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University of Michigan
1.
Liang, Zheming.
Strengthening Resilience of Electric Power Distribution Systems against Natural Disasters: A Perspective from Machine Learning and Optimization.
Degree: PhD, College of Engineering & Computer Science, 2020, University of Michigan
URL: http://hdl.handle.net/2027.42/156031
► The resilience issues in the power system have attracted increasing attention worldwide, especially for the distribution systems that suffer from extreme weather events, such as…
(more)
▼ The resilience issues in the power system have attracted increasing attention worldwide, especially for the distribution systems that suffer from extreme weather events, such as hurricanes and wildfire. In this dissertation, several novel algorithms, such as safe reinforcement learning algorithm and risk-constrained adaptive robust optimization approach are proposed to provide resilient proactive scheduling strategies, emergency response strategy and restoration strategy for central controllers in the distribution system. Microgrids are proposed to serve as single entities from the perspective of the distribution system operator to enhance the resilience of the distribution system, reduce the distribution system operator’s control burden and improve the power quality of the distribution system. Uncertainties related with the extreme weather events such as power
generation of distributed generators, intermittent load demand, point-of-common-coupling/tie-line conditions, and trend/trace of the extreme weather event are tackled through a combination of optimization approaches, artificial intelligence algorithms and risk management methods. Extensive simulation results based on real-world data sets show that the proposed novel algorithms based proactive scheduling strategies, emergence response strategy and restoration strategy can ensure the resilience of the distribution system in a real-world environment.
Advisors/Committee Members: Su, Wencong (advisor), Hong, Junho (committee member), Jiang, Ruiwei (committee member), Wang, Mengqi (committee member).
Subjects/Keywords: Electrical and Computer Engineering
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APA (6th Edition):
Liang, Z. (2020). Strengthening Resilience of Electric Power Distribution Systems against Natural Disasters: A Perspective from Machine Learning and Optimization. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/156031
Chicago Manual of Style (16th Edition):
Liang, Zheming. “Strengthening Resilience of Electric Power Distribution Systems against Natural Disasters: A Perspective from Machine Learning and Optimization.” 2020. Doctoral Dissertation, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/156031.
MLA Handbook (7th Edition):
Liang, Zheming. “Strengthening Resilience of Electric Power Distribution Systems against Natural Disasters: A Perspective from Machine Learning and Optimization.” 2020. Web. 06 Mar 2021.
Vancouver:
Liang Z. Strengthening Resilience of Electric Power Distribution Systems against Natural Disasters: A Perspective from Machine Learning and Optimization. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/156031.
Council of Science Editors:
Liang Z. Strengthening Resilience of Electric Power Distribution Systems against Natural Disasters: A Perspective from Machine Learning and Optimization. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/156031
2.
Ajao, Adetokunbo.
Intelligent Home Energy Management Systems for Distributed Renewable Generators, Dispatchable Residential Loads and Distribted Energy Storage Devices.
Degree: MSin Engineering, College of Engineering and Computer Science, 2017, University of Michigan
URL: http://hdl.handle.net/2027.42/138102
► The high demand for electricity and the consequent increase in electricity price as lead to recentstudy in reducingthe total operating cost of a residential building.…
(more)
▼ The high demand for electricity and the consequent increase in electricity price as lead to recentstudy in reducingthe total operating cost of a residential building. This research work focuson energy management in a residential green house.Two innovative approach is proposed to solve excessiveoperating cost of a residential green house, the system inputs which consist of temperature, activity level, and energyconsumption is based on five household occupant in Atlanta, Georgia, also a Chevy volt of 16kWh is used in the case studies.Moreover, for a single residential house, the overall goal is to reduce the total operating costs and the carbon emissions for a future residential house, while satisfying the end-users’ comfort levels. This paper models a wide variety of home appliances and formulates the economic operation problem using mixed integer linear programming. Case studies are performed to validate and demonstrate the effectiveness of the proposed solution algorithm. Simulation results also show the positive impact of dispatchable loads, distributed renewable generators, and distributed energy storage devices on a future residential house.For networked residential houses, we present an optimization of total operating cost of an interconnected nanogrid (ING) considering the effect of V2H andV2G, which helps tominimizethe total operating cost. The major objective is to reduce carbon emission, total operating cost and the peak load demand while satisfying the customer preferences of each nanogrid. A mixed integer linear program (MILP) is formulated to solve the economic operation of the ING. Furthermore, case studies are performed to demonstrate the positive impact INGs have on minimizing total operating cost.
