An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Safety impact of connected and autonomous vehicles on motorways: a traffic microsimulation study

Connected and Autonomous Vehicles (CAVs) promise to improve road safety greatly. Despite the numerous CAV trials around the globe, their benefit has yet to be proven using real-world data. The lack of real-world CAV data has shifted the focus of the research community from traditional safety impact assessment methods to traffic microsimulation in order to evaluate their impacts. However, a plethora of operational, tactical and strategic challenges arising from the implementation of CAV technology remain unaddressed. This thesis presents an innovative and integrated CAV traffic microsimulation framework that aims to cover the aforementioned shortcomings.A new CAV control algorithm is developed in C++ programming language containing a longitudinal and lateral control algorithm that for the first time takes into consideration sensor error and vehicle platoon formulation of various sizes. A route-based decision-making algorithm for CAVs is also developed. The algorithm is applied to a simulated network of the M1 motorway in the United Kingdom which is calibrated and validated using instrumented vehicle data and inductive loop detector data. Multiple CAV market penetration rate, platoon size and sensor error rate scenarios are formulated and evaluated. Safety evaluation is conducted using traffic conflicts as a safety surrogate measure which is a function of time-to-collision and post encroachment time. The results reveal significant safety benefit (i.e. 10-94% reduction of traffic conflicts) as CAV market penetration increases from 0% to 100%; however, it is underlined that special focus should be given in the motorway merging and diverging areas where CAVs seem to face the most challenges. Additionally, it is proven that if the correct CAV platoon size is implemented at the appropriate point in time, greater safety benefits may be achieved. Otherwise, safety might deteriorate. However, sensor error does not affect traffic conflicts for the studied network. These results could provide valuable insights to policy makers regarding the reconfiguration of existing infrastructure to accommodate CAVs, the trustworthiness of existing CAV equipment and the optimal platoon size that should be enforced according to the market penetration rate.Finally, in order to forecast the conflict reduction for any given market penetration rate and understand the underlying factors behind traffic conflicts in a traffic microsimulation environment in-depth, a hierarchical spatial Bayesian negative binomial regression model is developed, based on the simulated CAV data. The results exhibit that besides CAV market penetration rate, speed variance across lanes significantly affects the production of simulated conflicts. As speed variance increases, the safety benefit decreases. These results emphasize the importance of speed homogeneity between lanes in a motorway as well as the increased risk in the motorway merging/diverging areas.</div

Control and Optimization of Energy Storage in AC and DC Power Grids

Energy storage attracts attention nowadays due to the critical role it will play in the power generation and transportation sectors. Electric vehicles, as moving energy storage, are going to play a key role in the terrestrial transportation sector and help reduce greenhouse emissions. Bulk hybrid energy storage will play another critical role for feeding the new types of pulsed loads on ship power systems. However, to ensure the successful adoption of energy storage, there is a need to control and optimize the charging/discharging process, taking into consideration the customer preferences and the technical aspects. In this dissertation, novel control and optimization algorithms are developed and presented to address the various challenges that arise with the adoption of energy storage in the electricity and transportation sectors. Different decentralized control algorithms are proposed to manage the charging of a mass number of electric vehicles connected to different points of charging in the power distribution system. The different algorithms successfully satisfy the preferences of the customers without negatively impacting the technical constraints of the power grid. The developed algorithms were experimentally verified at the Energy Systems Research Laboratory at FIU. In addition to the charge control of electric vehicles, the optimal allocation and sizing of commercial parking lots are considered. A bi-layer Pareto multi-objective optimization problem is formulated to optimally allocate and size a commercial parking lot. The optimization formulation tries to maximize the profits of the parking lot investor, as well as minimize the losses and voltage deviations for the distribution system operator. Sensitivity analysis to show the effect of the different objectives on the selection of the optimal size and location is also performed. Furthermore, in this dissertation, energy management strategies of the onboard hybrid energy storage for a medium voltage direct current (MVDC) ship power system are developed. The objectives of the management strategies were to maintain the voltage of the MVDC bus, ensure proper power sharing, and ensure proper use of resources, where supercapacitors are used during the transient periods and batteries are used during the steady state periods. The management strategies were successfully validated through hardware in the loop simulation

Using a low-cost bluetooth torque sensor for vehicle jerk and transient torque measurement

