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This paper examines the potential of solar and hydrogen (H 2) energy-based hybrid energy systems for residential applications. The growing need for energy and the demand for sustainable energy sources have led to the development of integrated energy systems that combine renewable energy resources to meet energy needs. This paper overviews recent studies on hybrid energy systems for on-grid and off-grid residential utilizations. It discusses the system configuration and components of hybrid energy systems, including solar panels, electrolyzers, fuel cells (FC), and batteries. It also covers the technical optimization of integrated energy systems, including sizing, control strategies, and economic analysis. The key findings of this review paper indicate that hybrid energy systems can offer dependable and sustainable energy for residential applications. Through numerical analyses, the optimal dimensioning of the system elements and control strategies can significantly enhance the system's performance and lower the cost of energy. This study also highlights the challenges and opportunities for integrating hybrid energy systems within residential applications. Overall, it provides in-depth perspectives on the possibilities inherent in solar and hydrogen energy-based hybrid energy systems for residential applications. The findings can guide future research and the advancement of hybrid energy systems for sustainable energy solutions. • Comprehensive review on solar and hydrogen-based residential applications. • Holistic approach to system configuration, optimization, and economics. • Detailed analysis of interconnected components enhancing system efficiency. • Unique focus on real-world residential applications and scenarios. • Broad applicability across diverse geographical regions. [ABSTRACT FROM AUTHOR]

Vertical management auditing reforms achieve the centralization of audit institutions. The centralized structure of the auditing institutions affects their performance. This paper verifies the positive effect of vertical management auditing reform on carbon productivity through a difference-in-differences method. The conclusion still holds after robustness tests. Moreover, the policy effects only make sense when government officials face low promotion pressure or high public scrutiny pressure. The mechanism analysis shows that the vertical management auditing reform can improve carbon productivity by strengthening environmental regulation, promoting industrial structure rationalization, and improving regional green innovation and energy efficiency. This paper enriches the research on the relationship between auditing centralization and carbon productivity. [ABSTRACT FROM AUTHOR]

To enhance the utilization of clean energy sources, such as wind power and photovoltaic within virtual power plants, and mitigate carbon emissions, this paper proposes a virtual power plant participation in the electricity carbon joint market optimization operation model based on ensemble empirical mode decomposition–improved bat algorithm (IBA)–Markov chain new energy output prediction. First, complementary set empirical mode decomposition is performed on historical data to construct a Markov chain based wind power and photovoltaic prediction model optimized by IBA. Second, this prediction model is used to predict the daily generation power of wind power and photovoltaic power. Finally, with the optimization goals of maximizing the benefits and minimizing the carbon costs of virtual power plants, a virtual power plant system participating in the electricity carbon joint market model based on wind power and photovoltaic output prediction results is constructed. At the same time, demand response factors are introduced and solved using the NSGA-II algorithm. Taking a certain park as an example for simulation analysis, the research results show that the combined effect of carbon market and demand response can achieve 99.82% of new energy consumption in virtual power plants without significantly reducing profits, basically achieving complete new energy consumption, demonstrating the effectiveness of the proposed model in this paper. [ABSTRACT FROM AUTHOR]

Hydrogen is a kind of clean renewable energy with great development potential. However, traditional electrocatalytic water splitting methods often require high energy consumption and expensive catalysts, which limits their practical application. Transition metal selenides (TMSes), as a new type of hydrogen production materials from electrolytic water, have been the focus of research in recent years. The basic principle of electrochemical water cracking and the preparation of TMSes are reviewed in this paper. The electrocatalysts for hydrogen evolution, oxygen evolution and integral water cracking based on TMSes, including single metal selenides, binary metal selenides, and multinary mixed metal selenides, are discussed. Finally, the future research direction and the development prospect of TMSes electrocatalysts are prospected. • Eley-Rideal and Langmuir-Hinshelwood mechanisms were used to analyze the OER reaction mechanism. • The production and properties of transition metal selenides in recent years are introduced in detail. • In this paper, transition metal selenides are introduced from single TMSes, binary TMSes and multinary mixed TMSes. • The physical properties and electronic structures of transition metal selenides are described in detail. [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]

This paper reviews evidence on how the fast growth in renewable energy technologies can trigger social tipping dynamics that potentially accelerate a system-wide energy transition. It does so by reviewing a variety of literature across several disciplines addressing socio-technical dimensions of energy transitions. The tipping dynamics in wind and solar power create potential for cascading effects to energy demand sectors, including household energy demand. These most likely start with shift actions and adoption of household-scale batteries and heat pumps. Key enablers are strong regulations incentivising reductions in demand and setting minimum efficiency levels for buildings and appliances. While there is evidence of spillovers to more environmentally friendly behaviour, the extent of these and the key leverage points to bring them about present a knowledge gap. Moreover, these behavioural feedback loops require strong additional policy support to "make them stick". Understanding the economic and social tipping dynamics in a system can empower decision-makers, fostering realistic energy transition policies. This paper highlights energy communities as a promising niche for leveraging tipping dynamics. Ultimately, bridging the gap between these tipping dynamics and institutional reforms is crucial for unlocking the full potential of sustainable energy systems. [ABSTRACT FROM AUTHOR]

The object of the research of the article is transport system of a city. The paper reviews the necessity to assess the greenhouse emissions in the city and proposes the methods for greenhouse emissions inventory of the urban transport system. The proposed approach is aligned with guidelines for the development of Sustainable Energy and Climate Action Plan (SECAP) of Mayor Covenants of European Union (EU). The methodologies outlined in the paper allow to estimate annual greenhouse emissions from transport sector. The SECAP defines transport sectors based on ownership and functioning as following: municipal transport fleet, public transport, and private and commercial transport. The paper proposes the methodology to estimate direct and indirect emissions in each of the described sector based on the information that is typicaly available to municipalities in Ukraine. The assessment is conducted on disaggregated level for different fuel types (diesel, petroleum, natural gas, biofuel, electricity, etc.) and separately for each fleet type (buses, trucks, passenger vehicles, specialized machinery). Total CO2 emissions are then estimated by multiplying the amount of fuel consumed by the emission factor for each fuel type and vehicle type. Information of fuel consumption is estimated based on annual milage and estimated based on available data and number of assumptions proposed in the paper. The proposed methodology for greenhouse emissions inventory for the transport sector allows to analyze available data, recommendations for data collection and a methodology for determining CO2 emissions from the operation of the transport system with sufficient accuracy of calculations. Based on these results, it is possible to forecast changes in energy consumption and emissions in the transport sector as a result of various interventions. For example, in Zhytomyr city the results of inventory were used to develop a set of measures, which include updating the rolling stock of electric transport; increasing the energy efficiency of the power grids of the transport system, developing cycling infrastructure. [ABSTRACT FROM AUTHOR]