Advisors/Committee Members: Su, Wencong (advisor), Niewstadt, Lin Van (committee member), Bai, Kevin (committee member).
Subjects/Keywords: Vehicle to Home (V2H); Renewable energy; Vehicle to Grid (V2G); Demand Response; Distributed Energy Storage Device (DESD); Electrical Engineering
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APA ·
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APA (6th Edition):
Ajao, A. (2017). Intelligent Home Energy Management Systems for Distributed Renewable Generators, Dispatchable Residential Loads and Distribted Energy Storage Devices. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/138102
Chicago Manual of Style (16th Edition):
Ajao, Adetokunbo. “Intelligent Home Energy Management Systems for Distributed Renewable Generators, Dispatchable Residential Loads and Distribted Energy Storage Devices.” 2017. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/138102.
MLA Handbook (7th Edition):
Ajao, Adetokunbo. “Intelligent Home Energy Management Systems for Distributed Renewable Generators, Dispatchable Residential Loads and Distribted Energy Storage Devices.” 2017. Web. 06 Mar 2021.
Vancouver:
Ajao A. Intelligent Home Energy Management Systems for Distributed Renewable Generators, Dispatchable Residential Loads and Distribted Energy Storage Devices. [Internet] [Masters thesis]. University of Michigan; 2017. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/138102.
Council of Science Editors:
Ajao A. Intelligent Home Energy Management Systems for Distributed Renewable Generators, Dispatchable Residential Loads and Distribted Energy Storage Devices. [Masters Thesis]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/138102
3.
Ma, Rui.
Evaluate the Customer Behavior in Competitive EV Charging and Parking Services.
Degree: MSin Engineering, Electrical Engineering, College of Engineering and Computer Science, 2016, University of Michigan
URL: http://hdl.handle.net/2027.42/136067
► In the last decade, the U.S. government has spurred efforts to boost the utilization of transportation electrification technologies, because of their low-pollution emissions, energy independence,…
(more)
▼ In the last decade, the U.S. government has spurred efforts to boost the utilization of
transportation electrification technologies, because of their low-pollution emissions, energy
independence, and high fuel economy. An ever-increasing number of electric and plug-in
electric vehicles (EVs and PEVs) will radically change the traditional view of the transportation industry, social environment, and business world. Research on grid integration of EVs and PEVs typically addresses topics at the vehicle-grid boundary such as peak load impacts and optimal charging control. While researchers around the world are making significant advances in these areas, there is very little work investigating the customer behavior in competitive EV charging and parking services. On one hand, as a transportation tool and electricity carrier, EV can be charged at any charging facility and at any time, which brings spatial and temporal demand uncertainty to the service providers. On the other hand, the retail electricity price and parking fee may have an impact on customer behavior, eventually leading to a change in the expected profits of the service providers. In this thesis, the dynamic interactions between service providers and customers are studied and modeled using game theory. In the above mentioned competition, the players decide their own strategies (i.e., retail electricity price, parking fee, and rebate) while considering a variety of physical constraints such as transformer capacity. The customer segmentation is also taken into consideration. More specifically, the competitive market is studied using a non-cooperative Bertrand game. Case studies demonstrate the accuracy, and effectiveness of the proposed solution algorithms
Advisors/Committee Members: Su, Wencong (advisor), Zheng, Yu (committee member), Su%22%29&pagesize-30">Chen, Yi-
Su (committee member).
Subjects/Keywords: Electric vehicle; Game theory; Power system economics; Smart grid; Renewable energy; Electrical Engineering; Energy
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❌
APA ·
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MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Ma, R. (2016). Evaluate the Customer Behavior in Competitive EV Charging and Parking Services. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/136067
Chicago Manual of Style (16th Edition):
Ma, Rui. “Evaluate the Customer Behavior in Competitive EV Charging and Parking Services.” 2016. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/136067.