© IMechE 2019. This paper presents the use and development of a specific wireless torque measurement system that is used to obtain the transient torque performance of vehicle transmissions. The torque sensor is strain-based, using surface-mounted strain gauges on a prop shaft. The gauges are connected to a compact printed circuit board, which is clamped to the shaft next to the strain gauges using a three-dimensional printed housing. The printed circuit board contains an amplifier, low-pass filter, analog-to-digital converter, microcontroller and bluetooth transceiver. The printed housing is impact resistant carbon-reinforced nylon and securely retains the printed circuit board and the battery powering the device. The transmitted torque data are received by a transceiver, which is interfaced to a PC through an RS-232 connection. NI LabVIEW is used to process, display and save data. The wireless torque sensor was installed to the Unit Under Test at the output shaft of the five-speed manual transmission. The Unit Under Test was installed on a dynamometer for verification purposes and the transient torque was recorded under various operational conditions. The transient output torque of the manual transmission is measured and compared with results obtained from simulations performed under similar operating conditions. The two sets of transient responses show a good correlation with each other and hence demonstrate that the torque sensor meets the major design specifications. The data obtained will be used to enhance the fidelity of the software model

Controller Design and Experimental Validation for Connected Vehicle Systems Subject to Digital Effects and Stochastic Packet Drops

Vehicle-to-everything (V2X) communication allows vehicles to monitor the nearby traffic environment, including participants that are beyond the line of sight. Equipping conventional vehicles with V2X devices results in connected vehicles (CVs) while incorporating the information provided by V2X devices into the controllers of automated vehicles (AVs) leads to connected automated vehicles (CAVs). CAVs have great potential for improving driving comfort, reducing fuel consumption and advancing active safety for individual vehicles, as well as enhancing traffic efficiency and mobility for human-dominated traffic systems. In this dissertation, we study a class of connected cruise control (CCC) algorithms for longitudinal control of CAVs, where they respond to the motion information of one or multiple connected vehicles ahead. For validation and demonstration purposes, we utilize a scaled connected vehicle testbed consisting of a group of ground robots, which can provide us with insights about the controller design of full-size vehicles. On the one hand, intermittencies in V2X communication combined with the digital implementation of controllers introduce information delays. To ensure the performance of individual CAVs and the overall traffic, a set of methods is proposed for design and analysis of such communication-based controllers. We validate them with the scaled testbed by conducting a series of experiments on two-car predecessor-follower systems, cascaded predecessor-follower systems, and more complex connected vehicle systems. It is demonstrated that CAVs utilizing information about multiple preceding vehicles in the CCC algorithm can improve the system performance even for low penetration levels. This can be beneficial at the early stage of vehicle automation when human-driven vehicles still dominate the traffic system. On the other hand, we study the delay variations caused by stochastic packet drops in V2X communication and derive the stochastic processes describing the dynamics for the predecessor-follower systems. The dynamics of the mean, second moment and covariance are utilized to obtain stability conditions. Then the results of the two-car predecessor-follower system with stochastic delay variations are extended to an open chain as well as to a closed ring of cascaded predecessor-followers where stochastic packet drops lead to heterogeneity among different V2X devices. It is shown that the proposed analytical methods allow CCC design for CAVs that can achieve stability and stochastic disturbance attenuation in the presence of stochastic packet drops in complex connected vehicle systems.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145874/1/wubing_1.pd

Design and Control of Virtual Synchronous Machine Based Energy Systems

Conventionally, the operation and stability of power systems have been governed by the dynamics of large synchronous generators (SGs) which provide the inertial support required to maintain the resilience and stability of the power system. How-ever, the commitment of the UK to drive a zero-carbon economy is accelerating the integration of renewable energy sources (RESs) into the power system. Since the dynamics and operation of RESs differs from SGs, the large-scale integration of RESs will significantly impact the control and stability of the power system.This thesis focuses on the design of grid-friendly control algorithms termed virtual synchronous machines (VSMs), which mimic the desirable characteristics of SGs. Although several VSM topologies have been proposed in literature, most of them require further modifications before they can be integrated into the grid. Hence, a novel VSM algorithm for permanent magnet synchronous generator based wind turbines has been proposed in this thesis.The proposed VSM performs seamlessly in all operating modes and enables maxi-mum power point tracking in grid-connected operation (assuming strong grid), load following power generation in islanded mode and fault ride-through during faults. To ensure optimal performance of the VSM in all operating modes, a comprehensive stability analysis of the VSM was performed in the event of small and large per-turbations. The result of the analysis was used to establish design guidelines and operational limits of the VSM.This thesis further evaluates the impact of VSMs on the power systems low-frequency oscillations (LFOs). A detailed two-machine test-bed was developed to analyze the LFOs which exists when VSMs replace SGs. The characteristics of the LFO modes and the dominant states was comprehensively analyzed. The LFO modes which exists in an all-VSM grid was also analyzed. Further, the role of the power system stabilizers in an all-VSM grid was comprehensively evaluated. An IEEE benchmark two-area four-machine system was employed to validate the results of the small-signal analysis.The analysis and time-domain simulations in this thesis were performed in the MAT-LAB/SIMULINK environment

