Search Results (98)

Additive manufacturing (AM), or 3D printing, is increasingly recognised as a disruptive production technology with the capacity to reduce greenhouse gas (GHG) emissions across manufacturing and transportation sectors. By enabling material efficiency, lightweighting, part consolidation, and decentralised, on-demand production, AM offers pathways to lower embodied energy, minimise waste, and shorten supply chains. This review critically evaluates AM’s role in decarbonisation, with a focus on clean transportation applications, including electric vehicles, fuel cells, and hydrogen storage systems. Case studies quantify energy savings, operational efficiency gains, and life-cycle GHG reductions compared to conventional manufacturing routes. The analysis also addresses technical and economic limitations—such as material availability, scalability, certification, and cost competitiveness—and explores synergies with circular economy principles, digital design optimisation, and artificial intelligence. Policy recommendations and industry–academia collaboration models are proposed to accelerate AM adoption, integrate renewable energy sources, and strengthen recycling infrastructure. By synthesising technical, economic, and policy perspectives, the study positions AM as a critical enabler of net-zero manufacturing and a catalyst for sustainable industrial transformation. Full article

The development of efficient and reliable trajectory-planning strategies for swarms of unmanned aerial vehicles (UAVs) is an increasingly important area of research, with applications in surveillance, search and rescue, smart agriculture, defence operations, and communication networks. This article provides a comprehensive and critical review of the various techniques available for UAV swarm trajectory planning, which can be broadly categorised into three main groups: traditional algorithms, biologically inspired metaheuristics, and modern artificial intelligence (AI)-based methods. The study examines cutting-edge research, comparing key aspects of trajectory planning, including computational efficiency, scalability, inter-UAV coordination, energy consumption, and robustness in uncertain environments. The strengths and weaknesses of these algorithms are discussed in detail, particularly in the context of collision avoidance, adaptive decision making, and the balance between centralised and decentralised control. Additionally, the review highlights hybrid frameworks that combine the global optimisation power of bio-inspired algorithms with the real-time adaptability of AI-based approaches, aiming to achieve an effective exploration–exploitation trade-off in multi-agent environments. Lastly, the article addresses the major challenges in UAV swarm trajectory planning, including multidimensional trajectory spaces, nonlinear dynamics, and real-time adaptation. It also identifies promising directions for future research. This study serves as a valuable resource for researchers, engineers, and system designers working to develop UAV swarms for real-world, integrated, intelligent, and autonomous missions. Full article

The integration of electric vehicles (EVs) into smart grids (SGs) is reshaping both energy systems and mobility infrastructures. This review presents a comprehensive and cross-disciplinary synthesis of current technologies, methodologies, and challenges associated with EV–SG interaction. Unlike prior reviews that address these aspects in isolation, this work uniquely connects three critical pillars: (i) the evolution of energy storage technologies, including lithium-ion, second-life, and hybrid systems; (ii) optimisation and predictive control techniques using artificial intelligence (AI) for real-time energy management and vehicle-to-grid (V2G) coordination; and (iii) cybersecurity risks and post-quantum solutions required to safeguard increasingly decentralised and data-intensive grid environments. The novelty of this review lies in its integrated perspective, highlighting how emerging innovations, such as federated AI models, blockchain-secured V2G transactions, digital twin simulations, and quantum-safe cryptography, are converging to overcome existing limitations in scalability, resilience, and interoperability. Furthermore, we identify underexplored research gaps, such as standardisation of bidirectional communication protocols, regulatory inertia in V2G market participation, and the lack of unified privacy-preserving data architectures. By mapping current advancements and outlining a strategic research roadmap, this article provides a forward-looking foundation for the development of secure, flexible, and grid-responsive EV ecosystems. The findings support policymakers, engineers, and researchers in advancing the technical and regulatory landscape necessary to scale EV–SG integration within sustainable smart cities. Full article

