Optimal energy management and operations planning in seaports with smart grid while harnessing renewable energy under uncertainty

Abstract

The importance of energy efficiency and demand response management while harnessing renewable energy draws more attention from many industries in recent years. Seaports, as large scale end-users, aim to adopt energy management systems (EMS) since energy prices have increased over years and sustainable operations is a key target for greening the port industry. Many seaports start to install fully electrified equipment and use electricity as the source of energy because electricity consumption, instead of carbon-intensive energy sources, contributes to the climate change mitigation targets. In this study, a mixed integer linear programming model is suggested to solve the integrated operations planning and energy management problem for seaports with smart grid (e.g. port microgrid) considering uncertain renewable energy generation. The operations planning aims to determine the number of quay cranes (QCs) and yard equipment to assign to each ship for each one hour period. It also determines each ship’s berthing duration which affects the hourly energy consumption due to the cold ironing and the available reefer containers. These plans result in energy demand. Meanwhile, energy management matches energy demand and supply considering different energy pricing schemes and bidirectional energy trading between energy sources (e.g. utility grid, renewable energy sources) and energy storage systems. Results indicate that significant cost savings can be achieved with smart grid (port microgrid) compared to conventional settings. Deploying energy storage systems in port microgrid results in important cost savings. Energy consumption is dominated by QCs, cold-ironing and reefer containers. Finally ports which harness renewable energy obtain significant costs savings on total cost.