integration, thereby contributing to the advancement of renewable energy technologies and sustainable energy systems. [ABSTRACT FROM AUTHOR]

This paper delves into the critical role of tax credits, specifically Sections 45Q and 45V, in the financing and economic feasibility of low-carbon-intensity hydrogen projects, with a focus on natural-gas-based hydrogen production plants integrated with carbon capture and storage (CCS). This study covers the current clean energy landscape, underscoring the importance of low-carbon hydrogen as a key component in the transition to a sustainable energy future, and then explicates the mechanics of the 45Q and 45V tax credits, illustrating their direct impact on enhancing the economic attractiveness of such projects through a detailed net present value (NPV) model analysis. Our analysis reveals that the application of 45Q and 45V tax credits significantly reduces the levelized cost of hydrogen production, with scenarios indicating a reduction in cost ranging from USD 0.41/kg to USD 0.81/kg of hydrogen. Specifically, the 45Q tax credit demonstrates a slightly more advantageous impact on reducing costs compared to the 45V tax credit, underpinning the critical role of these fiscal measures in enhancing project returns and feasibility. Furthermore, this paper addresses the inherent limitations of utilizing tax credits, primarily the challenge posed by the mismatch between the scale of tax credits and the tax liability of the project developers. The concept and role of tax equity investments are discussed in response to this challenge. These findings contribute to the broader dialogue on the financing of sustainable energy projects, providing valuable insights for policymakers, investors, and developers in the hydrogen energy sector. By quantifying the economic benefits of tax credits and elucidating the role of tax equity investments, our research supports informed decision-making and strategic planning in the pursuit of a sustainable energy future. [ABSTRACT FROM AUTHOR]

Low or even zero carbon dioxide emissions will be an essential requirement for energy supplies in the near future. Besides transport and electricity generation, industry is another large carbon emitter. Hydrogen produced by renewable energy provides a flexible way of utilizing that energy. Hydrogen, as an energy carrier, could be stored in a large capacity compared to electricity. In Sweden, hydrogen will be used to replace coal for steel production. This paper discusses how the need for electricity to produce hydrogen will affect the electricity supply and power flow in the Swedish power grid, and whether it will result in increased emissions in other regions. Data of the Swedish system will be used to study the feasibility of implementing the hydrogen system from the power system viewpoint, and discuss the electricity price and emission issues caused by the hydrogen production in different scenarios. This paper concludes that the Swedish power grid is feasible for accommodating the additional electricity capacity requirement of producing green hydrogen for the steel industry. The obtained results could be references for decision makers, investors, and power system operators. [ABSTRACT FROM AUTHOR]

This paper presents an energy management strategy using a Stateflow controller related to DC microgrids with the important penetration of renewable energy. The increase in world electricity demand is one of the principal drivers of the exhaustion of fossil fuels and increased greenhouse gas emissions. To solve these problems, several countries have adopted actions for widespread renewable energy deployment, which includes wind energy, solar power, biomass power, tidal, and hydropower. These sources are considered as significant in delivering clean energy and reducing greenhouse gas emissions for sustainable improvement. As these sources play an increasingly vital role in the global energy landscape, the efficient management of these intermittent sources is essential for grid stability and sustainability. This paper aimed to develop an energy management strategy for DC microgrids to supply power to a DC microgrid system. The main objective of this paper was to implement an energy management system to ensure the proper operation of DC microgrid systems utilizing Simulink blocks available in MATLAB/Simulink 2020b software. The simulation results demonstrated that the developed energy management algorithm was unconditionally reliable, ensuring the proper operation of the microgrid systems. Additionally, the results demonstrated that the energy management strategy exhibited robust performance across different scenarios, effectively balancing energy generation and consumption while ensuring the reliable operation of the microgrid system. Moreover, the developed algorithm model presents another advantage, as it enables users to access and to change any control parameters within the DC microgrid. By comparing these results with the literature, the developed energy management algorithm provides safety and the automatic control of the microgrid. [ABSTRACT FROM AUTHOR]

Access to clean energy remains a major issue in developing countries, particularly Sub-Saharan Africa, despite successive policies and the assistance of international institutions or organizations. The United Nations (UN) launched some of the most ambitious initiatives with the Millennium Development Goals and, more recently, the Sustainable Development Goals and Power Africa, a United States (US) government initiative. Sub-Saharan Africa has an important potential in renewable energy for both biogas and solar photovoltaic energy, but they remain underexploited. This paper presents the challenges of access to clean energy in developing countries and the failure of remedial policies mostly based on public–private partnerships (PPPs) in the context of endemic poverty of rural populations. In addition, the development of modern energy technologies remains very limited. Appropriate reforms should be carried out to change the paradigm and allow universal access to clean energy. This paper also addresses the different structural barriers that hinder access to technology in Sub-Saharan Africa and the consequences of access to clean energy in the context of poverty. [ABSTRACT FROM AUTHOR]

The emerging energy transition is particularly described as a move towards a cleaner, lower-carbon system. In the context of the global shift towards sustainable energy sources, this paper reviews the potential and roadmap for hydrogen energy as a crucial component of the clean energy landscape. The primary objective is to present a comprehensive literature overview, illuminating key themes, trends, and research gaps in the scientific discourse concerning hydrogen production and energy policy. This review focuses particularly on specified geographic contexts, with an emphasis on understanding the unique energy policies related to renewable energy in Brazil, Austria, and Germany. Given their distinct social systems and developmental stages, this paper aims to delineate the nuanced approaches these countries adopt in their pursuit of renewable energy and the integration of hydrogen within their energy frameworks. Brazil exhibits vast renewable energy potential, particularly in wind and solar energy sectors, positioning itself for substantial growth in the coming years. Germany showcases a regulatory framework that promotes innovation and technological expansion, reflecting its highly developed social system and commitment to transitioning away from fossil fuels. Austria demonstrates dedication to decarbonization, particularly through the exploration of biomethane for residential heating and cooling. [ABSTRACT FROM AUTHOR]

