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This paper presents a detailed techno-economic review and assessment of a hydrogen refueling station (HRS) powered by a grid-connected photovoltaic (PV) system to address the issues of carbon emissions and energy sustainability in transportation. In the study, the HRS system with 1, 3 and 5 MW PV installed capacity for Ankara, the capital city of Türkiye, is considered for different system lifetimes. In the proposed HRS, on-site hydrogen production is achieved through anion exchange membrane water electrolysis (AEMWE) using a grid-connected PV system, and the produced hydrogen is stored in a cascaded storage system and is utilized at the HRS station. In order to evaluate the cost competitiveness and economic viability of the designed HRS system, the levelized cost of hydrogen (LCOH) is determined by considering the initial investment costs, operating expenses and potential revenue streams. The results show that the HRS capacity, PV installed capacity and system lifetime significantly impact the LCOH. The technoeconomic analysis results show that the best system configuration was determined as 8.54 €/kg H 2 in the 20-year long term refueling scenario for a 5 MW installed PV capacity with a daily refueling capacity of 170 kg H 2. This study contributes to the development of sustainable energy infrastructure by providing a comprehensive framework for the design, calculation and economic evaluation of PV-integrated hydrogen refueling stations. The results provide valuable information for policymakers, industry stakeholders, and researchers to help achieve a carbon-neutral transportation sector and promote energy sustainability. • PV integrated onsite hydrogen refueling station is proposed. • Techno-economic evaluation of the HRS was conducted. • The lowest levelized cost of hydrogen (LCOH) was obtained as 8.54 €/kg H 2. • HRS infrastructure required to support hydrogen vehicles through the carbon zero transition. [ABSTRACT FROM AUTHOR]

The competitiveness of hydrogen as a sustainable energy carrier depends greatly on its transportation and storage costs. Liquefying hydrogen offers advantages such as enhanced purity, versatility, and higher density, yet current industrial liquefaction processes face efficiency and cost challenges. Although various large-scale and efficient liquefaction concepts exist in the literature, they often overlook the economic and technical viability of such plants. Here, we addresses this issue by establishing a framework for modeling a large-scale hydrogen liquefaction concept and conducting both technical and economic assessments, with a specific focus on 125 tonnes per day (TPD) high-pressure hydrogen Claude-cycle concept. The technical analysis involves preliminary designs of key process components, while the economic assessment utilizes Aspen Process Economic Analyzer. Our findings indicate that at an electricity price of €0.1/kWh, the Claude-cycle liquefier concept yields a specific liquefaction cost (SLC) of €1.55/kg LH 2 . A sensitivity analysis was performed, which shows that electricity price has a significant influence on the economics. Further investigation on the compressors design shows that incorporating high-speed centrifugal compressors could reduce the SLC by 5.42% and potentially more. Scaling up to 250 and 500 TPD reveals further cost improvements, while cost projections indicate substantial declines as the technology matures. Ultimately, this paper presents novel cost-scaling and experience curves of hydrogen liquefaction technology, demonstrating the compelling economic viability of integrating large-scale hydrogen liquefaction into sustainable energy infrastructure. [Display omitted] • A process model of a large-scale Claude-cycle hydrogen liquefaction plant has been developed for both technical assessment and economic analysis. • The technical evaluation primarily centers on the preliminary design of key process equipment, such as compressors, turbo-expanders, and heat exchangers. • The techno-economic assessment is performed based on the process simulation and equipment preliminary design. • Capital cost estimation is carried out using the Aspen Process Economics Analyzer. • These cost estimations serve as the basis for predicting cost and experience curves of hydrogen liquefaction technology. [ABSTRACT FROM AUTHOR]

As the global market develops for green hydrogen and ammonia derived from renewable electricity, the bulk transmission of hydrogen and ammonia from production areas to demand-intensive consumption areas will increase. Repurposing existing infrastructure may be economically and technically feasible, but increases in supply and demand will necessitate new developments. Bulk transmission of hydrogen and ammonia may be effected by dedicated pipelines or liquefied fuel tankers. Transmission of electricity using HVDC lines to directly power electrolysers producing hydrogen near the demand markets is another option. This paper presents and validates detailed cost models for newly-built dedicated offshore transmission methods for green hydrogen and ammonia and carries out a techno-economic comparison over a range of transmission distances and production volumes. New pipelines are economical for short distances, while new HVDC interconnectors are suited to medium-large transmission capacities over a wide range of distances, and liquefied gas tankers are best for long distances. [Display omitted] • Future hydrogen and ammonia markets will require new-build long-distance transmission. • Energy may be transmitted in dedicated pipelines, liquid tankers or by HVDC lines. • Levelised cost of transmission depends on the transferred quantity and the distance. • Pipelines are the best option over short distances for hydrogen and ammonia. • HVDC has lowest cost for medium distances, tankers are suitable for long distances. [ABSTRACT FROM AUTHOR]

At present, two subsidy policies, which are based on electric vehicle (EV) consumers and EV charging station firms, have been widely implemented in different areas in China to promote EV adoption. However, the effectiveness of subsidy policies is significantly influenced by the indirect network and herd effects, depicting the positive impacts of the numbers of energy infrastructure firms and the sales of vehicles on consumers' utilities, respectively. Taking the aforementioned effects into consideration, this study examines the optimal subsidy policies by developing a Stackelberg game model. The game model analyzes the interaction and decisions of multiple stakeholders (i.e., consumers, energy infrastructure firms, EV and gasoline vehicle manufacturers, and the government). Interestingly, we find that a stronger herd effect will promote EV sales when the unit production cost of EVs is low; however, it will hinder EV sales when the unit production cost is high. Besides, we compare the effectiveness of the two subsidy policies for promoting EV adoption, reducing environmental impacts, and increasing the social welfare. Findings show that the effectiveness of subsidy policies highly depends on the extent of the indirect network and herd effects. Specifically, compared with EV consumers-based subsidy policy, EV charging station firms-based subsidy policy will be more effective in only two conditions: a weak indirect network effect and a strong herd effect. Otherwise, the EV consumers-based subsidy policy will be more effective. The findings of the paper are helpful in enhancing the effectiveness of subsidy policy in China. • Government subsidy cannot always promote electric vehicle adoption. • The indirect network and herd effects affect the effectiveness of subsidy policy. • A stronger herd effect will not always promote electric vehicle sales. • Either consumers or charging station investors can be the best subsidy object. [ABSTRACT FROM AUTHOR]

The safety of energy infrastructure is currently attracting more and more attention. Once accidents happened or improper incident handling, uncontrolled release of huge energy will lead catastrophic consequences. The manuscript takes the hydrogen refueling station as a typical representative of the energy infrastructure. Once the hydrogen in hydrogen refueling stations (HRSs) leaks, it easily forms a combustible cloud and can explode by encountering a heat source. At such a time, effective emergency management can prevent and reduce the impact of accidents. In this paper, the "scene-task-ability" scenario construction method is first applied to HRS leakage and explosive accidents and used to illustrate the risk evolution process during the different stages of an accident. This method separates the emergency tasks of various emergency responders and evaluates their emergency response ability. The values of prevention, preparation, response and recovery are coupled using the time-ordered weighted averaging and time-ordered weighted geometric averaging hybrid operator, in order to derive a systematic and comprehensive evaluation of the safe emergency management of HRSs. Finally, based on the results of the emergency response ability evaluation, targeted and effective suggested measures are proposed to improve the emergency management level of emergency responders. • The "scene-task-ability" method is first applied to HRS accident. • This scenario construction method separates the tasks of emergency responders. • This paper uses the TOWA-TOWGA hybrid operator model for dynamic evaluation. • Measures to improve the emergency level are proposed based on evaluation results. [ABSTRACT FROM AUTHOR]

Smart Cities are complex systems where digital innovations are applied to design enhanced city services and enable public value creation across various domains (e.g., mobility, energy and infrastructure, environment, and so). Such complexity challenges the alignment between city strategies with city services and underlying information systems, leading to providing services that may fail to achieve city goals and meet the needs of citizens. This paper defines a set of design principles to ensure strategic alignment in Smart City Enterprise Architectures (SCEA). The design principles were derived from the literature and validated by smart city domain experts, following a design-oriented research approach. The main contribution of this paper is the formulated design principles that deepen the knowledge of Enterprise Architecture design in the smart cities field. These design principles can be used by researchers and practitioners to guide the design of innovative digital services aligned with urban strategies. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon energy system can be depicted as a "great reconfiguration" from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district. • Hydrogen role in the transition to low carbon energy systems for urban energy district. • Data-driven urban energy modelling using regression-based approaches. • Probabilistic modelling of energy demand in terms of electricity and fuels. • Climate change impact and energy efficiency measures accounting. • Seasonal variations of energy demand patterns from short-term to long-term scenarios. [ABSTRACT FROM AUTHOR]

