Finding an energy efficient path for plug-in electric vehicles with speed optimization and travel time restrictions

Transportation is one of the main factors when global total energy consumption is considered and is a significant contributor to emissions of harmful gases including carbon dioxide (CO2). Due to their lower tailpipe CO2 emissions compared to the vehicles with internal combustion engines, electric vehicles provide an opportunity to reduce environmental impacts of transportation. In this direction, a problem for plug-in electric vehicles (PEVs) is studied where the aim is to find an energy efficient path. Given an origin–destination pair over a directed network, this problem involves determining a path joining origin and destination, the speed of the PEV on each road segment, i.e., arc, along the path, the charging stations the PEV will stop by, and how much to recharge at each stop so as to minimize the total amount energy consumption. There are speed limits on each road segment, and PEV has to arrive at the destination on or before a given total time limit. For this problem, firstly, a mixed-integer second order cone programming formulation (MISOCP) is proposed. Secondly, to be able to solve larger size instances, a matheuristic is developed. Lastly, an iterated local search (ILS) algorithm is designed for this problem. Solution quality and computation times of the heuristics and the exact algorithm are compared on different instances. Differently from the literature, the speed values of the PEV on the arcs are considered as continuous decision variables in all proposed solution approaches. Moreover, consideration of the speed limits which can be legal limits or limits imposed by congestion makes our problem more realistic. The analysis of the results of the computational experiments gives the user an insight to select the proper solution approach based on the instance settings. MISOCP formulation becomes inadequate for larger instances. On the other hand, the heuristic solution approaches can solve such instances within reasonable computational times and therefore they have the potential to be integrated in some software to dynamically find energy efficient paths.</p

Finding an energy efficient path for plug-in electric vehicles with speed optimization and travel time restrictions

Transportation is one of the main factors when global total energy consumption is considered and is a significant contributor to emissions of harmful gases including carbon dioxide (CO2). Due to their lower tailpipe CO2 emissions compared to the vehicles with internal combustion engines, electric vehicles provide an opportunity to reduce environmental impacts of transportation. In this direction, a problem for plug-in electric vehicles (PEVs) is studied where the aim is to find an energy efficient path. Given an origin–destination pair over a directed network, this problem involves determining a path joining origin and destination, the speed of the PEV on each road segment, i.e., arc, along the path, the charging stations the PEV will stop by, and how much to recharge at each stop so as to minimize the total amount energy consumption. There are speed limits on each road segment, and PEV has to arrive at the destination on or before a given total time limit. For this problem, firstly, a mixed-integer second order cone programming formulation (MISOCP) is proposed. Secondly, to be able to solve larger size instances, a matheuristic is developed. Lastly, an iterated local search (ILS) algorithm is designed for this problem. Solution quality and computation times of the heuristics and the exact algorithm are compared on different instances. Differently from the literature, the speed values of the PEV on the arcs are considered as continuous decision variables in all proposed solution approaches. Moreover, consideration of the speed limits which can be legal limits or limits imposed by congestion makes our problem more realistic. The analysis of the results of the computational experiments gives the user an insight to select the proper solution approach based on the instance settings. MISOCP formulation becomes inadequate for larger instances. On the other hand, the heuristic solution approaches can solve such instances within reasonable computational times and therefore they have the potential to be integrated in some software to dynamically find energy efficient paths.</p

Análisis de la direccionalidad armónica a nivel tensión de 60 KV para optimizar el funcionamiento de la sub estación Chiclayo Oeste de 220 / 60 KV

El sistema interconectado nacional en el Perú permite el abastecimiento de energía eléctrica a todos los usuarios del sistema, la transmisión de energía eléctricas desde los puntos de generación hasta los consumidores se realiza en niveles de tensión de 220 KV y 500 KV. La Sub estación Chiclayo-Oeste es la que conecta el sistema eléctrico de Chiclayo con el sistema eléctrico nacional, posee un patio de llave del 220 KV y otro en 60 KV, ambos en configuración doble barra más celda de acople, con el incremento de los equipos electrónicos viene consigo el incremento de las alteraciones. Se ha procedido a un registro y análisis de los principales armónicos (Tercer, Quinto, Séptimo, Noveno y Décimo Primer Armónico), en un periodo de tres meses, tanto en horas punta, como en horas fuera de punta, día de semana, día de fin de semana (sábado , domingo y feriados), los datos y formas de onda incluyen la siguiente información: tres voltajes, V1, V2, V3 y tres corrientes I1, I2 e I3; distribución espectral en magnitudes por armónico, distribución espectral en ángulo de fase por armónico, formas de onda y espectro de frecuencia. La aparición de una serie de perturbaciones, denominados armónicos de tercera, quinta, séptima, novena y undécimo nivel, lo cual origina la distorsión de la onda Senoidal elemental y el incremento del RMS (Valor medio efectivo de la onda de voltaje y de la onda de corriente), con el consecuente sobrecalentamiento, sobretensión y sobre amperaje de las redes. Las distorsiones son eliminadas con un sistema de filtrado, los filtros son calculados por complejos procedimientos que se basan en las series de Fourier. La mejora de la calidad de energía eléctrica nos permite corriente más estable y menos interrupciones además de menor cantidad de multas por parte de la entidad reguladora y fiscalizadora. La inversión inicial de suministro y montaje ha sido estimada es de S/ 469,640, con un valor estimado de ingresos de S/ 443,000 soles al año, lo cual nos permite el manejar un flujo de caja a soles constantes y flujos económicos, que nos determinan indicadores de VAN (Ganancia), de S/ 1,209,678 Soles y una rentabilidad de 80.23 % al año