Summary: With the rapid development of the global renewable energy source field, the importance of dynamic index processing technology in distributed energy systems has become more and more obvious. To better improve the real‐time dynamic interaction means of microgrids in the energy Internet and optimize the relevant methods for microgrid energy consumption detection, this article proposes to introduce the distributed Hadoop platform into the electrical thermal coupling multivariate data in the form of cluster configuration, and then use the Spark framework to detect and capture real‐time data, to complete the tracking and analysis of energy consumption data. At the same time, the Internet of Things and the cloud intelligent monitoring system are combined to further clean and explore the data, to achieve the in‐depth detection of the energy consumption problem of the microgrid under the premise of reducing the initial investment, and achieve the purpose of reducing the operating cost. In this case, the outliers are detected according to the photovoltaic indicators of photovoltaic power stations, the filtration and purification functions of photovoltaic indicators are used by the nuclear density curve, and the sustainable solar energy is optimized by combining multiple indicators such as wind direction and temperature. Based on reducing energy consumption, the overfitting phenomenon of the controller is controlled, and an optimized controller‐led cloud platform is established. By establishing the objective function model, the robustness of the controller is guaranteed and the detection expectation is satisfied by the experiment of energy consumption data. In addition, when the cloud platform is created, this study uses a genetic algorithm to optimize the controller index and then builds a cloud console detection mechanism that collaborates with the Internet. Through the research, it is found that outliers may lead to the redundancy of energy consumption indicators in the non‐processing state. This study adopts the optimization of energy consumption parameters and the help of a distributed data framework to deal with and effectively solve this problem. In terms of interpolation simulation verification combined with experimental data, this paper proposes to use the Internet of Things, wearable devices, sensors, and other means to monitor the cost of energy consumption, to realize the distributed dynamic storage of massive real‐time data in the process of parallel processing, as well as the evaluation and detection of real‐time data replacement. [ABSTRACT FROM AUTHOR]

There is a great desire to integrate multiple energy systems by forming low-carbon energy hubs. Among various energy platforms, the integration of power and gas networks via Power-to-Gas (PtG) technologies is introduced as a promising solution to enhance the flexibility of power grids and facilitate seamless adoption for high penetration levels of renewable energy resources. In addition, the production of green hydrogen from waste/inexpensive clean electricity has recently been identified as a potential means for large-scale energy storage, deployment of hydrogen mobility, and decarbonization of several processes that utilize hydrogen. As integrated hydrogen-based energy hubs (H 2 Hubs) attract more attention for widespread deployment, the security of such new platforms against various cyberattacks is also becoming a critical topic for investigation. This paper proposes a new data estimation technique, developed and integrated with H 2 Hubs scheduling models, for real-time optimal adaptive collection and organization of the system operating parameters for cybersecurity assessment. A new formulation is presented for the adaptive formation of a newly proposed concept, referred to as the system feasibility area , via real-time acquisition of the system operating information. The created feasibility areas are utilized for real-time post-occurrence detection of the bad scheduling data that is invisible to the existing cybersecurity layers. Numerical studies are conducted to demonstrate the efficacy and feasibility of the proposed model. The results demonstrate that the historical data can be adaptively collected in real time and successfully utilized to create feasibility areas to categorize the system operating points. • An optimal scheduling model is proposed for hydrogen-based energy hubs (H 2 Hubs). • A new data estimation method is developed and integrated with the scheduling model. • A new formulation is given for the adaptive creation of the feasibility area. • Simulation case studies are presented and discussed. [ABSTRACT FROM AUTHOR]

This paper proposes the Hybrid desalination and power generation through parabolic trough collectors. This study aims to examine the feasibility, performance optimization, and economic viability of power-generation plant and hybrid-desalination using multi-stage flash (MSF) and reverse osmosis (RO) technologies assessed by using the parabolic trough collectors (PTC). The objective is to discover the posibilities of this innovative approach in addressing water scarcity and clean energy demands. The studies usually focus on several key aspects. Firstly, it resolves the technical feasibility of integrating MSF and RO technologies with parabolic-trough-collectors to optimize energy efficiency and freshwater production. This involves evaluating the system design, heat transfer mechanisms, and operational parameters.Secondly, performance optimization is a key area of investigation. By optimizing these parameters the aim is to maximize freshwater production while minimizing energy consumption. Thirdly, the economic viability of the hybrid plant will be assessed. This involves considering capital investment, conducting a comprehensive cost analysis, maintenance costs, and operational expenses. The study also evaluates the potential for revenue generation through the sale of excess electricity produced by the system. The potential outcomes of this research include demonstrating the technical-feasibility as well as economic-viability of the hybrid desalination and power generation plant. The findings may indicate that this approach can effectively address water scarcity challenges while contributing to clean energy production. The study may also highlight the environmental benefits of integrating renewable energy sources (RESs) and decreasing greenhouse gas emissions compared to traditional desalination methods.The proposed method is executed in MATLAB platform and compared to various existing approaches. [ABSTRACT FROM AUTHOR]

This paper explores the feasibility of utilizing lead-free multilayer piezo stacks, particularly focusing on Zr-doped 0.95(Bi 0. 5 Na 0.5)TiO 3 -0.05(BaTiO 3) piezoceramics, for energy harvesting. Various lead-free BNT-BT disk samples with different Zr concentrations undergo structural, microstructural, and electrical characterizations. The results illustrate that Zr-doping improves piezoelectric constitutive parameters, notably at a 2.0 mol% concentration. Electromechanical tests were conducted on multilayer piezo stacks, involving variations in electric load, mechanical load, frequency, and number of stacked disks. These tests demonstrate the ability of the multilayer transducer to produce up to 1.5 V (peak) under particular conditions: a 250 Hz frequency, a 10 N mechanical load, and an open circuit electric load, utilizing a stack comprising 5 disks. Employing an analytical mathematical model, an effective d 33 e f f of the system is determined, yielding values ranging from 588 to 625 pC/N for a stack composed of 5 disks. These findings highlight the considerable potential of lead-free multilayer piezo stacks in energy harvesting applications, offering crucial insights for the development of sustainable and eco-friendly energy solutions. [ABSTRACT FROM AUTHOR]

