Street Lighting and Charging Stations with PATs Location Applying Artificial Intelligence

• Published in: Water (Basel) 2023-02, Vol.15 (4), p.616
• Main Authors: Pineda Sandoval, Joseph Daniel, Arciniega-Nevárez, José Antonio, Delgado-Galván, Xitlali, Ramos, Helena M., Pérez-Sánchez, Modesto, López-Jiménez, P. Amparo, Mora Rodríguez, Jesús
• Format: Article
• Language: English
• Subjects: Air quality management; Artificial intelligence; Battery chargers; Bicycles; Carbon dioxide; Clean technology; Climate change; Drinking water; Economic impact; Electric power production; Electric rates; Electric vehicles; Electricity; Electricity consumption; Emissions; Energy consumption; Energy industry; Energy recovery; Impact analysis; Lighting; Maximization; Methodology; Monitoring; Multiple objective analysis; Optimization; Optimization techniques; Pressure; Pressure reduction; Pumps; Quality of life; Return on investment; Smart cities; Society; Sustainable development; Turbines; Utility poles; Utility rates
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w15040616

This research proposes a methodology with multi-objective optimization for the placement of Pumps operating As Turbines (PATs), energizing street lighting, devices for monitoring the water network, and charging stations for small electric vehicles such as bikes and scooters. This methodology helps to find the most profitable project for benefiting life quality and energy recovery through pumps operating as turbines, replacing virtual pressure reduction valves to locate the best point for decreasing pressure. PATs are selected by maximizing power recovery and minimizing pressure in the system as well as maximizing recoverable energy. Benefits analyzed include the reduction of carbon dioxide emissions and fuel use, as well as the saving of electricity consumption and benefiting socio-economic impact with street lighting, monitoring, and charging station. It was considered that each PAT proposed by the methodology will supply a street light pole, a station for monitoring the water network, and a charging station; under these established conditions, the return on investment is up to 1.07 at 12 years, with a power generation of 60 kWh per day.