MLA Handbook (7th Edition):
Ma, Rui. “Evaluate the Customer Behavior in Competitive EV Charging and Parking Services.” 2016. Web. 06 Mar 2021.
Vancouver:
Ma R. Evaluate the Customer Behavior in Competitive EV Charging and Parking Services. [Internet] [Masters thesis]. University of Michigan; 2016. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/136067.
Council of Science Editors:
Ma R. Evaluate the Customer Behavior in Competitive EV Charging and Parking Services. [Masters Thesis]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/136067
4.
Luo, Jingwei.
Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market.
Degree: MSin Engineering, Electrical Engineering, College of Engineering and Computer Science, 2017, University of Michigan
URL: http://hdl.handle.net/2027.42/136613
► The power grid is undergoing a transformation from a monopolized control system to a more decentralized one. Distributed renewable energy generation, responsive loads, and distribution…
(more)
▼ The power grid is undergoing a transformation from a monopolized control system to a more decentralized one. Distributed renewable energy generation, responsive loads, and distribution automation are posing a new challenge to the traditional centralized control method. To address these challenges, we propose two innovative centralized and decentralized solutions for the information infrastructure of the future electricity market. For the centralized approach, we investigate the applications of an open-source control system platform VOLTTRON in the areas of building control and electric vehicle charging. For the case study, we implement the VOLTTRON platform to solve the economic dispatch (ED) problem. The VOLTTRON platform is used as a central message bus and 16 single-board computers are used to simulate distributed generators and dispatchable loads. For the decentralized approach, we propose an innovative Bitcoin-style distributed transactional model “Bit-Energy” using radically different Internet-of-Things technologies (Blockchain and Ethereum’s smart contract). “Bit-Energy” enables transparent, auditable, and peer-to-peer energy transactions between active market participants. We implement a highly efficient buyer/seller matching algorithm. Case studies demonstrate the accuracy, robustness, effectiveness, and scalability of the proposed Bit-Energy platform under various operating conditions.
Advisors/Committee Members: Su, Wencong (advisor), Rawashdeh, Samir (committee member), Zheng, Yu (committee member).
Subjects/Keywords: Smart Grid; Electricity Market; Distributed Control; Multi-Agent System (MAS); Internet-of-Things (IoT); Bitcoin; Electrical Engineering
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Luo, J. (2017). Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/136613
Chicago Manual of Style (16th Edition):
Luo, Jingwei. “Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market.” 2017. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/136613.
MLA Handbook (7th Edition):
Luo, Jingwei. “Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market.” 2017. Web. 06 Mar 2021.
Vancouver:
Luo J. Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market. [Internet] [Masters thesis]. University of Michigan; 2017. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/136613.
Council of Science Editors:
Luo J. Investigate Centralized and Decentralized Information Infrastructure for Future Electricity Market. [Masters Thesis]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/136613
5.
Jin, Fanning.
FPGA Applications in Hybrid Energy Storage System and Field-oriented Motor Control.
Degree: MSin Engineering, Electrical Engineering, College of Engineering & Computer Science, 2017, University of Michigan
URL: http://hdl.handle.net/2027.42/140770
► This thesis demonstrates the utilization of FPGA chip in hybrid energy storage system (HESS) and motor control, which contains four sections. 1. In order to…
(more)
▼ This thesis demonstrates the utilization of FPGA chip in hybrid energy storage system (HESS) and motor control, which contains four sections. 1. In order to compensate for such mismatches, a HESS composed of battery and ultracapacitor (UC) is presented in this thesis. To optimize the power allocation in the HESS, a global-level fuzzy logic-based power management strategy is proposed. It has the following objectives: 1) manage the power distribution between the battery and the UC to achieve power balance without over charging/discharging the two sources; 2) make full use of the nature of the two sources to smooth out power fluctuation and extend the lifespan of batteries. Case studies are provided under various scenarios. 2. This thesis not only considered the PV-involved system, it also considered hybrid electric vehicles (HEV) system issues, which means we also developed two fuzzy logic power management strategies for HEV-involved system.