This manuscript explores the relationship between the economic awareness (as a part of energy awareness) of Polish households and their sustainable energy consumption practices. Sustainable consumption is measured by the frequency of behaviors such as turning off electrical devices when not in use, removing mobile device chargers from sockets, switching off lights when leaving a room, preferring showers over baths, using washing machines and dishwashers only when full, and purchasing energy-efficient appliances and light bulbs. Economic awareness is gauged through variables such as knowledge of electricity tariffs, understanding of electric bill components, awareness of electricity prices, exact knowledge of electricity expenses, electricity usage in kWh, knowledge of effective energy-saving methods, and familiarity with the energy efficiency classes of appliances and light bulbs. This study presents profiles of households with high and low economic awareness regarding their electricity expenditures and examines how these profiles differ in their sustainable energy consumption behaviors. This research is based on a survey of 1407 Polish households conducted online in 2023. Data collected from the survey were subjected to statistical analysis and are presented in tables and graphs. The findings are discussed in the context of the existing literature in the field, highlighting the implications of economic awareness on sustainable energy consumption practices. This research contributes to understanding how economic knowledge influences energy-saving behaviors among Polish households, providing insights for policymakers and energy conservation initiatives. One of the key findings of this paper is the significant association between economic awareness, energy-saving knowledge, and the adoption of sustainable energy consumption behaviors among Polish households. This study reveals that households with higher levels of economic awareness demonstrate a notably higher frequency of practices related to sustainable energy consumption compared to those with lower economic awareness. Similarly, households equipped with greater knowledge about energy-saving techniques exhibit a higher propensity to adopt energy-efficient behaviors. This underscores important roles of economic literacy and education in fostering behavioral changes towards more sustainable energy practices, highlighting the importance of targeted interventions and educational campaigns aimed at enhancing economic awareness and promoting energy-saving knowledge among consumers. [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]

To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology. [ABSTRACT FROM AUTHOR]

With the urgent global need to limit warming to 2 °C as well as a localized need in our case study to address rising energy demand amid electrical and thermal network limitations, a critical examination of demand-side energy reductions and the concept of energy sufficiency is needed. This paper contributes to the sparse literature on bottom-up analysis by utilizing Iceland—a leader in renewable energy generation—as a case study to explore the socio-economic factors influencing energy footprints. Our findings reveal significant energy footprints across various consumption domains, particularly housing and mobility, influenced by income levels, urbanization, and lifestyle choices. The study highlights the paradox of a high renewable energy supply leading to potential misconceptions regarding abundant and low-cost energy, resulting in substantial energy consumption-related environmental impacts. Using detailed household consumption survey data, this research provides insights crucial for developing sustainable energy policies that not only target technological advancements but also address the need for a reduction in energy demand and a shift towards energy sufficiency. This work marks a contribution to the literature through the provision of a case study of low income inequality and high energy footprints in a highly renewable energy system context. Further, this work is useful for Icelandic and international policymakers to understand in such high-demand contexts which consumption domains would be most relevant for sufficiency policies. This comprehensive analysis opens pathways for future research to further explore the intersections of energy consumption, socio-economic factors, and well-being, offering a nuanced understanding necessary for crafting sufficiency and demand-side policies aimed at a sustainable energy future. [ABSTRACT FROM AUTHOR]

Energy generation and pollutant emissions are two faces of the same coin, as the current energy sources i.e., fossil energy, are still considered to be major sources of greenhouse gases (GHG). Therefore, shifting to cleaner energy sources imposes itself as an inevitable solution to reduce this environmental cost. In this paper, a hybrid system based on the multi-agent approach and Long Short-Term Memory (LSTM) neural networks to forecast the energy production and its carbon dioxide (CO2) emissions and simulate the potential emission reduction in case of switching to renewable energy sources is presented. The proposed system's architecture consists of combining LSTM models with the agent-based technology, where multiple LSTM forecasting models were trained to forecast the production of each type of the studied energies and then estimate the equivalent emitted CO2 and calculate the influence of the renewable energy inputs on the carbon emissions and the fossil fuels consumption. The simulation process consists of two phases: firstly, each forecasting agent uses a specific LSTM model to forecast short-term energy production. Secondly, these agents send the forecasted values to the coordination agent who is responsible for calculating the total CO2 emissions and the benefits of the renewable energy inputs. [ABSTRACT FROM AUTHOR]

As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia's grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia. [ABSTRACT FROM AUTHOR]

Climate change has emerged as a global focal point, notably affecting vulnerable countries like Pakistan. The country faces heightened risk, prompting concern among many due to its susceptibility to climate-related hazards. An imperative challenge arising from this phenomenon is the necessary shift towards sustainable energy, particularly concerning energy consumption within the building sector. Buildings significantly contribute to daily energy usage and subsequent GHG emissions. In Pakistan, transitioning to energy-efficient building stock holds pivotal importance in mitigating climate change impacts. This hinges on establishing a robust institutional framework and regulatory structure centered around energy efficiency. While Pakistan possesses policies and national guidelines advocating for energy-efficient buildings, their practical enforcement and application remain inadequate. The inception of the Building Energy Code of Pakistan in 1990, based on ASHRAE 90.1 standards, marked a step forward. However, obstacles rooted in institutional weakness and limited capacity building have impeded its effective adoption and adherence. Although the Energy Provisions of 2011 introduced modifications, their scope remained confined mainly to commercial structures. This paper conducts an extensive assessment of Pakistan's existing institutional and regulatory framework for building energy efficiency and transition. Drawing on literature insights and stakeholder perspectives, an in-depth understanding of prevailing policies and institutions uncovers underlying reasons for noncompliance and limited implementation. Additionally, input was gathered from stakeholders through interviews, aiming to identify barriers obstructing the reinforcement of building energy efficiency measures in Pakistan. Discourse and narrative analysis, informed by literature and stakeholder interviews, revealed the significance of awareness, participation, coordination, capacity building, technical expertise, finance, and resources as key factors contributing to deficient compliance and implementation of existing codes and policy guidelines. This paper also proposes actionable recommendations to expedite the transition towards a sustainable, energy-efficient building stock in Pakistan. [ABSTRACT FROM AUTHOR]

In this paper, we selected representative electric buses (EBs) and diesel buses as research cases, aiming to explore a localized method suitable for various vehicle types that can be implemented in any region to measure the carbon emissions of urban buses throughout the lifecycle. We take into account the influence of seasonal factors over the lifecycle. We fully consider the production, assembly, and recycling stages of vehicle systems. We construct a model for estimating CO2 emissions during the fuel cycle. We analyze and compare the impacts of the optimized power grid structure on the lifecycle CO2 emissions of the two types of buses. The results indicate that seasonal factors affect both bus types' energy consumption, with EBs being more sensitive. Carbon emissions primarily stem from manufacturing the body, chassis, and notably, the lithium‐ion batteries, with the latter having a pronounced impact on EBs. A decrease in coal power generation from 71% to 21% in the grid reduced EB fuel‐cycle emissions by 70.7%. Although EBs are sensitive to seasonal factors, they still have the greatest potential for carbon reduction, depending on the proportion of clean energy in the power grid and the production processes of vehicle components. [ABSTRACT FROM AUTHOR]

