Abstract
Seaport cranes operate continuously and consume large amounts of energy while aiming to minimise containerships’ berthing time. Although previous studies have contributed to addressing the crane scheduling problem, most have focused exclusively on loading time, often overlooking the aspect of energy consumption. Furthermore, crane activity is typically modelled in a simplified manner—commonly assuming a fixed cycle duration or constant energy usage when handling a container—without accounting for the impact of variable container masses. In this study, an energy-aware quay crane scheduling formulation for container terminals is proposed, highlighting the importance of integrating an energy model into the scheduling problem. The optimisation problem is formulated as a Mixed Integer Linear Programming (MILP) model. The objective is to minimise total energy costs by reordering the sequence in which containers are handled, while respecting precedence constraints defined by the ship’s stowage plan. Two solution methods—a MILP approach solved using CPLEX and a genetic algorithm (GA)—are compared. The results indicate that, for larger containerships, the genetic algorithm provides a more efficient solution method. Moreover, incorporating detailed energy consumption models for electric cranes may significantly reduce energy costs during containership handling operations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
Recently, there has been growing attention on the decarbonisation of maritime transport, particularly regarding the landside operations at ports. This has spurred the development and implementation of strategies and policies aimed at enhancing the environmental performance of port activities. Among these strategies, the electrification of port infrastructure is emerging as a potential industry standard for the future. However, there remains a significant gap in understanding the patterns of electricity consumption in ports and how to forecast them accurately. To address this gap, this paper provides a review of the current literature on electricity demand in ports, examining practical applications, methodologies employed, and their key limitations. The findings indicate that, despite its importance in supporting the electrification process, electricity demand forecasting in ports has not received substantial attention in either industry or academic research, and there are no clearly established policies to support port authorities in obtaining the necessary data. Finally, the paper outlines potential directions for future research and how port authorities or local government agencies can contribute to these efforts.

Abstract
In this paper an analytical approach is proposed to solving the Environmental/Economic Dispatch problem (EED). The EED is a multiobjective optimization problem (MOP) that has as objectives to minimize the emissions of pollutants and the total fuel cost of meeting the energy requirements of an electrical power network. The Weighted Sum Method is used for the scalarization of the MOP and therefore to find the whole Pareto front. To solve the obtained quadratic programming problem, the Karush-Kuhn-Tucker conditions were used, based on a theoretical condition that allowed us to obtain solutions by solving a system of lineal equations. This strategy was tested on two systems with different number of generators and characteristics. The obtained results were compared with other previously reported elsewhere, showing some evident advantages of our proposal.

Abstract
In this paper, Lagrangian dual formulation is used to solve the Environmental/Economic Dispatch problem. The proposed method, that results quite different from the metaheuristic methods employed in literature, was tested on a six generating units system. The results obtained improve others reported in previous investigations, by simultaneously diminishing the total fuel cost and pollutants emissions.

Abstract
In this paper a duality theory approach is proposed for solving the environmental/economic dispatch problem. For the multiobjective problem scalarization, weighted sum method is used and the associated dual problem is solved using a quadratic programming algorithm. This strategy is tested on three systems with different number of generators and characteristics. The obtained results are compared with other previously reported, showing some advantages of the proposed approach.

Abstract
Although electricity is a clean and relatively safe form of energy when it is used, the generation and transmission of electricity have severe effects on the environment. An alternative to diminish the polluting emissions released by the generating units is the Emission Constrained Economic Dispatch (ECED). This is an optimization problem where the total fuel cost is minimized while treating emissions as a constraint with a pre-specified limit. Usually, the fuel cost and emission functions of the generating units must be experimentally derived, introducing then uncertainties in the obtained models. However, these uncertainties are often neglected and the ECED problem is solved considering the coefficients of the functions involved as exact (totally known) values. In this investigation we analyzed the effect of the uncertainties associated to the experimental derivation of the input–output curves of thermal power plants. Particularly, when polynomial models are fitted through multiple linear regression, we proposed an approach that, based on the respectively prediction intervals, can provide solutions immunized, in some sense, against variability in the coefficients estimates. We tested the proposed approach in a real system from the Chilean electrical power network. For the analyzed system we noted that, when uncertainties are not considered, the deterministic optimal solutions can be environmentally infeasible in some scenarios; whereas solutions obtained through the proposed approach, can significantly diminish the risk of environmental violations. The robustness of the prediction interval-based solutions was obtained with a negligible increase of the total fuel cost in all the cases studied.