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Integration of Plug-in Electric Vehicles into Power Grid: Impact Analysis and Infrastructure Planning

Mao, Daijiafan
http://orcid.org/0000-0002-8508-5044
http://rave.ohiolink.edu/etdc/view?acc_num=osu1574632021559188

Abstract Details

2019, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.
Widespread adoption of Plug-in Electric Vehicles (PEVs) brings significant social and economic benefits. The development and promotion of PEV are essential to scale up the transition to electric mobility. Overall, the large-scale integration of PEV can lead us towards a more connected and environmentally friendly world. However, without proper preparation and management, the massive PEV charging could exert an increasingly disruptive influence on the electric power grid. The goal of this dissertation is to propose algorithms and methods for grid operators and electric utilities to accurately analyze PEV's charging impact on the power system from both distribution and transmission voltage levels. The practical impact metrics provide an important tool to develop proper mitigation strategies through infrastructure planning. PEVs are characterized as a stochastic and impulsive electric load, which means they are of high power density and vary in a fast and discrete manner. These load characteristics make conventional assessment methods unsuitable. This dissertation first proposes an algorithm, which captures the inter-temporal response of grid assets and allows fast assessment through an integrated interface. To realize these advantageous features, we establish analytic models for two generic classes of grid assets and recast their cost functions in the statistical settings of PEV charging. The proposed impact analysis algorithm can be developed into software planning tool and embedded into utilities' strategy of impact mitigation. The current auto industry has envisioned the ability to recharge PEV at speeds comparable to the traditional gas refueling. This trend has facilitated the integration of Fast Charging Stations (FCS) into transportation service infrastructure. This dissertation, for the first time, proposes a graph-computing based integrated FCS location planning model, which maximizes PEV charging convenience while ensuring the power grid's reliability. The proposed model is cast as a multi-objective mixed-integer problem and solved by the cross-entropy optimization algorithm, in which the computational efficiency is significantly improved with graph parallel computing techniques. On the transmission level PEV charging impact, this dissertation proposes a Graph-computing based Cascading Failure Evolution (G-CFE) analysis to predict potential cascading outages induced by FCS on power transmission systems. Fundamentally different from the existing cascading analysis tools, which are based on DC power flow or require a long computation time, the proposed method greatly improves accuracy by using AC power flow, while guaranteeing the analyzing speed with graph parallel computing techniques. The proposed G-CFE model can accurately capture the stochastic PEV charging patterns with Monte-Carlo simulation and be easily scaled to various network configurations through a graph-based scheme.
Jiankang Wang, Dr. (Advisor)
Mahesh Illindala, Dr. (Committee Member)
Jin Wang, Dr. (Committee Member)
150 p.
Electrical Engineering

Recommended Citations

Citations

  • Mao, D. (2019). Integration of Plug-in Electric Vehicles into Power Grid: Impact Analysis and Infrastructure Planning [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574632021559188

    APA Style (7th edition)

  • Mao, Daijiafan. Integration of Plug-in Electric Vehicles into Power Grid: Impact Analysis and Infrastructure Planning. 2019. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1574632021559188.

    MLA Style (8th edition)

  • Mao, Daijiafan. "Integration of Plug-in Electric Vehicles into Power Grid: Impact Analysis and Infrastructure Planning." Doctoral dissertation, Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574632021559188

    Chicago Manual of Style (17th edition)

osu1574632021559188
481
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This open access ETD is published by The Ohio State University and OhioLINK.