With the acceleration of the global warming process, the clean energy crisis is becoming serious; conventional energy is unlikely to solve the current crisis, so people pay attention to new energy. As wave energy is widely distributed, renewable, and clean, hundreds of wave energy converters emerge. In order to understand the research progress of wave energy converters better, this paper divides wave energy converters into overtopping type, oscillating water column type, and oscillating body type according to the working principle and divides the oscillating body type into oscillating float type and oscillating pendulum type by different ways of energy capture. Based on the classification, various types of engineering cases, physical tests and digital simulation, and other academic research results are summarized, especially the generation power and energy conversion efficiency of various devices, and some shortcomings and suggestions are put forward, hoping to provide help for readers to study wave energy generation converters. [ABSTRACT FROM AUTHOR]

The need for sustainable integrated energy systems to mitigate environmental impact is hindered by challenges in fluctuating demand, trading reliability, and trustworthiness. This paper proposes an innovative approach to tackle these challenges by introducing a blockchain-based integrated energy system trading model with smart contracts. It is intricately linked with the operation of carbon capture and storage (CCS) technology and power-to-gas (P2G) equipment. The CCS-P2G-coupled operation principle is first outlined, followed by the presentation of a comprehensive system model. The peer-to-peer (P2P) energy trading algorithm is enhanced using the Bloom filtering technique. Leveraging smart contracts, a distributed energy trading mechanism is employed, resulting in a meticulously constructed integrated energy system trading model for CCS-P2G-coupled operation. The proposed model is rigorously evaluated for energy trading efficiency and system performance, revealing significant improvements compared to prior studies and showcasing substantial cumulative benefits. Three operation scenarios are examined, with experimental results highlighting the model's superior carbon emission reduction capacity. This study introduces an innovative paradigm for trading and managing integrated energy systems, holding potential implications for the sustainable development and decarbonization transition of future energy systems. [ABSTRACT FROM AUTHOR]

Open water transposition channels in hot and arid regions, like those in the São Francisco River Integration Project (PISF) in Brazil, suffer significant water losses through evaporation. This paper proposes covering these channels with photovoltaic (PV) panels to reduce evaporation while simultaneously generating clean energy. The research aims to quantify water savings and energy generation potential across all channel lengths and assess whether the generated solar power can substitute grid electricity for powering the transposition pumps during peak hours, thereby enhancing energy efficiency. This study analyzed the state-of-the-art of PV generation and calculated their solar potential. Identified the specific characteristics of PISF channels and watercourses considering the regional geography, meteorology, irradiation, and social peculiarities. And, finally, assessed the feasibility of covering the watercourses with solar panels. The results reveal that covering all current PISF channels with PV panels could save up to 25,000 cubic meters of water per day, significantly contributing to water security and improving the quality of life for the local population. Additionally, the project could generate 1200 gigawatt-hours of electricity annually, meeting the energy demands of the transposition pumps during peak hours and promoting energy efficiency within the project. This research paves the way for utilizing PV technology to address water scarcity challenges and enhance the sustainability of water infrastructure projects in arid regions worldwide. [ABSTRACT FROM AUTHOR]

In today's smart communities, small-scale energy systems are essential for sustainable development and efficient resource management. However, ensuring the confidentiality, safety, and accurate prediction of energy consumption patterns in energy trading is a major challenge. To address these issues, an innovative solution that synergistically combines two cutting-edge technologies: blockchain and machine learning is proposed. This paper unveils a novel approach that harmoniously merges blockchain with the Recalling-Enhanced Recurrent Neural Network (RERNN) to revolutionize energy trading systems called 'Blockchain-Enhanced Energy Trading with Recalling-Enhanced Recurrent Neural Network (BET-RERNN).' Data from IoT-enabled smart devices is securely stored in blockchain blocks, ensuring data integrity and immutability. Blockchain's decentralized nature creates a trust-less environment for energy trading, protecting the privacy and anonymity of participants while maintaining transparency. At the heart of our system lies the advanced machine-learning capabilities of the RERNN model. By processing the data stored on the blockchain, RERNN accurately predicts optimal power generation for small-scale energy systems, enabling smart communities to make informed decisions and optimize their energy consumption. The BET-RERNN scheme provides a plethora of strengths. First, participants can securely engage in energy trading without compromising sensitive information, fostering a more resilient and efficient market. Second, blockchain technology ensures that all energy-related data is protected from tampering and unauthorized access, ensuring system reliability and trust. An in-depth comparison of RERNN's performance to traditional General Regression Neural Network (GRNN) and Gradient Boost Decision Tree (GBDT) methods is conducted. To verify the strategy's effectiveness, MATLAB simulations are employed, demonstrating its real-world applicability and scalability. By combining blockchain and machine learning, a secure and privacy-preserving smart community is established, promoting sustainable energy practices for a greener future. [ABSTRACT FROM AUTHOR]

The green transition is a challenge for the Polish economy and energy sector. In this paper, the expert method of analysis was applied and findings revealed that the challenges and prerequisites for an effective transformation of the power sector mainly include technical, technological and organizational issues of energy production and use. The provision of electricity at competitive prices and with a low carbon footprint, for individual consumers and industry, is a prerequisite for maintaining the well-being of the population and ensuring the competitiveness of domestically produced goods. The ambitious climate policy goals of the European Union require immediate action and call for radical changes in the Polish energy sector; in the coming years, it must drastically reduce the amount of energy produced from fossil fuels and replace it with so-called green energy from renewable sources. The main purpose of this article was to highlight the need to modify Poland's energy policy until 2040 in order to make it more consistent with the ambitious climate goals of the European Union. This article also shows that Poland's energy transition must include a shift from fossil fuels to renewables, while ensuring that energy security is stabilized by the current energy and generation resources. To this end, we discuss the issues of creating reserves in the national energy system for the entire period of Poland's energy transition. [ABSTRACT FROM AUTHOR]

A major goal of the "14th Five-Year Plan" phase is to promote the green transformation of industrial enterprises to address the 'dual carbon' challenge. Utilizing the China Industrial Enterprises Database and the Polluting Enterprises Database, this paper calculates the carbon emissions of Chinese industrial enterprises from 2001 to 2010 at the micro level. It presents an analysis of the heterogeneity of carbon emission efficiency (TPI) in industrial enterprises, as well as the factors influencing corporate TPI. This study finds that enterprises within a subdivided industry exhibit heterogeneous levels of TPI, with carbon emissions largely affected by the structure of energy consumption. The researchers suggest accelerating the transition of industrial enterprises to green technology and argue that carbon emission policies should shift from controlling direct total targets to strengthening market-oriented policy tools. Carbon reduction targets should be more stringent for enterprises with lower TPI, considering the heterogeneity among enterprises. To meet the challenges of emission reduction, industrial enterprises are encouraged to actively reform their energy consumption structure. Government policies should aim to reduce clean energy costs and encourage the use of clean energy by industrial enterprises. [ABSTRACT FROM AUTHOR]