In recent years, sustainable development has become a challenge for many societies due to natural or other disruptive events, which have disrupted economic, environmental, and energy infrastructure growth. Developing hydrogen energy infrastructure is crucial for sustainable development because of its numerous benefits over conventional energy sources. However, the complexity of hydrogen energy infrastructure, including production, utilization, and storage stages, requires accounting for potential vulnerabilities. Therefore, resilience needs to be considered along with sustainable development. This paper proposes a decision-making framework to evaluate the resilience of hydrogen energy infrastructure by integrating resilience indicators and sustainability contributing factors. A holistic taxonomy of resilience performance is first developed, followed by a qualitative resilience assessment framework using a novel Intuitionistic fuzzy Weighted Influence Nonlinear Gauge System (IFWINGS). The results highlighted that Regulation and legislation, Government preparation, and Crisis response budget are the most critical resilience indicators in the understudy hydrogen energy infrastructure. A comparative case study demonstrates the practicality, capability, and effectiveness of the proposed approach. The results suggest that the proposed model can be used for resilience assessment in other areas. • A Holistic taxonomy of resilience is proposed for hydrogen infrastructure. • A Novel IFWINGS is proposed for advanced qualitative resilience assessment. • Importance of regulation, government preparation, and crisis response budget are discussed. • A Practical and effective application on a real hybrid wind-hydrogen power plant is presented. • Framework provides a tool for promoting sustainable development. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive framework for analysing embodied carbon in TBM tunnelling. • Evaluate module-based carbon outputs with functional units via BIM-driven platform. • Baseline surveys for segmental lining designs and carbon reduction strategies. • Establish correlations between geotechnical parameters and TBM carbon emissions. • Identify limitations of current assessment methods suggesting a holistic framework. Alongside the transition towards sustainable and renewable infrastructure and energy production, tunnelling projects that adopt tunnel boring machines (TBM) continue to increase in size and complexity. Life Cycle Assessment (LCA) methodologies have a significant impact on the Architecture, Engineering and Construction (AEC) industry, with a shift in focus to cost and carbon management across the infrastructure lifecycle through the use of digitalisation techniques and sustainability rating systems. This paper aims to develop a systematic framework to enhance the sustainability of underground infrastructure in the early design and construction stages, aiming for "build clever and efficiently". This framework integrates digitalisation, carbon assessment standards, numerical modelling, and optimisation techniques to assess carbon emissions and establish benchmarks for construction products and processes. The approach uses parametric models to define tunnelling-related entities such as geological formations, TBM, and segments, designed with dimensional constraints that allow for adaptive modelling and interactions. Enabled by building information modelling (BIM) through parametric models enriched with domain properties, module-based carbon accounting is adopted to evaluate the footprint of material- and asset-level key emitters with functional units. Leveraging established databases, baselines for segmental lining designs and carbon reduction strategies are established. Through project-driven case studies, the correlations among geotechnical conditions, tunnel dimensions, and TBM operating parameters are developed to quantify TBM carbon emissions. A prototype programme demonstrates the framework's application on typical metro and road tunnels at different levels of details (LoD). This paper serves as a guideline for conducting embodied carbon assessments specifically tailored to TBM tunnelling, acknowledging the substantial contribution of the TBM construction process, which is controlled by geotechnical conditions. [ABSTRACT FROM AUTHOR]

In this paper, we propose an effective numerical method to solve the one- and two-dimensional time-fractional convection-diffusion equations based on the Caputo derivative. The presented approach employs a hybrid method that combines Lucas and Fibonacci polynomials with the Caputo derivative definition. The main objective is to transform the problem into a time-discrete form utilizing the Caputo derivative technique and then approximate the function's derivative using Fibonacci polynomials. To evaluate the efficiency and accuracy of the proposed technique, we apply it to one- and two-dimensional problems and compare the results with the exact as well as with existing methods in recent literature. The comparison demonstrates that the proposed approach is highly efficient, accurate and ease to implement. [ABSTRACT FROM AUTHOR]

The evaluation of communities' vulnerability to prolonged power outages offers valuable insights for prioritizing improvements in infrastructure resilience, thereby alleviating societal consequences. This study proposes a data-driven approach aiming at developing a Social Vulnerability Index (SoVI) to prolonged power outages leveraging three county-level datasets in California including (1) demographic features, (2) power outage factors, and (3) backup power factors. Furthermore, the study conducts a sensitivity analysis on three distinct datasets under two scenarios (Scenario 1: the current SoVI in 2022, Scenario 2: the prediction of SoVI in the year 2030). The results of Scenario 1 indicate that the counties with more affected customers, the number of power outages, and less education attainment tend to be more vulnerable to power outages in 2022. Scenario 1 reveals that the number of affected customers and power outages are the primary features influencing around 29% and 18% of counties, while educational attainment, public Electric Vehicles (EVs) chargers, and homes with rooftop photovoltaic (PV) substantially impact approximately 32%, 11%, and 8% of counties, respectively. However, in Scenario 2, crucial factors affecting the anticipated SoVI in 2030 include public EV chargers, houses with rooftop PV, power outages, and adults living alone. In contrast to Scenario 1, the prevalence of adults living alone has emerged as a notable factor impacting SoVI in 2030, while both scenarios underscore the pivotal role of EV chargers in influencing SoVI concerning power outages. The proposed SoVI facilitates informed policy decisions and infrastructure improvements in energy resilience, resource allocation, and disaster preparedness, contributing valuable insights for targeted interventions in these domains. • A data-driven approach was proposed to quantify the social vulnerability index (SoVI) to power outages. • This paper applies Principal Component Analysis (PCA) to identify the most correlated features from county-level datasets. • The paper conducts a sensitivity analysis to predict SoVI in2030 and evaluate how counties' dynamics change over time. • This paper provides insights into how policymakers can reduce the social vulnerability to power outages in California. [ABSTRACT FROM AUTHOR]

Pathways to decarbonisation are commonly explored by government and industry through the use of energy system models. However, such models rarely consider where new energy infrastructure might be located. This is problematic as the spatial context of new renewable energy infrastructure will determine, in part, the environmental, social, and technical impacts of the energy transition. This paper presents the ADVENT-NEV model which brings together innovations in energy and natural capital modelling to identify the optimal locations of multiple renewable energy technologies at a national scale and high spatial resolution. Using Great Britain as a case study, the results show how the spatial distribution of renewable energy technologies changes when a natural capital approach is taken. In particular, the least-cost locations for onshore wind farms and bioenergy crops are highly influenced by the value of carbon sequestration, or emissions associated with their land use change. Siting using a natural capital approach produced appreciable ecosystem service benefits, such that the overall welfare gain to society was estimated at nearly £25 B. Overall, this paper demonstrates that understanding the geospatial context of the energy transition is essential to identifying which renewable energy pathways are consistent with decarbonisation and environmental objectives. [Display omitted] [ABSTRACT FROM AUTHOR]