India, the world's most populous country, is the world's third-largest emitter of greenhouse gases (GHGs). Despite employing several energy sources, it still relies heavily on coal, its primary energy source. Given India's swiftly rising energy demand, this challenges meeting emission reduction targets. In recent years, India has significantly increased investments in renewables like solar and hydrogen. While commendable, these initiatives alone cannot meet the country's expanding energy demands. In the short term, India must rely on both domestic and imported fossil fuels, with natural gas being the most environmentally friendly option. In this context, this paper attempts to forecast energy consumption, natural gas production, and consumption in India until 2050, using both univariate and multivariate forecasting methods. For multivariate forecasting, we have assumed two alternative possibilities for GDP growth: the business-as-usual and the high-growth scenarios. Each of our forecasts indicates a notable shortfall in the projected production of natural gas compared to the expected demand, implying our results are robust. Our model predicts that nearly 30–50 percent of India's natural gas consumption will be met by imports, mainly in the form of LNG. Based on these findings, this paper recommends that Indian government policies emphasize increasing domestic natural gas production, importing LNG, and expanding renewable energy resources. [ABSTRACT FROM AUTHOR]

Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction, traditional deep learning methods often generate predictions for long sequences one by one, significantly impacting the efficiency of model predictions. As the scale of photovoltaic power stations expands and the demand for predictions increases, this sequential prediction approach may lead to slow prediction speeds, making it difficult to meet real-time prediction requirements. (2) Feature extraction is a crucial step in photovoltaic power generation prediction. However, traditional feature extraction methods often focus solely on surface features, and fail to capture the inherent relationships between various influencing factors in photovoltaic power generation data, such as light intensity, temperature, and more. To overcome these limitations, this paper proposes a mid-term PV power prediction model that combines Graph Convolutional Network (GCN) and Informer models. This fusion model leverages the multi-output capability of the Informer model to ensure the timely generation of predictions for long sequences. Additionally, it harnesses the feature extraction ability of the GCN model from nodes, utilizing graph convolutional modules to extract feature information from the 'query' and 'key' components within the attention mechanism. This approach provides more reliable feature information for mid-term PV power prediction, thereby ensuring the accuracy of long sequence predictions. Results demonstrate that the GCN–Informer model significantly reduces prediction errors while improving the precision of power generation forecasting compared to the original Informer model. Overall, this research enhances the prediction accuracy of PV power generation and contributes to advancing the field of clean energy. [ABSTRACT FROM AUTHOR]

In the realm of Natural Gas Combined Cycle (NGCC) power plants, it is crucial to prioritize the mitigation of CO2 emissions to ensure environmental sustainability. The integration of post-combustion carbon capture technologies plays a pivotal role in mitigating greenhouse gas emissions enhancing the NGCC's environmental profile by minimizing its carbon footprint. This research paper presents a comprehensive investigation into the integration of solar thermal energy into the Besmaya Natural Gas Combined Cycle (NGCC) power plant, located in Baghdad, Iraq. Leveraging advanced process simulation and modeling techniques employing Aspen Plus software, the study aims to evaluate the performance and feasibility of augmenting the existing NGCC facility with solar assistance for post-carbon capture. The primary objective of this research is to conduct a thorough simulation of the Besmaya NGCC power plant under its current operational conditions, thereby establishing a baseline for subsequent analyses. Subsequently, a solar-assisted post-combustion capture (PCC) plant is simulated and seamlessly integrated into the existing power infrastructure. To accurately estimate solar thermal power potential at the Baghdad coordinates, the System Advisor Model (SAM) is employed. The integration of solar thermal energy into the NGCC power plant is meticulously examined, and the resulting hybrid system's technical viability and performance metrics are rigorously evaluated. The paper contributes to the field by providing valuable insights into the technical feasibility and potential benefits of incorporating solar thermal energy into conventional natural gas power generation infrastructure, particularly in the context of the Besmaya NGCC plant in Baghdad. The power generation capacity of the plant was set at 750 MW. With this capacity, the annual CO2 generation was estimated at 2,119,318 tonnes/year which was reduced to 18,064 tonnes/year (a 99% reduction). The findings aim to inform future decisions in the pursuit of sustainable and efficient energy solutions, addressing both environmental concerns and energy security in the region. [ABSTRACT FROM AUTHOR]

In recent years, the growing demand for efficient and sustainable energy management has led to the development of innovative solutions for embedded systems. One such solution is the integration of hybrid nanogrid energy management systems into various applications. There are currently many energy management systems in different domains, such as buildings, electric vehicles, or even naval transport. However, an embedded nanogrid management system is subject to several constraints that are not sufficiently studied in the literature. Indeed, such a system often has a limited energy reserve and is isolated from any energy supply for a long time. This paper aims to provide a comprehensive overview of the current state of research, advancements, and challenges in the field of hybrid nanogrid energy management systems. Furthermore, it offers a comparative analysis between hybrid nanogrids and microgrids and the implications of their integration in embedded systems. This paper also discusses the key components, operation principles, optimization strategies, real-world implementations, challenges, and future prospects of hybrid nanogrid energy management systems. Moreover, it highlights the significance of such systems in enhancing energy efficiency, reducing carbon footprints, and ensuring reliable power supply. [ABSTRACT FROM AUTHOR]