This paper examines the complex relationship between the role of H 2 , carbon emissions and their impact on global warming and the economy. Despite improvements in energy efficiency, fossil fuel consumption continues to increase. CO 2 from industrial activities at high temperatures, such as cement, iron, steel and glass production, have increased rapidly, resulting in an increase in the concentration of greenhouse gases in the atmosphere. These emissions accelerate climate change, leading to dangerous consequences such as increasing average atmospheric temperature and decreasing agricultural productivity. To combat this, it is advocated to reduce CO 2 emissions by using renewable energy sources such as hydroelectricity, biomass, wind solar energy. Current study also discusses carbon reduction methods, including oxy-fuel combustion capture, pre-combustion capture, and post-combustion capture. Despite their unique advantages and disadvantages, these methods play an important role in reducing CO 2 emissions from power plants. Additionally, the article highlights the importance of H 2 as a cornerstone in the development of synthetic fuels and future energy systems. H 2 from renewable sources holds the potential to use carbon-neutral synthetic liquid fuels and revolutionize transportation. Although traditional H 2 production methods are associated with emissions, sustainable H 2 production techniques can facilitate low-carbon fuel production. The article concludes by highlighting the importance of sustainable energy practices and the role of H 2 in reducing carbon emissions, highlighting research efforts to improve production methods, integrate renewable energy, and develop carbon capture technologies for a sustainable future. • Methods used in synthetic fuel production and sources of hydrogen production. • Carbon capture methods and their comparative discussion. • The importance of hydrogen production in synthetic fuel production and future plan. [ABSTRACT FROM AUTHOR]

Photovoltaic panels play a pivotal role in the renewable energy sector, serving as a crucial component for generating environmentally friendly electricity from sunlight. However, a persistent challenge lies in the adverse effects of rising temperatures resulting from prolonged exposure to solar radiation. Consequently, this elevated temperature hinders the efficiency of photovoltaic panels and reduces power production, primarily due to changes in semiconductor properties within the solar cells. Given the depletion of limited fossil fuel resources and the urgent need to reduce carbon gas emissions, scientists and researchers are actively exploring innovative strategies to enhance photovoltaic panel efficiency through advanced cooling methods. This paper conducts a comprehensive review of various cooling technologies employed to enhance the performance of PV panels, encompassing water-based, air-based, and phase-change materials, alongside novel cooling approaches. This study collects and assesses data from recent studies on cooling the PV panel, considering both environmental and economic factors, illustrating the importance of cooling methods on photovoltaic panel efficiency. Among the investigated cooling methods, the thermoelectric cooling method emerges as a promising solution, demonstrating noteworthy improvements in energy efficiency and a positive environmental footprint while maintaining economic viability. As future work, studies should be made at the level of different periods of time throughout the years and for longer periods. This research contributes to the ongoing effort to identify effective cooling strategies, ultimately advancing electricity generation from photovoltaic panels and promoting the adoption of sustainable energy systems. [ABSTRACT FROM AUTHOR]

Energy management systems (EMSs) play a central role in improving the performance of microgrids by ensuring their efficient operation while minimizing operational costs and environmental impacts. This paper presents a comprehensive study of mixed integer linear programming (MILP) based EMSs developed and implemented in MATLAB 2021a using YALMIP software for the energy management of a new positive energy district in the city of Savona, Italy, as part of the Interreg Alpine Space Project ALPGRIDS. The main objective of this research is to optimize the functioning of the microgrid, focusing on cost efficiency and environmental sustainability. In pursuit of this objective, the EMS undergoes comprehensive testing and analysis, replicating actual conditions and addressing the diverse demands of end-users across typical days throughout the year, considering real electricity selling and purchase prices. The EMS also accounts for the reactive power capabilities of the various technologies integrated into the microgrid. The levelized cost of electricity (LCOE) serves as a metric for assessing curtailment costs, while penalties related to reactive power absorption from the distribution network are appraised in alignment with prevailing regulatory guidelines. The case study provides valuable insights into the practical implementation of EMS technology in microgrids and demonstrates its potential for sustainable energy management in complex urban energy districts. In all scenarios, the battery energy storage system (BESS) and combined heat and power (CHP) are pivotal for load satisfaction and microgrid resilience. BESSs balance supply and demand, which are crucial in periods of low renewable energy availability, while the versatile CHP efficiently addresses energy demands, contributing significantly to overall microgrid effectiveness. Their synergy ensures reliable load satisfaction, showcasing the dynamic and adaptive nature of microgrid energy management across diverse scenarios. [ABSTRACT FROM AUTHOR]

Considering the escalating global warming and its severe consequences, the exploitation of hydrogen, an eco-friendly energy carrier, is gaining great interest. This paper comprehensively reviews the most common hydrogen production, storage, transportation and utilization processes, while their effectiveness is explored from energy, water, economic and environmental perspectives. Their main characteristics, advantages, shortcomings and challenges are discussed as well. The research reveals that the hydrogen's water footprint, energy consumption, carbon emissions, and cost vary significantly depending on the specific technologies used throughout its life cycle, from production to end use. For instance, fossil fuel-based hydrogen production methods, such as steam methane reforming, offer elevated energy performance and cost-effectiveness, but have a significant carbon footprint. In contrast, water electrolysis is environmentally friendly, but requires more water and has lower energy efficiency. Besides, high-pressure containers are the preferred method for hydrogen storage, while liquid and solid storages are better suited for high-energy-density applications. Regarding hydrogen transportation, pipelines are effective over long distances, whereas tankers are convenient for short distances. Furthermore, fuel cells are more energy, carbon and water efficient when using hydrogen as fuel, but they are generally more expensive than internal combustion engines. [Display omitted] • Hydrogen production, storage, transportation and utilization methods are reviewed. • Their energy efficiency, water use, cost, and environmental impact are explored. • Key recommendations to boost the utilization of hydrogen systems are outlined. • Fossil fuel-based technologies are more energy-efficient and cost-effective. • Renewable-based processes are more environmentally friendly but water-intensive. [ABSTRACT FROM AUTHOR]

In this paper, an integrated system is proposed for the production of turquoise hydrogen from methane cracking using solar energy. The produced hydrogen and carbon by-products are used in fuel cells to generate clean electricity. Syngas is produced through power generated via photovoltaics, using a solid oxide electrolyzer cell (SOEC). The SOEC co-electrolyzes the exhaust CO 2 from the direct carbon fuel cell, along with H 2 O. The resulting syngas is subsequently converted into methanol. The system is modelled using Aspen Plus to obtain the thermodynamic evaluation. Mass, energy, entropy, and exergy balances are performed over the system's units. The energy and exergy efficiency of the subsystems is determined, with solar methane cracking system achieving energy and exergy efficiencies of 82.2% and 92.5%, respectively. The overall system produces methanol and generates 7.71 MW of electricity with the overall energy and exergy efficiencies of 40.6% and 37.5%, respectively. • Energy and exergy analysis of an integrated methane cracking system. • Carbon black by-product is used in a direct carbon fuel cell. • Produced CO 2 is co-electrolyzed with water to produce syngas. • Processes modelled on Aspen Plus to obtain thermodynamic evaluation. • The proposed system has an energy and exergy efficiency of 40.6% and 37.5%, respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