The pressure head generated by the upper reservoir of a pumped hydro energy storage system can be sufficient for creating the pressure gradient required for a reverse osmosis desalination plant. Combined with the fact that many drought-stricken coastal areas have nearby mountains at the necessary elevation for these upper (mountaintop) reservoirs, a symbiotic relationship can be ascertained through the co-location of a pumped storage hydropower (PSH) system with a reverse osmosis (RO) desalination system. Merging PSH and RO into one Integrated Pumped Hydro Reverse Osmosis System (IPHROS) instead of implementing each individually could result in a number of benefits, including reduced capital investment, lower maintenance costs, and a natural mechanism for diluting the highly saline brine discharge generated from the RO process. This paper extends the work of Slocum et al. in 2016, who first introduced the concept of IPHROS, by optimizing the amount of seawater sent to and diverted from the upper reservoir for maximal energy recapture and freshwater production, respectively, while also seeking to maximize the RO system recovery ratio. For this multiobjective optimization, a new reverse osmosis model is created that utilizes a blend of empirical and fundamental equations based on the solution–diffusion model of membrane transport and boundary layer effects that naturally occur along reverse osmosis membranes. Additionally, surrogate models are developed to predict the permeate flowrate and fractional salt rejection rate for a Seamaxx™-440 RO element. Optimizing the presented IPHROS model reveals a 16% decrease in the break even time for IPHROS compared to PSH and RO being implemented individually, and that at the best design with regards to the energy, freshwater, and RO system recovery objectives, 79.5 million kWh of energy and 5.79 million cubic meters of fresh water can be delivered to a population, significant amounts for a population seeking to transition to a renewable energy-based grid and alleviate dire freshwater conditions. Enhanced modeling and optimization, as was initiated in this paper, will eventually aid in IPHROS' large-scale adoption into energy and freshwater infrastructures. • MDO of an Integrated Pumped Hydro Reverse Osmosis System (IPHROS) is presented. • Fractional salt rejection rate and permeate flowrate surrogate models are developed. • Tradeoffs exist between optimal IPHROS designs with respect to different objectives. • IPHROS cost savings results in 16% faster break even time from simple NPV estimates. [ABSTRACT FROM AUTHOR]

• Presents analysis of the governance, processes and branching points of two natural gas transitions in Greece. • Transition 1: a state-led pathway from early plans and visions to technological infrastructures. • Transition 2: a pathway towards governance logics heavily influenced by market-oriented priorities. • During the financial crisis, powerful transnational actors reconfigured regime dynamics. • Shows the value for transition studies of acknowledging the potential influence of transnational actors and their visions. This paper studies the emerging natural gas transitions in Greece from 1966 to 2016. We place the actors and the governing processes in historical perspective, to position the regime actors, their power and their agency in the context of decision making that influenced the transition pathway and its key branching points. We argue that during the two transitions there was a passage from years of politicized visions promoted and dominated by national and local actors to years of contested visions of Greece as a transnational natural gas corridor, promoted both by national and transnational actors. There has been a reconfiguration of the governance logics action space because of the increasing agency and power of transnational actors (the EU and the 'Troika') especially at times of political or financial crisis. The paper shows the importance of considering how transitions are affected by asymmetries in power and agency between national and international actors and indeed between different actors in a state. [ABSTRACT FROM AUTHOR]

[Display omitted] • This paper presents a novel dataset pre-processing method based on a phase-sensitive optical time-domain reflectometry system. • The detection and classification campaign consists of four phases: detection, feature extraction, classification, and evaluation. • A combination of wavelet and normalized differential methods is used for detection to improve the signal-to-noise ratio. • The techniques used are envelope-wrapped, local maxima, averaging, truncation, rearrangement, and random permutation. • The classification performance was considered good, that is higher than 95 %. Intrusion into the critical energy assets area is a serious problem that may cause essential operations to be disrupted. Besides using closed-circuit television to detect early intrusion, perimeter fencing using fiber optic distributed acoustic sensing is becoming popular. This paper proposes a phase-sensitive optical time-domain reflectometry system-based classification of human activities using a coexisting support vector machine which the Gammatone filter cepstrum coefficient envelope as input features. The detection and classification campaign consists of four phases: detection, feature extraction, classification, and evaluation. A combination of wavelet and normalized differential methods is used for detection to improve the signal-to-noise ratio. Simple dataset management methods that use envelope-wrapped, local maxima, averaging, truncation, rearrangement, and random permutation are beneficial for reducing the dimensionality of problems with lower computational power. The classification performance was considered good, which is higher than 95 %. Despite using the legacy classifier algorithm, an improvement in dataset management presented in this paper proves that it is still realistic to implement and does not require demanding computational power to achieve a good classification result. Also, the way datasets are managed in this paper is made to be flexible enough to work with other legacy classifiers. [ABSTRACT FROM AUTHOR]

Impact assessment as a discipline continues to evolve and search for ways to address challenges that are wicked, systemic, and unconventional. More guidance however is required on integrating multi-disciplinary and novel approaches without losing the richness of impact assessments. This paper explores integrating the causal network approach, underpinned by a community well-being framework, into environmental and social impact assessments. We do this by using a hypothetical scenario of large-scale green hydrogen industry in Australia and engage an interdisciplinary team of experts representing a broad experience across the social, economic, and environmental sectors, via interviews and a workshop. The result is a complex detailed causal network, depicting both environmental and social risks and opportunities associated with the hydrogen industry. We discuss using simple and complex versions of causal networks as both are needed to when communicatng with all relevant stakeholders. We found that the causal network approach is useful for the initial scoping of potential social and environmental impacts, especially for a multi-disciplinary team. Three areas were identified to further strengthen such an approach to facilitate a fully-fledged impact assessment in a real case. First, causal relationships need to be evaluated to assess the magnitude of the impacts and identify mitigation measures and incentives. Second, stakeholders, including local communities, should be involved throughout the assessment process, beginning from the conceptualisation of such assessments. Third, the causal network approach presented in this paper is likely to benefit from incorporating ecological frameworks (or similar) to expand environmental pathways in the network. • Structured mapping of cause-and-effect relationships of complex systems. • Use of a community well-being framework for social and biophysical dimensions. • Value in developing complex and simplified representations of reality. [ABSTRACT FROM AUTHOR]

• Integrate natural gas, solar and geothermal energy into park-level integrated energy systems. • Study park-level integrated energy systems' characteristics in china's climate zones. • Propose a confidence interval combination method. • Propose a two-stage optimization model. Park-level integrated energy systems (PIESs) have a unique role in developing communities' energy infrastructure in more economical and sustainable ways. The design and operation of a PIES depend on the energy demand of buildings, which could be significantly affected by climate change. This paper presented the PIES in China's different climate zones (Harbin, Dalian, Changsha, and Haikou). The PIES integrating natural gas, solar and geothermal energy simultaneously produces electric, heating and cooling loads. A two-stage optimal approach was proposed in this paper to model the PIES mathematically. In the first stage, the worst-case scenario was obtained by the confidence interval combination method to optimize the minimum total cost. In the second stage, the operation strategies of following electric loads and following thermal loads were used to optimize the operation cost. The results revealed that the annual total cost of the PIES presented a v–shaped cost curve with the power generation unit (PGU) capacity from 400 kW to 2000 kW. PIES-1, located in Dalian, had the lowest total cost of $0.71 million. The carbon dioxide emissions had the same trend. When the PGU's capacity reached the optimum (1000 kW), the PGU's utilization rate was between 50% and 60% in all scenarios. From Harbin to Haikou, the operation cost gap between PIES-1 and PIES-2 narrowed from $0.18 million to $0.01 million. Moreover, PIES-1, located in Harbin, had the lowest CO 2 emissions. [ABSTRACT FROM AUTHOR]

A smart grid is a developing electrical network of transmission lines, switches, transformers, protection equipment, sensors, and information technologies working together and are the result of a dynamic co-evolution process that leverages the integration of technological advances. These are facing several challenges with renewable energy resources, has high consumption, and the ever-increasing demand for electricity at commercial, residential, and industrial levels. In recent decades, the main grid is facing several challenges related to the integration of renewable energy resources, deployment of grid-level energy storage devices, deployment of new usages such as the electric vehicle, massive usage of power electronic devices at different electric grid stages, and the inter-connection with microgrids and prosumers. This paper aims to identify the challenges, control these perspectives, for attaining the energy infrastructures, to achieve the directions of future research and development, with respect to power generation, transmission, distribution, and consumption. In this study, future smart grids creation and dimensionality reduction with signal handling on the smart grid using, targeted projection pursuit for future smart grids signal analysis is proposed, in which the Signal handling on the smart grid uses Blind equalization and is imposed to transmit the signal which is inferred from the received signal. The smart grid is based on the Non-negative matrix factorization; the Sallen-key topology is implemented to reduce the noise in the signal. Moreover, in this paper, we perform the targeted projection pursuit, the Cognitive Dimensionality Reduction is used for the analysis of n-way arrays, nonlinear dimensionality reduction, and we use the Linear predictive coding, and Hilbert spectrum which represents the spectral envelope of a digital signal of speech in the compressed form. The experiments on the proposed method, show the effectiveness of our method is 92 % well organised with extensive results at Targeted projection pursuit for future smart grids. The signal analysis shows the execution between past research and the ongoing research has achieved an efficiency rate of 92.2 %, in which the current approach outperforms 94.87 % compared existing approach. The analysis of future smart grids creation, Signal Dimensionality Reduction is 75 % higher than the existing analysis. The proposed system flow is performed with more versatility, and energy efficiency is 75.65 % and 34.54 % efficiency than the existing system. • These are facing several challenges with renewable energy resources. • Related to the integration of renewable energy resources. • Aims to identify the challenges, control these perspectives. • The smart grid using, targeted projection pursuit for future smart grids signal analysis. [ABSTRACT FROM AUTHOR]

