An Investigation Into Using GIS In Network Planning In Rural Kwazulu-Natal

RESULTS
For routing a new network, four criteria were considered, these being household positions, land cover, slope, and proximity to roads. Weighting and overlaying these four layers in a combined raster enabled the calculation of a cost weighted route from the network to schools in the study sites. Initial estimations for electrification of an area must be within 65% of the final cost (Eskom, 2000) and GIS can help to make this far more accurate.

Shayilanga / Kamlenze area is closest to UBR680 on Bulwer NB2 so the most logical start point was to extend the network from that transformer. This area has two schools with a large number of pupils – namely Mashaliyanga Primary School (889 pupils) and Skofill School (342 pupils) and over 52% of the people living in the ward this area falls in are under 15 years old. The schools were therefore used as a central point for placing a transformer, but in practice, any logical central point could be used or a centroid determined from groupings of households.

The two schools and nearest existing transformer fall roughly in a triangle so different routes could be considered. Initially two paths were derived; from the transformer to the two schools and then a third, which ran between the two schools. Comparisons between the routes found that the shortest path would start at the transformer, run via Mashaliyanga Primary School and end at Skofill School. The route between the schools is shorter than running the connection along the road, an option that may not have been obvious without using GIS.

Land cover in this area is predominantly divided between unimproved grassland and temporary cultivated subsistence farming which were allocated the same number of points so land cover did not have an effect on the outcome. Most of the slope is between 0 and 10% so slope was not a factor in determining the optimal route.

Household density along the extensions is relatively high (in places around 80 houses per square kilometre) – and the network extensions were designed to avoid going through those households.

Figure 8: Study site: Shayilanga / Kamlenze: Shortest path from Bulwer NB2 to schools in Shayalinga / Kamlenze.

CONCLUSIONS
Utility companies worldwide are starting to appreciate the benefits of using GIS for purposes other than that of facilities management and automated mapping and their experience could benefit Eskom Distribution in restructuring their data model to also realize the benefits of spatial analysis. GIS is increasingly being used for managing rural electrification, ranging from basic planning models to full Information Management Systems. Ground breaking practices in using GIS and sharing information with other service providers and local communities are gaining momentum. It is strongly recommended that Eskom Distribution research some of these projects, especially in areas with similar demographics such as in other countries in Africa, with a view to deciding what type of system would be best to use.

Planning the shortest path for an extension to a network is a complex exercise when working manually with a combination of a number of maps, statistics, and constraints. Instead, all standards and current planning procedures could be used to build a network planning tool based on GIS that would standardize analysis and allow the planner to easily compare all constraints in order to accurately determine the shortest path from a selected network to a predefined point or points in a community. Using GIS for electrification and network planning would completely revise current methods used and result in viable planning for network extensions where there is still currently spare capacity. Where no spare capacity exists, GIS can also be used for identification of overloaded networks and ideal placing of new substations.

Any number of further optional criteria could be built into the network planning tool to assist in determining the shortest path for connecting new customers to existing networks and in so doing assist in improving network performance and reducing short and long-term costs. These could include conditions such as environmental impact studies which have to be assessed as part of each new network or extension (Eskom, 2003), and areas with extreme weather conditions which can prove costly in terms of future maintenance. For instance, avoiding areas with extremely damp conditions can extend the life of wood poles and save on costs of early replacement. Care also needs to be taken when incorporating rivers in network planning as only perennial rivers with no bridge near the proposed network position need to be avoided. This could be verified as part of the standard site visit and then added into the network planning tool if necessary.

Currently, electrification plans already far advanced have to be put aside on occasion, due to various reasons such as a lack of capacity, and when those constraints are resolved, the entire project has to be researched and replanned due to changes on the ground. However, if a plan created using the principles in this study has to be put aside for any reason, it would be relatively simple to rerun the analysis with new data.

In essence, electrification plans could be created now for every village, and the planners could keep those plans up to date by rerunning analysis as new developments are planned or growth in areas takes place. This would result in a transparent plan to support other service providers and the South African government in building a better life for all.

REFERENCES

(Williams et al, 2003, Glasgow et al, 2004).
Raps
(Eskom, 2003)
(Eskom, 2000):