The goal is to investigate the effect of two fuzzy logic strategy when considering battery
degradation. In that case, the battery degradation model is presented and compared. The simulation results verified that one of the proposed strategy can greatly reduce the battery degradation. 3. Due to the fluctuation and instability of photovoltaic (PV) output power, mismatches between the power supply and the power demand may occur in a stand-alone PV system. In order to test the potential of FPGA chip, both fuzzy algorithm and field-oriented control (FOC) algorithm are implemented in FPGA. The digital design of each fuzzy logic stage is presented. The results validate the effectiveness of the proposed fuzzy logic-based power management strategy. 4. For FOC algorithm implementation, the goal is to utilize the rapidity of the FPGA chip to generate high-frequency PWM signals for power converter board. Both simulation and hardware results are presented, which shows the advancement of FPGA chip.
Advisors/Committee Members: Wang, Mengqi (advisor), Bai, Kevin (committee member), Su, Wencong (committee member).
Subjects/Keywords: Fuzzy logic control; Energy storage system; Battery degradation; FPGA; Field-oriented control; PMSM; Electrical engineering
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Jin, F. (2017). FPGA Applications in Hybrid Energy Storage System and Field-oriented Motor Control. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/140770
Chicago Manual of Style (16th Edition):
Jin, Fanning. “FPGA Applications in Hybrid Energy Storage System and Field-oriented Motor Control.” 2017. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/140770.
MLA Handbook (7th Edition):
Jin, Fanning. “FPGA Applications in Hybrid Energy Storage System and Field-oriented Motor Control.” 2017. Web. 06 Mar 2021.
Vancouver:
Jin F. FPGA Applications in Hybrid Energy Storage System and Field-oriented Motor Control. [Internet] [Masters thesis]. University of Michigan; 2017. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/140770.
Council of Science Editors:
Jin F. FPGA Applications in Hybrid Energy Storage System and Field-oriented Motor Control. [Masters Thesis]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/140770
6.
Zhang, Bowen.
Optimal Routing and Ecological Driving Systems for EVs/HEVs.
Degree: MSin Engineering, Electrical Engineering, College of Engineering and Computer Science, 2017, University of Michigan
URL: http://hdl.handle.net/2027.42/136617
► Nowadays, there has been an unprecedented growth of energy demand and environmental concerns, in terms of the vehicle emissions and fuel efficiency. Transportation electrification is…
(more)
▼ Nowadays, there has been an unprecedented growth of energy demand and environmental concerns, in terms of the vehicle emissions and fuel efficiency. Transportation electrification is seen as an effective way to substantially satisfy both requirements. By applying the secondary electric power source, Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) become the promising solutions, and have potential to revolutionize urban transportation systems. Therefore, the pre-trip planning and power management problems regarding EVs and HEVs have attracted many researchers’ attention. However, there is little work addressing the EV/HEV fuel economy with the consideration of detailed vehicle powertrain model and meet the constraints from various perspectives. To address these challenges, on one hand, we propose a simulation framework for the economic operation of pure EV considering dynamic electricity price. We address optimal routing and charging problems of Uber-like EV considering dynamic electricity price and passenger satisfaction. It aims not only at finding the best route over a finite driving cycle, but also optimizing the EV charging behavior, in order to achieve optimal fuel efficiency and reduce cost. On the other hand, the detailed powertrain model for the individual power-split HEV is proposed. Constraints from vehicle power flows, road conditions, and speed limits are included. Two stochastic methods, the generic algorithm (GA) and the estimation of distribution algorithm (EDA) are implemented to verify the feasibility, accuracy, robustness, and effectiveness of the proposed methods. Moreover, the proposed models for individual EV/HEV can be further tailored and extended to multiple considering other emerging technologies (e.g., connected and automated vehicles) in the near future.
Advisors/Committee Members: Su, Wencong (advisor), Bai, Hua (committee member), Wan, Mengqi (committee member).
