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This study aims to examine the impact of compressor station availability on the techno-economic aspects of natural gas pipeline transportation, using the proposed Trans-Saharan Gas Pipeline (TSGP) project as a case study. A scenario-based technical and economic analysis was conducted to highlight the economic sensitivities of the systems to availability. The economic assessment of the project was performed using a discounted cash flow method, considering lifecycle costs. The techno-economic model was developed using MATLAB R2020b, accounting for variations in ambient temperatures at the compressor station under different flow conditions. Findings indicate an 8.41% increase in project lifecycle cost in one scenario compared to the baseline, assuming a 15% discount rate. However, the baseline case with a 100% compressor station availability assumption appears unrealistic, as shown by its lifecycle cost and net present value estimates. This is because constant operating conditions throughout the project lifecycle are impossible. Additionally, when station availability increases by 7.87% and the cost of standby units rises by 10.24%, avoided income loss due to station unavailability increases by 14.06%. This reveals a trade-off between the extra capital expenditure on standby units and the savings from avoiding income loss. Furthermore, the impact of 2% and 4% escalation rates of fuel and maintenance costs on lifecycle costs results in a rise of 2.70% and 6.15%, respectively, in one scenario compared to the 0% escalation rate. The results demonstrate the significant influence of compressor station availability analysis on pipeline projects, particularly in reducing engine downtime costs and enhancing project revenue. Therefore, the methods presented here help in understanding the importance of compressor station availability in pipeline techno-economics, leading to more effective resource and financial management.

As a core component of the railway signalling system, the condition assessment and maintenance strategy optimisation of point machines are critical to railway safety. However, current issues include vague condition assessment standards and rigid maintenance strategies. This paper employs image processing techniques to extract current curves, constructs a curve difference assessment model based on PCHIP inter-polation and RMSE, and compares it with commonly used methods such as Fréchet distance and Bray-Curtis dissimilarity to classify the switch machine into five state levels. By introducing maximum likelihood estimation combined with Markov chain calculations to determine state transition probabilities, an ageing model is constructed to predict the state changes of the switch machine throughout its entire lifecycle. Results show that the fault repair strategy can extend the physical lifespan of the switch machine to nearly the design value of 14.73 years, far exceeding the maintenance strategy’s 7.29 years. However, from an economic lifespan perspective, the maintenance effects of the two strategies differ by no more than 4 years. This study provides a technical pathway for intelligent maintenance of railway signal equipment, driving the transformation of critical equipment toward “state prediction” and “precision repair”.

Energy-efficient retrofitting has emerged as a primary strategy for reducing the energy consumption of buildings. Buildings in China account for about 40% of total national energy consumption. Large office buildings account for the most. Less than 5% of the building area of existing office buildings is energy efficient. Energy-efficient retrofitting for sustainable buildings is a complicated system that involves various sustainable dimensions and operational technical schemes. Making multi-criteria decisions becomes a challenging problem for stakeholders. Based on the theory of sustainability, this paper establishes a sustainable analysis framework to guide stakeholders to select an optimal technical combination of energy-efficient retrofit measures for large office buildings. Based on empirical data collected in Beijing, a number of energy efficiency measures are selected, tailored and applied to a virtual model of a typical large office building. Technical features and the energy performance are simulated accordingly. The energy consumption, energy-saving ratio and lifecycle costs are derived to identify the optimal configuration. The outcome of this research offers a feasible technical plan for stakeholders relating to technical design and design making. The study finds that an LED lighting system and frequency conversion device for the cooling water chiller cannot only sufficiently reduce the building’s energy consumption but also perform economically. Different thermal insulation materials for reconstructing the building envelope have no obvious effect on the thermal performance in comprehensive simulations of technology combinations. The sustainable analysis framework offers theoretical and practical support and can be used as a reference for the other types of buildings in future research.

The integration of energy storage systems is an effective solution to grid fluctuations caused by renewable energy sources such as wind power and solar power. This paper proposes a hybrid energy storage system (HESS) capacity optimization method combining flywheel and battery energy storage. Firstly, improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is employed to decompose the original wind–solar power signal into a grid-connected signal and a leveling command signal. Low-pass filtering is then applied to separate the leveling command signal by frequency and assign it to the flywheel and battery of the HESS, respectively. Secondly, with the goal of minimizing the full lifecycle cost, a capacity optimization model for a flywheel–battery HESS aimed at minimizing wind–solar power fluctuation is established based on the particle swarm optimization (PSO) algorithm. Finally, a simulation analysis is conducted on a microgrid consisting of a 10 MW wind power generation system, a 10 MW solar power generation system, and a flywheel-battery HESS. The results show that the use of hybrid energy storage has a significant power smoothing effect, with a maximum power fluctuation rate of 3.2% in 1-min intervals and a maximum power fluctuation of less than 8% in 10-min intervals in most cases. Under the same stabilizing effect, the HESS reduces costs by 45.1% compared to single-battery energy storage.

