smart_meter10

Customer Trial data conducted as part of
Smart Grid Smart City (SGSC) project
(2010-2014) based in Newcastle,
New South Wales
and areas in Sydney.
It contains half hourly interval meter readings (KWh)
of electricity consumption of households.

datasets

Provides tools for systematically exploring large quantities of
temporal data across nonlinear temporal granularities
(deconstructions of time) by visualizing probability distributions.
Nonlinear time granularities can be circular, quasi-circular or
aperiodic. 'gravitas' computes nonlinear
single-order-up or multiple-order-up granularities, check the
feasibility of creating plots for any two nonlinear granularities
and recommend probability distributions plots for exploring
periodicity in the data.

Sayani Gupta

gravitas

Explore Probability Distributions for Bivariate Temporal
Granularities

Rob Hyndman

Di Cook

Antony Unwin

smart_meter10 function

A tsibble with 259, 235 rows and 3 columns.<dl class="dl-horizontal">
 <dt>customer_id</dt><dd>household ID</dd>
 <dt>reading_datetime</dt><dd>Date time for which data is recorded (index)</dd>
 <dt>general_supply_kwh</dt><dd>electricity supplied to this household</dd>
</dl>

Format

Smart meter data for ten households — smart_meter10

A tsibble with 259, 235 rows and 3 columns.<dl class='dl-horizontal'>
 <dt>customer_id</dt><dd>household ID</dd>
 <dt>reading_datetime</dt><dd>Date time for which data is recorded (index)</dd>
 <dt>general_supply_kwh</dt><dd>electricity supplied to this household</dd>
</dl>

smart_meter10: Smart meter data for ten households

Description

Usage

Arguments

Format