An innovative multi-objective optimization approach for long-term energy planning. (15th December 2017)

• Record Type: Journal Article
• Authors: Mahbub, Md Shahriar; Viesi, Diego; Cattani, Sara; Crema, Luigi
• Is Part Of: Applied energy. Volume 208(2017)
• Page Start: 1487
• Page End: 1504
• Publication Date: 2017-12-15
• Subjects: Energy system optimization -- Multi-objective evolutionary optimization -- Long-term energy planning -- Energy transition; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2017.08.245
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Future optimized scenarios are identified by considering future demands and costs. Optimized scenarios are identified for three different time-horizons. A method is proposed for selecting target scenarios from optimized ones. A technique is proposed to design a smooth transition path. Best suited transient scenarios are chosen from the selected scenarios. Abstract: 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.