Chance-constrained optimization of storage and PFC capacity for railway electrical smart grids considering uncertain traction load

Chen, Yinyu and Chen, Minwu and Xu, Lie and Liang, Zongyou (2024) Chance-constrained optimization of storage and PFC capacity for railway electrical smart grids considering uncertain traction load. IEEE Transactions on Smart Grid, 15 (1). pp. 286-298. 3276198. ISSN 1949-3053 (https://doi.org/10.1109/tsg.2023.3276198)

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Abstract

To foster the utilization of regeneration braking energy and suppress voltage unbalance (VU), a railway electrical smart grid (RESG), intergraded with power flow controller (PFC) and energy storage (ES), is proposed as an important part of next-generation electrified railways. However, under the uncertain traction load, how to design the optimal size of PFC-ES is a challenge during the planning period. Hence, this paper proposes a chance-constrained two-stage programming approach. The first-stage aims to minimising the overall cost of RESG’s devices. The second-stage aims to arrange the energy flow of the PFC-ES with the objective of minimising the expected operation cost under the dynamic VU restriction, and the stochastics characteristics of traction load are transformed into a chance constraint by using a scenario approach. Then, traction power predictions are combined with multivariate Gaussian Mixture Model (multi-GMM) model to generate correlated traction power flow scenarios and to assess VU probabilistic metrics distribution with different confidence levels. Finally, a novel algorithm is designed to select the confidence level and violation probability so that the capacity planning results can ensure the high-efficient and high-quality operation of the RESG. Case studies based on an actual electrified railway demonstrate that the proposed PFC-ES sizing approach can reduce the overall cost by up to 13%.

ORCID iDs

Chen, Yinyu, Chen, Minwu, Xu, Lie ORCID logoORCID: https://orcid.org/0000-0001-5633-7866 and Liang, Zongyou;
  • Item type:Article
    ID code:85694
    Dates:
    Date
    Event
    1 January 2024
    Published
    15 May 2023
    Published Online
    10 May 2023
    Accepted
    Notes:© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering > Production of electric energy or power
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:05 Jun 2023 15:20
    Last modified:11 Nov 2024 13:57
    URI:https://strathprints.strath.ac.uk/id/eprint/85694
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