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Many seaports are facing increasing pressure to reduce their carbon footprint, while increasing their energy efficiency and global competitiveness. Moreover, energy consumption in seaports is continuously monitored to manage the increasing energy costs, these rising costs are reflected in the increased fuel demand. The fishing industry is one of the most energy intensive activity at seaports. In addition, the global human consumption of fish increased dramatically from 1950 to 2012. This paper will develop a roadmap to convert fishing ports into carbon-free ports. A number of techniques and methodologies will be used to analyze energy consumption in the port and buildings, and will include sustainability informed decision making. The overall objective of the net-zero port is to reduce energy dependence from the national grid by taking advantage of the electricity produced locally from solar energy. The roadmap that we have developed will contribute to the emergence of carbon-free fishery port ecosystem that can implement sustainable energy practices, including an assessment of the quality of the energy used in the fishery port and informed practices for promoting carbon-free societies.

The Irish Seafood agency reports that 15% of global energy is consumed by operations related to refrigeration and air conditioning in the fish industry which stresses the importance of integration with clean renewables and adoption of smart energy management solutions. While fish processing industries have high energy costs with continuous refrigeration, air conditioning and ice making processes, there is a real need to analyse and model energy use in fish ports to understand environmental impacts in terms of CO2 emissions while exploring the potential for integrating renewable energy sources.In this paper, we conduct energy modelling and optimization for the Milford Haven fish processing port in South Wales. We explain how a simulation capability can be developed at the fish industry port level and propose a simulation-based optimization strategy to determine optimized schedules for appliances. The results show that energy consumption can be reduced with the use of optimized appliance schedules developed in relation to the total energy demand as well as a wide range of optimization constraints. Keywords: Energy analysis, Energy modelling, Simulation, Optimization, Renewable energy, Scheduling appliances

The aerospace industry faces challenges in managing inventory effectively due to long product life cycles and unpredictable demand. Additive Manufacturing (AM) is a promising technology that enables the on-demand production of spare parts, potentially reducing inventory costs and improving supply chain efficiency. This paper proposes a novel conceptual framework for employing AM in the aerospace spare parts industry to isolate demand volatility. A conceptual approach is employed in this study, which involves a comprehensive literature review to identify the factors to consider when employing AM for spare parts and the methods for demand volatility isolation, followed by a structured framework development that outlines the decision-making steps for AM utilization based on the identified factors. The framework outlines a structured approach for using AM to produce spare parts and isolate demand volatility, which can help mitigate the impact of demand uncertainty on inventory management. The proposed approach provides a basis for future research and has the potential to transform how spare parts are produced and managed in the aerospace industry. Overall, this paper contributes to the emerging literature on AM in the aerospace industry by presenting a novel approach to improving inventory management and addressing demand uncertainty.

Marine activities in seaports account for circa 3% of total carbon emissions worldwide, prompting several initiatives to decarbonise their energy systems and make seaports smarter and greener. This paper provides a thorough and authoritative review of the vast array of research in this field, including past and ongoing initiatives. The study reveals that existing research leverages recent ad-vances in digital technologies while focusing on one or several of the following themes: carbon reduction, use of renewable energy resources, cost-performance optimisation, deployment of smart control technologies, the regulatory land-scape for greening seaports, and implementing green port practices guidelines. As such, the paper provides a critical review of existing technologies and con-cepts that promote and contribute to the decarbonisation of seaports, including Smart Grids and Virtual Power Plants. Several avenues for future research are then discussed, including (a) total life cycle approach to seaport energy manage-ment, (b) Semantic-based modelling, forecasting and optimisation of seaports energy systems, (c) Secure and reliable seaports energy services, and (d) Transi-tion towards prosumer-driven seaport energy communities. The paper concludes by emphasising the importance of an adapted energy regulatory landscape at a national and EU-wide level to meet EU phased energy reduction targets.

With the rapid growth in clean distributed energy resources involving micro-generation and flexible loads, users can actively manage their own energy and have the capability to enter in a market of energy services as prosumers while reducing their carbon footprint. The coordination between these distributed energy resources is essential in order to ensure fair trading and equality in resource sharing among a community of prosumers. Peer-to-Peer (P2P) networks can provide the underlying mechanisms for supporting such coordination and offer incentives to prosumers to participate in the energy market. In particular, the federation of energy clusters with P2P networks has the potential to unlock access to energy resources and lead to the development of new energy services in a fast-growing sharing energy economy. In this paper, we present the formation and federation of smart energy clusters using P2P networks with a view to decentralise energy markets and enable access and use of clean energy resources. We implement a P2P framework to support the federation of energy clusters and study the interaction of consumers and producers in a market of energy resources and services. We demonstrate how energy exchanges and energy costs in a federation are influenced by the energy demand, the size of energy clusters and energy types. We conduct our modelling and analysis based on a real fish industry case study in Milford Haven, South Wales, as part of the EU H2020 INTERREG piSCES project.

Air quality and energy consumption are among the top ten environmental priorities in seaports as stated by the European Sea Ports Organization. Globally, it is estimated that 15% of energy consumption can be attributed to refrigeration and air conditioning systems in fishing activities. There is a real need to understand energy usage in fishery ports to help identify areas of improvements, with a view to optimize energy usage and minimize carbon emissions. In this study, we elaborate on ways in which a simulation capability can be developed at the community level with a fishery port, using a real-world case study seaport in Milford Heaven (Wales, UK). This simulation-based strategy is used to investigate the potential of renewable energy, including local solar farms, to meet the local power demand. This has informed the development of a simulation-based optimization strategy meant to explore how smart energy communities can be formed at the port level by integrating the smart grid with the local community energy storage. The main contribution of the paper involves a co-simulation environment that leverages calibrated energy simulation models to deliver an optimization capability that (a) manages electrical storage within a district an environment, and (b) promotes the formation of energy communities in a fishery port ecosystem. This is paving the way to policy implications, not only in terms of carbon and energy reduction, but also in the formation and sustained management of energy communities.