Subjects/Keywords: Electric Vehicle; Hybrid Electric Vehicle; Ecological Driving; Optimal Routing and Charging; Electrical Engineering
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Zhang, B. (2017). Optimal Routing and Ecological Driving Systems for EVs/HEVs. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/136617
Chicago Manual of Style (16th Edition):
Zhang, Bowen. “Optimal Routing and Ecological Driving Systems for EVs/HEVs.” 2017. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/136617.
MLA Handbook (7th Edition):
Zhang, Bowen. “Optimal Routing and Ecological Driving Systems for EVs/HEVs.” 2017. Web. 06 Mar 2021.
Vancouver:
Zhang B. Optimal Routing and Ecological Driving Systems for EVs/HEVs. [Internet] [Masters thesis]. University of Michigan; 2017. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/136617.
Council of Science Editors:
Zhang B. Optimal Routing and Ecological Driving Systems for EVs/HEVs. [Masters Thesis]. University of Michigan; 2017. Available from: http://hdl.handle.net/2027.42/136617
7.
Pourbabak, Hajir.
Distributed Control Approaches for Power Systems.
Degree: PhD, College of Engineering & Computer Science, 2019, University of Michigan
URL: http://hdl.handle.net/2027.42/151932
► The energy industry is undergoing through a reconstruction from a monopolistic electricity market to a more open and transactive one. The next generation grid is…
(more)
▼ The energy industry is undergoing through a reconstruction from a monopolistic electricity market to a more open and transactive one. The next generation grid is a level playing field in terms of electricity transactions, where all customers have an equal opportunity. The emerging concepts of electricity prosumers are expected to have a significant impact on the retail electricity market. As a result, there is an urgent need to control the interactions among numerous consumers and prosumers. The existing control approaches can be divided into three categories, namely, centralized control, decentralized control, and distributed control. The majority of existing literature focuses on the centralized control. In most cases, the dedicated communication links are required to exchange data between the central controller and the local agents. The centralized control approaches are suitable for relatively small-scale systems without reconstructing the existing communication and control networks. However, as the number of consumers and prosumers are increasing to hundreds of thousands, there are some technical barriers on the centralized control-based economic operations such as heavy computation burden and single point of failure. The decentralized control is an intermediate solution to address the above mentioned challenges. The overall objective is to maximize the benefits of local agents and there is no guarantee that the decisions made by each local agents can contribute to the global optimal decision of the entire system. The distributed control has the potential to solve the economic operation problems of multiple consumers and prosumers. Local agents can share information through two-way communication links in order to find the global optimal decision. Application of distributed control methods in power system increase system’s scalability, alleviate monopoly and monopsony, improve the privacy and distribute computational load among various entities.
Advisors/Committee Members: Su, Wencong (advisor), Hong, Junho (committee member), Hu, Zhen (committee member), Rawashdeh, Samir (committee member).
Subjects/Keywords: Power systems; Smart grids; Energy Internet; Distributed control approach; Power flow; Power system optimization; Optimal power flow; Economic dispatch; Electrical and Computer Engineering
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Pourbabak, H. (2019). Distributed Control Approaches for Power Systems. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/151932
Chicago Manual of Style (16th Edition):
Pourbabak, Hajir. “Distributed Control Approaches for Power Systems.” 2019. Doctoral Dissertation, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/151932.
MLA Handbook (7th Edition):
Pourbabak, Hajir. “Distributed Control Approaches for Power Systems.” 2019. Web. 06 Mar 2021.
Vancouver:
Pourbabak H. Distributed Control Approaches for Power Systems. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/151932.
Council of Science Editors:
Pourbabak H. Distributed Control Approaches for Power Systems. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/151932
8.
Chen, Tao.
Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization.