Passive buildings are proving to be a solution to menaces of energy crisis and greenhouse gas emissions across the world. Such buildings tend to exhibit low energy demand owing to their cleverly designed envelopes, which comprise of walls, roofs, doors, windows and other openings. This requires use of new materials and technology, leading to an increased initial construction cost. However, with reduced energy consumption, the lifecycle cost of a passive building may be lower than that of a conventional building. These passive buildings also need to cater to occupants’ comfort which is subject to local climatic conditions and climate change. This article discusses economic feasibility and climatic adaptability of a passive building, in addition to advances in passive building strategies. Owing to lack of general awareness and standards related to passive building construction, these buildings have not achieved enough popularity. While many countries are striving hard to bring passive buildings to common masses, a large number of countries are yet to initiate the move. This article outlines several active organizations, standards and rating systems for passive buildings. This article also presents some of the recent research trends and a comprehensive bibliography for the benefit of researchers and practitioners.

Ocean-going ships are one of the primary sources of Greenhouse Gas (GHG) emissions. Several actions are being taken to reduce the GHG emissions from maritime vessels, and integration of Renewable Energy Sources (RESs) is one of them. Ocean-going marine ships need a large amount of reliable energy to support the propulsive load. Intermittency is one of the drawbacks of RESs, and penetration of RESs in maritime vessels is limited by the cargo carrying capacity and usable area of that ship. Other types of reliable energy sources need to be incorporated in ships to overcome these shortcomings of RESs. Some researchers proposed to integrate fossil fuel-based generators like diesel generators and renewable energy in marine vessels to reduce GHG emissions. As the penetration of RESs in marine ships is limited, fossil fuel-based generators provide most of the energy. Therefore, renewable and fossil fuel-based hybrid energy systems in maritime vessels can not reduce GHG emissions to the desired level. Fossil fuel-based generators need to be replaced by emissions-free energy sources to make marine ships free from emissions. Nuclear energy is emissions-free energy, and small-scale nuclear reactors like Microreactors (MRs) are competent to replace fossil fuel-based generators. In this paper, the technical, environmental, and economic competitiveness of Nuclear-Renewable Hybrid Energy Systems (N-R HES) in marine ships are assessed. The lifecycle cost of MR, reliability of the proposed system, and limitations of integrating renewable energy in maritime vessels are considered in this study. The proposed N-R HES is compared with three different energy systems, namely ‘Standalone Fossil Fuel-based Energy Systems’, ‘Renewable and Fossil Fuel-based Hybrid Energy Systems’, and ‘Standalone Nuclear Energy System’. The cost modeling of each energy system is carried out in MATLAB simulator. Each energy system is optimized by using the Differential Evolution Algorithm (DEA), an artificial intelligence algorithm, to find out the optimal configuration of the system components in terms of Net Present Cost (NPC). The results determine that N-R HES has the lowest NPC compared to the other three energy systems. The performance of the DE algorithm is compared with another widely accepted artificial intelligence optimization technique called ‘Particle Swarm Optimization (PSO)’ to validate the findings of the DE algorithm. The impact of control parameters in the DE algorithm is assessed by employing the Adaptive Differential Evolution (ADE) algorithm. A sensitivity analysis is carried out to assess the impact of different system parameters on this study’s findings.

In arid climates, almost half of the urban peak load of energy demand is used to supply cooling and air-conditioning in the summertime. The pressure placed on energy resources to satisfy inhabitants’ indoor comfort requirements is mounting due to accelerated urbanisation rates in developing countries and has led countries such as those in the GCC (Gulf Cooperation Council) to establish sustainable building codes to enhance their environmental performance. Using the extensive parametric energy simulations provided by DesignBuilder, this study addresses the potential of applying different GCC energy efficiency measures to reduce annual energy consumption and carbon emissions in a typical residential dwelling in the Kingdom of Bahrain. To do so, first, a base case validation simulation model was generated, followed by four design scenarios addressing the minimum requirements for Bahrain’s Energy Conservation Code, Abu Dhabi’s ESTIDAMA 1, Saudi Arabia’s code, and Kuwait’s building code. Then, a feasibility study was conducted using the simple payback period (SPP) and lifecycle cost (LCC) analysis. Overall energy and carbon emission (CO2) reduction showed the potential for building sustainable codes to improve building environmental performance throughout the year. In terms of energy performance and CO2 reduction, Abu Dhabi’s ESTIDAMA 1 code recorded the best energy savings at a 24.4% and a 26.3% reduction in carbon emissions, followed by the Saudi code with a 14.6% annual energy savings and 12.3% less carbon emissions. Regarding the economic analysis, although the SPP indicates the Bahraini code offered payback in just under two years for subsidised energy and half a year for unsubsidised, the LCC analysis suggests that applying Abu Dhabi’s ESTIDAMA 1 code was the most feasible, followed by the Saudi building code. Consequently, the study suggests a comprehensive evaluation of the relationship between the sustainable building codes and their economic feasibility in order to enhance and promote the wide application in the GCC based on the code’s capabilities and their benefits for residential households and the overall economy.

