22 April 2010
The Higland Perthsire tourism portal was recently launched to enable tourism businesses to work together in areas where there is no conflict in business interests.
21 December 2009
The winners of the 2009 FNB Enablis Seda Business LaunchPad competition were announced recently and Paul Storry, a director of Quartex technologies, is the winner in the ICT, business expansion category.
14 October 2009
Quartex technologies were appointed as part of the VAMP consortium to undertake Eskom's Western Gauteng Network Master Plan. Our role in this project was the development of the Geographical Load Forecast.
29 September 2009
We have recently completed a web-based mapping application for a forestry company. The solution allows the end-users to interact with their data and extract critical information related to the forestry compartments. They also have the ability to create and print Pdf maps.
Geographical Load Forecasting
The objective of the load forecast is to provide a twenty year
forecast of expected load on high voltage transformers. This
forecast is then used to model future load flows and facilitate
long term infrastructure rollout and maintenance planning. In order
to derive these forecasts, a number of factors need to be taken
into account including:
Current and future landuse
Usage profiles (i.e. What is the load at various
times of the day)
Load growth (i.e. as consumers become more
sophisticated or wealthier their consuption increases)
Future developments
Economic factors
Forecasts from large power users, such as mines and
other industry
- Current and future landuse
- Usage profiles (i.e. What is the load at various times of the
day)
- Load growth (i.e. as consumers become more sophisticated or
wealthier their consuption increases)
- Future developments
- Economic factors
- Forecasts from large power users, such as mines and other
industry
Methodology
The study area is situated in Gauteng and can be effectively
divided into two portions; that largely supplied by City Power in
the east, and the more rural area, dominated by agriculture and
mining, to the west and surrounding the towns of Krugersdorp,
Randfontein and Westonaria.
Two different approaches were taken in the areas since the
area supplied by City Power had been subject to a recent Network
Master Plan itself, undertaken by Netgroup. The approach taken for
the City Power area is not detailed here. The approach taken for
the western portion of the area, where forecasting was done on a
spatial basis, is described here.
The methodology aims to:
- Group homogenous areas into various demand categories
- Take account of the cadastral to avoid meaningless boundaries
between load zones
- Relate the resulting polygons to the network to identify feeder
supply zones
Land use data (Department of Agriculture) was used as the
basis of the analysis. This data was intersected with the cadastral
information (Surveys and Mapping) to provide land use by cadastral
parcel. Each of these parcels was then assigned a feeder by
buffering 11kv transformers and intersecting the buffers with the
landuse/cadastral data.
This led to the definition of five hundred and thirty one load
zones for the study area. Spot checks using Spot 5 imagery were
then used to validate the data, and to clarify areas of
uncertainty. Landuse classes were mapped to the subclass
categories defined in the modelling tool (Netgroup Power GLF ver
1.3.2.2), and baseloads determined, based onthe subclass parameters
and the size of the loadzone. Population and house hold statistics,
sourced from both Statistics South Africa and Eskom were used to
estimate households and population for each of the polygons.
These load zones were then fed into PowerGLF where
forecasting was completed.
Alignment with socio-economic analysis
The results of the spatial forecast were compared with the
results of the Economic analysis and were found to be broadly in
line. Growth predicted by the economic models matches well
with the demand forecasts.
Large power users
In interviews held with Eskom customer account executives, large
power users were identified (LPUs). For the purposes of this study,
only large power users with a maximum demand over 1GVA were
considered to be LPUs. Data for LPUs were included in the
model.
Future development
Strategic planning documentation was scrutinised for the study
area and new developments and growth areas were identified through
interviews with relevant representatives of the municipalities in
the area. These growth areas have been included as additional loads
in the forecast.
Acknowledgements
This work was undertaken in conjunction with Inspired
Interfaces, Isikhugusetu, Keith Moors and Clive Coetzee
29 December 2009
Paul Storry
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