Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks

Abstract

Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs) with competing charging stations to exchange data, such as electricity price, energy demand, and time of arrival. EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system, electricity price from charging stations, powertrain component efficiencies, and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations, EVs charging demand estimation is done much more accurately. Then, the optimal power flow problem is solved for the power system, to find the locational marginal price at load buses where charging stations are connected. Finally, the electricity prices are communicated from the charging stations to the EVs, and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems, i.e. optimal power flow and optimal routing problem. Electricity price depends on the power demand, which is affected by the charging of EVs. On the other hand, location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation, holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks.The idea, framework, methodology, and required hardware for the proposed method in this article is patent pending [P1].[P1] Mohammadhadi Amini and Orkun Karabasoglu, US Patent Office Application #62/494,289, "Optimization of the interdependent electrical power and electrified transportation networks considering intelligent routing of electric vehicles and charging stations pricing strategy: framework and methodology",

Fractional‐order modeling and SOC estimation of lithium‐ion battery considering capacity loss

“…KEYWORDS capacity estimation, fractional-order model, lithium-ion battery, state-of-charge estimation 1 | INTRODUCTION Lithium-ion batteries are being widely used in electric vehicles because they exhibit high energy, long life, and low self-discharge rate. 1,2 To ensure safe and efficient operation of battery systems under fleeting and even demanding conditions, an effective battery management system (BMS) is highly necessary. BMS is the key focus in the current research field of electric vehicles, and state-of-charge (SOC) estimation is one of the significant challenges of BMS.…”

“…Lithium‐ion batteries are being widely used in electric vehicles because they exhibit high energy, long life, and low self‐discharge rate . To ensure safe and efficient operation of battery systems under fleeting and even demanding conditions, an effective battery management system (BMS) is highly necessary.…”

An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected Communities

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