Designing future energy scenarios is an important topic to energy planners. As designing future optimized scenarios is a multi-objective optimization problem; therefore, it is required to identify trade-off scenarios (Pareto-front) in order to optimize conflicting objectives. In this study, three Pareto-fronts are identified for designing future scenarios for Val di Non (VdN) for three different time horizons. As the community has to reach different emission targets in different time horizons, it is require to select the optimized scenarios that fulfill the targets. In this regards, we propose a new approach for selecting scenarios based on maximizing decision space diversity in order to provide a diverse set of scenarios to the decision makers. The technique is tested on optimized scenarios of VdN and three sets containing 10 diverse scenarios for different time horizons are selected. Moreover, a smooth transition (in terms of decision variables) is desirable when having a transition from a scenario from one time horizon to a consecutive time horizon. A novel method is proposed to choose scenarios from the sets for a smooth transition based on minimizing distances among the scenarios. The approach is applied on VdN where transient scenarios are identified among different possible optimized scenarios.

设计未来的能源方案是能源规划人员的重要课题。设计未来的优化方案是一个多目标优化问题。因此，需要确定权衡方案（Pareto-front）以优化冲突的目标。在这项研究中，确定了三个Pareto前沿，以便为三个不同的时间范围设计Val di Non（VdN）的未来方案。由于社区必须在不同的时间范围内达到不同的排放目标，因此需要选择能够实现目标的优化方案。在这方面，我们提出了一种基于最大化决策空间多样性来选择方案的新方法，以便为决策者提供一组多样化的方案。该技术在VdN的优化方案上进行了测试，并选择了三组包含10种不同方案的不同时间范围。此外，当具有从一个时间范围的场景到连续时间范围的过渡时，期望平滑的过渡（就决策变量而言）。提出了一种基于最小化场景之间距离的，从集合中选择场景以进行平滑过渡的新方法。该方法适用于VdN，其中在不同的可能优化方案中标识了临时方案。提出了一种基于最小化场景之间距离的，从集合中选择场景以进行平滑过渡的新方法。该方法适用于VdN，其中在不同的可能优化方案中标识了临时方案。提出了一种基于最小化场景之间距离的，从集合中选择场景以进行平滑过渡的新方法。该方法适用于VdN，其中在不同的可能优化方案中标识了临时方案。