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    Assessing the Impacts of DER on Customer Voltages Using Smart Meter-Driven Low Voltage Line Models

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    Author
    Wang, Yiqing
    Date
    2020
    Affiliation
    Electrical and Electronic Engineering
    Metadata
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    Document Type
    Masters Research thesis
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/253892
    Description

    © 2020 Yiqing Wang

    Abstract
    The rapid adoption of distributed energy resources (DER) in low voltage (LV) networks is driving the need for distribution companies to assess their impacts on customer voltages in any demand/generation condition (also known as what-if analyses). Although this can be done by running conventional power flow analyses, there are two main challenges. The first one is that LV line models (three-phase LV feeder lines and single-phase service lines) are needed. However, the corresponding impedances are often poorly recorded by distribution companies. In other words, the information is incomplete or not available. The second challenge is that, if such studies are needed for operational purposes (calculations in near real-time), then implementing power flows to be run for hundreds of LV feeders can be a complex task for distribution companies. Several studies have attempted to solve the challenges of impedance estimation and simplified voltage calculations, but there are still some gaps. Given the rollout of smart meters in many places, several works have exploited smart meter measurements to estimate impedances of LV line models. However, in most cases, the three-phase nature of LV feeders (i.e. the phase couplings) is not adequately considered; and thus, such approaches cannot cater for the needs of inherently unbalanced LV networks. For the voltage calculations, existing simplified methods are based on the single-phase voltage drop equations and an additional ‘unbalanced factor’. Given that the ‘unbalanced factor’ is determined either empirically or using data-driven techniques that require large amounts of data, such methods cannot be precise or practical enough for their actual implementation by distribution companies. This thesis proposes a practical approach to determine customer voltages (in what-if analyses) using smart meter-driven LV line models that adequately capture the effects among the three phases. Firstly, impedances (three-phase LV feeder lines and single-phase service lines) are estimated using linearised voltage drop equations and a regression technique. This process exploits historical time-series measurements from smart meters and at the head of the LV feeder and assumes that the customer connectivity and customer phase connection are known. Then, using the linearised voltage drop equations and the estimated impedances, simplified calculations of customer voltages can be carried out for what-if analyses (any demand/generation condition). The proposed approach is demonstrated on realistic LV networks from Australia and the UK. Impedances are estimated considering realistic weekly historical meter measurements (i.e. active power, reactive power, and voltage magnitudes) with a 15-minute resolution (672 time steps). Voltage calculations (what-if analyses) consider weekly demand and generation profiles with 1-minute resolution (10,080 time steps). Results show a very good accuracy for most of the estimated impedances. More importantly, the calculated voltages are not only highly accurate but are also obtained much faster than with a power flow engine. Consequently, the findings suggest that the proposed approach is accurate and practical enough for its use by distribution companies.
    Keywords
    Distributed Energy Resources; Impedance Estimation; Low Voltage Distribution Network; Multiple Linear Regression; Smart Meter; Voltage Calculation

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