This study examines the role of aggregators in the context of digital energy and the integration of renewable energy sources (RES). The primary economic functions of aggregators are examined, including their role in optimizing energy markets and enhancing the flexibility and resilience of electricity systems. Different business models are presented, including the Energy as a Service (EaaS) model, and the effects of aggregators’ participation in electricity markets and balancing markets are examined. Special attention is paid to models for optimizing trading strategies and energy storage management. A comparative assessment of two scenarios for the distribution of the energy mix between solar and wind energy in the period 2022–2024 is conducted, evaluating the necessary storage capacities to achieve energy sustainability. The study highlights the importance of aggregators for grid stability, the integration of RES, and achieving higher efficiency through digitalisation and decentralisation in the context of European energy policy and the transition to a low-carbon economy. Full article

The research and analyses presented in this paper are an attempt to prove the concept that a flexible and efficient energy transformation requires a gradual digitalization of the energy system, starting from the inside out, i.e., from the low-voltage micro- and nano-grids, which mostly integrate low-power photovoltaic power plants and consumers with similar demand profiles. This approach is supported by the two main advantages of these grids: they are almost similar in structure and they are scalable, the two characteristics indicating a possible successful digitalization. For this to happen, we need to study the problems in these grids and be aware of the technological maturity of the energy facilities. This paper (the first of several to follow) examines the electricity performance problems caused by the stochastic nature of solar generation. A technique for monitoring and predictive load analysis is proposed, as well as technical measures for implementing decentralised control. Full article

In rural Ghana, limited access to affordable, clean cooking fuels drives the need for decentralised waste-to-energy solutions. Anaerobic co-digestion (AcoD) offers a viable route for transforming organic residues into renewable energy, with the added benefit of improved process stability resulting from substrate synergy. This study aims to evaluate the technical feasibility and stabilisation challenges of AcoD, using locally available fruit waste and beet molasses at a secondary school in Bedabour (Ghana). Biological methane potential (BMP) assays of different co-digestion mixtures were conducted at two inoculum-to-substrate (I/S) ratios (2 and 4), identifying the highest yield (441.54 ± 45.98 NmL CH₄/g VS) for a mixture of 75% fruit waste and 25% molasses at an I/S ratio of 4. Later, this mixture was tested in a 6 L semi-continuous AcoD reactor. Due to the high biodegradability of the substrates, volatile fatty acid (VFA) accumulation led to acidification and process instability. Three low-cost mitigation strategies were evaluated: (i) carbonate addition using eggshell-derived sources, (ii) biochar supplementation to enhance buffering capacity, and (iii) the integration of a bioelectrochemical system (BES) into the AcoD recirculation loop. The BES was intended to support VFA removal and enhance methane recovery. Although they temporarily improved the biogas production, none of the strategies ensured long-term pH stability of the AcoD process. The results underscore the synergistic potential of AcoD to enhance methane yields but also reveal critical stability limitations under high-organic-loading conditions in low-buffering rural contexts. Future implementation studies should integrate substrates with higher alkalinity or adjusted organic loading rates to ensure sustained performance. These findings provide field-adapted insights for scaling-up AcoD as a viable renewable energy solution in resource-constrained settings. Full article

This research introduces a two-stage, low-carbon industrial heating process, leveraging advanced waste heat recovery (WHR) technologies and exploiting waste heat (WH) to drive decentralised hydrogen production. This study is supported by a data-driven analysis of individual technologies, followed by 0D modelling of the integrated system for technical and feasibility assessment. Within 10 years, the EU industry will be supported by two main strategies to transition to low-carbon energy: (a) shifting from grid-mix electricity towards fully renewable sources, and (b) expanding low-carbon hydrogen infrastructure within industrial clusters. On the demand side, process heating in the industrial sector accounts for 70% of total energy consumption in industry. Almost one-fifth of the energy consumed to fulfil the process heat demand is lost as waste. The proposed heating solution is tailored for process heat in industry and stands apart from the dual-mode residential heating system (i.e., heat pump and gas boiler), as it is based on integrated and simultaneous operation to meet industry-level reliability at higher temperatures, focusing on WHR and low-carbon hydrogen. The solution uses a cascaded heating approach. Low- and medium-temperature WH are exploited to drive high-temperature heat pumps (HTHPs), followed by hydrogen burners fuelled by hydrogen generated on-site by electrolysers, which are powered by advanced WHR technologies. The results revealed that the deployment of the solution at scale could fulfil ~14% of the process heat demand in EU/UK industries by 2035. Moreover, with further availability of renewable energy sources and clean hydrogen, it could have a higher contribution to the total process heat demand as a low-carbon solution. The economic analysis estimates that adopting the combined heating solution—benefiting from the full capacity of WHR for the HTHP and on-site hydrogen production—would result in a levelised cost of heat of ~EUR 84/MWh, which is lower than that of full electrification of industrial heating in 2035. Full article

