ANALYSIS AND SIMULATION OF POWER DISTRIBUTION IN AKURE TOWNSHIP USING AUTOMATED LOAD MANAGEMENT APPROACH

Abstract

The Akure township electricity distribution network (TEDN) consisted of four 33/11 kV substations fed from the Akure 132/33 kV transmission substation. The total capacity of the 33/11 kV substations was 70 MVA. These substations were supplying twelve 11 kV feeder lines with 504 distribution transformers (DTs), with population per feeder ranging from 7 to 77 DTs, and nominal capacities ranging from 50 kVA to 500 kVA. This work identified the major technical problems of the network using power system analysis tools, designed appropriate automation functions to mitigate the problems and assess the impact of these on the network. Garmin® GPSmap 76CSx mobile equipment was used to obtain the coordinates of network elements. ArcView 3.2 application package was utilized to load the obtained data points on a digitized map of Akure, to create the GIS mapping of the network. The data collected during field work and the as erected drawings produced on feeder by feeder basis, were applied in obtaining the single line diagram of Akure TEDN. Outage data collected from the system records of the dispatch office of the distribution company were analyzed to identify the causes, frequency and duration of outages on the TEDN. Relative distribution statistics (RDS) was used to determine the contribution of each outage cause to unavailability. The cost of energy not supplied (CENS) due to faults, was calculated at a rate of N 6 per kWHr. Using frequency distribution method, voltage deviation, an indicator of the quality of power supply was also evaluated. In order to know the status of automation in the network, the automation intensity level (AIL) was computed using a proposed equation. The load flow of the network was done for various system configurations using Etap® 12.6.0. The cost of implementing the proposed distribution automation system (DAS) was computed, and the value was compared with the annual loss of revenue due to faults in the system to determine the cost benefit of DA. In view of the regular load shedding on the feeders, poor downtime management and low voltage profile, three automation functions were designed, modelled, and simulated in MATLAB/Simulink®, using SimPowerSystems module. The GIS map and attribute tables containing the materials schedule would solve the problem of poor asset management and enhance situational awareness of the network. Data analysis shows that the major cause of outage on the network was load shedding, which accounted for 67% of outage events, and 58% of outage durations. The system Unavailability of over 10% for outages due to faults revealed that downtime management was poor. The load flow result using Etap® 12.6.0 power system simulator on a model of the network confirmed poor voltage profile, as low as 43% or 0.43 per unit in several portions of the network. In order to maintain voltage profile within standard limit of 0.94 and 1.06 per unit, network system reinforcement was required in addition to the deployment of AVRs. The automation intensity level (AIL) was low at 0.5%, meaning that automation was insignificant in the network It was concluded that reinforcing the network with new feeder lines, and construction of more 33/11 kV power transformer substations were absolutely necessary; the use of obtained GIS would enhance asset management, improve situational awareness of system conditions in real time and provide information about system elements and their locations in the event of an emergency; installation of proposed DA will improve downtime management significantly, optimize power utilization, increase availability, and improve power quality.