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In this volatile, uncertain, complex, and ambiguous (VUCA) era, resilient and sustainable construction methods, such as prefabricated construction, are essential for addressing the planet’s sustainability challenges. However, disruptions in the prefabricated construction supply chain (PCSC) frequently arise, seriously impeding the performance of prefabricated building projects. Therefore, this study aims to identify the factors influencing the prefabricated construction supply chain (RPCSC) and analyze their intrinsic interconnections. Initially, an exhaustive literature review was conducted to identify the primary factors affecting the RPCSC. Subsequently, the Delphi technique was applied to validate and refine the list of factors, resulting in the identification of 11 key concepts. Finally, the impact of these concepts on the RPCSC, along with their interactions, was assessed using the fuzzy cognitive map (FCM) approach. The results indicate that these factors can be ranked by their degree of effect on the RPCSC: information exchange/sharing, research and development, the performance of prefabricated components, decision alignment, the construction of prefabricated buildings, relationship quality among members, professional management personnel/labor quality, supply–demand consistency, cost/profit sharing, policies and regulations, and transport risk. Furthermore, this study elucidates both the individual and synergistic effects of these factors on the RPCSC by constructing a pathway map. Full article

With the continuous adjustment of energy structure and the improvement of environmental protection requirements, combined heat and power microgrids (CHP-MG) have received widespread attention as an efficient and economical way of utilizing energy. The complexity of energy supply relationships and energy coupling within the microgrid system necessitates optimizing the power output of each equipment unit. In this paper, an optimization strategy for a multi-energy microgrid system is proposed based on the efficient energy supply of cogeneration microgrids: decoupling the thermoelectric connection by using the energy storage equipment on the supply side, utilizing the flexibility of the electrical loads and the diversity of the system’s heating methods, and reducing the electrical loads and changing the selection of the heating methods on the demand side. The optimization model in the paper is mainly based on mixed-integer linear programming and demand-side management theory, which simulates the system operation under different scenarios so as to find the optimal equipment output and load management strategies. Simulation results show that the optimized CHP-MG system can ensure a reliable power supply while effectively reducing operating costs, improving energy utilization and promoting sustainable operation of the energy system. The optimized microgrid system offers significant advantages in terms of economic efficiency and energy management when compared to conventional CHP systems. These findings provide actionable insights for policymakers, system operators, and researchers aimed at driving the development of efficient and sustainable energy management solutions. Full article

Due to the energy transition, the future electric power system will face further challenges that affect the functionality of the electricity grid and therefore the security of supply. For this reason, this article examines the future frequency stabilisation in a 100% renewable electric power system. A focus is set on the provision of inertia and frequency containment reserve. Today, the frequency stabilisation in most power systems is based on synchronous generators. By using grid-forming frequency converters, a large potential of alternative frequency stabilisation reserves can be tapped. Consequently, frequency stabilisation is not a problem of existing capacities but whether and how these are utilised. Therefore, in this paper, a collaborative approach to realise frequency stabilisation is proposed. By distributing the required inertia and frequency containment reserve across all technologies that are able to provide it, the relative contribution of each individual provider is low. To cover the need for frequency containment reserve, each capable technology would have to provide less than 1% of its rated power. The inertia demand can be covered by the available capacities at a coverage ratio of 171% (excluding wind power) to 217% (all capacities). As a result, it is proposed that provision of frequency stabilisation is made mandatory for all capable technologies. The joint provision distributes the burden of frequency stabilisation across many participants and hence increases redundancy. It ensures the stability of future electricity grids, and at the same time, it reduces the technological and economic effort. The findings are presented for the example of the German electricity grid. Full article

The integration of energy generation and consumption is one of the most effective ways to reduce energy-system-related waste, costs, and emissions in cities. This paper considers a university district consisting of 32 buildings where electrical demand is currently met by the national grid, and 31% of thermal demand is supplied by a centralized heating station through a district heating network; the remainder is covered by small, dedicated boilers. Starting from the present system, the goal is to identify “retrofit” design solutions to reduce cost, environmental impact, and the primary energy consumption of the district. To this end, three new configurations of the multi-energy system (MES) of the district are proposed considering (i) the installation of new energy conversion and storage units, (ii) the enlargement of the existing district heating network, and (iii) the inclusion of new branches of the electrical and heating network. The configurations differ in increasing levels of integration through the energy networks. The results show that the installation of cogeneration engines leads to significant benefits in both economic (up to −12.3% of total annual costs) and energy (up to −10.2% of the primary energy consumption) terms; these benefits increase as the level of integration increases. On the other hand, the limited availability of space for photovoltaics results in increased CO₂ emissions when only total cost minimization is considered. However, by accepting a cost increase of 8.4% over the least expensive solution, a significant reduction in CO₂ (−23.9%) can be achieved while still keeping total costs lower than the existing MES. Full article