The goals of the European Union towards the energy transition imply profound changes in the energy field, so as to promote sustainable energy development while fostering economic growth. To achieve these changes, the incorporation of sustainable technologies supporting decentralisation, energy efficiency, renewable energy production, and demand flexibility is of vital importance. Blockchain has the potential to change energy services towards this direction. To optimally exploit blockchain, innovative business models need to be designed, identifying the opportunities emerging from unmet needs, while also considering potential risks so as to take action to overcome them. In this context, the scope of this paper is to examine the opportunities and the risks that emerge from the adoption of blockchain in four innovative business models, while also identifying mitigation strategies to support and accelerate the energy transition, thus proposing optimal approaches of exploitation of blockchain in energy services. The business models concern Energy Performance Contracting with P4P guarantees, improved self-consumption in energy cooperatives, energy efficiency and flexibility services for natural gas boilers, and smart energy management for EV chargers and HVAC appliances. Firstly, the value proposition of the business models is analysed and results in a comprehensive SWOT analysis. Based on the findings of the analysis and consultations with relevant market actors, in combination with the examination of the relevant literature, risks are identified and evaluated through a qualitative assessment approach. Subsequently, specific mitigation strategies are proposed to address the detected risks. This research demonstrates that blockchain integration into these business models can significantly improve energy efficiency, reduce operational costs, enhance security, and support a more decentralised energy system, providing actionable insights for stakeholders to implement blockchain solutions effectively. Furthermore, according to the results, technological and legal risks are the most significant, followed by political, economic, and social risks, while environmental risks of blockchain integration are not as important. Strategies to address risks relevant to blockchain exploitation include ensuring policy alignment, emphasising economic feasibility, facilitating social inclusion, prioritising security and interoperability, consulting with legal experts, and using consensus algorithms with low energy consumption. The findings offer clear guidance for energy service providers, policymakers, and technology developers, assisting in the design, deployment, and risk mitigation of blockchain-enabled business models to accelerate sustainable energy development. Full article

Implementing energy-efficient solutions and developing energy complexes to decentralise power supply are key objectives for enhancing national security in Ukraine and Eastern Europe. This study compares the design, numerical, and experimental parameters of a channel-type jet-reaction turbine. A steam turbogenerator unit and a pilot industrial experimental test bench were developed to conduct full-scale testing of the unit. The article presents experimental data on the operation of a steam turbogenerator unit with a capacity of up to 475 kW, based on a channel-type steam jet-reaction turbine (JRT), and includes the validation of a computational fluid dynamics (CFD) model against the obtained results. For testing, a pilot-scale experimental facility and a turbogenerator were developed. The turbogenerator consists of two parallel-mounted JRTs operating on a single electric generator. During experimental testing, the system achieved an electrical output power of 404 kW at a turbine rotor speed of 25,000 rpm. Numerical modelling of the steam flow in the flow path of the jet-reaction turbine was performed using ANSYS CFX 25 R1 software. The geometry and mesh setup were described, boundary conditions were defined, and computational calculations were performed. The experimental results were compared with those obtained from numerical simulations. In particular, the discrepancy in the determination of the power and torque on the shaft of the jet-reaction turbine between the numerical and full-scale experimental results was 1.6%, and the discrepancy in determining the mass flow rate of steam at the turbine inlet was 1.34%. JRTs show strong potential for the development of energy-efficient, low-power turbogenerators. The research results confirm the feasibility of using such units for decentralised energy supply and recovering secondary energy resources. This contributes to improved energy security, reduces environmental impact, and supports sustainable development goals. Full article