• The interfacial bond-slip behavior of weathering steel reinforced seawater sea-sand concrete (WSRSSC) structures in corrosive marine environments was investigated. • Simulated marine corrosion tests and push-out tests on the WSRSSC specimens were conducted. • The failure mode, load-slip curve, ultimate bond stress and residual bond stress of WSRSSC specimens were obtained. • A calculation model for the ultimate bond stress and residual bond stress of WSRSSC specimens was proposed. • A four-stage bond-slip constitutive model between weathering steel and seawater sea-sand concrete was established. To improve the durability of marine renewable energy infrastructures, this paper proposed a weathering steel reinforced seawater sea-sand concrete (WSRSSC) structure and investigated its interfacial bond-slip behavior. Forty specimens were designed and underwent simulated marine corrosion tests and push-out tests to explore the effect of various factors, including the corrosion time, shaped steel type, steel section form, seawater sea-sand concrete (SSC) strength, and stirrup spacing. The findings indicated that the ultimate bond stress and residual bond stress increase with higher SSC strength but decrease with greater stirrup spacing. The steel section form significantly affected the ultimate bond stress. With the increase in corrosion time, the ultimate bond stress of WSRSSC specimens first increased and then slowly decreased in the later stages. Weathering steel specimens demonstrated superior corrosion resistance and long-term performance compared to carbon steel specimens. Considering the bond formation mechanism and corrosion damage, the calculation model for the ultimate bond stress and residual bond stress of WSRSSC specimens was proposed. Furthermore, the four-stage bond-slip constitutive model between weathering steel and seawater sea-sand concrete was established, aligning with the bond characteristics of different corrosion degrees and contributing to the numerical simulation of WSRSSC structures in corrosive marine environments. [ABSTRACT FROM AUTHOR]

The accelerating global urbanization demands a paradigm shift in urban energy systems towards sustainability. This paper presents an integrated approach using Ant Colony Optimization (ACO) to optimize the transition from conventional to renewable energy sources in urban areas. The study focuses on minimizing operational costs and emissions by strategically allocating resources between conventional units, hydrogen production, and renewable energy sources. Through extensive simulations and analysis, our approach demonstrates its effectiveness in achieving a balance between economic viability and environmental sustainability. We provide a detailed breakdown of operational costs and emissions, offering valuable insights for policymakers and urban planners. The results underscore the pivotal role of ACO in guiding decision-making processes, ensuring cities transition to cleaner, more efficient energy systems. This research not only contributes to academic discourse but also provides actionable solutions for building greener and economically viable urban energy infrastructures. The methodologies and insights presented here offer a valuable framework for shaping the future of urban energy landscapes in the face of growing environmental challenges. • ACO for Urban Energy: Introduces ACO for efficient urban energy transition. • Simulation Insights: Detailed results guide economic and eco-friendly decisions. • Urban Planning Guidance: Practical solutions for greener urban energy infrastructures. [ABSTRACT FROM AUTHOR]

The integration of smart grids with Advanced Metering Infrastructure (AMI) has bridged the realms of the Internet of Vehicles (IoV) and Electric Vehicles (EVs), yet challenges persist in managing EV Battery Range and charging infrastructure effectively. This paper presents an innovative IoV-based framework tailored for EVs, with a specific focus on forecasting electricity consumption in a Vehicle-to-Grid (V2G) scenario. By exploring the hurdles surrounding electric vehicle usage, the research lays the foundation for Electric Vehicles (EVs). The proposed IoV model optimizes IoT sensor utilization through a fog layer and employs a Back Propagation (BP) neural network for battery State of Charge (SoC) estimation, integrating Principal Component Analysis (PCA) for data dimensionality reduction. Leveraging substantial computing capabilities, the cloud layer predicts Electricity Consumption Data (ECD) associated with EVs in V2G scenarios. Performance evaluation metrics like Akaike Information Criteria (AIC), Mean Error (ME), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE) are assessed across state-of-the-art forecasting algorithms. Incorporating EV potential into the optimal model reveals a significant 10% reduction in electricity demand. This research advances IoV-based frameworks, offering insights to enhance EV efficiency within the broader energy infrastructure. • An innovative Internet of Vehicles (IoV) framework for depicting electricity demand on the demand side in V2G scenarios. • In-depth experimentation and evaluation of the state-of-the-art approaches of clustering and forecasting. • The devised model successfully projected a 10% decrease in demand side for consumers. [ABSTRACT FROM AUTHOR]

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation's energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. This paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events. [Display omitted] • A systematic summer droughts generating capacity assessment framework is developed. • Capacity derating models for various generation technologies are presented. • The impacts of summer droughts on generating fleet in PJM and SERC are studied. • Impact of extreme summer drought on usable capacity of generators is significant. [ABSTRACT FROM AUTHOR]

For twenty years, social scientists have used place concepts to understand energy infrastructure siting. Much of this research stemmed from attempts to provide theoretical explanations that avoid pejorative NIMBY (Not in My Back Yard) assumptions about community objections. Despite a burgeoning literature, a comprehensive review of place-related energy infrastructure research is lacking. This paper addresses this gap for the first time by collating and systematically reviewing a corpus of 190 articles published between January 1999 and March 2022, using search terms combining 'energy' and five place concepts (place attachment, sense of place, place identity, identity of a place, place-technology fit). Content analysis revealed the application of place concepts most frequently to wind energy, as well as nuclear power, fossil-fuel extraction and energy distribution; a high number of journal outlets (n = 76); a prevalence of single case study and survey methods; geographical concentration in developed countries, and a high prevalence of female authors. Bibliometric analysis of key words indicated a hub and spoke structure centered on the term place attachment, with low levels of coherence. 8 research clusters were identified comprising disparate technologies, geographical contexts, concepts and methods. Two of the search terms (identity of a place, place-technology fit) had low prevalence. Analysis revealed the application of place concepts to be highly varied, with 15 place concepts identified that are often not the primary focus of research, and sometimes used superficially. To improve coherence, cumulative learning and rigour in future studies, a lexicon of place definitions and specific recommendations are provided. • A corpus of 190 articles draws on place concepts to research energy infrastructure. • This literature spans diverse technology sectors, countries and numerous journals. • Studies on renewable energy, in particular wind energy, are most prevalent. • Eight clusters with weak coherence are identified, indicating a fragmented literature. • Recommendations to improve coherence, cumulative learning and rigour are provided. [ABSTRACT FROM AUTHOR]

• Comprehensively review 30 state-of-the-art energy infrastructure models using the emerging concept of resilience. • Summarize common topics and typical implementation approaches for the modeling and simulation of energy infrastructures. • Propose five resilience indicators for the evaluation of energy infrastructure models. • Offer insights and future trends for model developers and model users. Abstract Recent years have witnessed an increasing frequency of disasters, both natural and human-induced. This applies pressure to critical infrastructures (CIs). Among all the CI sectors, the energy infrastructure plays a critical role, as almost all other CIs depend on it. In this paper, 30 energy infrastructure models dedicated for the modeling and simulation of power or natural gas networks are collected and reviewed using the emerging concept of resilience. Based on the review, typical modeling approaches for energy infrastructure resilience problems are summarized and compared. The authors, then, propose five indicators for evaluating a resilience model; namely, catering to different stakeholders, intervening in development phases, dedicating to certain stressor and failure, taking into account different interdependencies, and involving socio-economic characteristics. As a supplement, other modeling features such as data needs and time scale are further discussed. Finally, the paper offers observations of existing energy infrastructure models as well as future trends for energy infrastructure modeling. [ABSTRACT FROM AUTHOR]