Degree: PhD, College of Engineering & Computer Science, 2018, University of Michigan
URL: http://hdl.handle.net/2027.42/145686
► On top of Smart Grid technologies and new market mechanism design, the further deregulation of retail electricity market at distribution level will play a important…
(more)
▼ On top of Smart Grid technologies and new market mechanism design, the further deregulation of retail electricity market at distribution level will play a important role in promoting energy system transformation in a socioeconomic way. In today’s retail electricity market, customers have very limited ”energy choice,” or freedom to choose different types of energy services. Although the installation of distributed energy resources (DERs) has become prevalent in many regions, most customers and prosumers who have local energy generation and possible surplus can still only choose to trade with utility companies.They either purchase energy from or sell energy surplus back to the utilities directly while suffering from some price gap. The key to providing more energy trading freedom and open innovation in the retail electricity market is to develop new consumer-centric business models and possibly a localized energy trading platform. This dissertation is exactly pursuing these ideas and proposing a holistic localized electricity retail market to push the next-generation retail electricity market infrastructure to be a level playing field, where all customers have an equal opportunity to actively participate directly. This dissertation also studied and discussed opportunities of many emerging technologies, such as reinforcement learning and deep reinforcement learning, for intelligent energy system operation. Some improvement suggestion of the modeling framework and methodology are included as well.
Advisors/Committee Members: Su, Wencong (advisor), Su%22%29&pagesize-30">Chen, Yi-
Su (committee member),
Lakshmanan, Sridhar (committee member),
Rawashdeh, Samir (committee member).
Subjects/Keywords: Electricity market; Smart grid; Prosumer; Reinforcement learning; Power system; Machine learning; Electrical and computer engineering
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Chen, T. (2018). Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/145686
Chicago Manual of Style (16th Edition):
Chen, Tao. “Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization.” 2018. Doctoral Dissertation, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/145686.
MLA Handbook (7th Edition):
Chen, Tao. “Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization.” 2018. Web. 06 Mar 2021.
Vancouver:
Chen T. Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/145686.
Council of Science Editors:
Chen T. Understanding Deregulated Retail Electricity Markets in the Future: A Perspective from Machine Learning and Optimization. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/145686
9.
Rongali, Prudhvi Raj.
An Integratable V-X Communication based Conventional Vehicle Fuel Optimization model for distance based Ecological Driving Scheme.
Degree: MSin Engineering, Computer Engineering, College of Engineering and Computer Science, 2018, University of Michigan
URL: http://hdl.handle.net/2027.42/146734
► This thesis paper proposes An Integratable V-X Communication-based Conventional Vehicle Fuel Optimization model for real-time traffic conditions. Before departure, the speed profile for an entire…
(more)
▼ This thesis paper proposes An Integratable V-X Communication-based Conventional Vehicle Fuel Optimization model for real-time traffic conditions. Before departure, the speed profile for an entire route is optimized using signal phase and timing (SP AT) information and location of traffic lights to provide smooth transitions at traffic signal intersections. In this study, we are going to develop ”nonstop” optimal speed model that can be integrated to existing distance based eco-driving schemes. The initial simulation is done using MATLAB to evaluate optimal speed, fuel economy, the travel time of the ”nonstop” model and the results are compared with the optimization results from distance based eco-driving scheme which uses an estimation of distribution algorithm (EDA). Further integration compatibility of ”nonstop” model with the distance based eco-driving
scheme is analyzed.
Advisors/Committee Members: Su, Wencong (advisor), Wang, Mengqi (committee member), Islam, Riadul (committee member).
Subjects/Keywords: V-X communication; Eco-driving; Conventional vehicle; Fuel optimization; Urban traffic environment; MATLAB; SPAT; Nonstop model; EDA; Dijkstra algorithm; Computer engineering
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APA ·
Chicago ·
MLA ·
Vancouver ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Rongali, P. R. (2018). An Integratable V-X Communication based Conventional Vehicle Fuel Optimization model for distance based Ecological Driving Scheme. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/146734
Chicago Manual of Style (16th Edition):
Rongali, Prudhvi Raj. “An Integratable V-X Communication based Conventional Vehicle Fuel Optimization model for distance based Ecological Driving Scheme.” 2018. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/146734.
MLA Handbook (7th Edition):
Rongali, Prudhvi Raj. “An Integratable V-X Communication based Conventional Vehicle Fuel Optimization model for distance based Ecological Driving Scheme.” 2018. Web. 06 Mar 2021.
Vancouver:
Rongali PR. An Integratable V-X Communication based Conventional Vehicle Fuel Optimization model for distance based Ecological Driving Scheme. [Internet] [Masters thesis]. University of Michigan; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/146734.
