The Batch Pan Scheduling Problem represents a major operational challenge in white sugar refineries, where production planning must balance throughput objectives against high and fluctuating energy demands driven by crystallisation. This paper examines batch pan scheduling from an integrated production and energy-aware perspective. A discrete-time mixed-integer linear programming model and a mixed-integer multi-objective formulation are developed to represent the initiation of batch crystallisation cycles across sequential pan stages while accounting for total energy consumption. The models capture material flow dependencies, stage capacity constraints, and the temporal structure of industrial sugarhouse operations. The single-objective model maximises the number of completed batch cycles at the final pan stage within a given planning horizon, directly representing final sugar production. Building on this solution, the multi-objective model incorporates the achieved production level as a constraint with controlled relaxation to minimise total energy consumption. Numerical experiments investigate the influence of planning horizon length on scheduling flexibility and energy performance. Results indicate that extending the planning horizon enhances temporal coordination, enabling a more even distribution of operations and yielding substantial reductions in energy consumption without compromising production output. Furthermore, the multi-objective formulation achieves consistently stable energy performance, with total energy requirements comparable to or lower than those obtained from the single-objective model under the same horizon length. These findings demonstrate the critical role of planning horizon selection in energy-aware batch scheduling and show that energy savings and variability reduction can be realised through improved temporal coordination. The proposed framework provides a transparent and effective decision-support tool for energy-efficient production planning in batch process industries.