Title :
Economic Analysis of Real-Time Large-Scale PEVs Network Power Flow Control Algorithm With the Consideration of V2G Services
Author :
Tan Ma ; Mohammed, Osama A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Florida Int. Univ., Miami, FL, USA
Abstract :
In this paper, the economic analysis of a real-time power flow control algorithm for charging a large-scale plug-in electric vehicles (PEVs) network is proposed. Such a system is in an urban area power system with optimized renewable energy resources in South Florida. In this model, the PEVs charging rates are controlled by a central aggregator through wireless communication. To limit the impact of the PEVs´ charging to the utility grid, while optimizing the scheduling of vehicle-to-grid (V2G) frequency regulation services, a V2G intelligent power flow management algorithm based on fuzzy logic control was developed. The smart charging system will improve the power system stability and robustness while bringing benefits to the utility ac grid, the PEVs network, and its customers. An economic analysis model was built with the consideration of the battery degradation and capital cost. The proposed smart charging algorithm was tested with a 50 000 PEVs network model. The simulation results show the effectiveness and economic value of the proposed model.
Keywords :
battery powered vehicles; fuzzy control; intelligent control; load flow control; power grids; power system stability; V2G intelligent power flow management algorithm; V2G services; battery degradation; economic analysis; frequency regulation services; fuzzy logic control; large-scale PEVs network; plug-in electric vehicles network; power flow control algorithm; power system stability; renewable energy resources; smart charging algorithm; utility grid; vehicle-to-grid; wireless communication; Analytical models; Batteries; Economics; Frequency control; Load modeling; Renewable energy sources; Wind speed; Charging optimization; economics; frequency regulation; fuzzy logic; plug-in electric vehicles (PEVs) network; real-time power flow management;
Journal_Title :
Industry Applications, IEEE Transactions on
DOI :
10.1109/TIA.2014.2346699