Council of Science Editors:
Rongali PR. An Integratable V-X Communication based Conventional Vehicle Fuel Optimization model for distance based Ecological Driving Scheme. [Masters Thesis]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/146734
10.
You, Changqi.
An Isolated High-Voltage High-Frequency Pulsed Power Converter for Plasma Generation.
Degree: MSin Engineering, Electrical Engineering, College of Engineering & Computer Science, 2018, University of Michigan
URL: http://hdl.handle.net/2027.42/143180
► This thesis reviews plasma technology, pulsed power technology, basic structures of pulsed power generator and semiconductor devices. Based on above, an isolated high voltage pulsed…
(more)
▼ This thesis reviews plasma technology, pulsed power technology, basic structures of pulsed power generator and semiconductor devices. Based on above, an isolated high voltage pulsed power converter with high repetitive frequency for low power level application such as ozone generation is proposed in this thesis. The hardware for proposed pulsed power converter is well set up. The output pulsed voltage can reach -12 kV with pulse frequency up to 15 kHz. The pulse interval is designed as 1.6 μs. The proposed pulsed power converter system could be divided into two main parts, which are boost converter stage and a resonant stage. This thesis detailly introduces the structure and operating principles of the boost converter stage and the resonant stage. As for the boost converter stage, both analog control and digital control are applied to achieve the boost voltage function and power limiting function. As for the resonant stage, a pulse generating signal and spark protection function is achieved with a DSP control.This thesis also detailly gives an analysis for parasitic parameters of the proposed pulsed power converter system. Parasitic capacitances of SiC MOSFETs will affect spike performance of the proposed pulsed power converter system. A mathematical model of describing a relationship between parasitic capacitances of SiC MOSFETs and the spike voltage of the proposed pulsed power converter is proposed in this thesis. A comparison test is conducted to prove the proposed analysis.
Advisors/Committee Members: Wang, Mengqi (advisor), Bai, Kevin (committee member), Su, Wencong (committee member).
Subjects/Keywords: Pulsed power; Power electronics; Boost; Resonant; Parasitic parameters; SiC MOSFETs; Electrical engineering
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APA (6th Edition):
You, C. (2018). An Isolated High-Voltage High-Frequency Pulsed Power Converter for Plasma Generation. (Masters Thesis). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/143180
Chicago Manual of Style (16th Edition):
You, Changqi. “An Isolated High-Voltage High-Frequency Pulsed Power Converter for Plasma Generation.” 2018. Masters Thesis, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/143180.
MLA Handbook (7th Edition):
You, Changqi. “An Isolated High-Voltage High-Frequency Pulsed Power Converter for Plasma Generation.” 2018. Web. 06 Mar 2021.
Vancouver:
You C. An Isolated High-Voltage High-Frequency Pulsed Power Converter for Plasma Generation. [Internet] [Masters thesis]. University of Michigan; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/143180.
Council of Science Editors:
You C. An Isolated High-Voltage High-Frequency Pulsed Power Converter for Plasma Generation. [Masters Thesis]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/143180
11.
Liu, Chang.
Optimal Power Management Based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles.
Degree: PhD, College of Engineering & Computer Science, 2018, University of Michigan
URL: http://hdl.handle.net/2027.42/140754
► Energy optimization for plug-in hybrid electric vehicles (PHEVs) is a challenging problem due to its system complexity and various constraints. In this research, we present…
(more)
▼ Energy optimization for plug-in hybrid electric vehicles (PHEVs) is a challenging problem
due to its system complexity and various constraints. In this research, we present
a Q-learning based in-vehicle model-free solution that can robustly converge to the optimal control. The proposed algorithms combine neuro-dynamic programming (NDP) with future trip information to effectively estimate the expected future energy cost (expected cost-to-go) for a given vehicle state and control actions. The convergence of those learning algorithms is demonstrated on both fixed and randomly selected drive cycles. Based on the characteristics of these learning algorithms, we propose a two-stage deployment solution for PHEV power management applications. We will also introduce a new initialization strategy that combines optimal learning with a properly selected penalty function. Such initialization can reduce the learning convergence time by 70%, which has huge impact on in-vehicle implementation. Finally, we develop a neural network (NN) for the battery state-of-charge (SoC) prediction, rendering our power management controller completely model-free.