Cooperative Traffic Control Framework for Mixed Vehicular Flows

A prompt revolution is foreseen in the transportation sector, when the current conventional human-driven vehicles will be replaced by fully connected and automated vehicles. As a result, there will be a transition period where both types will coexist until the later type is fully adopted in the traffic networks. This new mix of traffic flow on the existing transportation network will require developing a new ecosystem able to accommodate both types of vehicles in traffic network environments of the future. A major challenging issue related to the emerging mixed transportation ecosystem is the lack of an adequate model and control framework. This is especially important for modeling traffic safety and operations at network bottlenecks such as highway merging areas. Therefore, the main goal of this thesis is to develop a microscopic modeling and hierarchical cooperative control framework specifically for mixed traffic at highway on-ramps. In this thesis, a two-level hierarchical traffic control framework is proposed for mixed traffic at highway merging areas. In this regard, for the lower level of the proposed framework, this thesis establishes a set of fundamental trajectory-based cooperative control algorithms for different merging scenarios under mixed traffic conditions. We identify six scenarios, consisting of triplets of vehicles, defined based on the different combinations of CAVs and conventional vehicles. For each triplet, different consecutive movement phases along with corresponding desired distance and velocity set-points are defined. Via the movement phases, the CAVs engaged in each triplet cooperate to calculate their optimal-smooth trajectories aiming at facilitating the merging maneuver while complying with the realistic constraints related to the safety and comfort of vehicle occupants. The vehicles in each triplet are modeled by a distinct system, and a Model Predictive Control scheme is employed to calculate the cooperative optimal control inputs (acceleration values) for CAVs, accounting for conventional vehicles’ uncertainties. In the next step of the thesis, for the higher level of the proposed framework, a merging sequence determination and triplets’ formation methodology is developed based on predicting the arrival time of vehicles into the merging area and according to the priority in choosing different triplet types. To model the merging maneuvers when two consecutive triplets share a vehicle, the interactions between triplets of vehicles are also investigated. In order to develop a microscopic traffic simulator, we analytically formulate different vehicles’ driving behaviors under cooperative (i.e., the proposed traffic control framework) and non-cooperative (i.e., normal) operation modes and discuss the switching conditions between these driving modes. To evaluate the effectiveness of the proposed framework, first, each triplet is simulated in MATLAB and evaluated for different sets of system initial values. Without a need for readjusting the algorithm for different initial values, the simulation results show that the proposed cooperative merging algorithms ensure smooth merging maneuvers while satisfying all the prescribed constraints, e.g., speed limits, safe distances, and comfortable acceleration and jerk values. Moreover, a simulator is developed in MATLAB for the entire framework (including both the higher and lower level of the framework) to evaluate the impact of all the triplets on continuous mixed traffic flow. Different penetration rates of CAVs under different traffic flow conditions are evaluated through the developed simulator. The simulation results show that the proposed cooperative methodology, comparing to the non-cooperative operation, can improve the average travel time of merging vehicles without disturbing the mainstream flow, provide safer merging maneuvers by avoiding the merging vehicles to stop at the end of the acceleration lane, and guarantee smooth motion trajectories for CAVs (i.e., derivable position and speed along with limited changes in acceleration values). Generally, the results emphasize that the proposed cooperative traffic control framework can improve the mixed traffic conditions in terms of both traffic safety and operations. Moreover, the simulator provides a tool for the transportation community to evaluate their existing infrastructures under different penetration rates of CAVs and examine different traffic control plans for a mixed traffic environment. As the merging maneuver is only one application of gap-acceptance models, other types of maneuvers (e.g., lane changing, vehicle turning, etc.) can be similarly modelled. Thus, we can extend the proposed framework to the multi-lane highways, roundabouts, and urban area intersections. Furthermore, the arrival time prediction of the vehicles can be improved to elevate the performance of the proposed framework during the very congested traffic conditions