Peak Shaving the Electrical Power Demand of Ship-to-shore Cranes

Abstract

Electrification of numerous end-users is a worldwide trend to address climate change, according to the International Energy Agency. This trend has also reached container terminal operators. Currently most of the ship-to-shore cranes employed are electrified, leading to an increase in the required electrical power demand and to an increase in the volatility of the electrical power demand of container terminals. As a result, the contractual power demand charged by the grid operator, based on the maximum required power demand (peak power) at any moment in time, is upscaled, leading to additional costs for the container terminal operator. However, the highest required power demand values occur infrequently, leading to significant expenses for a resource that is rarely utilised. By implementing a peak shaving strategy, the peak power can be reduced, leading to a decrease in the contractual power demand related costs. Nevertheless, it is crucial to minimise the impact of the specific peak shaving strategy on the productivity of a container terminal to actually derive economic benefits from its implementation.

The aim of this study is to develop operational policies that effectively maintain productivity for a cluster of six ship-to-shore cranes under increasingly restrictive peak power limitations. A discrete event simulation approach was employed for evaluating the operational and economic impact. In total four policies were developed, two according to the `who fits is served' approach (policy 0 and policy 1) and two according to the `priority based' approach (policy 2 and policy 3). In the first approach the initiation of a movement only depends on the power availability, while for the second approach the initiation of a movement depends on the power availability and the urgency of the movement in terms of productivity. Moreover, for both approaches one policy allows only one kinematic profile (policy 0 and policy 2) and one policy allows varying kinematic profiles (policy 1 and policy 3). A metaheuristic was employed to find near-optimal adapted kinematic profiles.

The findings of this study suggest that the established `priority based' approach is more effective than the `who fits is served' approach in maintaining productivity under increasingly restrictive peak power limitations. When combined with the allowance of adapted kinematic profiles (policy 3), this strategy achieves the most cost savings. Policy 3, has been shown to reduce the contractual power demand related costs by 53\% compared to the baseline scenario, which is the greatest recorded reduction of all created policies without adversely affecting the ship-to-shore cranes' productivity.