The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage; solar, wind, hydro, green hydrogen, etc.; renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations. • The nexus between energy transition, energy poverty and their impacts are investigated. • Influence of climate change, COVID-19, geo-politics, and energy infrastructure on energy transition. • Exhaustive prospects and recommendations are rendered. • Requirement for inclusive investigations and recognition of energy poverty. [ABSTRACT FROM AUTHOR]

Offshore wind and wave energies are both important and abundant renewable energy resources. Offshore wind turbines have entered the commercial phase, while wave energy converters are far lagging behind. Combined wind and wave energy conversion system have been proposed and investigated in recent years, to effectively use the ocean space and energy by sharing infrastructures. In this review paper, global wind and wave resources and the potential for combined use are firstly discussed, then various types of combined wind-wave systems are summarized with a new categorization method proposed. Then, a review on conceptual developments and synergies of combined systems based on the new categorization is elaborated on. Numerical methods used in the combined concepts are summarized with a special discussion on control strategy, extreme load effects and survivability. Model testing techniques are also discussed, highlighting the issues due to scaling laws. The economic aspects of the combined system are also discussed with a case study. • A review of global wind and wave energy resources with assessment techniques. • A review on types of combined wind-wave systems, with a new categorization method proposed. • A review on conceptual developments and synergies of combined systems with promising configurations recommended. • Numerical methods and model testing techniques for the combined concepts. • The economic aspects of the combined system. [ABSTRACT FROM AUTHOR]

This paper addresses the challenges inherent in Microgrids (MGs), Renewable Energy Sources (RES), and Plug-in Hybrid Electric Vehicles (PHEVs), presenting a pioneering approach for a sustainable energy future. The focal point is a novel Multi-Stage Dynamic Energy Management (EM) framework, strategically designed to optimize the use of non-dispatchable RES and PHEVs while reducing dependency on the Utility Grid (UG). The research integrates Solar Photovoltaic arrays (SPVs), Wind Turbines (WTs), Micro Turbines (MTs), Battery Energy Storage Systems (BESS), PHEVs, and loads, forming a comprehensive MG to enhance overall efficiency and resilience. The core innovation lies in the dynamic EM framework, minimizing UG dependency and adapting to stochastic RES generation and PHEV charging patterns. The study underscores the significance of demand response in enhancing energy efficiency and grid reliability. Demonstrating effective RES utilization, the research showcases the potential for a greener and more resilient energy infrastructure. Through advanced simulations, the proposed framework's performance is rigorously evaluated under various scenarios, including high RES penetration. The results not only affirm the framework's effectiveness but also highlight its potential to revolutionize MG management by reducing grid dependency and maximizing renewable resource utilization. [ABSTRACT FROM AUTHOR]

• An energy-inclusive SVI indicator system is proposed to increase resilience. • Energy factor extends the inclusiveness and integrity of traditional SVI system. • Energy-inclusive SVI reveals spatial differences in potential social vulnerability. • Uneven urbanization exacerbates risks and inequalities for vulnerable groups. A comprehensive vulnerability assessment is a scientific basis for the realization of the United Nations' sustainable development goals. Energy resilience plays a crucial role in mitigating social vulnerability due to disaster shocks. Often, energy infrastructure and services collapse after disasters. The recent Russia-Ukraine war has exacerbated Europe's energy crisis and social vulnerabilities, making it even more urgent to add energy resilience to vulnerability assessments. This paper takes the Netherlands as the study area for vulnerability assessment, constructs a new social vulnerability indicator (SVI) system supplemented with the energy element, and compares that with the traditional energy indicator system. The results indicate that: 1) The introduction of energy indicators fills the gap of traditional SVI assessment. 2) Energy indicators reveal regional and spatial differences in potential social vulnerability in the Netherlands. 3) Energy-inclusive SVI demonstrates that uneven urbanization exacerbates risks and inequalities for vulnerable groups, with potential impacts on social vulnerability. Sustainable urban development requires the search for a recognized and coordinated approach to managing vulnerability across regions. The complementarity of energy indicators offers opportunities to provide a more comprehensive assessment of spatial patterns of social vulnerability, identify potentially vulnerable areas, enhance urban disaster resilience, and achieve sustainable urban development. [ABSTRACT FROM AUTHOR]

Increased globalization, deregulation of energy markets, and environmental constraints, together with associated uncertainty, have created a highly dynamic and uncertain process manufacturing environment. Responding effectively to this increased variation and uncertainty is critical for a company to remain competitive. In this paper, we consider the plant infrastructure in relation to the energy and global market infrastructures. We describe changes to the plant infrastructure system in order to function more effectively in the current manufacturing environment, as well as key research advances that are aligned to addressing challenges faced by present day plant operation. • Discusses relationship between plant, energy, and global market infrastructures. • Identifies challenges associated with the current plant operating environment. • Discusses industry response to identified challenges. • Overview of PSE tools and paradigms aligned with addressing these challenges. • PSE approaches illustrated in the context of industrial air separation plants. [ABSTRACT FROM AUTHOR]

The decentralization of energy production and recovery of excess heat (EH) to reach climate targets is essential for renewable and fully decarbonized heating systems. This paper identifies current and potential industrial EH sources providing baseload capacity for district heating (DH) systems. These sources are evaluated by sector and process for supplying baseload capacities explored for current 3rd generation district heating (3GDH) and 4th generation district heating (4GDH) systems with lower grid temperatures and losses, with and without expansions. The method combines geographical analysis and available baseload capacity estimations for 360 Danish DH systems scenario-making and an additional sensitivity analysis evaluating baseload capacity full-load hours. It is found that 80 % of Danish DH systems have an unmet baseload capacity of 50 % or higher. Half of the systems have geothermal capacity available and up to 20 % of industrial EH baseload capacity potential, which sums up to 5 PJ of EH potential within a 2 km distance. The findings also suggest that there is an additional opportunity for the placement of future energy infrastructure able to supply EH, which is highly contextual and strategic in heat planning, particularly considering the future development of sustainable and energy-efficient DH systems. • Maps 360 Danish DH systems with expansion potentials for 3GDH and 4GDH. • Identifies 9235 sources and 19.8 PJ of exploitable industrial excess heat. • Spatially evaluates 3 PJ and 5 PJ of EH for supplying 3GDH and 4GDH baseload capacity. • Locates 5–10 GW of total available baseload capacity in Danish DH systems. • Provides placement opportunities for future excess heat sources. [ABSTRACT FROM AUTHOR]

• Solar hydrogen production and blending with natural gas is proposed. • A 3D numerical model for anion exchange membrane electrolyser is developed. • The exergy cost of mixture of the natural gas and hydrogen gas is determined. • 3.44% of carbon dioxide emission is prevented by injecting 10% vol. hydrogen per year. Hydrogen production using solar energy and blending in a natural gas pipeline is a cost-effective alternative to hydrogen storage and transmission that leads to lower CO2 emissions caused by the energy infrastructure. In this paper, energy, exergy, and Exergoeconomic analyses of a solar hydrogen production system and its blending with natural gas in a city gate station of Isfahan city are performed in three days with minimum, average, and maximum solar irradiations. The system includes photovoltaic arrays, anion exchange membrane electrolyzer cells (AEMECs), a hydrogen compressor, and a system blending. The AEMEC is used due to its less expensive catalysts, non-acidic electrolyte, and high efficiency at high pressures. A three-dimensional numerical model is developed to determine the AEMEC's polarization curve, accurately. The results show that with increasing solar irradiation and decreasing ambient temperature, the maximum power of the PV increases and the energy and exergy efficiency of the PV decreases. By increasing the injection of hydrogen into natural gas from 1% to 10% vol., the lower heating value of the fuel and the Wobbe Index decrease by 6% and 1.55%, respectively. By injection of 10% vol. hydrogen gas into natural gas compared to the case of using natural gas without hydrogen, the exergy cost of natural gas blended with hydrogen increases by 5.9%. Considering the environmental benefits of using hydrogen in combination with natural gas, including the reduction of greenhouse gases, and the fact that blending hydrogen up to 10% vol. with natural gas does not require any change in urban gas supply facilities, this process is feasible. In the case of using high-pressure AEMEC and removing the compressor to produce hydrogen at high pressure, the exergy cost of high-pressure hydrogen reduces by 29.3%. [ABSTRACT FROM AUTHOR]