For political and economic reasons, renewable sources of energy have gained much importance in establishing a sustainable energy economy. By their very nature, however, their benefits depend on changeable weather conditions, and are unrelated to the generation and consumption patterns in industrial or home environments. This generation–dissipation disparity induces price fluctuations and threatens the stability of the supply system, yet can be alleviated by installing energy depots. While the classic methods of energy storage are hardly cost-effective, they may be supplemented, or replaced, by a distributed system of small-scale hydropower plants with ponds used as energy reservoirs. In this paper, following a rigorous mathematical argument, a dynamic model of a multi-cascade of hydropower plants is constructed, and a cost-optimal controller, with formally proven properties, is designed. On the one hand, it allows for an increase in the owners' revenue by as much as 30% (compared to a free-flow state); on the other hand, it reduces the load fluctuation imposed on the grid and the legacy supply system. Moreover, the risk of floods and droughts downstream resulting from inappropriate use of the plants is averted. [ABSTRACT FROM AUTHOR]

The paper investigates the interplay between clean energy, environmental pollution reduction, and economic growth in the Gulf Cooperation Council (GCC) countries from 1980 to 2019, utilizing the autoregressive distributed lag (ARDL) method. The study underscores the global transition towards cleaner energy sources and its implications for the region. In assessing the determinants of economic growth, the findings reveal a positive and significant short- and long-term impact of energy production, with energy consumption exhibiting a positive and significant effect solely in the long term. The absence of a confirmed relationship in the short term is notable. Causality tests demonstrate a significant link from both energy consumption types to environmental pollution, alongside causal relationships from urbanization, energy production, and consumption to economic growth. Moreover, the results include the pivotal role of energy production in driving GDP growth, caution in short-term energy consumption effects, and significant causal links between energy consumption and environmental pollution. The recommendations to incentivize sustainable energy production, engage in long-term energy consumption planning, and adopt integrated urbanization policies provide actionable insights for policymakers. These suggestions are aimed at guiding the GCC countries in balancing the pursuit of economic growth with environmental sustainability—a delicate equilibrium that necessitates careful consideration of various factors. [ABSTRACT FROM AUTHOR]

The All-electric ship (AES) concept has revolutionized the maritime sector. Indeed, AES is a promising solution for modern vessels where decreasing emission pollution, suppressing fossil fuel consumption, and making economical operation are its brilliant merits. Fuel cell (FC) technology based on clean hydrogen energy sources can play a significant role in meeting these requirements in the AES platform. Because of the slow transient response of the FC, an energy storage system (ESS) is required to improve AES performance in different operation scenarios. Therefore, optimal sizing of the FC and the ESS and proper design of energy management strategy is a challenging problem. This paper proposes a systematic approach for the optimal design of hybrid FC-ESS of AES power systems. The proposed method is based on an optimization technique to determine the optimal sizing of the FCs and the ESS. Capital investment, fuel consumption, personnel electrical safety, and occupied volume of the AES power system are the main objectives. The FC size, the battery size, the scheduled output power of the FC, and the battery are the decision variables. Genetic Algorithm (GA) is used to solve the optimization problem. To validate the numerical results, the optimization problem is also solved by Mayfly Algorithm (MA) separately. To assess the feasibility of the proposed strategy, the optimal design of hybrid FC-ESS for a vessel is implemented based on the proposed method. The simulation results validate the proposed approach's sufficiency to investigate and optimize the economic, safety, and dimensional aspects of designing the FC ship's IPS. Numerical results are reported for each design aspect. Considering the minor differences of the numerical results obtained by GA and MA, the optimum points are validated by the two techniques. Using the obtained results, various perceptions can be derived from the FC ship's IPS design. For example, the IPS cost in the cases with optimum volume, weight, and safety, has 2.3%, 2.6%, and 7.3% penalties, respectively compared to the case with the minimum cost. • Fuel cell-based electrification of a fishing ship based on practical information. • Systematic approach for optimal power system design of hydrogen-powered ship. • Proposing safety objective function for integrated power system of fuel cell ship. • Fuel cell hybrid IPS optimization based on volume, mass, cost and safety. • Estimation of propulsion power demand based on ship's resistance and speed profile. [ABSTRACT FROM AUTHOR]

The global aluminium industry faces a serious challenge in reducing greenhouse gas emissions as the demand for aluminium continues to increase. The aluminium industry has a responsibility to streamline its energy consumption, especially in the production process. There have been many studies discussing energy consumption performance in the industry. However, most of them only discuss energy saving partially, without involving energy consumption with various items produced. This paper proposes an energy savings measurement in the manufacturing industry. An energy baseline consumed per unit volume has been developed using the equivalent volume method with an energy management control system (EMCS). The study takes a case example from the automotive--aluminium component industry. The steps taken in the study are: examining the production process, converting the production volume to equivalent, calculating the energy consumption ratio, developing an energy baseline, simulating the savings performance, and then proposing an EMCS with key performance indicators (KPI) for sustainability. The results show that the development of a baseline using the ratio of energy and an equivalent volume of production gives a better data correlation with an R² value close to one. From the baseline, the bestdemonstrated performance (BDP) can be used as a reference to set energy goals. Furthermore, the data and the deviant deleted have the same baseline value. They differ in energy reduction goal percentages. The practical application of this study is not only in the manufacturing industry but in other industries as well, such as building management. This study contributes to energy savings achieved with EMCS. [ABSTRACT FROM AUTHOR]

This paper explores the innovative application of Quality of Service (QoS) principles, traditionally rooted in network and telecommunications, across various sectors to enhance the achievement of the United Nations Sustainable Development Goals (SDGs). By establishing a parallel between QoS in technological systems and sectors such as healthcare, education, energy, and urban development, we examine how these principles can be adapted to improve service delivery and efficiency in critical areas of sustainable development. The core premise is that methodologies used to optimize data flow and service reliability in networks can similarly enhance the quality, accessibility, and sustainability of essential services. This study conducts a comprehensive comparative analysis to illustrate the potential of QoS frameworks in promoting efficiency, effectiveness, and equity across multiple domains of the SDGs. Key areas of focus include enhancing healthcare outcomes, increasing educational accessibility, ensuring sustainable energy use, and improving urban infrastructure. The findings advocate for a cross-disciplinary approach to applying QoS principles, suggesting that such integration can lead to substantial improvements in service delivery and contribute significantly to global sustainable development efforts. [ABSTRACT FROM AUTHOR]

