International Journal of Innovative Engineering, Technology & Science

Automatic Control Model for Load Shedding in Atani 33KV Injection Substation – Nigeria Network

Automatic Control Model for Load Shedding in Atani 33KV Injection Substation – Nigeria Network

Publication Date : 23/06/2021

Author(s) :

David, E. E., Atuchukwu, A. J., Okonkwo, I. I..

Volume/Issue :
Volume 4
Issue 2
(06 - 2021)

Abstract :

Energy demand is high and the so is the satisfaction derived from steady power supply. Power availability and steady supply promotes business undertaking in most localities. This in turn promotes economic growth and human wellbeing. There are serious challenges facing the power sector in Nigeria which covers generation, transmission and distribution. This has led to unsteady power supply and incessant power outage. Lack of power infrastructures, ageing facilities, poor maintenance, negligence and overloading the transformers are factors that can affect power supply as they affect inability to manage the power generated properly. Managing the little generated power for the teaming users becomes difficult. The allocated power to different load centers is inadequate resulting to emergency load shedding. This paper focuses on how to reduce this emergency load shedding in distribution lines. Automatic control method was adopted to reduce emergency load shedding in distribution lines, with emphasis on allocate load (megawatts) to maintain, monitor and raise alarm if consumption exceeds the allocated load. This method also presents control or isolation mechanism for substations that exceeds load allocation. The Atani 33KV Injection Substation in Anambra State was used as a case study where distribution line outages data was collated and automatic control model using MATLAB was used to analyze the distribution Line Network outage data and results were simulated. Hypertext Pre-processor (PHP) software was used to write a program that monitored and controlled load allocation.. The result showed that automatic control model reduces emergency load shedding by 8%. This model can be extended to the entire grid to reduce emergency load shedding.

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