A multi-objective framework for long-term generation expansion planning with variable renewables. (1st November 2019)

• Record Type: Journal Article
• Authors: Oree, Vishwamitra; Sayed Hassen, Sayed Z.; Fleming, Peter J.
• Is Part Of: Applied energy. Volume 253(2019)
• Publication Date: 2019-11-01
• Subjects: Flexibility objective -- Generation expansion -- Evolutionary algorithm -- Unit commitment -- Decision-making -- Pareto-optimal investment plans; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.113589
• Languages: English
• ISSNs: 0306-2619

Abstract

Graphical abstract: Highlights: Framework considers flexibility, cost and CO2 emissions as separate objectives. Overlooking flexibility in generation planning gives rise to infeasible portfolios. Analysis of Pareto-optimal solutions reveals potential correlations among objectives. Unit commitment validates evaluation of flexibility in generation plans by model. Parallel coordinates plots help in the selection of preferred investment plan. Abstract: The growing importance of operational flexibility in generation expansion planning with increased integration of variable renewables has been regularly highlighted in recent research. Yet, operational flexibility has been largely overlooked in order to reduce the prohibitive problem size that results when operational details at small timescales are included in this long-term exercise. In this work, we present a multi-objective optimization framework that effectively and tractably incorporates flexibility screening of candidate generation portfolios in long-term generation expansion planning. Operational flexibility is considered as a separate objective along with the traditional economic and environmental objectives. The ability of the proposed methodology to provide valuable insights into the correlations between flexibility, total costs and carbon emissions is demonstrated using a case study. The results clearly reveal that omission of flexibility from the framework gives rise to deficient generation mixes that are unable to match the more frequent and steeper variations in net load. A high-level evaluation of the flexibility needed in generation portfolios to balance net loads with different degrees of variability is also provided. Finally, a procedure is proposed to support the decision-making process for selecting the most appropriate investment plan among the many solution options provided by the multi-objective optimization framework.