In recent times, the research in sustainable energy resources was integrated with the control approaches of various hybrid renewable energy systems for balancing the electricity generation. The accelerated hybrid energy storage systems and steadily growing energy consumption make the variability and the predictable behavior occur in the renewable energy sources, which requires an energy management system. This paper aims to control hybrid renewable energy systems for power management. The systems consist of photovoltaic (PV) arrays, diesel generators, wind systems with boost converter DC-DC, and inverters. The optimum of the real-time process is less due to prediction errors of multiple renewable sources, which track the output voltage and load current. Model predictive control (MPC) is proposed for problem-solving time operation to address this issue and compensate for the prediction error. The major impact factors, such as optimal split power, stability, reliability of energy, and desired dynamic responses, have been identified by applying the MPC technique. A simulation model has been constructed using MATLAB/Simulink environment to confirm the effectiveness of the MPC technique model. [ABSTRACT FROM AUTHOR]

With the wide application of high proportion of distributed clean energy in regional microgrids, the issue of maximizing the utilization of renewable energy among multi-microgrids has become a research hotspot. Based on the proposed multi-microgrids' energy collaborative optimization and complementation model, a multi-microgrids' energy real-time optimization management and dispatch strategy is proposed that fully considers the real-time complementarity of renewable energy between multi-microgrids and achieves the best coordinated dispatch of energy. Two typical scenarios were set up in the IEEE 33-bus network model for verification, and the synergistic effects of different schemes were compared and set up. The data obtained demonstrate that the dispatch and management strategy proposed in this paper can achieve the maximum integration of renewable energy and the lowest operating cost among multi-microgrids, and it also validates the real-time, feasibility, and effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Rising fossil energy prices and the significantly decreasing prices of energy technology have resulted in electricity consumers having the option to install solar PV rooftops to rely on the self-consumption of clean energy. However, the increase in this amount is affecting the revenue of electricity as a utility, which must adapt and develop its business model to accommodate the situation. If the utility cannot be adapted in time, it may lead to a loss of income from services and the sale of electricity from fossil energy. The utility in Thailand's electricity market that acts as the distribution system operator (DSO) is known as the Provincial Electricity Authority (PEA), and the Metropolitan Electricity Authority (MEA) is responsible for managing distribution networks and customers. There are four types of solar rooftop-as-a-service (RaaS) business perspectives they could consider as opportunities through which to minimize revenue impact. The business services were designed for the DSO customer as follows: Consulting, Design, and Installation (CDI); Operation and Maintenance (O&M); Energy Service Company (ESCO); and Power Purchase Agreement (PPA). The model comprises four customer segments: residential buildings and small-, medium-, and large-scale commercial buildings. This paper applies SWOT, Five Forces, 4P marketing, and economic impact analyses to identify the possibilities when using the DSO business model. The SWOT analysis demonstrates that ESCO and PPA are strengths in the DSO's performance characteristics and existing customer data. In the electricity industry, both models offer enormous customer bargaining power in terms of a Five Forces analysis. The main reason is that there is currently high competition in the installation service. In the 4P analysis result, the price per unit is found to be significantly lower than in residential scenarios. Therefore, there is a format for presenting promotions with an advantage over competitors. Deploying an after-sales service that brings convenience to all customer segments is needed. The economic analysis conducted using Cournot competition game theory shows a significant differential in the Medium (M) and Large (L) customer sectors' competition due to lower technology prices. In conclusion, with the current regulatory framework and criteria, the ESCO and PPA show the best practical model from a utility business perspective. The recommendation for DSO is to create a strategic ecosystem and to link it with private companies as their partnership business. [ABSTRACT FROM AUTHOR]

This article discusses the challenges and importance of building energy efficiency and the role of incentive policies and sustainable business models in achieving energy-saving goals. It highlights the various monetary incentive tools, such as grants, subsidies, and tax rebates, that have contributed to the rise of sustainability-focused entrepreneurial practices. The article also introduces a special issue on building energy efficiency, which aims to address the prospective challenges in incentive policies and entrepreneurial approaches. It includes papers that analyze energy use and efficiency at the city and building type levels, as well as the adoption of cooperative behavior and innovative business models to increase the renovation rate of the building stock. [Extracted from the article]

• A bibliometric analysis of the relevant literature on tunnel lighting was conducted. • The literature is sorted by energy saving, visual comfort, and low carbon. • The relationship between energy saving and low carbon is discussed. • The relationship between energy saving and comfort is also discussed. • The optimization methods of tunnel light environment are summarized. A reasonable and applicative tunnel light environment is important to ensure driving safety. This review aims to contribute to this growing area of research by exploring the tunnel lighting, which expands from safety to visual comfort, energy saving, and low carbon This paper employs bibliometric method to a visual analysis of the relevant literature and summarizes current research efforts and development directions. Firstly, the literature is visually presented by CiteSpace to elaborate the state-of-art with the dimensions of the timeline graph, the keyword co-occurrence graph, and the institutions & countries co-occurrence graph. Afterwards the literature is reviewed from three major perspectives: energy saving, visual comfort, and low carbon. Current research is mainly on luminaire arrangement, auxiliary lighting and other measures to reduce energy consumption. Visual comfort is mainly improved by optimizing the light environment's physical quantities, e.g. luminance, color temperature, color rendering etc. Current measures to achieve low carbon targets include green energy, green photoconductivity, green luminaires and green operation. Energy saving, visual comfort and low carbon are interrelated and complementary. However, a systematic understanding of how tunnel lighting contributes to carbon emission is still lacking. There is still room for development in tunnel lighting to achieve full intelligent control and the goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

As stated in Sustainable Development Goals number 6 and 13, clean water and sanitation and energy-related carbon emissions as climate action issues have emerged as serious issues within the United Nations. Around 150 countries rely on seawater desalination plants as their water resource. Reverse osmosis membrane technology is the most widely used seawater desalination technology for water supply. Taking water resources, developing renewable energy, and recycling resources have become the United Nations' core sustainable development goal. Therefore, this paper aims to provide an overview of renewable energy in reverse osmosis, especially newly developed renewable energy such as wave power. This paper includes technical issues, environment, and economic impact. In addition, compared with other energy sources, photovoltaic and hydropower energy utilization leads to a lower carbon footprint. Both energy produce a carbon footprint of around 0.08 kg CO 2 eq/m3. Control systems and energy storage management are the challenges in developing integrated renewable energy with reverse osmosis. Suitable pretreatment and the effect of direct use of renewable energy on the reverse osmosis process, especially on membrane and pump lifetime, should also be considered in future studies. [Display omitted] • Fluctuations and intermittence in wind and PV would affect on the process performance. • Energy storage management helps to keep the system stable • Water storage can assist in having enough water and store extra • PV and hydropower energy produce carbon footprint around 0.08 kg CO 2 eq/m3. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