The Mediterranean region is increasingly confronted with intersecting environmental, agricultural, and socio-economic challenges, including biowaste accumulation, soil degradation, and high dependency on imported fossil fuels. Biomethane, a renewable substitute for natural gas, offers a strategic solution that aligns with the region’s need for sustainable energy transition and circular resource management. This review examines the current state of biomethane production in the Mediterranean area, with a focus on anaerobic digestion (AD) technologies, feedstock availability, policy drivers, and integration into the circular bioeconomy (CBE) framework. Emphasis is placed on the valorisation of regionally abundant feedstocks such as olive pomace, citrus peel, grape marc, cactus pear (Opuntia ficus-indica) residues, livestock manure, and the Organic Fraction of Municipal Solid Waste (OFMSW). The multifunctionality of AD—producing renewable energy and nutrient-rich digestate—is highlighted for its dual role in reducing greenhouse gas (GHG) emissions and restoring soil health, especially in areas threatened by desertification such as Sicily (Italy), Spain, Malta, and Greece. The review also explores emerging innovations in biogas upgrading, nutrient recovery, and digital monitoring, along with the role of Renewable Energy Directive III (RED III) and national biomethane strategies in scaling up deployment. Case studies and decentralised implementation models underscore the socio-technical feasibility of biomethane systems across rural and insular territories. Despite significant potential, barriers such as feedstock variability, infrastructural gaps, and policy fragmentation remain. The paper concludes with a roadmap for research and policy to advance biomethane as a pillar of Mediterranean climate resilience, energy autonomy and sustainable agriculture within a circular bioeconomy paradigm. Full article

As electric vehicles (EVs) become increasingly integrated into urban mobility, the load on electrical grids increases, prompting innovative energy management strategies. This paper investigates the deployment of vehicle-to-grid (V2G) services at the University of Rome Tor Vergata, leveraging high-resolution floating car data (FCD) to forecast and schedule energy transfers from EVs to the grid. The methodology follows a four-step process: (1) vehicle trip detection, (2) the spatial identification of V2G in the campus, (3) a real-time scheduling algorithm for V2G services, which accommodates EV user mobility requirements and adheres to charging infrastructure constraints, and finally, (4) the predictive modelling of transferred energy using ARIMA and LSTM models. The results demonstrate that substantial energy can be fed back to the campus grid during peak hours, with predictive models, particularly LSTM, offering high accuracy in anticipating transfer volumes. The system aligns energy discharge with campus load profiles while preserving user mobility requirements. The proposed approach shows how campuses can function as microgrids, transforming idle EV capacity into dynamic, decentralised energy storage. This framework offers a scalable model for urban energy optimisation, supporting broader goals of grid resilience and sustainable development. Full article

Biomimetics has emerged as a transformative interdisciplinary approach that harnesses nature’s evolutionary strategies to develop sustainable solutions across diverse fields. This study explores its integrative role in shaping smart cities, advancing artificial intelligence and robotics, innovating biomedical applications, and enhancing computational design tools. By analysing the evolution of biomimetic principles and their technological impact, this work highlights how nature-inspired solutions contribute to energy efficiency, adaptive urban planning, bioengineered materials, and intelligent systems. Furthermore, this paper discusses future perspectives on biomimetics-driven innovations, emphasising their potential to foster resilience, efficiency, and sustainability in rapidly evolving technological landscapes. Particular attention is given to neuromorphic hardware, a biologically inspired computing paradigm that mimics neural processing through spike-based communication and analogue architectures. Key components such as memristors and neuromorphic processors enable adaptive, low-power, task-specific computation, with wide-ranging applications in robotics, AI, healthcare, and renewable energy systems. Furthermore, this paper analyses how self-organising cities, conceptualised as complex adaptive systems, embody biomimetic traits such as resilience, decentralised optimisation, and autonomous resource management. Full article

