University of Wisconsin Milwaukee UWM Digital Commons Theses and Dissertations May 2018 Optimization for Integration of Plug-in Hybrid Electric Vehicles into Distribution Grid Shuaiyu Bu University of Wisconsin-Milwaukee Follow this and additional works at: https://dc.edu/etd Part of the Electrical and Electronics Commons Recommended Citation Bu, Shuaiyu, "Optimization for Integration of Plug-in Hybrid Electric Vehicles into Distribution Grid" (2018). Theses and Dissertations.edu/etd/1763 This Thesis is brought to you for free and open access by UWM Digital Commons. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of UWM Digital Commons. For more information, please contact open-access@uwm.
OPTIMIZATION FOR INTEGRATION OF PLUG-IN HYBRID ELECTRIC VEHICLES INTO DISTRIBUTION GRID by Shuaiyu Bu A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering at The University of Wisconsin-Milwaukee May 2018 ABSTRACT OPTIMIZATION FOR INTEGRATION OF PLUG-IN HYBRID ELECTRIC VEHICLES INTO DISTRIBUTION GRID by Shuaiyu Bu The University of Wisconsin-Milwaukee, 2018 Under the Supervision of Dr. Lingfeng Wang Plug-in hybrid electric vehicles (PHEVs) feature combined electric and gasoline powertrains with internal combustion engine and electric motors powered by battery packs. The battery packs of PHEVs are mostly charged during off-peaks hours at lower prices and meanwhile absorb the excess power from the grid. Similarly, the power stored in the batteries can also flow back to the electric grid in response to ease the peak load demands.
With the increasing penetration and integration of PHEVs, the reliability of PHEVs is essential to overall power system reliability since the charging mechanisms of PHEVs can influence the reliability of power system. Furthermore, due to the direct integration of PHEVs into the residential distribution network, the PHEVs can work as backup batteries for power systems in case of power outage. Therefore, the reliability analysis of power systems and the ancillary services provided by PHEVs are also proposed in this thesis study. For the driving pattern of each PHEV, there are three basic elements modeled, which are the departure time, the arrival time and the daily mileage, all represented by probability ii density functions.
Based on these basic concepts, the methodology for modeling the load demand of PHEVs is introduced. In the proposed system, both the Differential Evolution and the Particle Swarm Optimization are proposed to optimize the control strategies for power systems with integration of PHEVs. Aside from using the minimum cost as a figure of merit when designing and determining the best PHEV charging mechanism, the reliability improvement brought to the power systems by PHEVs and the extra earnings obtained by performing frequency regulation services are also quantified and taken into account. Although the reliability of power systems with PHEV penetrations has been well-studied, the adoption of the Differential Evolution algorithm for minimizing the cost of overall system is not exercised, not to mention a thorough comparative study with other common optimization algorithms.
To sum up, the Differential Evolution can not only achieve multiple goals by improving the power quality, reducing the peak load, providing regulation services and minimizing the total virtual cost in this system, it can also offer better results compared with the Particle Swarm Optimization in terms of minimizing the cost. iii © Copyright by Shuaiyu Bu, 2018 All Rights Reserved iv TABLE OF CONTENTS Introduction .1 Introduction of Plug-in Hybrid Electric Vehicles .2 Power System and Power System Reliability .3 Reliability Cost and Reliability Worth .4 Types of Electric Vehicles .5 The concept of Vehicle-to-Grid .7 Power Markets and Ancillary Services .2 Reliability Evaluation Method .2 PHEV Load Demand .1 Predicted Driving Pattern .2 Stochastic Fuzzy Model .4 PHEV Load Profile .3 Distribution System Model .2 Residential Distribution System .2 The Model of Battery Degradation Cost .5 Mathematics Models and Objective Function. 24 Power System Reliability Analysis Methodology .1 Overview of Approach.3 Particle Swarm Optimization .3 Conclusions and Future Work. 36 Simulation Results and Case Study.2 Load Demand of Simulations .3 Comparison of Load Voltage .1 The total cost In Different Pricing Scenarios .3 Conclusions and Future Work.
49 vi LIST OF FIGURES Figure 1-1 Hierarchical Levels of Power System. 3 Figure 1-2 Utility Cost, Consumer Cost and Total Cost. 4 Figure 1-3 Schematic of control connections between PHEVs and power grid. 7 Figure 2-1 Load profile Model.
17 Figure 2-2 Topology of IEEE 34-node test feeder. 19 Figure 2-3 Real-time charging pricing tariff. 20 Figure 2-4 Time-of-use charging pricing tariff. 22 Figure 3-1 The flow diagram of Genetic Algorithm.
31 Figure 4-1 Load demand curves for different charging algorithms at 10% PHEV penetration level. 39 Figure 4-2 Load demand curves for different charging algorithms at 20% PHEV penetration level. 40 Figure 4-3 Load demand curves for different charging algorithms at 50% PHEV penetration level. 40 Figure 4-4 Load demand curves for different charging algorithms at 100% PHEV penetration level.
41 Figure 4-5 Voltage curves of IEEE 34-node test feeder for different charging algorithms at 10% penetration level. 42 Figure 4-6 Voltage curves of IEEE 34-node test feeder for different charging algorithms at 20% penetration level. 42 Figure 4-7 Voltage curves of IEEE 34-node test feeder for different charging algorithms at 50% penetration level. 43 vii Figure 4-8 Voltage curves of IEEE 34-node test feeder for different charging algorithms at 100% penetration level.
43 Figure 4-9 Load demand curves for different charging algorithms at 50% PHEV penetration level. 45 viii LIST OF TABLES Table 1-1 Percentage of PHEVs with different AER. 6 Table 2-1 Constants in distribution functions of departure time, arrival time and daily mileage. 14 Table 4-1 Charging Cost, Regulation Earnings and Total Cost results with Differential Evolution.
