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Chance-constrained multi-stage stochastic energy system expansion planning with demand satisfaction flexibility
Journal article   Open access   Peer reviewed

Chance-constrained multi-stage stochastic energy system expansion planning with demand satisfaction flexibility

Yuang Chen, Beste Basciftci and Valerie M. Thomas
International journal of electrical power & energy systems, Vol.155(Part A), 109499
01/2024
DOI: 10.1016/j.ijepes.2023.109499
url
https://doi.org/10.1016/j.ijepes.2023.109499View
Published (Version of record) Open Access

Abstract

A classic multi-period stochastic energy system expansion planning (ESEP) model aims to address demand uncertainty by requiring immediate demand satisfaction for all scenarios. However, this approach may result in an expensive system that deviates from the planner’s long-term goals, especially when facing unexpectedly high demand scenarios. To address this issue, we propose a chance-constrained stochastic multi-stage ESEP model that allows for a portion of demand to remain unmet in specific periods while still ensuring complete demand satisfaction during most of the planning horizon, including the final period. This approach provides more time flexibility to build infrastructure and assess needs, ultimately reducing costs and allowing for a broader view of infrastructure planning options. To solve the chance-constrained stochastic model, we introduce a binary-search-based progressive hedging algorithm heuristic, which is particularly useful for large-scale models. We demonstrate the effectiveness and benefits of implementing the chance-constrained model through a case study of Rwanda using real-world data. •A novel multi-stage stochastic energy planning model is developed.•Chance constraints are used for time flexibility in demand satisfaction.•A binary-search based progressive hedging algorithm is designed.•Case study results show cost savings by using the chance-constrained model.•The proposed model may better reflect how a decision maker may want to proceed.
Sub-Saharan Africa Chance constraints Energy system expansion planning (ESEP) Multi-stage stochastic optimization Power deficit flexibility Progressive hedging algorithm (PHA)

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