This study investigates the optimal service life of urban Electric Multiple Units (EMUs) by integrating two complementary evaluation methods: economic service life and maintenance limit life. Using a comprehensive dataset from Seoul Metro—including 498 trainsets and 3554 overhaul records—this research examines the relationship between long-term maintenance costs, depreciation, and residual values. The economic service life is derived by minimizing the average equivalent annual cost (AEC), while maintenance limit life is assessed based on government guidelines that define cost-inefficiency thresholds. The analysis finds that the average economic service life for EMUs on Lines 1–4 is approximately 39 years—substantially exceeding the traditional 25-year benchmark used in past replacement policies. Maintenance limit life, based on permissible cost ratio thresholds, extends up to 47 years in some cases. Sensitivity analysis indicates that maintenance cost variations exert a greater influence on optimal service life than discount rate assumptions, highlighting the importance of strategic maintenance management. The proposed dual-framework approach demonstrates the limitations of rigid, statutory-based replacement planning and supports a transition toward data-driven, line-specific decision-making. The findings provide actionable insights for transit authorities and policymakers seeking to improve capital investment efficiency and optimize lifecycle management of urban rail assets. Beyond economic efficiency, the study contributes to sustainability by supporting resource-efficient asset utilization, reducing premature disposal of serviceable rolling stock, and lowering lifecycle carbon emissions associated with manufacturing new vehicles. The proposed framework thus offers a practical basis for integrating economic and environmental considerations in sustainable urban rail asset management.

Energy retrofitting the existing building stock is crucial to reduce thermal discomfort, energy consumption, and carbon emissions. However, insulating and enhancing the thermal mass of an existing building wall using traditional methods is a very challenging and expensive task. There is a need to develop a material that can be applied easily in an existing occupied building without much interruption to occupants’ daily life while also having high thermal resistance and heat storage capacity. This study aimed to investigate a potential building wall retrofit strategy combining aerogel render and Phase change materials (PCM) because aerogel render is highly resistive to heat and PCM has high thermal mass. While a number of studies investigated the thermal and energy-saving performances of aerogel render and PCM separately, no study has been done on the thermal and energy-saving performance of the combination of PCM and aerogel render. In this study, the performance of 12 different retrofit strategies, including aerogel and PCM, were evaluated numerically in terms of heat stress, energy savings, peak cooling, emission, and lifecycle cost using a typical single-story Australian house. The results showed that applying aerogel render and PCM on the outer side of the external walls and PCM and insulation in ceilings is the best option considering all performance indicators and ease of application. Compared to the baseline, this strategy reduced severe discomfort hours by 82% in a free-running building. In an air-conditioned building, it also decreased energy use, peak cooling demand, CO2 emission, and operational energy cost by 40%, 65%, 64%, and 35%, respectively. Although the lifecycle cost savings for this strategy were lower than the “insulated ceiling and rendered wall without PCM” case, the former one was considered the best option for its superior energy, emission, and comfort performance. Parametric analysis showed that 0.025 m is the optimum thickness for both PCM and aerogel render, and the 25 °C melting point PCM was optimum to achieve the best results amongst all performance indicators for a typical Australian house in Melbourne climate.

As the importance of energy efficiency and smart readiness in the building sector has been on the rise, the financial evaluation of smart-ready technologies (SRTs) remains a gap in this field. This study introduces a methodology that comparatively evaluates the cost–benefit relationship between 11 different SRTs across three European countries—Cyprus, Italy and The Netherlands. Key performance indicators (KPIs) for energy-focused aspects such as Country-Specific Energy Savings Potential (CSESP) and Seasonal Smart Efficiency Coefficient (SSEC) and financial aspects such as Smart Readiness Cost Index (SRCI), Labor Cost Impact Factor (LCIF), Return on Smart Investment (RoSI), and Smart Investment Break-Even Period (SIBEP) were used to quantify the performance of the SRTs. The results indicate that regional labor rates, energy pricing, and climatic conditions—as well as relative technology cost–benefit tradeoffs—play a significant role in the economic viability of smart-ready devices. Having low labor costs and energy pricing, Cyprus exhibited the most cost-effective outcomes among the three countries. Italy showed strong returns although the initial investments were higher. The Netherlands was observed to benefit the most from heating-oriented technologies. The study comes to the conclusion that regionally specific methods are necessary for the adoption of SRTs and that techno-economic performance cannot be assessed separately from local market dynamics. The proposed framework supports stakeholders and policymakers in smart building investment and planning by offering a scalable method for device-level benchmarking. These indicators are developed specifically for this study and are not part of the official EU SRI (Smart Readiness Indicator) methodology. Their inclusion supports device-level evaluation and complements ongoing efforts toward SRI standardization. This research directly addresses Sustainable Development Goal (SDG) 7 on Affordable and Clean Energy, as well as SDG 11 on Sustainable Development, by evaluating how smart-ready technologies can contribute to energy efficiency and decarbonization in buildings. Based on the results, further research is needed to expand the indicator framework to additional technologies, include building typology effects, and integrate dynamic factors such as CO2 pricing and real-time tariffs.