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137. Strategic Planning for Transition to Next Generation Clean Energy Technologies using Stochastic Programming

Invited abstract in session MA-21: Planning problems in electrical energy systems, stream OR in Energy.

Monday, 8:30-10:00
Room: 49 (building: 116)

Authors (first author is the speaker)

1. Burak Kocuk
Industrial Engineering, Sabanci University
2. Neman Karimi
Industrial Engineering, Sabanci University

Abstract

In recent years, the transition from fossil fuels to clean energy technologies has accelerated. Although this transition might bring environmental and economic benefits, it requires a long-term strategic plan due to the large investment costs involved. In addition, the uncertainties in the technical and economic development of next generation clean energy technologies should be included in this plan. Our research focuses on optimizing strategic plans for the transition to next generation clean energy technologies using stochastic programming. As a case study, we examine the Machine Replacement Problem under Technological Advances. Although it is common to periodically replace machines that completed their economic lifetimes, the exact times of replacement should be optimally determined. For example, in the short-term, it might seem beneficial to replace a conventional machine with an existing clean technology whereas in the long-term, it might be more beneficial to wait and replace it with a future technology that is currently evolving. We formulate this problem using multistage stochastic programming by creating technology advancement scenarios. We analyze the underlying problem structure and the computational complexity of deterministic and stochastic versions. We also present how to solve large-scale problems more efficiently. Finally, we discuss potential applications of our approach to real-life problems such as clean energy transitions for fleets and campuses.

Keywords

Status: accepted

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