Automation and Operational Performance in Hydro-electric Power Generation Sector

Abstract

The purpose of the study was to determine the extent or level of automation, the nature of automation and the effect of automation on operational performance in the Kenyan hydro-electric power sub-sector. The target population was all the five major hydroelectric power generating stations of a major hydro electric power generating company in Eastern Africa. The study used primary data which was gathered by means of a selfadministered questionnaire issued to respondents. Data analysis involved the use of descriptive statistics and multiple regression analysis to determine the nature of automation and the relationship between the variables respectively. The study found that two of the power plants could be classified as technology centered while the remaining three were of the fixed human centered type. None of the plants was of the adaptive human centered classification. The findings also revealed that all the plants were of the ‘supervisory control, level of automation according to Endsley’s level of automation classification taxonomy. The study concludes that there is a significant relationship between automation approach and operational performance and in particular automation was confirmed to have a significant effect on speed and mistake proofing which in turn have a positive impact on operational performance. The study recommends that organizations intending to implement automation strategies should consider the automation approach as it has been shown to have an effect on operational performance. A quantitative survey is also recommended to corroborate these findings.