Abstract

The oversupply condition is due to differences in the current electricity supply which is higher than actual electricity demand. One option to increase demand is by converting LPG stoves into induction stoves. To achieve the conversion goal successfully, a customer selection process must be carried out to determine the conversion targets, aiming for a significant increase in electricity demand with the lowest investment costs. The main problem is the absence of a standard for determining conversion targets. The combination of clustering techniques and Multiple Criteria Decision Making (MCDM) analysis provides the best ideal solution to overcome these problems. The research included several main criteria for selecting customers that support the success factors of implementing a conversion program. The initial analysis involved clustering customers based on coordinates using the k-means method. By using the clustered customer data, the TOPSIS (Technique for Ordering Preference by Similarity to an Ideal Solution) method identified the best cluster based on general criteria. Additionally, using detailed customer data, the TOPSIS method also identified the ranking of customer priorities for each selected cluster. The recommended priority target customers are those with the greatest potential for additional kWh, the best level of electricity reliability, shortest distance to the cluster centroid, and supplied by feeders and distribution transformers with the largest reserve margin. The results indicated the difference in revenue improvement compared to the current method was US$ 16,291.31 per month. Investment costs were also reduced by US$ 166,084.80 compared to the current method. The other results were a reduction in operational costs, improvement in average reliability according to the SAIDI SAIFI, improvement in the average operation-hours, and an improvement in the distribution transformer average reserve margins.

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