Advisors/Committee Members: Murphey, Yi Lu (advisor), Su, Wencong (committee member), Wang, Shige (committee member), Yi, Ya Sha (committee member).
Subjects/Keywords: Plug-in hybrid electric vehicles; Reinforcement learning; Q-learning; Power management; Energy optimization; Neuro-dynamic programming; Information Systems Engineering
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Liu, C. (2018). Optimal Power Management Based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/140754
Chicago Manual of Style (16th Edition):
Liu, Chang. “Optimal Power Management Based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles.” 2018. Doctoral Dissertation, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/140754.
MLA Handbook (7th Edition):
Liu, Chang. “Optimal Power Management Based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles.” 2018. Web. 06 Mar 2021.
Vancouver:
Liu C. Optimal Power Management Based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/140754.
Council of Science Editors:
Liu C. Optimal Power Management Based on Q-Learning and Neuro-Dynamic Programming for Plug-in Hybrid Electric Vehicles. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/140754
12.
[No author].
Rotor Position and Phase Inductance Estimation of Permanent Magnet Synchronous Machine Using PWM Excitation.
Degree: PhD, College of Engineering & Computer Science, 2018, University of Michigan
URL: http://hdl.handle.net/2027.42/145174
► This thesis provides rotor position estimation and online inductance estimation using the PWM signals used for motor control. The position estimation technique provides an alternative…
(more)
▼ This thesis provides rotor position estimation and online inductance estimation using the PWM signals used for motor control. The position estimation technique provides an alternative rotor position information that enables to eliminate the backup position sensor hardware needed for safety critical applications. The sensorless position estimation using PWM based excitation provides the methodology to obtain the position information without influencing the motor performance such as audible noise and torque ripple. The techniques provided can be utilized for online estimation of inductance parameters. These inductance parameters are needed in the reference current calculation in a typical motor control scheme. An Extended Kalman Observer is proposed to enhance inductance and position estimation. Fast sampling of motor phase current is needed to calculate the current slope in the PWM excitation scheme for position and inductance estimation. This thesis provides a methodology of fast current sampling using the microcontroller without sacrificing the processor throughput time. A method to improve the accuracy of the current slope calculation is also provided. This thesis also analyzes the effect of position sensor errors on the performance of the permanent magnet motor drive. The error has significant influence on the motor torque ripple. A mathematical analysis and experimental verification at different operating conditions is provided in this thesis.
Advisors/Committee Members: Wang, Mengqi (advisor), Hofmann, Heath (committee member), Jayaraman, Tanjore (committee member), Kim, Taehyung (committee member), Sebastian, Tomy (committee member), Su, Wencong (committee member).
Subjects/Keywords: Pulse width modulation (PWM) excitation; PMSM/IPMSM; Rotor position estimation; Stator inductance estimation; Sensorless estimation; Automotive Systems Engineering
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Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
author], [. (2018). Rotor Position and Phase Inductance Estimation of Permanent Magnet Synchronous Machine Using PWM Excitation. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/145174
Chicago Manual of Style (16th Edition):
author], [No. “Rotor Position and Phase Inductance Estimation of Permanent Magnet Synchronous Machine Using PWM Excitation.” 2018. Doctoral Dissertation, University of Michigan. Accessed March 06, 2021.
http://hdl.handle.net/2027.42/145174.
MLA Handbook (7th Edition):
author], [No. “Rotor Position and Phase Inductance Estimation of Permanent Magnet Synchronous Machine Using PWM Excitation.” 2018. Web. 06 Mar 2021.
Vancouver:
author] [. Rotor Position and Phase Inductance Estimation of Permanent Magnet Synchronous Machine Using PWM Excitation. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/2027.42/145174.
Council of Science Editors:
author] [. Rotor Position and Phase Inductance Estimation of Permanent Magnet Synchronous Machine Using PWM Excitation. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/145174
.