Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks
SYSU-CMU Joint Institute of Engineering（中山大学-卡内基梅隆大学联合工程学院）；Carnegie Mellon University（卡内基梅隆大学）；School of Electronics and Information Technology, SYSU（中山大学电子与信息工程学院）；Scott Institute for Energy Innovation, Carnegie Mellon University（卡内基梅隆大学斯科特能源创新研究所）
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.
Envisioning a future 100% electrified transportation sector, this paper uses socio-economic, demographic, and geographic data to assess electric energy demand from commuter traffic. We explore the individual mode choices, which allows to create mode-mix scenarios for the entire population, and quantify the electric energy demand for each scenario using technical specifications of battery and electric drives technology in combination with different charging scenarios. Using data sets for New York City, our results highlight the need for infrastructure investments, the usefulness of flexible cha…
The increasing urban population imposes a substantial and growing burden on the supporting infrastructure, such as electricity, water, heating, natural gas, road transportation, etc. This paper presents a Hetero-functional graph theory (HFGT) based modeling framework for these integrated infrastructures followed by an analysis of network robustness. The supporting infrastructures along with the infrastructure repair facilities are considered. In contrast to conventional graph representations, a weighted HFGT model is used to capture the system processes and mutual dependencies among resources.…
The high penetration of transportation electrification and its associated charging requirements magnify the interdependency of the transportation and power distribution systems. The emergent interdependency requires that system operators fully understand the status of both systems. To this end, a visualization tool is presented to illustrate the interdependency of battery bus transit and power distribution systems and the associated components. The tool aims at monitoring components from both systems, such as the locations of electric buses, the state of charge of batteries, the price of elect…
The operation of future intelligent transportation systems (ITSs), communications infrastructure (CI), and power grids (PGs) will be highly interdependent. In particular, autonomous connected vehicles require CI resources to operate, and, thus, communication failures can result in non-optimality in the ITS flow in terms of traffic jams and fuel consumption. Similarly, CI components, e.g., base stations (BSs) can be impacted by failures in the electric grid that is powering them. Thus, malicious attacks on the PG can lead to failures in both the CI and the ITSs. To this end, in this paper, the …
This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification of mobile transportation systems, such as automobiles and aircraft, presents the ability to improve key performance metrics such as efficiency and cost. However, the strong bidirectional coupling between electrical and thermal dynamics within new components creates integration challenges, increasing component degradation and reducing performance. Diminishing these issues requires novel plant designs and control strategies. The electrified mobility literature provi…
Disruptive changes in vehicles and transportation have been triggered by automated, connected, electrified and shared mobility. Autonomous vehicles, like Internet data packets, are transported from one address to another through the road network. The Internet has become a general network transmission paradigm, and the Energy Internet is a successful application of this paradigm to the field of energy. By introducing the Internet paradigm to the field of transportation, this paper is the first to propose the Transportation Internet. Based on the concept of the Transportation Internet, fundament…
It is well known that physical interdependencies exist between networked civil infrastructures such as transportation and power system networks. In order to analyze complex nonlinear correlations between such networks, datasets pertaining to such real infrastructures are required. However, such data are not readily available due to their proprietary nature. This work proposes a methodology to generate realistic synthetic power distribution networks for a given geographical region. A network generated in this manner is not the actual distribution system, but its functionality is very similar to…
Electric vehicles (EVs) are being actively adopted as a solution to sustainable transportation. However, a bottleneck remains with charging, where two of the main problems are the long charging time and the range anxiety of EV drivers. In this research, we investigate the deployment of dynamic charging systems, i.e., electrified roads that wirelessly charge EVs on the go, with a view to accelerating EVs adoption rate. We propose a traffic-based deployment strategy, statistically quantify its impact, and apply the strategy to two case studies of real traffic in New York City (USA) and Xi'an (Ch…
Integrated simulation models are emerging as an alternative for analyzing large-scale interdependent infrastructure networks due to their modeling advantages over traditional interdependency models. This paper presents an open-source integrated simulation package for the asset-level analysis of interdependent infrastructure systems. The simulation platform, named 'InfraRisk' and developed in Python, can simulate disaster-induced infrastructure failures and subsequent post-disaster restoration in interconnected water-, power-, and road networks. InfraRisk consists of an infrastructure module, a…
Electric Vehicles' (EVs) growing number has various consequences, from reducing greenhouse gas emissions and local pollution to altering traffic congestion and electricity consumption. More specifically, decisions of operators from both the transportation and the electrical systems are coupled due to EVs' decisions. Thus, decision-making requires a model of several interdependent operators and of EVs' both driving and charging behaviors. Such a model is suggested for the electrical system in the context of commuting, which has a typical trilevel structure. At the lower level of the model, a co…
Artificial Intelligence for Power-Converter-Rich Electrical Systems: A Review
University of Cambridge（剑桥大学）；Shanghai Jiao Tong University（上海交通大学）；University of Leicester（莱斯特大学）；Shanghai University of Electric Power（上海电力大学）；National Tsing Hua University（国立清华大学）；Nanyang Technological University（南洋理工大学）
Cyber-physical systems (CPS) incorporate the complex and large-scale engineered systems behind critical infrastructure operations, such as water distribution networks, energy delivery systems, healthcare services, manufacturing systems, and transportation networks. Industrial CPS in particular need to simultaneously satisfy requirements of available, secure, safe and reliable system operation against diverse threats, in an adaptive and sustainable way. These adverse events can be of accidental or malicious nature and may include natural disasters, hardware or software faults, cyberattacks, or …