37 Table 4-2 Charging Cost, Regulation Earnings and Total Cost results with Particle Swarm Optimization. 38 Table 4-3 Peak load of DE and PSO in different penetration levels. 44 Table 4-4 The cost result after adding V2G into simulation. 45 Table 4-5 The comparison of Time-of-use and Real-time pricing scenarios in different penetration levels.
46 ix ACKNOWLEDGEMENTS First of all, I would like to express my deepest appreciation to my thesis advisor Dr. Lingfeng Wang for guiding me to research on such an important topic of these days. This thesis would not have been completed without his help, patience and support. He gives me valuable insights into various aspects in power and reliability fields, and his tireless efforts in research and academics also inspires me.
Furthermore, I wish to thank professors, Professor Jun Zhang, Professor Wei Wei, who attended my dissertation committee with their consistent support, suggestions and directions. I would also like to express my sincere gratitude to my friends for their suggestions in my research. I was touched deeply by their accompany and support. Finally, I would like to appreciate the financial support and love from my family, who always stand by me and encourage me.1 Introduction of Plug-in Hybrid Electric Vehicles As the fossil fuel energy becoming increasingly scarce, technologies that have potential to reduce energy use are evaluated.
Since the transportation sector accounts for about two- thirds of the gasoline consumption in United States, new transportation technologies are booming, especially the application of Plug-in Hybrid Electric Vehicles (PHEVs). Plug-in hybrid electric vehicles (PHEVs) feature combined electric and gasoline powertrains with internal combustion engine and electric motors powered by battery packs. The battery pack of PHEVs can be charged by plugging vehicles into the power grid and using excess engine power. Furthermore, due to the battery pack of PHEVs as well as the directly connections between PHEVs and power grid, PHEVs can work as backup batteries to power system when power outage happened.
Additionally, PHEVs have great potential to reduce oil consumption and greenhouse gases emission. With using electricity grids as a substitute for burning gasoline, PHEVs increase the use of coal, natural gas and nuclear energy in power plants, and also increase energy independence for petroleum.2 Power System and Power System Reliability The power system is a complex and integrated system including power generation systems, composite generation, transmission and distribution systems. It works as converting the energy of nature into electricity by power generation power device, and then supply electric energy to each customer through power transmission, transformation and distribution, which are the basic functional zones of power system. According to the power system management system, organization, power grid structure and voltage level, a concept of hierarchical levels (HLs) is developed to establish a way to identify and constitute function zones [1].
From the figure below, the first level (HL I) indicates the generation facilities. The second level (HL II) refers the combination of generation facilities and transmission facilities. As for the third level (HL III), it represents the whole system facilities and it can provide energy demand of users. 2 Figure 1-1 Hierarchical Levels of Power System [1].
The reliability of power system includes two aspects: adequacy and security. The former concept means that the power system has sufficient power generation capacity and transmission capacity, which can meet the peak load demand from customers at any time, and represents the steady state performance of the power grid. The latter aspect, security, refers to the safety of the power system of disturbances and the ability to avoid large-scale power outages, showing the dynamic performance of the power system.3 Reliability Cost and Reliability Worth Reliability cost and reliability worth are two concepts related with each other simply. The relationship between them can be presented by Figure 1.
It can be seen that, from these two curves, with the investment cost is increasing, the reliability will be higher. In this way, the total cost is the sum of customer cost and investment cost. The minimum total cost is viewed as the optimum result of reliability. 3 Figure 1-2 Utility Cost, Consumer Cost and Total Cost [2].
The reliability indices of distribution system include the average failure rate, λ, the average outage duration, γ, and the annual outage duration, U. These three indices are the most important and basic indices for reliability analysis, which can work to calculate other system reliability indices like SAIFI (System Average Interruption Frequency Index), SAIDI (System Average Interruption Duration Index), ASUI (Average Service Unavailability Index) and CAIDI (Customer Average Interruption Duration Index). For reliability cost and worth indices of Expected Energy Not Supply (EENS) and Expected Interruption Cost (ECOST).4 Types of Electric Vehicles Combining with V2G technology, electric vehicles can be divided into three different types, including (1) Battery Electrical Vehicles; (2) Fuel cell Electrical Vehicles, and (3) Plug-in Hybrid Electric Vehicles. All types of electric vehicles mentioned above contains an electric motor, which can provide all or part of driving power.
The power electronics including sinusoidal AC with varying frequencies, which can be set to 60Hz. Battery Electrical Vehicles are vehicles who have electrochemically battery to store energy. Types of batteries including nickel metal-hydride (NiMH), lithium-metal-polymer, and lithium-ion batteries. The battery electrical vehicles becoming more and more popular because of their longer battery life time, lighter weight and smaller volume.
However, the current in-vehicle batteries are expensive and not reliable to some extent. Furthermore, since the battery electrical vehicles have to connect with grid to charge, adding V2G to this kind of vehicles has the minimal costs and adjustments of operations. 4 Fuel cell electrical vehicles indicates the EVs whose batteries store energy into molecular hydrogen. Then with chemical reaction with the oxygen in the atmosphere, producing electric power, heat as well as water.
The development of storage and production of hydrogen, including pressurizing the hydrogen, getting hydrogen gas from gasoline, methanol, natural gas as well as fossil fuel and others. Up to now, the power losses during hydrogen transferring and storage is the biggest challenge to the fuel cell electric vehicles. Plug-in Hybrid Electric Vehicles (PHEVs) have internal combustion engines to drive generators. The charging of PHEV can be used to improve system reliability.
A battery inside the vehicle can buffer the generator and absorbs energy. Additionally, the battery and generator power can supply electrical power to one or even more motors to control the wheels.