Sökning: "Data från smarta mätare"

Visar resultat 1 - 5 av 7 uppsatser innehållade orden Data från smarta mätare.

  1. 1. Assessment of building renovations using Ensemble Learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Paul Lieutier; [2023]
    Nyckelord :Energy consumption; time series; ensemble learning; renovation works; Energiförbrukning; tidsserier; ensembleinlärning; renoveringsarbeten;

    Sammanfattning : In the context of global warming, to reduce energy consumption, an unavoidable policy is to renovate badly-isolated buildings. However, most studies concerning efficiency of renovation work do not rely on energy data from smart meters but rather on estimates. LÄS MER

  3. 2. Load profiling and customer segmentation for demand-side management

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Anne Baril; [2023]
    Nyckelord :Smart meter data; TLP; customer segmentation; DSM; EE; D R; clustering; Data från smarta mätare; TLP; kundsegmentering; DSM; EE; D R; klustring;

    Sammanfattning : The energy transition is accompanied by massive electrification of uses and sectors such as transport. As a result, the pressure on the electricity grid is increasing, and the time to connect to the power system is lengthening. LÄS MER

  4. 3. Passive estimation of supply impedances at the meterpoint

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Zhanzhan Liu; [2021]
    Nyckelord :Impedance estimation; Loop theory; System fault detection; Impedansuppskattning; Loopteorin; Systemfelupptäckt;

    Sammanfattning : Modern digital energy meters are installed between the distribution network and customers. Network operators and customers can use those meters to monitor electrical parameters, i.e., voltages and currents and to calculate statistics such as RMS value, fundamental Fourier component, etc. LÄS MER

  5. 4. Identifying Power Quality Issues in LV Distribution Grid by Using Data from Smart Meters : Exploring possibilities of machine learning algorithms

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Samantha Chen; [2020]
    Nyckelord :;

    Sammanfattning : Since there is a significant potential to supervise the low voltage network with the assistance of the end-customer smart meters, Vattenfall Eldistribution AB wants to take advantage of such data. Therefore, this project’s overall goal is to investigate how some specific grid disturbances could be detected in certain meter data types. LÄS MER

  7. 5. Machine Learning for Sparse Time-Series Classification - An Application in Smart Metering

    Master-uppsats, KTH/Matematisk statistik

    Författare :Carl Ridnert; [2019]
    Nyckelord :;

    Sammanfattning : Smart Meters are measuring devices collecting labeled time series data of utility consumptions from sub-meters and are capable of automatically transmit-ting this between the customer and utility companies together with other companies that offer services such as monitoring of consumption and cleaning of data. The smart meters are in some cases experiencing communication errors. LÄS MER