The operation of parallel inverters can enhance the reliability of power supply and meet the demand of the grid forming system; however, due to the difference in the Zero Sequence Voltage (ZSV) and the existence of the Zero Sequence Path (ZSP), the problem of Zero Sequence Circulating Current (ZSCC) inevitably occurs. This paper proposes a fixed-time control strategy based on the Extended Kalman Filter (EKF), used in order to suppress the ZSCC issue in a paralleled inverter system. Firstly, the detailed mathematical model of ZSCC is described, where the inductance perturbations are considered according to the generation mechanism of ZSCC, and a novel ZSCC controller is designed based on the principles of the fixed-time stability theory which can assure the action time of the zero vectors in one switching cycle. Secondly, to reduce the influence of the inductor parameters on the ZSCC control effect, the EKF is used to identify the online inductance parameters of the filter, and the robustness of the algorithm can be improved. Subsequently, based on the Lyapunov stability criterion, it has been proved that the proposed control strategy is fixed-time stable. Finally, the simulation and experiments are employed to demonstrate the effectiveness of the proposed control method. Full article

The imbalance between supply and demand for slot resources and empty containers has led to resource waste and excessive operating costs for liner companies. Moreover, intense competition among ports has made both container ship slots and port equipment resource allocation inefficient. To address these challenges, this paper aims to solve the collaborative optimization problem of slot allocation and empty container repositioning within port clusters concerning inventory control. A cooperative possession strategy and a hybrid (T, s) inventory control policy are incorporated in this paper. A novel mixed-integer programming model is proposed, enabling us to simultaneously track slot allocation, empty container repositioning, empty container leasing, and slot renting. To solve the model, a new branch-and-bound algorithm based on Lagrangian relaxation and the ascendancy principle (BBLRAP) is developed. Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. Compared to state-of-the-art studies, the following paper makes new contributions to proposing a cooperative possession strategy within port clusters for the first time. This paper ensures that liner companies and partners achieve a win–win situation in the cooperative game, expanding market shares and improving customer satisfaction. Full article

The rational allocation of urban public open spaces (UPOS) is critical for creating a livable urban environment. Traditional Two-Step Floating Catchment Area (2SFCA) models often lack sufficient quantitative analysis regarding the supply of urban public service facilities and population demand. This study, taking the area within Chengdu’s Second Ring Road as an example, proposes a 2SFCA model that integrates both supply and demand improvements to evaluate UPOS accessibility. The accessibility results are further analyzed using hotspot analysis, and blind zone detection. In terms of supply improvements, the model incorporates additional indicators beyond the spatial area of UPOS, including service quality and the diversity of surrounding environmental service functions, to better evaluate the overall attractiveness of UPOS to residents. On the demand side, besides population size, the model incorporates the spatial distribution of residents and differences in social characteristics affecting UPOS demand. Results indicate that the improved 2SFCA model, which considers both the attractiveness of UPOS and residents’ demand, significantly enhances the accuracy of accessibility assessments. There are substantial differences in service quality among UPOS, while the diversity of surrounding environmental service functions remains generally high. UPOS demand follows a “high in the northeast—low in the southwest” spatial pattern. The spatial distribution of UPOS accessibility shows a “high in the west—low in the east” pattern, opposite to the demand distribution, indicating a supply–demand mismatch. UPOS accessibility identifies one hotspot cluster and four cold spot clusters, with large areas showing no significant characteristics. Additionally, 10.58% of the study area remains blind zones, requiring urgent attention. This study offers a more scientific method and framework for research on the spatial layout and supply–demand matching of UPOS. Full article

