Tag
AEMO
- Asset type
- Location
- Data
Electricity Statement of Opportunities (ESOO)
2019
Australian Energy Market Operator (AEMO)
AEMO's 10-year forecast of electricity supply reliability.
- Report
Aggregate solar PV estimation
CSIRO
This project estimates the aggregate PV generation of a feeder downstream from a device that can measure active and reactive power only. This aggregate PV estimation can then be used as an input to operational demand forecasting, or any state-estimation algorithms required for the reliable operation of the grid.
- Report
Apartment Buildings Stock Model
Connecting AEMO electricity usage data to the built environment
CSIRO
The NEAR Program developed energy data profiles for a range of residential property types, grouped by attributes including climate zone and dwelling count.
- Report
Commercial Buildings Stock Model FY2020-21
CSIRO
In FY2019-20 the NEAR Program provided valuable inputs around the physical nature of the national commercial building stock to fill data gaps for the updated 2019-20 CBBS study. This activity aims to build upon this work in order to provide DISER’s Commercial Buildings policy team with aggregate energy data linked to building taxa to underpin the development of the subsequent Commercial Buildings Baseline Study. A major component is exploratory research in linking groups of properties with aggregated electricity usage data, in conjunction with the Australian Energy Market Operator (AEMO).
- Report
Identifying control schemes for residential battery storage installations
CSIRO
This report provides a methodology and appraisal for determining the control schemes of residential battery storage installations given half-hourly electricity interval meter data for a set of households with known residential battery storage installations.
- Report
Operational Demand Forecasting Using Ensemble Learning
This project investigated ensemble learning methods for day-ahead electricity operational forecasting across all National Electricity Market (NEM) regions in Australia, in collaboration with Australian Energy Market Operator (AEMO) and the Department of Industry, Science, Energy and Resources (DISER), Australia. Using historical operational demand and weather data, machine learning methods were developed that can select and combine from multiple forecasting models to maximize the forecasting accuracy.
- Report
Probabilistic forecasting of operational demand in Australia
This research presents one-day ahead probabilistic load forecasting of operational demand across the National Electricity Market (NEM).
- Report
Quantifying the temperature sensitivity of residential households in the NEM
CSIRO
This report provides a methodology and summary of results for assessing the temperature sensitivity of residential households across the National Energy Market (NEM), with the intention of providing insights as to whether there are sufficient grounds to base AEMO’s future consumption forecasts on greater disaggregation than they currently are.
- Report
Retail Properties Stock Model
Linking AEMO electricity usage data to the built environment
CSIRO
The NEAR Program developed electricity usage profiles for a range of retail property types – including malls, arcades and bulky goods centres – grouped by attributes including climate zone, lettable area, age (year opened), and NABERS star rating.
