Decarbonising fishery ports through smart cluster energy systems

The rising energy prices at seaports and fishing industries pose a major challenge because the pace of work and high demand for fish products has increased dra‐matically. This comes at a time of growing international pressure and global moti‐vations to address climate change and reduce carbon emissions in many different sectors of the economy. In the literature review, a few research studies were found to highlight the op‐timal use of power energy in ports, while some studies proposed certain measures that contribute to some extent to reducing energy consumption and carbon emis‐sions. However, there is an absence of a study that discusses the possibility of de‐veloping a holistic energy analysis and management that can be scaled from a site to a community level to achieve economically and environmentally viable benefits to the community. The research study that is described in this thesis aims to develop a compre‐ hensive integrated system for the optimal use of energy in seaports through the de‐velopment of a smart grid system that is based on the renewable energy at Milford Haven Port, which was developed and used as an applied case stud. It is hoped that this study will contribute to reducing energy prices and that the port will achieve economic benefits by sharing its surplus power with the national grid. A five‐stage research methodology has been developed, starting with the pro‐ cess of collecting and analysing data on fishery buildings, known as and energy audit. It then develops energy simulation models at the port using energy simula‐tion software. The next stage aims to propose a smart grid model at multi‐levels, namely a building, port and a community of 200 houses around a fishery port. The next stage consists of the development of two smart decision‐making systems: the first aimed at sharing surplus power with the neighbours of the port through a Peerto Peer (P2P) energy sharing approach; and the second aims to achieve financial in‐comes for the port by selling surplus power to the national grid when energy prices rise, a price‐based control strategy is used in this system The model was developed and tested within 24 hours on randomly selected days during the four seasons of the year. The simulation was characterised by the fact that it was carried out instantaneously to get an accurate result, which resem‐ bles a real‐life system. In addition, the optimal number of energy storage systems was determined at multi‐levels, which achieve the self‐sufficiency of the electric power that is needed to meet the energy demand during the day. Finally, a proposed road map has been developed to achieve nearly zero carbon fishery ports that can be applied to different ports in different locations