Modelling and implementing smart micro-grids for fish-processing industry

Fish processing industries involve the usage of energy-intensive equipment, such as refrigerators, air conditioners and ice making machines leading to high energy costs and, indirectly, to an increase of the carbon emissions. As most fish industries sites are old, there is a strong need to make them more sustainable and achieve economic competitiveness in the energy market. Micro-grids have been utilised as efficient solutions in energy-intensive industries greatly balancing energy consumption and production at different scales. Smart micro-grids can also reduce carbon emissions by using renewable energy resources and applying smart energy management techniques.In this paper, we propose a smart micro-grid system for fish-processing industries with a validation use-case at Milford Haven Port in South Wales, UK. The system has been modelled using EnergyPlus and Matlab with the infinite grid, renewable energy resource, battery and charge/discharge controllers utilized for optimising energy consumption and production and for reducing carbon emissions. The preliminary results show that local power demand can meet the local power generation with the implementation of smart energy management techniques to support decision making for fish-processing industries

Analysis and simulation of smart energy clusters and energy value chain for fish processing industries

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

Optimal control-based price strategies for smart fishery ports micro-grids

The recent ongoing digital transformation of the energy landscape provides new opportunities to decarbonise energy-intensive industries, including the fish processing sector. The paper explores the potential of deploying multi-vector smart micro-grid solutions in fishery ports, sourced from dispatchable renewable generation, including solar energy. This is demonstrated in the Milford Haven Port in South Wales, United Kingdom. The proposed system is modelled using control scenarios developed based on data and energy models of the port. The control scenario makes energy use decisions based on the availability of dispatchable renewable sources and the price of energy from the local energy market. Also, we consider local energy storage by utilising the local electric fishing boat fleet as an alternative energy storage system. The results demonstrate optimised energy use through multi-vector smart micro-grid model by providing more than 70 percent reduction of energy use from grid

Federating smart cluster energy grids for peer-to-peer energy sharing and trading

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

Developing smart energy communities around fishery ports: toward zero-carbon fishery ports

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

Decarbonisation of seaports: A review and directions for future research

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 advances 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 landscape for greening seaports, and implementing green port practices guidelines. As such, the paper provides a critical review of existing technologies and concepts 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 management, (b) Semantic-based modelling, forecasting and optimisation of seaports energy systems, (c) Secure and reliable seaports energy services, and (d) Transition 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