In recent decades, the use of fossil fuels has had a harsh impact on the climate, and the frequency and intensity of various extreme weather events have increased, which has triggered an increased the use of renewable energy sources and reflection on technological advances. Many countries are trying to promote renewable energy to reduce their impact on climate change, but the impact of national energy policies in the climate risk framework remains poorly understood. Based on the panel data of 84 developed/developing countries around the world from 2006 to 2019, this paper studies and analyzes the impact of renewable energy use on climate risk. The study found that the increase in the proportion of renewable energy use can reduce the climate risk, and this result is still robust after undergoing robustness tests such as changing variables, samples, and research methods. The findings offer an important solution for European countries, where climate risks are most acute. The heterogeneity analysis shows that the higher the level of economic development, population density and the lower the level of incorruptibility, the weaker the inhibitory effect of renewable energy use on climate risk. The mechanism analysis also shows that the increase in the proportion of renewable energy use can reduce climate risk by reducing carbon dioxide (CO 2), methane (CH 4), nitrogen monoxide (NO), PM2.5 emissions, and the proportion of fossil fuel use, but it does not reduce climate risk by increasing biodiversity. In particular, we find that technological progress has not played a role in the use of renewable energy to reduce climate risk, breaking the stereotype. The policy recommendation of this paper is that under the increasing pressure of climate change, the transition to clean energy is an indispensable option, and the need to accelerate the energy transition becomes more urgent. There is a greater need to further protect biodiversity and enhance technological progress. • The increase in the proportion of renewable energy use can reduce the climate risk. • The mechanism is to reduce CO 2 , CH 4 , NO, PM2.5 emissions and fossil fuels use. • The use of renewable energy cannot reduce climate risks by increasing biodiversity. • The impact of renewable energy use on climate risk is heterogeneous. • Technological progress has not played a role in the use of renewable energy to reduce climate risk. [ABSTRACT FROM AUTHOR]

In the background of exhaustion of the traditional fossil energy sources and environmental deterioration, developing renewable energy has become a strategic choice for countries to achieve energy sustainable utilization and carbon neutrality target. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. However, the commonly used weight calculation methods in the existing renewable energy evaluation have obvious shortcomings, such as the randomness of the subjective method is strong and the gap in the weight allocation of the objective method is too large, which affect the reliability and accuracy of the sorting result. In this paper, a novel weight calculation method based on non-dominated sorting genetic algorithm (NSGA-II) is proposed, and is applied to renewable energy evaluation. The study in this paper focuses on methodology. Firstly, for the linear normalized and Zeros normalized evaluation data, the differences between renewable energy plans in the two normalized evaluation data are measured, and the ranking deviations of the two normalized data are calculated. Then, the multi-objective weight solving model is constructed in terms of plans differences minimization and ranking vectors deviations minimization. The NSGA-II algorithm is applied to the optimization of multi-objective functions to find the Pareto non-dominated solution, so as to determine the weight values of each evaluation index. Finally, the TOPSIS method is used to determine the relative closeness value of each plan, and the rankings of renewable energy technical plans are achieved. Based on the actual renewable energy development data of a province in China, experiments were carried out to investigate the effectiveness of the proposed method. Experimental results show that the proposed method performs better than some popular renewable energy evaluation methods. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Apply non-dominated sorting genetic algorithm II to determine the index weights. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors of renewable energy consumption in the fifth Technology Revolution with specific evidence from ASEAN countries. The study applies an autoregressive distributed lag (ARDL) approach. The paper also uses the unrestricted fixed and random panel data methods. The manuscript identifies significant factors such as technological innovation, governmental policies, public awareness, electricity consumption, country population, foreign direct investment inflows, imports, exports, and economic growth that have influenced the renewable energy sector in these nations. This study also investigates the determinants that influence renewable energy in the context of international integration and the fifth technology revolution in ASEAN countries. The research analyzes data spanning two decades, from 2000 to 2022, through a combination of econometric modeling and machine learning techniques. Preliminary findings indicate that technological innovation, government policies, and public awareness significantly affect renewable energy consumption in these countries. The empirical results offer insights for policymakers and stakeholders in leveraging technological advancements for sustainable energy development. The findings from this study on the determinants of renewable consumption in the context of the Fifth Technology Revolution in ASEAN countries also have several important policy implications for the sustainable development goal. • This study aims to investigate the factors of renewable energy consumption in the fifth Technology Revolution. • The study uses panel data analysis, and the paper identifies significant factors that have influenced the renewable energy sector. [ABSTRACT FROM AUTHOR]

• A new DPV-5G BS-ES communication and power mutual coupling system is developed. • A BSSCP model is proposed to minimize the number of 5G base station deployments. • The ISOM model is used to optimize the microgrid connection lines in 3D space. • Economically optimal simulation experiments are conducted for different PV systems. The emergence of ultra-dense 5G networks and a large number of connected devices will bring with them significant increases in energy consumption, operating costs, and CO 2 emissions. At the same time, the deployment of distributed photovoltaic (DPV) in megacities plays an important role in promoting the integration of "building-photovoltaic", adjusting the city's clean energy supply system, and building a green, and low-carbon smart city. The development of a new "DPV-5G Base Station-Energy Storage (DPV-5G BS-ES)" coupled DC microgrid system and its pre-deployment investment costs are fundamental factors to be considered when the problem of large-scale DPV and BS deployment in cities has to be addressed. There are almost no published papers on this issue in the literature, which only consider the problem of maximizing the deployment of 5G BS service coverage or only perform optimization analyses for the performance of microgrid systems without considering the economic optimality and low-carbon green issues in the construction of urban utilities. In order to solve the problem of 5G BS deployment and economic optimization of topology in the "DPV-5G BS-ES" coupled DC microgrid system, a novel deployment strategy is proposed in this paper. The strategy is divided into: (a) The Geographic Information System (GIS) for extracting and analyzing 3D data from all buildings in the area. (b) A GIS-based formulation of a mixed integer quadratic constrained planning model (BSSCP) under discrete fixed radius coverage constraints is used to delineate building clusters within the area and determine the optimal deployment location of 5G BS under each sub-cluster. (c) An Improved Self-Organizing Mapping (ISOM) model combines GIS and microgrid performance parameters to address the economically optimal connection of grid lines for DPV in 3D space. (d) Simulation experiments were conducted for the power output and profitability of eight different PV panels and tracking systems to calculate the economically optimal type of DPV generation hardware. The experimental results show that the BSSCP model proposed in this study reduced the 5G BS deployment cost input by up to 35.8974 % compared to that of the control experimental model. Meanwhile, the ISOM model obtained an average reduction of 52.3741 % in the cost of connecting cables for the optimized 25 DPV planning and DC microgrid topology. [ABSTRACT FROM AUTHOR]