• Energy Research

With increasing interest in alternative energy resources and technologies, mass penetration of PHEVs (plug-in hybrid vehicles) into the electricity grid and widespread utilization of DERs (distributed energy resources) are anticipated in the near future. As an aggregation unit, the VPP (virtual power plant) is introduced for load management and resource scheduling. In this article, we develop an energy management model for VPPs and analyze the cost and emission impacts of VPP formation and PHEV penetration. We conduct a case study for the state of California using real-world data from official resources. An average of 29.5% cost reduction and 79% CO2 and 83% NOx emission reductions are attained as shared benefits of consumers in the case study. Results are illustrative of opportunities that VPP formation can provide for the community. Sensitivity of the results to the DER costs and capacities, battery and gasoline prices are also analyzed. In addition, we prove that charging and discharging do not simultaneously occur in the solutions, which leads to a simplification in traditional energy management models.

Abstract In a road network with refueling and fast charging stations, the minimum-cost driving path of a plug-in hybrid electric vehicle (PHEV) depends on factors such as location and availability of refueling/fast charging stations, capacity and cost of PHEV batteries, and driver tolerance towards extra mileage or additional stopping. In this paper, our focus is long-distance trips of PHEVs. We analyze the impacts of battery characteristics, often-overlooked driver preferences and road network features on PHEV travel costs for long-distance trips and compare the results with hybrid electric and conventional vehicles. We investigate the significance of these factors and derive critical managerial insights for shaping the future investment decisions about PHEVs and their infrastructure. In particular, our findings suggest that with a certain level of deployment of fast charging stations, well established cost and emission benefits of PHEVs for the short range trips can be extended to long distance. Drivers׳ stopping intolerance may hamper these benefits; however, increasing battery capacity may help overcome the adverse effects of this intolerance.

Abstract We introduce a practically important and theoretically challenging problem: finding the minimum cost path for PHEVs in a road network with refueling and charging stations. We show that this problem is NP-complete and present a mixed integer quadratically constrained formulation, a discrete approximation dynamic programming heuristic, and a shortest path heuristic as solution methodologies. Practical applications of the problem in transportation and logistics, considering specifically the long-distance trips, are discussed in detail. Through extensive computational experiments, significant insights are provided. In addition to the charging infrastructure availability, a driver’s stopping tolerance arises as another critical factor affecting the transportation costs.

Smart Grid is transforming the way energy is being generated and distributed today, leading to the development of environment-friendly, economic and efficient technologies such as plug-in electric vehicles (PEVs), distributed energy resources and smart appliances at homes. Among these technologies, PEVs pose both a risk by increasing the peak load as well as an opportunity for the existing energy management systems by discharging electricity with the help of Vehicle-to-grid (V2G) technology. These complications, together with the PEV battery degradation, compound the challenge in the management of existing energy systems. In this context, microgrids are proposed as an aggregation unit to smartly manage the energy exchange of these different state-of-the-art technologies. In this chapter, we consider a microgrid with a high level of PEV penetration into the transportation system, widespread utilization of smart appliances at homes, distributed energy generation and community-level electricity storage units. We propose a mixed integer linear programming energy management optimization model to schedule the charging and discharging times of PEVs, electricity storage units, and running times of smart appliances. Our findings show that simultaneous charging and discharging of PEV batteries and electricity storage units do not occur in model solutions due to system energy losses.

Abstract The refugee crisis is one of the major challenges of modern society. The influxes of refugees are usually sudden and the refugees are in sheer need of services such as health care, education and safety. Planning public services under an imminent humanitarian crisis requires simultaneous strategic and operational decisions. Inspired by a real-world problem that Red Crescent is facing in Southeast Turkey, we study the problem of locating refugee camps and planning transportation of public service providers from their institutions to the located camps. Our modeling approach brings a new facet to the location and routing problem by considering the location of beneficiaries as variables. We develop a branch-price-and-cut algorithm for the problem. To solve the pricing problem, we introduce a cycle-eliminating algorithm using nested recursion to generate elementary hop constrained shortest paths. The best version of our algorithm efficiently solves 244-node real-world instances optimally.