Dirichlet sampled capacity and loss estimation for LV distribution networks with partial observability

Telford, Rory and Stephen, Bruce and Browell, Jethro and Haben, Stephen (2021) Dirichlet sampled capacity and loss estimation for LV distribution networks with partial observability. IEEE Transactions on Power Delivery, 36 (5). 2676 - 2686. ISSN 0885-8977 (https://doi.org/10.1109/TPWRD.2020.3025125)

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Abstract

With low voltage (LV) distribution networks increasingly being re-purposed beyond their original design specifications to accommodate low carbon technologies, the ability to accurately calculate their actual spare capacity is critical. Traditionally, within the Great Britain (GB) power system, there has been limited monitoring of LV distribution networks, making this difficult. This paper proposes a method for estimating spare capacity of unmonitored LV networks using demand data from customer Smart Meters. In particular, the proposed method infers existing LV network capacity, as well as losses, across scenarios where only a limited number of customers have Smart Meters installed. Typical daily load profiles across customers with Smart Meters are learned using a Dirichlet sampled Gaussian mixture model (GMM). Learned profiles are then applied to all unmetered customers to estimate network parameters. Method accuracy is assessed by comparing estimations with simulated, fully observed, LV network models. The method is also compared to benchmark models for establishing unobserved demand profiles. Overall, results in the paper show that the proposed method outperforms benchmark models in terms of accurately assessing substation headroom, particularly in scenarios where only 10-50% of customers have Smart Meters installed.

ORCID iDs

Telford, Rory ORCID logoORCID: https://orcid.org/0000-0001-6450-4302, Stephen, Bruce ORCID logoORCID: https://orcid.org/0000-0001-7502-8129, Browell, Jethro ORCID logoORCID: https://orcid.org/0000-0002-5960-666X and Haben, Stephen;
  • Item type:Article
    ID code:73916
    Dates:
    Date
    Event
    October 2021
    Published
    18 September 2020
    Published Online
    14 September 2020
    Accepted
    Notes:© 2020 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
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:18 Sep 2020 14:18
    Last modified:11 Nov 2024 12:50
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/73916
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