The growing demand for lithium, driven by its crucial role in energy storage technologies such as lithium-ion batteries for electric vehicles, renewable energy storage, and portable electronics, is intensifying the need for sustainable extraction methods. While lithium is sourced from both primary and secondary resources, particularly from recycled materials, the recovery from spent lithium-ion batteries remains challenging. This article presents acidic reductive leaching as a promising alternative for lithium extraction from secondary sources and unconventional ores, emphasizing its potential benefits, such as higher recovery rates, faster processing, and adaptability to various waste materials. Notably, this method facilitates the selective recovery of lithium before cobalt and nickel, providing a strategic advantage. This study highlights the lack of optimization studies on leaching conditions (e.g., acid concentration, reducing agents, temperature, and time) that could maximize lithium recovery while minimizing environmental and economic costs. The article aims to investigate and optimize the parameters of acidic reductive leaching for more efficient lithium recovery. Additionally, the results contribute to the principles of the circular economy and sustainable supply chains in the energy sector, providing a method to reduce dependency on geopolitically constrained lithium resources and supporting the global energy transition toward cleaner energy solutions. Full article

The widespread adoption of Electric Vehicles (EVs) in the smart grid is transforming the traditional grid into a more complex system. EVs have the ability to both charge and discharge, acting as loads that draw high power and sources that inject energy back into the grid. Consequently, energy sharing and management within smart grid communities integrated with EVs have become interesting aspects to study in order to efficiently utilize this energy. However, most existing research focuses solely on energy sharing within single communities, utilizing homogeneous energy profiles and neglecting the potential of heterogeneous energy across multiple communities. EVs also possess the capability to travel to different places and communities, where they can engage in energy sharing with areas that have varying load profiles and prices. In this work, a novel three-level energy sharing management approach is proposed for a multiple community system integrating movable energy storage such as EVs. This model involves three main entities: the Utility Company (UC), Community Energy Aggregator (CEA), and EVs. The energy sharing problem is formulated as a Stackelberg game, with all entities striving to maximize their utility through optimal strategies, including pricing, energy demand, or supply. The proposed model is validated through comparison with typical human charging behavior, as well as single- and multiple-community two-level game models. The findings reveal that the proposed model successfully optimizes pricing and energy strategies, significantly lowering the peak-to-average ratio and smoothing the overall energy profile. Full article

This paper proposes a dynamic membrane algorithm (DMA)-oriented computing framework designed to optimize decision-making in Customer-to-Green-Manufacturer (C2GM) operations on industrial internet platforms. Unlike traditional methods that focus solely on economic metrics, the DMA integrates membrane computing principles with evolutionary optimization techniques and incorporates green manufacturing objectives (e.g., energy efficiency, waste reduction, carbon footprint). By doing so, it dynamically aligns customer demands with manufacturing capabilities in real time, ensuring both operational efficiency and environmental stewardship. The DMA facilitates parallel and hierarchical processing of complex decision tasks, mapping evolutionary rules and manufacturing operations into a structured membrane system that accelerates convergence and improves scalability. Experimental evaluations—both in controlled simulations and a real-world case study of C2GM operations in Yiwu—demonstrate that the DMA not only achieves faster and more stable convergence than genetic algorithms but also supports greener production processes. This integrated approach thus enhances strategic decision-making, offering a sustainable pathway for advancing industrial internet ecosystems and global supply chains. Full article

The balance between water supply and demand is essential for industrial growth, affecting economic, social, and environmental sustainability. Our research employs a Gaussian process regression for demand prediction. Additionally, it takes into account water limits and policy thresholds when determining the supply, thereby defining a range of uncertainty for both the industrial demand and the supply. A pattern recognition method matches this trade-off range, identifying three patterns to support water management. The study focuses on the analysis of industrial water supply and demand dynamics under uncertain conditions in nine cities (Baiyin, Dingxi, Gannan, Lanzhou, Linxia, Pingliang, Qingyang, Tianshui, and Wuwei) in Gansu Province of China’s Yellow River Basin in 2030. The results of the study show that industrial water use in Baiyin, Linxia, Dingxi, and Tianshui cities falls into Pattern I, providing water resources to support industrial development. Industrial water use in Wuwei, Pingliang, Qingyang, and Gannan cities represents Pattern II, which maintains a balance between supply and demand while allowing flexibility in water demand. Finally, the industrial water use in Lanzhou city is characterized by Pattern III, which requires optimization through structural, technological, and management improvements to mitigate the negative impacts of water scarcity on the sustainable development of the economy and society. The results of the research can be used as a reference for policy making in water resources planning and management in the basin. Full article