The integration of distributed energy resources (DERs) into contemporary energy communities (ECs) has revolutionized power systems, fostering sustainable and clean energy infrastructures. This paper focuses on the effective load-carrying capability (ELCC) to enhance grid resilience in the presence of DERs. We introduce an innovative network topology-based optimization framework that seamlessly integrates economic and resilience metrics within ECs while reducing carbon emissions. The Pareto front of non-dominated solutions for the proposed three-objective optimization problems is extracted, providing a comprehensive visualization of the trade-off between economic, resilience, and emission objectives, enabling informed decision-making. Analytical results, validated on the IEEE 33-bus test system, demonstrate the effectiveness of DER-based ELCC quantification in managing load supply during emergencies. Case studies show how the synergy between economic and resilience-based metrics significantly enhances grid resilience. The proposed framework has diverse applications, including enhancing grid adaptability to climate change, promoting sustainable energy integration, optimizing demand response strategies, and supporting the transition to a decarbonized energy community. This work addresses the challenges and opportunities in the evolving energy landscape, emphasizing the importance of our approach in achieving a cleaner and more resilient energy future. [ABSTRACT FROM AUTHOR]

Future electricity generation systems must be optimized to provide flexibility that counteracts the variability of non-dispatchable renewable energy sources and ensures the reliability and safety of critical infrastructure, including the electric grid. The current state-of-the-art is to co-optimize the design and operation of integrated energy systems (IES) treating historical or predicted time-series electricity prices as fixed parameters. Recent literature has shown the limitations of this price taker assumption, which neglects how IES optimization decisions influence market outcomes. As such, this paper proposes a new optimization formulation that uses machine learning surrogate models, trained from a library of annual market operation simulations, to embed IES market interactions into the co-optimization problem directly. Using a thermal generator example built in the open-source IDAES computational environment, we show that the price taker approach routinely over-predicts annual revenues by 8% or more compared to a validation simulation, where the proposed approach has a typical relative error of 1% or less. • Multiscale simulations reveal complex interactions between IESs and energy markets. • Standard price taker formulations are not predictive in realistic design scenarios. • Neural network surrogates accurately predict IES/market interactions. • Optimization with market surrogates is tractable and accurate. • Computational design framework is built entirely from open-source tools. [Display omitted] [ABSTRACT FROM AUTHOR]

Solar PVs are widely proposed as sustainable alternatives to electricity generation from fossil fuels to fulfil the ever-growing energy demands. They have demonstrated great potentials to mitigate devastating environmental impacts of power generation; but, is it enough for a sustainable development? The aim of this paper is to provide a better understanding of how large scale deployment of solar power generation would affect sustainability of a community energy infrastructure. Along with site-specific environmental impacts, cost and social dimensions of sustainability are also considered throughout the life cycle of energy systems and fuels. The proposed framework acknowledges different perspectives and captures the complexities and limitations of power generation. We developed a multi-criteria sustainability appraisal framework to evaluate and compare the sustainability of two different fuel mix scenarios. In this study, accountability of the energy system as well as the safety and resource depletion issues are included as Social Impacts by introducing proper indicators. Assessment results indicated that solar PVs performance has to be improved in cost and social sustainability criteria. The paper also explores the challenges and complexities of sustainability evaluation of energy systems and identifies the bottlenecks of solar PVs deployment in large scales. We concluded that the rate of large-scale penetration of photovoltaics with the purpose of sustainability enhancement should be addressed by adaptive management approaches examining energy demands, solar PV manufacturing and efficiency improvement trends. [ABSTRACT FROM AUTHOR]

Integration of different energy infrastructures (heat, electricity and gas vectors) offers great potential for better managing energy sources, reducing consumption and waste as well as enabling a higher share of renewables, lower environmental impact and lower costs. This paper aims at reviewing the state-of-the-art energy system infrastructures in order to provide a comprehensive overview of technologies, operational strategies, modelling aspects and the trends towards integration of heat, electricity and gas infrastructures. Various technological domains are taken into account, ranging from energy distribution networks (thermal, electric and gas), components for the energy vector conversion (e.g. combined heat and power, power to heat, power to gas, etc.) and energy storage. Furthermore, the aspects related to smart management in energy systems are investigated, such as integration of renewable energy sources and energy recovery systems. • A review of separated and integrated energy infrastructures (EI) is here presented. • The main components in EI are networks, energy vector conversion systems and storages. • Electricity, thermal and gas facilities are increasingly interconnected. • Transition towards multi-energy systems is changing conception of EI. • Trends, technology and modelling aspects are here investigated. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive review of hydrogen and ammonia in maritime applications. • Ammonia is decomposed using several prominent decomposition techniques on board. • Solar energy is integrated into the vessel for electricity and heating/cooling requirement. • Onboard boil-off gas reliquefication using natural refrigerants for ammonia and hydrogen recovery. • Evaluation ranking is applied to determine the most suitable and environmental-friendy option. The growing interest in the potential role of hydrogen in reducing CO 2 emissions as an energy carrier has significant implications in the natural gas industry. Hydrogen will eventually replace natural gas as the most widely used cleaner energy carrier. However, due to the challenges of transporting pure hydrogen and its technological immaturity, transporting ammonia would be a practical alternative. Furthermore, unlike hydrogen, ammonia's distribution and transportation system has already been developed widely and is adaptable to several novel and promising purposes. Additionally, it is noted that ammonia commonly acts as a hydrogen carrier, meaning that the end product is likely to be hydrogen. Hence, there is a need to convert ammonia into hydrogen at the destination port or onboard. To date, existing literature primarily focuses on hydrogen production in general. There is a lack of intensive research on hydrogen production from ammonia decomposition, especially considering the boil-off gas recovery on board. Furthermore, there are limited studies on solar integration infrastructure for energy carrier ships due to the conventional utilization on land, in factories, or onshore plants. Therefore, this paper aims to comprehensively review various ammonia decomposition techniques to produce clean hydrogen by recovering the boil-off ammonia while integrating solar energy infrastructures onboard the energy carrier ship for electricity and heat requirements. Four techniques of ammonia decomposition were investigated: thermal decomposition, catalytic membrane reactor, electrochemical decomposition, and ammonia cracker integrated Solid Oxide Fuel Cell. Moreover, parabolic through collectors, linear Fresnel reflectors, solar dishes, and solar towers were examined as potential solar energy technologies for onboard applications. The selection of natural refrigerants and reliquefication methods was also studied based on their limiting and determining factors to define the suitable options for the reliquefication of boil-off gas onboard. [ABSTRACT FROM AUTHOR]

Critical Infrastructure Systems are highly complex and interdependent. Growing complexity and interdependency between infrastructure systems and frequent exposure to extreme events have inevitably increased the probability of cascading failures and the prolonged lack of serviceability in urban communities, especially so for energy systems. The resilience analysis of interdependent infrastructure systems against natural hazards provides stakeholders with a comprehensive outlook on recovery strategies to minimize the damage costs and losses caused by extreme events. This paper introduces the ResQ-IOS, a Resilience Quantification Iterative Optimization-based Simulation (IOS) framework for quantifying the resilience of interdependent infrastructure systems to natural hazards with the capability of considering the real-world conditions for the status of infrastructure systems' components. The ResQ-IOS framework consists of five modules: risk assessment, simulation, optimization, database, and controller. To evaluate the capabilities of this framework, the seismic resilience of interdependent energy infrastructure networks (power, natural gas, and water) in Shelby County (TN), USA, was assessed. The results of the resilience analysis of the case study suggest that the water network is the best candidate for implementing pre-disaster Resilience Enhancement Measures (REMs), like increasing the supply capacity. Due to the controlling role of the power network in the community's recovery process, it is recommended that post-disaster REMs, such as increasing the number of Repair and Maintenance (R&M) teams, should be applied to the power network to speed up the restoration of failed components in that network and consequently, shorten the recovery duration of the community. The ResQ-IOS can be employed as a useful computational tool for planning the resilience-oriented sustainable development of urban communities by, for example, deploying Renewable Energy (RE)-based strategies to enhance their disaster resilience. • ResQ-IOS can quantify interdependent critical infrastructure systems' resilience. • This framework can consider partial failure and functionality level for components. • ResQ-IOS allows for components' nonlinear properties and time-dependent demands. • ResQ-IOS can be utilized for the resilience-oriented development of communities. • Resilience of interdependent infrastructure systems in Shelby County is assessed. [ABSTRACT FROM AUTHOR]

