Nghiên cứu giải pháp tối ưu hóa điều khiển, vận hành trạm sạc điện mặt trời tại Việt Nam

BỘ CÔNG THƯƠNG TRƯỜNG ĐẠI HỌC ĐIỆN LỰC NGUYỄN NGỌC VĂN NGHIÊN CỨU GIẢI PHÁP TỐI ƯU HÓA QUÁ TRÌNH ĐIỀU KHIỂN VÀ VẬN HÀNH TRẠM SẠC TÍCH HỢP ĐIỆN MẶT TRỜI TẠI VIỆT NAM LUẤN ÁN TIẾN SĨ: KỸ THUẬT NĂNG LƯỢNG Hà Nội – 2023 BỘ CÔNG THƯƠNG TRƯỜNG ĐẠI HỌC ĐIỆN LỰC NGUYỄN NGỌC VĂN NGHIÊN CỨU GIẢI PHÁP TỐI ƯU HÓA QUÁ TRÌNH ĐIỀU KHIỂN VÀ VẬN HÀNH TRẠM SẠC TÍCH HỢP ĐIỆN MẶT TRỜI TẠI VIỆT NAM Ngành: Kỹ thuật Năng lượng Mã số: Thí điểm LUẬN ÁN TIẾN SĨ: KỸ THUẬT NĂNG LƯỢNG NGƯỜI HƯỚNG DẪN KHOA HỌC PGS. NGUYỄN HỮU ĐỨC Hà Nội - 2023 THE MINISTRY OF INDUSTRY AND TRADE ELECTRIC POWER UNIVERSITY VAN NGUYEN NGOC A RESEARCH ON OPTIMAL SOLUTIONS FOR CONTROL AND OPERATION OF PHOTOVOLTAIC INTEGRATED CHARGING STATIONS IN VIETNAM Field: Energy engineering Code: Pilot DISSERTATION: ENERGY ENGINEERING SUPERVISOR ASSOC. DUC NGUYEN HUU Hanoi - 2023 i DECLARATION I hereby declare that this is my original research work. The cited information in the dissertation has been properly referred and the sources are clearly indicated.

The data and research results presented in this thesis are truthful and have not been published in any other scientific work. Hanoi, August 10th, 2023 Supervisor Ph. Duc Nguyen Huu Van Nguyen Ngoc ii AKNOWLEDGEMENTS I would like to express my sincere gratitude to the supervisor, Assoc. Duc Nguyen Huu, for his supervision, support, and encouragement throughout the course of my research.

He has motivated and inspired my research and was constantly supportive of my endeavors. His profound expertise and insightful advice had been invaluable in my research. Under his supervision, I not only built my research skills but learnt a lot of interpersonal skills as well. I am deeply appreciative of the Electric Power University's leadership, the Postgraduate Training Department, the Faculty of Energy Technology, and the Electrical Engineering Faculty, as well as professors, colleagues etc.

who had provided me assistance and motivation during the research. I had the opportunity of collaborating with numerous fellow students and engineers throughout my Ph. I am sincerely grateful for their valuable contribution. Lastly, I would like to thank my wife and my beloved family.

Their unconditional love had been invaluable in maintaining my dedication and enthusiasm during the research. Hanoi, August 10th, 2023 Ph. Candidate Van Nguyen Ngoc iii TABLE OF CONTENTS DECLARATION .ii TABLE OF CONTENTS. vi LIST OF TABLES .vii LIST OF FIGURES.

Motivation for research .1 COP26 and PDP VIII – the commitments of Vietnam to sustainable development .2 The transition to electric two-wheeler mobility in Vietnam’s urbans .3 Rooftop solar power development in Vietnam and its impacts .4 PV-integrated charging stations – A solution for both E2W and rooftop solar development. Research goals, scope, and research questions. Research contributions and outline of the thesis .10 CHAPTER I: OVERVIEW OF ELECTRIC VEHICLE CHARGING STATIONS – ARCHITECTURES AND CONTROL ALGORITHMS.1 Charging station architectures.1 Centralized control architecture .2 Decentralized control architecture .3 Hierarchical control architecture .4 Proposal of E2W charging station architecture .2 EV charging station control algorithms .1 Algorithms focus on technical aspects .2 Algorithms focus on economic objectives .24 iv CHAPTER II: MODELING OF PV-INTEGRATED ELECTRIC- TWOWHEELER CHARGING STATIONS.2 Charging station block diagram .1 PV module and PV array .3 DC-DC boost converter and maximum power point tracking (MPPT) algorithm .4 Grid-tie inverter .5 Bi-directional charger/discharger .4 Long-term model .36 CHAPTER III: CHARGING POWER ALLOCATION ALGORITHM FOR E2W CHARGING STATIONS .2 Input data requirements.1 Electric bike and electric motorcycle specifications .3 Conventional load profile .4 Solar power output profile .5 Battery degradation - A crucial consideration of V2G technology .3 Charging power allocation algorithm for E2Ws .1 Mathematical formulation of the algorithm.62 CHAPTER IV: OPTIMAL CHARGING ALGORITHM BASED ON RECEDING HORIZON FRAMEWORK .2 Mathematical formulation, control framework and algorithm flowchart .2 Quadratic Programming with MATLAB.3 Receding horizon framework .3 Case study and simulation results .1 Charging station at university .2 Office charging station .3 Apartment charging station .4 Charging station at factory.106 CHAPTER V: REALTIME RESPONSES OF E2W CHARGING AND PRACTICAL VERIFICATION .2 Real-time charging/discharging simulation .3 Testing workbench set up .1 The technical scope of the test bench .2 Test bench design and operation.3 Test bench set up. 127 LIST OF PUBLICATIONS.