Increasing energy efficiency and promoting the use of sustainable energy sources are crucial for addressing global energy challenges. Organic Rankine cycle (ORC) technology offers a promising route for efficient decentralised power generation. This study examines the energy performance of a biomass-fired recuperative ORC for micro-scale applications. The investigation proposes an extensive experimental analysis to characterise the ORC behaviour under design and off-design conditions due to the limited data in the literature. The work examines the impact of different operating parameters (e.g., pump speed, hot source temperature, superheating degree, expander inlet pressure) to provide suitable insights for the efficient design and operation of recuperative micro-generation units fuelled by biomass. The experimental analysis highlights that the micro-scale ORC properly operates under a wide range of operating conditions. Electric power ranges between 0.37 kW and 2.30 kW, and the maximum net electric efficiency reaches 8.55%. The selection of the proper operating conditions guarantees efficiency higher than 7% for power larger than 800 W, demonstrating that biomass-fired recuperative ORC systems represent a valuable option for low-carbon micro-scale generation, with good performance in design and off-design conditions. For this purpose, the pump speed and the superheating degree at the expander inlet are essential parameters to maximise the performance of the investigated recuperative ORC. Full article

This paper presents an analysis of energy use and sector coupling in a local energy community using a model based on energy cost centres (ECCs), functional units for decentralised responsibility and optimisation of energy use within defined system boundaries. The ECC model enables structured identification and optimisation of energy and material flows in complex industrial and urban settings. It was applied to a case study involving an energy-intensive steel plant and its integration with the surrounding community. The study assessed the potential for renewable electricity production (7914 MWh annually), green hydrogen generation, battery storage, and the reuse of 11,440 MWh of excess heat. These measures could offset 9598 MWh of grid electricity through local production and savings, reduce natural gas use by 4,116,850 Nm³, and lower CO₂ emissions by 10,984 tonnes per year. The model supports strategic planning by linking sectoral actions to measurable sustainability indicators. It is adaptable to data availability and stakeholder engagement, allowing both high-level overviews and detailed analysis of selected ECCs. Limitations include heterogeneous data sources, uneven stakeholder participation, and the need for refinement of sub-models. Nonetheless, the approach offers a replicable framework for integrated energy planning and supports the transition to sustainable, decentralised energy systems. Full article

Inverter-based resources (IBRs) are becoming more prominent due to the increasing penetration of renewable energy sources that reduce power system inertia, compromising power system stability and grid support services. At present, optimal coordination among generation technologies remains a significant challenge for frequency control services. This paper presents a novel networked multi-agent deep reinforcement learning (N—MADRL) scheme for optimal dispatch and frequency control services. First, we develop a model-free environment consisting of a photovoltaic (PV) plant, a wind plant (WP), and an energy storage system (ESS) plant. The proposed framework uses a combination of multi-agent actor-critic (MAAC) and soft actor-critic (SAC) schemes for optimal dispatch of active power, mitigating frequency deviations, aiding reserve capacity management, and improving energy balancing. Second, frequency stability and optimal dispatch are formulated in the N—MADRL framework using the physical constraints under a dynamic simulation environment. Third, a decentralised coordinated control scheme is implemented in the HPP environment using communication-resilient scenarios to address system vulnerabilities. Finally, the practicality of the N—MADRL approach is demonstrated in a Grid2Op dynamic simulation environment for optimal dispatch, energy reserve management, and frequency control. Results demonstrated on the IEEE 14 bus network show that compared to PPO and DDPG, N—MADRL achieves 42.10% and 61.40% higher efficiency for optimal dispatch, along with improvements of 68.30% and 74.48% in mitigating frequency deviations, respectively. The proposed approach outperforms existing methods under partially, fully, and randomly connected scenarios by effectively handling uncertainties, system intermittency, and communication resiliency. Full article