The application prospects of shared energy storage services have gained widespread recognition due to the increasing use of renewable energy sources. However, the decision-making process for connecting different renewable energy generators and determining the appropriate size of the shared energy storage capacity becomes a complex and interrelated problem when considering the multi-site spatio-temporal characteristics. This paper presents an optimal planning and operation architecture for multi-site renewable energy generators that share an energy storage system on the generation side. Furthermore, an economic-environmental model is proposed to minimize the costs associated with the energy system infrastructure while maintaining a high penetration rate of renewable energy. The centralized multi-objective model allows renewable energy generators to make cost-optimal planning decisions for connecting to the shared energy storage station, while also optimizing the size of the storage capacity to maximize renewable energy generation and minimize costs. The Non-dominated Sorting Genetic Algorithm-II is employed in a centralized manner to solve the multi-objective nonlinear model. Numerical experiments are conducted to demonstrate the economic and environmental benefits of the proposed system. Therefore, this method is highly recommended for implementation on the generation side. • Design a centralized renewable energy connecting and shared energy storage sizing framework. • Exploit multi-site renewables with spatio-temporal complementarity on the power generation side. • Propose an economic-environmental model for renewable energy connecting and energy storage sizing. • Shared storage service is an effective approach toward a grid with high penetration of renewable energy. [Display omitted] [ABSTRACT FROM AUTHOR]

The energy infrastructure literature focuses on the economic and environmental dimensions of sustainability, neglecting the social dimension. Particularly obscure is how the programme governance frameworks of energy projects and programmes shape their social performance. We address this gap in knowledge by leveraging a cross-case analysis of comparable energy infrastructures planned and delivered in contexts with different programme governance frameworks (i.e., Iran, Italy, Nigeria, Norway, Saudi Arabia, and the USA). This article first clarifies how investigating social sustainability at the infrastructure/project level is inadequate, showing that the overarching programme governance framework - set at the country level - is a major driver for social sustainability. Second, this article identifies three perspectives to examine the link between the programme governance framework and social sustainability: 1) Types of contracts, 2) Leadership of the infrastructure programme, and 3) Maturity of the legal and regulatory framework. These perspectives are combined to provide a novel analytical framework, useful to both examine the present status and plan future energy infrastructures. Last, this article discusses the findings from a policy perspective deriving a research agenda. • The literature about energy infrastructures focuses on their economic and environmental impact; • The social sustainability dimension of energy infrastructures is often neglected; • This paper fills this gap by an empirical cross-case analysis; • It identifies three perspectives to look at the link between programme governance framework and social sustainability; • The programme governance framework is a major driver for social sustainability; [ABSTRACT FROM AUTHOR]

• Proposed a generalized strategy to advance electrochemical energy devices. • Key innovation pillars are characterization, modeling, design, and implementation. • Advances and contributions made by the Bazylak group are highlighted. Electrochemical devices such as fuel cells, electrolyzers, and batteries, are essential building blocks for an environment-positive and sustainable energy infrastructure. Design and selection of materials and testing conditions heavily influence physiochemical processes and dictate performance, durability, and affordability of clean energy devices. In this paper, we reflect on strategies employed and advances made by the Bazylak Group in the pursuit of next-generation electrochemical clean energy devices. Four essential pillars are identified in our efforts: a) characterization, b) modeling, c) design, and d) implementation. Advances made within each pillar is discussed and the importance of the synergy between these pillars is emphasized. In addition to serving as a resource to highlight discoveries and challenges in developing electrochemical devices, we envision to share and build a generalized approach to advance next-generation materials and processes in clean energy and other diverse applications. [ABSTRACT FROM AUTHOR]

Optimal design of building envelopes/HVAC systems and free cooling strategies are today necessary to reduce energy, economic and environmental impact of telecommunication, electricity distribution, or electric transportations infrastructures. To this aim, designers and operators require advanced techniques and tools. Target of this paper is to present the development of a simulation model for assessing and optimizing cooling performance of new/existing infrastructures to be designed/refurbished from the energy point of view. The model is implemented in a computer tool to assess the related potential benefits of different energy saving technologies/strategies and optimize different objective functions. By the presented approach new design and operating criteria are developed by varying all the occurring boundary conditions (weather, temperature limitations, electricity tariffs, etc.). To show the capability and suitability of the proposed approach, a case study concerning the equipment cooling of a railway substation is developed. The analysis is conducted for different Italian climates, obtaining remarkable energy savings. Specifically, by optimizing free cooling operation and thermal insulation the cooling energy consumption can be decreased up to 80% and 10%, respectively. By an energy refurbishment of all the Italian railway substations an annual electricity cost reduction due to equipment conditioning of about 0.5 M€ can be achieved, 47% lower. • Distributed building infrastructures have great potential of reducing cooling energy consumption. • Dynamic simulation is a paramount tool to design enhanced energy management strategies. • Free cooling contributes to 50% reduction of energy demand for equipment cooling. • Operational energy and use of material can be reduced with optimal envelope design. • The study proposes design criteria aimed at increasing energy efficiency at the infrastructure level. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, renewable energy, especially wind power, solar PV and hydropower, will become the most important power sources in the future low-carbon power system. Since wind power and solar PV are specifically intermittent and space-heterogeneity, an assessment of renewable energy potential considering the variability of wind power and solar PV with high temporal resolution in different regions will facilitate more accurate identification of the decarbonization pathway of power system. In this paper, the complementary output potential of wind-solar-hydro power every 15 min in 31 Chinese provinces is evaluated by developing a multi-objective optimization model based on Nondominated Sorting Genetic Algorithm II. The results show that the total annual complementary power generation potential in China is 17.57 PWh, of which the three components account for 47.8%, 25.3% and 26.9%, respectively. Inner Mongolia and Tibet are the major renewable energy source provinces with annual complementary power generation potential of 5330 TWh and 3907 TWh, accounting for 30.3% and 13.7% of the total power generation potential, respectively. The temporal potential of wind-solar-hydro power varies greatly, with daily potential is more volatile than monthly. Seasonal and spatial heterogeneity of the complemental renewable potential makes some provinces suffer power shortage during long-hours period especially in winter. Our findings will encourage a higher penetration of renewable energy, the promotion of multi-energy complementarity, and the development of inter-provincial power transmission and energy storage infrastructure in China's future power sector. • A multi-objective wind-solar-hydro complementary optimization model is developed. • Electricity supply and demand have gaps at different temporal and spatial scales. • Wind-solar-hydro complementary potential shows great temporal and spatial variation. • Renewable complementarity can improve China's future power system stability. [ABSTRACT FROM AUTHOR]

Global climate change, global warming, and unplanned urbanization have resulted in industrial facilities and livelihoods encroaching on wildlands. Wildfire risks concerns about natural hazards triggering technological accidents (Natech) caused by wildfires in wildland-industrial and -urban interface areas are globally increasing. As wildfires that could trigger Natech accidents occur infrequently but often with unpredicted and uncontrollable consequences, critical infrastructure and industrial facilities should prepare for the potential catastrophic impact of wildfires beforehand. This paper describes a case study of wildfire-threatened critical energy infrastructure located in wildland-industrial interface (WII) and wildland-urban interface (WUI) areas in South Korea. The energy infrastructure avoided a serious Natech accident through intensive risk and emergency management. Although there was no Natech disaster or dreadful damage to the energy facility, this threat to the energy infrastructure is a reminder to prepare for future Natech disasters in WII and WUI areas that could result in unmanageable consequences. This study highlights the need for intensive and integrated wildfire-specific Natech risk management, considering critical infrastructure and industrial facilities in WII and WUI areas, that should include all stakeholders with local residents and enhance Natech resilience. [ABSTRACT FROM AUTHOR]

