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ABSTRACT: Economics and environmental incentives, as well as advances in technology, are reshaping the traditional view of industrial systems. The anticipation of a large penetration of plug-in hybrid electric vehicles (PHEVs) and plug-in electric vehicles (PEVs) into the market brings up many technical problems that are highly related to industrial information technologies within the next ten years. There is a need for an in-depth understanding of the electrification of transportation in the industrial environment. It is important to consolidate the practical and the conceptual knowledge of industrial informatics in order to support the emerging electric vehicle (EV) technologies. This paper presents a comprehensive overview of the electrification of transportation in an industrial environment. In addition, it provides a comprehensive survey of the EVs in the field of industrial informatics systems, namely: 1) charging infrastructure and PHEV/PEV batteries; 2) intelligent energy management; 3) vehicle-to-grid; and 4) communication requirements. Moreover, this paper presents a future perspective of industrial information technologies to accelerate the market introduction and penetration of advanced electric drive vehicles.
IEEE Transactions on Industrial Informatics 03/2012; · 2.99 Impact Factor
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IEEE Trans. Industrial Informatics. 01/2012; 8:1-10.
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IEEE Trans. Smart Grid. 01/2012; 3:308-315.
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ABSTRACT: There is a need to address the potential problems caused by the emergence of plug-in hybrid electric vehicles (PHEVs) within the next 20 years. The penetration of these vehicles into the marketplace poses a potential threat to the existing power grid. Adding a large number of PHEVs/PEVs into our society will create a large-scale aggregated load, as well as acting as a substantial energy resource. In this paper, we evaluate the impact of the integration of PHEVs/PEVs into the grid. First, we simulate the aggregated load pattern at a municipal PHEV/PEV parking deck, taking into account real world parking deck scenarios. Then we propose two smart charging programs to optimally allocate available power from the utility to a large number of PHEVs/PEVs at a municipal parking deck. In a smart grid environment, the proposed energy management programs can improve the stability and reliability of the power grid. We characterize the system performance and illustrate the potential improvement using several steady-state simulations. The simulation results provide a general overview of the impact of the proposed charging scenarios in terms of voltage profiles, peak demand, and charging cost.
North American Power Symposium (NAPS), 2011; 09/2011
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ABSTRACT: There is expected to be a large penetration of Plug-in Hybrid Electric Vehicles (PHEVs) into the market in the near future. As a result, many technical problems related to the impact of this technology on the power grid need to be addressed. The anticipating large penetration of PHEV into our societies will add a substantial energy load to power grids, as well as add substantial energy resources that can be utilized. There is also a need for in-depth study on PHEVs in term of Smart Grid environment. In this paper, we propose an algorithm for optimally managing a large number of PHEVs (i.e., 500) charging at a municipal parking station. We used Particle Swarm Optimization (PSO) to intelligently allocate energy to the PHEVs. We considered constraints such as energy price, remaining battery capacity, and remaining charging time. A mathematical framework for the objective function (i.e., maximizing the average State-of-Charge at the next time step) is also given. We characterized the performance of our PSO algorithm using a MATLAB simulation, and compared it with other techniques.
Power and Energy Society General Meeting, 2011 IEEE; 08/2011
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ABSTRACT: The large penetration of Plug-in Hybrid Electric Vehicles (PHEVs) and Plug-in Electric Vehicles (PEVs) brings up many technical problems that needs to be addressed and reassured on. There is also a need for in-depth study on PHEVs in term of Smart Grid environment. In this paper, we introduced the existing testbed of a Large-scale PHEV charging infrastructure developed by FREEDM/ATEC center to achieve the optimal power allocation. Then we applied Monte Carlo method to simulate the myriad real-world scenarios at a municipal parking deck. Case studies were performed to analyze the system performance of intelligent charging algorithms for a large amount of PHEVs using Monte Carlo simulation. Accordingly, the simulation results characterized the optimization performance in terms of the optimal electricity consumption and the PHEV battery State-of-Charge at plug-out.
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on; 08/2011
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ABSTRACT: Networked Control Systems (NCS) is a fast growing technology that integrates distributed sensors, actuators, and computing processors over a communication network for a vast amount of applications. However, the NCS can be vulnerable to various network attacks when the network used is insecure (e.g., Internet). Thus, secure NCS need to have embedded security mechanism to ensure its security operating requirements, which may sacrifice its performance due to limited system resources. This paper addresses the trade-off between NCS security and its real-time performance and use a secured networked DC motor system for illustration. This paper will present a trade-off model for system dynamic performance and system security. This model can be used to adapt security configurations to provide sufficient protection and satisfy real-time dynamic performance requirements of the NCS simultaneously. The construction of this model includes the development of a set of metrics to quantitatively measure the performance and security levels of NCS and the development of a trade-off objective function incorporating performance and security. A Simulink based test-bed implemented to control the speed of the DC motor is used to illustrate the effectiveness of this model.
Industrial Electronics (ISIE), 2011 IEEE International Symposium on; 07/2011
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ABSTRACT: Economic, technology and environmental incentives are changing the features of electricity generation and transmission. Centralized power systems are giving way to local scale distributed generations. At present, there is a need to assess the effects of large numbers of distributed generators and short-term storage in Microgrid. To accommodate the high demand of renewable energy and the environment policy, the planning and operation of Micro-source generators has been studied using HOMER. Simulation results show a case study of an optimal microgrid configuration on Ontario area in Canada. Sensitivity variables are specified to examine the effect of uncertainties (e.g. diesel price and average wind speed), especially in a long-term planning. The effect of air emission penalties on Microgrid planning is also well presented.
Power and Energy Society General Meeting, 2010 IEEE; 08/2010
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ABSTRACT: An in-depth need exists to address the potential problems caused by the emergence of plug-in hybrid electric vehicles (PHEVs) and plug-in electric vehicles (PEVs) within in the next 20 years. The large penetration of these vehicles into the marketplace poses a potential threat to the existing power grid. A large number of PHEVs/ PEVs may cause serious system instability without a sophisticated control strategy. Energy storage is the key enabling technology for PHEVs/PEVs. The battery state information is critical to ensure optimal utilization of the available energy. It enables optimal control over the battery's charging and discharging process, thereby reducing the risk of overcharge or undercharge and prolonging battery life. In this paper, we first simulate real-world parking deck scenarios and implement four types of battery models (i.e., the linear model, relaxation model, hysteresis model, and combined model). We then evaluate optimal performance of the proposed large-scale PHEV/PEV charging algorithms under certain operating conditions. We characterize system performance and illustrate the importance of battery modeling to large-scale charging algorithms. The simulation results provide a general overview of the impact of battery modeling on optimal performance.
