MAPPING ENCROACHMENT ON POWERLINE CORRIDORS USING LIDAR. SSEMAGANDA GILBERT DOUGLAS F19/35705/2010 Mr DK Macoco

Transcription

1 MAPPING ENCROACHMENT ON POWERLINE CORRIDORS USING LIDAR SSEMAGANDA GILBERT DOUGLAS F19/35705/2010 Mr DK Macoco

2 BACKGROUND Power interruptions by tree contacts contribute to over 20% of service interruptions. This may reflect in momentary interruptions or current diversions, but the varying power quality can add up to huge monetary losses. For instance, industries that rely on powerintensive processes for their operations would be some of the hardest hit by power interruptions/fluctuations; industries such as the manufacturing, electronic/system designs, and telecommunications firms.

3 PROBLEM STATEMENT Vegetation encroachment on power lines is a safety concern and can cause service interruptions requiring expensive, emergency repairs. Because monitoring vegetation encroachment on power lines is labour intensive, it is often neglected and subsequent problems arise with little or no warning As a result, forced outages caused by falling trees is common phenomena making vegetation within the ROW a major concern to utility companies and one of the greatest risk factors to power line structures.

4 PROBLEM STATEMENT The situation currently is that powerline companies have to send a maintenance crew to, first of all, check on the vegetation (trees) that are encroaching on the powerline structures and right of way and then later send a team to cut or trim the trees within the ROW that will have been found to be encroaching. LiDAR provides a spatial solution by which vegetation (trees) to be cut can be located, monitored and quantified using the increasingly available data type that gives extremely accurate 3D representations of buildings, trees, power lines and other structures, to effectively monitor vegetation encroachment on power lines without a large commitment of labour hours.

5 PROBLEM STATEMENT KPLC is also mandated to ensure that the end consumers enjoy the provision of power twenty four hours a day without interruptions

6 OBJECTIVES The main objective of this project is to map encroachment on powerline corridors using LiDAR technology.

7 OBJECTIVES The specific objectives are: To map all vegetative features around the powerline in order to identify those within the powerline s ROW To classify the LiDAR waveforms in order to extract of the powerline corridor and vegetation To quantify the encroachment on the powerline by way of measurements made using LiDAR data.

8 MATERIALS

9 STUDY AREA The study area is the stretch along State House Road, from St. Paul s Chapel to Ufungamano house, stretching a distance of 740M, in Nairobi, Kenya. The area is bound the following UTM coordinates: Northings: to Eastings: to

10 STUDY AREA

11 METHODOLOGY

12 METHODOLOGY

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14 RESULTS AND ANALYSIS

15 RESULTS AND ANALYSIS

16 RESULTS AND ANALYSIS

17 RESULTS AND ANALYSIS

18 CONCLUSIONS LiDAR was manipulated to provide a static monitoring of the ROW so as to tell the status of the vegetation within the wayleave. GIS functionalities were applied to be able to locate the trees encroaching and within the Erdas IMAGINE environment, measurements to determine the level of encroachment were also possible and were carried out.

19 CONCLUSIONS Unlike the Vegetation Management System in which KPLC can only monitor the vegetation by when field teams go to the ground to determine the status of encroachment, or for some areas when they react to the vegetation when there are power blackouts caused by the same, using LiDAR enables the company to monitor encroachment on all its facilities in a more detailed and accurate way.

20 CONCLUSIONS Apart from providing a safe and reliable electric service to customers, having a proper vegetation management program enables the utility company to operate at a quite reasonable cost. Also, from the maps generated, workers are able to safely access the facilities for inspection, maintenance, and repair. Overall the project aims to solve a part of the problem of vegetation that poses a risk to powerlines going undetected.

21 RECOMMENDATIONS Have a number of LiDAR data collection cycles, say two per year Cost of data collection can be taken care of by companies in different sectors say roads and electricity coming together and taking care of the data collection cost. Storage requirements: use servers and cloud storage. Use LiDAR together with imagery Use a wider area

22 THANK YOU