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Unformatted text preview: use load profiles are divided into classes to group the
different load profiles in classes that are more homogeneous. 52 The spatial load forecast addresses the questions of how much, where and
when. Geographical maps are used to indicate the location (where) of the
expected loads, or increase in new supply points. The service territory is
divided into smaller areas. The smaller areas can be small square areas or
irregularly shaped and sized to determine the expected loads on feeders. Willis mentions that short-range planning must at least look as far as
equipment lead times (manufacturing and commissioning times). Long-range
planning looks beyond the lead times in order to assure that the short-time
range decisions provide lasting value. Short -range planning decisions are concerned that system additions are made in time, and long-range planning is
concerned that the short-range planning decisions have lasting investment
and performance values. The long-range plans look whether the load growth
in the area will continue after additions to the network have been made, and
whether more network additions, such as substations will be required to meet
the load growth in the area.
Interesting statement by Willis is that forecasting is part of the planning
process. It is a decision-making tool, and its value is ultimately judged by its
contribution to that process’s success, not by how closely it comes to
predicting the eventual future load level. “If the forecast leads the planner to
make correct decisions, then it has no error from a practical standpoint. If it
leads to wrong decisions, then it is a poor forecast, regardless of what
statistical evaluation of its ability to predict future load might say”.
The load curve for residential peaks looks sharp (needle effect) and erratic.
This is because of the switching-on of equipment such as stoves, heaters,
geysers, etc. If a number of those curves are combined, the load curve
becomes smoother. Peak load per customer drops as more customers are
added to a group. This tendency of observed peak load per customer dropping and the size of the customer group increasing is termed
“coincidence” and is measured by the coincidence factor. 53 coincidence factor = (observed peak for the group) ∑ (individual (3.2.7) peaks) Some loads are sensitive to temperature and humidity. Sensitivity analysis
can highlight the impact, but it is, however, maybe not that important for the
loads at system peak. Normally the country experiences severe cold conditions. The importance here is whether it is a mild or a severe winter that
really impact on the peaks at time of system peak.
All growth in an area is due to:
1) New customers connected, or existing customers increasing their
2) New uses for electricity, existing customers may add new
appliances, or replace existing equipment with improved devices
that require more power. Two load forecast techniques are used for spatial electrical forecasts.
Trending involves extrapolating past load growth into the future, or simulation,
which involves modelling the process of load growth itself. The simulation
process works well for high spatial resolution - when the region studied is
divided into very small areas. Trending is most suited to “large area” forecasting. The simulation process starts by distinguishing customers by class, based on
various residential, commercial, and industrial classes and subclasses.
Simulation attempts to reproduce the process of load growth to forecast
where, when, and how many loads will develop. It also identifies some of the
reasons behind the load gro wth. The land use-based simulation concept can be applied on a grid or a polygon
(irregularly shaped and sized small areas) basis. Polygon-based modelling is 54 done more for feeders. A grid basis assures uniform resolution of analysis
Simulation methods have proven themselves to be quite good at forecasting
vacant area growth. Incremental growth on a small area basis is not wellhandled by simulation based methods. Maps are used to identify the area to be forecasted, and each sub-area
locating a class is marked with a different color. Different maps are prepared
for each year to identify the growth in the area and the individual growth for
each class. Based on this information, the following is calculated:
1) customers / square metres 2) kVA / customers Then the kVA per small area is determined as: kVA = kVA / customers (3.2.8) customers / square metre The kVA is aggregated from one level to another by simulation software
programs, until it is at the leve l that models the distribution substations. Much
more is involved in spatial load forecasting as what is summarised above. [44
Similar to the electrical spatial load forecasts is an article on spatial analysis of
crime using GIS-based data. This serves as a proactive tool that can anticipate or provide early warning of criminal patterns so that they may be
prevented. In the fifth chapter the assumption is made that criminal activity
can be modelled as a chaotic sy...
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This document was uploaded on 03/04/2014.
- Spring '14