130 vi ABBREVIATIONS No. Abbreviation English Vietnamese Hệ thống tích trữ năng 1 BESS Battery energy storage system lượng bằng ắc quy 2 DOD Depth of discharge Mức xả sâu 3 DSM Demand side management Quản lý nhu cầu điện Người vận hành hệ 4 DSO Distributed system operator thống phân phối 5 E2W Electric Two-wheeler Xe điện hai bánh 6 EV Electric vehicle Xe điện 7 EVCS Electric vehicle charging station Trạm sạc xe điện 8 EVG Electric vehicle group Nhóm xe điện 9 FIT Feed-in-tariff Biểu giá FIT 10 G2V Grid to vehicle Lưới tới xe điện 11 GHG Greenhouse gas Khí nhà kính 12 HEV Hybrid electric vehicle Xe điện lai 13 ICE Internal combustion engine Động cơ đốt trong 14 OP Optimization problem Bài toán tối ưu 15 PCC Point of common coupling Điểm kết nối 16 PDF Probability density function Hàm mật độ xác suất 17 PDP Power development plan Quy hoạch điện 18 PEV Plug-in electric vehicle Xe điện có cắm sạc 19 PHEV Plug-in hybrid electric vehicle Xe điện lai có cắm sạc 20 PV Photovoltaic Quang điện Quy hoạch toàn 21 QP Quadratic programming phương 22 RES Renewable energy source Nguồn tái tạo Người vận hành hệ 23 SO System operator thống 24 SOC State of charge Trạng thái sạc 25 TOU Time of use Thời điểm sử dụng 26 UI User interface Giao diện người dùng 27 V2G Vehicle to grid Xe điện tới lưới 28 VIS Vehicle information system Hệ thống thông tin xe vii LIST OF TABLES Table 1.1 Classification of charging station problems .1 PV panel specifications .1 The family of L-category vehicles .4 Load variance in four different scenarios .1 Load variance in different scenarios.2 Arrival/ departure time probability distribution parameters .3 Load variance in different scenario .4 Arrival/ departure time probability distribution parameters .5 Load variance in different scenarios.6 Arrival/ departure time probability distribution parameters .7 Load variance in different scenarios.8 Arrival/ departure time probability distribution parameters .9 Load variance in different scenarios .2 Battery pack specifications .3 Micro grid tie inverter specifications .4 Specifications of boost/buck converters .5 Specifications of solar inverter and solar panel .120 viii LIST OF FIGURES Figure 1 Private vehicle ownership in Vietnam and other countries .2 Figure 2 Traffic congestion in Hanoi .2 Figure 3 The fifteen most polluted cities in Southeast Asia in 2018 .3 Figure 4 Map of average daily global horizontal irradiance (GHI) in Vietnam .4 Figure 5 Top 10 countries by PV installed capacity in 2020 .4 Figure 6 A PV-integrated E2W charging station.6 Figure 7 Charging station block diagram.1 Charging station architecture.1 Charging station block diagram.2 The one-diode model and Thevenin equivalent circuit .3 PV panel model.4 The equivalent circuit model of a battery .6 DC-DC boost converter block .7 Flowchart of P&O algorithm .9 Flowchart of INC algorithm .10 Transformation to the 𝑑𝑞 coordinate system.12 Control signal block for generating PWM signals.13 PWM signal generation and the inverter power circuit.14 Bi-directional charger .1 Arrival/departure distribution function - trip home .2 Probability densities of home arrival and departure times .3 Probability densities of workplace arrival and departure times .4 Arrival/departure distribution function (shift operation) .5 Flowchart of stage 1 algorithm .6 Flowchart of stage 2 algorithm .7 Flowchart of stage 3 algorithm .8 Initial SOC distribution.9 Non-EV load profile.10 PV power profile in a typical day of months.11 Total load profile after stage 1 implementation.12 Load variance in four scenarios .13 Smart charging power profile.14 Group charging power profile in January.15 Group charging power profile in June.16 Individual charging pattern for group 9 .17 Individual charging pattern for group 1 .18 Profiles of a typical E2W in groups in January.19 Profiles of a typical E2W in groups in June .1 Scheduling and implementing timeline.2 Illustration of receding horizon time window .3 Flowchart of the algorithm.4 Average charging pattern .5 Max rate charging pattern .6 Total load profile in scenarios 1, 2, 3 .7 Charging profile – RHC based algorithm (scenario 4.8 Total load profile – RHC based algorithm (scenario 4.9 Charging profile – RHC based algorithm (scenario 4.10 Total load profile – RHC based algorithm (scenario 4.11 Load variance in different cases .12 Load variance in the two proposed algorithms .13 Average charging pattern .14 Max rate charging pattern .15 Total load profile in scenarios 1, 2, 3.16 Charging profile – RH algorithm scenario 4.17 Total load profile – RH algorithm scenario 4.18 Charging profile – RH algorithm scenario 4.19 Total load profile – RH algorithm scenario 4.20 Load variance in different scenarios .21 Average charging pattern .22 Max rate charging pattern .23 Total load profile in scenarios 1, 2, 3 .24 Charging profile – RH algorithm scenario 4.25 Total load profile – RH algorithm scenario 4.26 Charging profile – RH algorithm scenario 4.27 Total load profile – RH algorithm scenario 4.28 Load variance in different scenario .29 Average charging pattern .30 Max rate charging pattern .31 Total load profile in scenarios 1, 2, 3 .32 Charging profile – RH algorithm scenario 4.33 Total load profile – RH algorithm scenario 4.34 Charging profile – RH algorithm scenario 4.35 Total load profile – RH algorithm scenario 4.36 Load variance in different scenario .37 Average charging pattern .38 Max rate charging pattern .39 Total load profile in scenarios 1, 2, 3 .40 Charging profile – RH algorithm scenario 4.41 Total load profile – RH algorithm scenario 4.42 Charging profile – RH algorithm scenario 4.43 Total load profile – RH algorithm scenario 4.44 Load variance in different scenarios .1 Typical total charging profile.2 Total charging current at 5.6 kW charging power command .3 Charging response when power command changes from 5.4 Total charging power at charging commands of 5.5 PV power, grid power, conventional load and charging load .6 SOC and battery voltage of a typical E2W.7 Test bench block diagram .8 Testing workbench design .10 Single phase grid-tie inverter .11 Boost/Buck converter .12 Solar inverter and solar panel .13 Modbus RTU connection .14 Test bench set up.15 Real-time charging response .16 Real-time discharging response .17 Real-time charge to discharge response. Motivation for research 1.1 COP26 and PDP VIII – the commitments of Vietnam to sustainable development At the COP26 conference, Vietnam made strong commitments and responsible contributions to tackle global climate change. Accordingly, Vietnam has committed to bring net emissions to zero by the middle of the century and joined the Global Coal to Clean Power Transition Statement.

In line with these commitments, the government has outlined a comprehensive roadmap with eight key tasks aiming at achieving sustainable and low-emission economic development [143]. These tasks involve promoting the transition from fossil fuel to green/clean renewable energy sources (RESs), reducing greenhouse gas (GHG) emissions in energy, transportation, and other sectors. Notably, the reduction in the use of fossil fuel vehicles, the encouragement of electric vehicle (EV) research, EV development and adoption are also promoted. The Ministry of Transport needs to study the feasibility of phasing out fossil fuel vehicles by 2040 and develop a roadmap for the transition to clean energy transportation.

Worth mentioning, on May 15th, 2023, the Vietnamese government adopted the Power Development Plan VIII (PDP VIII), showing a strong commitment towards decarbonization. The PDP VIII sets a new RES development direction by increasing the amount of renewable power generation capacity (i., up to 48 percent of the total capacity by 2030, and 65.8-71 percent by 2050) while significantly reducing coal power share in the electricity distribution plan (i., from 20 percent of the total capacity to 0 percent by 2050). The PDP VIII no longer prioritizes grid-connected solar power projects. It strongly promotes the development of solar energy for self-consumption (i.