Nanogrids are becoming an essential part of modern home power systems, offering sustainable solutions for residential areas. These medium-to-low voltage, small-scale grids, operating at medium-to-low voltage, enable the integration of distributed energy resources such as wind turbines, solar photovoltaics, and battery energy storage systems. However, ensuring power quality, stability, and effective energy management remains a challenge due to the variability of renewable energy sources and evolving customer demands, including the increasing charging load of electric vehicles. This paper reviews the current research on nanogrid architecture, functionality in low-voltage distribution systems, energy management, and control systems. It also explores power-sharing strategies among nanogrids within a microgrid framework, focusing on their potential for supplying off-grid areas. Additionally, the application of blockchain technology in providing secure and decentralized energy trading transactions is explored. Potential challenges in future developments of nanogrids are also discussed. Full article

Water resources security is crucial to the survival and development of human society. A water resources security assessment and dynamic early warning system was constructed. The weights of water resources evaluation indexes were calculated by the entropy weight method, and the water resources security was evaluated with the comprehensive index method. The obstacle degree model was used to identify and analyze the main obstacle factors. The grey model was adopted to predict the future water resources security situation. The empirical study was carried out in Jinan. The results showed that the grade of water resources security in Jinan from 2008 to 2021 showed a gradually increasing trend. The obstacle factors were mainly concentrated in the pressure subsystem, indicating that the contradiction between supply and demand of water resources was the main problem affecting water resources security, which was accorded with the actual situation. The comprehensive index of water resources security from 2022 to 2026 shows a gradually increasing trend on the whole, and the warning situation develops towards a good trend, indicating that remarkable results in comprehensively building a water-saving society and vigorously promoting water pollution control have been achieved. The measures such as optimizing economic structure, improving water use structure, and improving water use efficiency will promote the further development of water resources security in Jinan. Full article

The demand for Critical Raw Materials (CRM) is increasing due to the need to decarbonize economies and transition to a sustainable low-carbon future achieving climate goals. To address this, the European Union is investing in the discovery of new mineral deposits within its territory. The S34I project (Secure and Sustainable Supply of Raw Materials for EU Industry) is developing Earth observation (EO) methods to support this goal. This study compares the performance of two satellites, Sentinel-2 and Landsat-9, for mineral exploration in two geologically distinct areas in northern Spain. The first area, Ria de Vigo, contains marine placer deposits of heavy minerals, while the second, Aramo, hosts Co-Ni epithermal deposits. These sites provide exceptional case studies to improve EO-based methods for CRM exploration onshore and coastal regions, focusing on deposits often overlooked in remote sensing studies. Standard remote sensing methods such as RGB combinations, Principal Component Analysis (PCA), and band ratios were adapted and compared for both satellites. The results showed similar performance in the Ria de Vigo area, but Sentinel-2 performed better in Aramo, identifying a higher number of zones of mineral alterations. The study highlights the advantages of Sentinel-2’s higher spatial resolution, especially for mapping smaller or more scattered mineral deposits. These findings suggest that Sentinel-2 could play a larger role in mineral exploration. This research provides valuable insights into using EO data for diverse CRM deposits. Full article

In recent years, the increasing complexity of natural disasters has highlighted the limitations of existing emergency material assistance systems. To address these challenges, this study proposes a collaborative adaptation mechanism for “peacetime and emergency integration” and develops a supplier evaluation framework. The framework incorporates multi-dimensional indicators such as profit, business credit, regional advantages, and emergency capability. Using a DEMATEL-ANP-based model, supplier L2 is identified as the optimal choice with a weight of 0.285. A fuzzy comprehensive assessment approach is applied to classify emergency materials based on demand urgency, identifying drinking water, rescue tools, medical supplies, and other critical items as priority resources. The evaluation vectors for these materials range from 0.1540 to 0.9909. This study enhances emergency material management through improved information systems, a better control of critical processes, and a unified assurance strategy. It provides theoretical support and practical guidance for more scientific and standardized disaster management practices. Full article