Cost Optimal Planning of Energy Supply and Storage Under Demand Uncertainty

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Uncertainties in our energy system, such as consumption and renewables, pose a challenge to system-wide planning. Deterministic approaches are thus insufficient for making techno-economically optimal decisions for the type, scale, and operations of energy supply and storage facilities. This work adopts a stochastic approach and develops a general multi-period optimization model of an energy system consisting of renewable and non-renewable energy supply sources, storage facilities, and uncertain parameters such as energy demand. It uses multi-stage stochastic programming to address multiple probabilistic scenarios for the stochastic parameters modeled as scenario trees. The model evaluates all the scenarios including the deterministic case and prescribes minimum cost options for the energy supply and storage capacities, and multi-period supply allocations to meet energy demand over a time horizon. The model enables assessment of the potential impacts of variations in demand on energy supply and storage costs and plans as demonstrated by the results of the numerical cases.

    Original languageBritish English
    Title of host publication2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages687-691
    Number of pages5
    ISBN (Electronic)9798350323153
    DOIs
    StatePublished - 2023
    Event2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023 - Singapore, Singapore
    Duration: 18 Dec 202321 Dec 2023

    Publication series

    Name2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

    Conference

    Conference2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023
    Country/TerritorySingapore
    CitySingapore
    Period18/12/2321/12/23

    Keywords

    • Energy storage
    • Energy supply
    • Multistage stochastic programming
    • Optimization modeling
    • Planning
    • Uncertainty

    Cite this