Improve customer service quality, reduce operating expenses, and improve energy sales by the K-MEANS method and path optimization algorithms

Managing consumer expectations was essential to maintaining customer satisfaction throughout the electricity contract. However, the service provided to customers was based on the location of electrical meters. In the absence of addressing in rural areas, it was too difficult to ensure a comprehensive survey of electrical meter indexes and intervene in time for troubleshooting. The method adopted was the choice of a site with a significant number of meters and energy transformers and the geolocation of electrical installations by a GPS that allowed the assignment of a universal address to electrical installations and facilitated the location of facilities for maintenance and emergency response. The study of optimization algorithms has directed the choice toward the algorithm of the nearest neighbor that remains fast and aims to other algorithms whose number of iterations can be exponential (n! iterations) but less exact. The integration of route optimization algorithms has improved the reactivity of technicians, reduced operational costs, and ensured accurate reading of indexes and transparent billing. The study presents a specific case in Morocco, where route optimization based on GPS coordinates of électric meters in reading indexes has significantly improved efficiency and customer satisfaction. In addition, the K-Means method was used to determine the centroids and clusters that represent respectively the transformation stations and the groups of electrical meters. These groupings allow the calculation of energy sales by transformer station to increase them by reducing energy losses