The use of clustering algorithm as a planning support tool for rural electrification optimization - Parreño, Ronaldo P. Jr. (2006)
Rural electrification is recognized as an important element in the development process of an area especially in the remote regions of developing countries. However, electric power utilities often tend to prioritize urban areas from rural areas due to high cost of electrification, thus leaving rural areas unelectrified even if a particular barangay (or village) is willing to avail of the energy service. This study has developed a planning support tool which will optimize electrification plans by clustering potential consumers to be supplied with electricity. The planning support tool utilizes the combination of conceptual and distance-based clustering algorithms which analyze the spanning tree using the shortest possible edge weight and create the final cluster trees based on the test of inconsistency for the edges. The clustering algorithm developed in this utilities the commonly used distance measure and the household information as the basis for the ability to pay (ATP) value. The use of these two parameters resulted to a more significant and real cluster since distance measure alone could not take the effect of the household characteristics in screening the most sensible groupings. The algorithm also incorporated the implications of using routing index across geographical features. The case study illustrates the new approach of connecting the households in an area which could be used as a basis for the initial network arrangement for the power utilities. Scenario analysis generated two strategies of connecting the households thereby providing alternatives for the optimization of the cost of electrification. The benefit cost ratio (B/C) was used in this study to evaluate the benefits associated with the two strategies formulated from the two scenarios. And based on the result of benefit cost ration analysis, the planner can compare which strategy is more economically advantageous. The results of this study showed that that the best plan for rural electrification can be accomplished by applying clustering algorithm. In conclusion, clustering algorithm proved to be effective in solving electrification optimization problem. It serves as a planning support tool which can facilitate electrification in rural setting and achieve cost effectiveness.
"October 2006."
Thesis (M.S. Energy Engineering) -- University of the Philippines Diliman.
Keywords: Rural electrification -- Philippines; Rural electrification -- Case studies. -- Philippines; Electric utilities -- Costs