Abstract: The Energy Strategy of the Republic of Croatia was adopted by the Croatian Parliament in 2009 for the period until 2020 in order to harmonize national energy goals with goals and time framework of strategic documents of the European Union. The adoption of the Energy Strategy Implementation Program with associated measures is still in process. The goal of the Strategy was to create sustainable energy system that will make a balanced contribution to the security of energy supply, competitiveness and environmental protection in Croatia. In this paper an overview of the energy production, final energy consumption and planned development of energy infrastructure is given. The intention of the paper was to research and stress out the abilities and opportunities of Croatian energy system and to give recommendations for Energy Strategy implementation and practical realization of planned energy infrastructure projects for improvement of security of energy supply and competitiveness of energy system of the Republic of Croatia. [Copyright &y& Elsevier]

The Smart Meter Implementation Programme (SMIP) is arguably one of the most expansive and complex smart meter programmes globally. The UK government regards smart meters to be enablers of a low-carbon energy grid and has set out ambitious consumer-orientated aims within their programme across England, Scotland, and Wales. Despite considerable amount of research on how consumers will (or not) engage with smart meters, media discourses, where some public debates about smart meters are created and reproduced, have received little attention. This paper presents a content analysis of how smart meters are discussed within 11 years of popular print media coverage. A collection of nine discourses are identified: Four of these – “empowered consumers”, “energy conscious world”, “low-carbon grid”, and “future smart innovation” – depict smart meters as a harbinger of positive social change. Five of these – “hacked and vulnerable grid”, “big brother”, “costly disaster”, “astronomical bills”, and “families in turmoil” – represent smart meters as negative forces on society. The results show that discourses and associated storylines mainly represent continuous struggles over particular socio-technical promises linked to smart meters. Somewhat missing are attempts to open up the smart energy debate to broader issues of democracy and energy justice within the print media coverage. [ABSTRACT FROM AUTHOR]

Abstract: This paper analyses sustainability transitions in the electricity system, using recent theories on socio-technical pathways. The paper describes three possible transition pathways and indicates the implications for (grid) infrastructures. The ‘transformation pathway’ is characterised by a further hybridization of the infrastructure; in the ‘reconfiguration pathway’, internationalisation and scale increase in renewable generation lead to the emergence of a ‘Supergrid’. The ‘de-alignment and re-alignment pathway’ is dominated by distributed generation and a focus on more local infrastructures. We suggest that this pathway, which involves a major restructuring of the electricity system, is less likely than the other two. The de-alignment and re-alignment pathway is therefore more dependent on external developments and/or strong policy interventions. All pathways, however, require major investments in infrastructure and innovative technologies. [ABSTRACT FROM AUTHOR]

Asian Infrastructure Investment Bank (AIIB) was officially established by China in 2016 with one of the aims to develop energy infrastructure based on green and sustainable principles in Asia. To achieve that, AIIB has set forth safeguard policies, including the Environmental and Social Framework (ESF) applied for funded projects and the AIIB Energy Sector Strategy, to guide its energy investments. However, the effects of the safeguard policies and further safeguard operations on the energy projects remain unknown. This study reviews AIIB's safeguard mechanism on energy projects, including the safeguard policies, assessment and management plans, and implementations of AIIB's energy projects. We find that AIIB's current safeguard mechanism on energy projects, in comparison with other established multilateral development banks (MDBs), is still at its beginning stage, which does not match its goal and promise on sustainable energy development in Asia. • This paper examines AIIB's safeguard mechanism, including its safeguard policies and safeguard operations. • This paper finds the gaps of AIIB's safeguard policies by comparing that to the practices of other established MDBs. • This paper identifies the gaps of AIIB's safeguard operations by comparing co-financed and stand-alone energy projects. [ABSTRACT FROM AUTHOR]

Future electric grids will face severe uncertainties with the unprecedented penetration of renewable energy sources, which may cause problems in grid exploitation. It is essential to evaluate the uncertainty of system performance in this grid; therefore, traditional exploitation methods may not be suitable for distributions grid such as multi-carrier microgrids when considering the electricity and gas grid constraints. This paper proposes an effective method for simultaneously optimizing different types of energy infrastructure in an environment with various uncertainties while considering grid constraints. To address the multi-energy synergy supply optimization problem in the micro energy grid, a coordinated two-stage programming approach is also suggested. A day-ahead and real-time phases are separated in the scheduling cycle to overcome the effects of the unpredictability of wind energy and solar power. The findings of the day-ahead forecast are then taken into account as uncertain variables for the higher-layer model. The demand response programming model and the energy storage revision model are lower-layer models considering the actual value as the realization of uncertain variables. The competitive swarm optimization algorithm is used to solve the problem mentioned above The Cumulative search optimization (CSO) uses global and local systems in particle swarm optimization and adopts a novel learning mechanism for creating competition between particle pairs. Comprehensive numeric examinations show that convergence speed and precision are critical, especially in solving large-scale problems. Therefore, we use chaos theory to improve its performance. Finally, the proposed method is tested and discussed on a system. The results showed that: (1) power-to-gas could convert extra electricity into natural gas; (2) the proposed two-stage optimization model and algorithm achieved different energy optimizations; (3) price-based demand response (DR) can level the energy load curve and maximize multi energy grid (MEG) revenue by using complementary specifications of energy price; and (4) the micro energy grid could communicate with the high-degree energy grid in order to gain more economic benefits. Accordingly, the incentive-based demand response (IBDR) output is reduced. The electricity and heating provided by convention gas turbine (CGT) is increased, which is fed to upper power grid (UPG) and upper heating grid (UHG). Since MEG's purchasing power from UPG during the peak period generates more total revenue than island operations. Based on the obtained results, it can be seen that the proposed algorithm was about 50% faster compared to other methods and its standard deviation was about 0.0013 with different implementations, which was much better compared to other models. • A new model of MEG, including EP, EC, and ES based DR program. • A coordinated two-stage scheduling program for the MEG. • Application of WPP and PV uncertainties on proposed problem. • Application of new optimization algorithm to solve the problem. [ABSTRACT FROM AUTHOR]

Civil aviation provides an essential transportation network that connects the world and supports global economic growth. To maintain these benefits while meeting environmental goals, next-generation aircraft must have drastically reduced climate impacts. Hydrogen-powered aircraft have the potential to fly existing routes with no carbon emissions and reduce or eliminate other emissions. This paper is a comprehensive guide to hydrogen-powered aircraft that explains the fundamental physics and reviews current technologies. We discuss the impact of these technologies on aircraft design, cost, certification, and environment. In the long term, hydrogen aircraft appear to be the most compelling alternative to today's kerosene-powered aircraft. Using hydrogen also enables novel technologies, such as fuel cells and superconducting electronics, which could lead to aircraft concepts that are not feasible with kerosene. Hydrogen-powered aircraft are technologically feasible but require significant research and development. Lightweight liquid hydrogen tanks and their integration with the airframe is one of the critical technologies. Fuel cells can eliminate in-flight emissions but must become lighter, more powerful, and more durable to make large, fuel cell-powered transport aircraft feasible. Hydrogen turbofans already have these desirable characteristics but produce some emissions, albeit much less damaging than kerosene turbofans. Beyond airframe and propulsion technologies, the viability of hydrogen aircraft hinges on low-cost green hydrogen production, which requires massive investments in the energy infrastructure. [ABSTRACT FROM AUTHOR]

• Issues of knowledge, subjectivity, and objectivity are vital for understanding risk. • There are potential overlaps among information, misinformation, and disinformation. • Risk analysis efforts should consider implications of how risk study credibility is perceived. The practice of risk analysis and management involves uncertainty. When negative risk events occur, as they often do, it's not apparent whether the event resulted from properly conducted risk analysis and management, or from improper work, intent to mislead, or other types of misinformation. Additionally, risk management involves decision-making, such that inherently subjective values are imposed upon the scientific analysis. As a result, disagreement is an expected component of any risk analysis or management activity. The question then arises: Can properly conducted risk analysis and management be instead interpreted as misinformation? If so, what are the boundaries between properly conducted risk analysis/management and misinformation? This paper conducts an investigation of those questions by: 1) Evaluating the existing literature to define constructs of subjectivity and objectivity as they relate to risk analysis, risk management, and misinformation, 2) Defining characteristics of information generated from a properly conducted risk analysis/management and those that generate misinformation, recognizing that areas of overlap are the most concerning and in need for further investigation, 3) Demonstrating an evaluation of information using the newly defined characteristics on a case study involving energy infrastructure management, and 4) Addressing the implications for the practice of risk analysis and management. [ABSTRACT FROM AUTHOR]