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Reliability assessment of smart microgrid considering the impact of electric vehicles and PMU

Number of pages: 92 File Format: word File Code: 32151
Year: 2014 University Degree: Master's degree Category: Electrical Engineering
Tags/Keywords: planning - PMU - Power system - Reliability - Smart measurement - The car is broken - Unit of measurement
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  • Summary of Reliability assessment of smart microgrid considering the impact of electric vehicles and PMU

    Dissertation of the Discontinuous Master of Electrical Engineering (M.Sc.)

    Inclination: Strength

    Abstract

    Reliability in any system is a concept that refers to the safe and reliable operation of the system. Although this concept is undefined in most systems such as electrical, mechanical, pneumatic, etc., it is of interest to designers and consumers, but with the advancement of technology and the increase in the presence of sensitive loads and dependence on the continuous work of systems, today this concept has gained more meaning and application. In general, it can be said that the wider the system and the more important it is, the more attention and need there is to calculate the reliability of that system in planning and making decisions. In this thesis, the calculation of reliability in the power system and the study of the effect of electric vehicles as well as phasor measurement devices in increasing reliability have been discussed. For this purpose, by examining the sample system and with different reliability indicators in power systems, it has been tested once in the presence of vehicle sources and phasor measurement devices and once again without considering the presence of these sources. The results indicate.

    Keywords: Reliability, smart car, intelligent measurement unit, power system style="direction: rtl;">Reliability is a basic concept in planning, designing and building any system. In power systems, reliability is based on the centrality of equality of production[1] and demand[2]. Various reliability indicators [3] are defined in the power system, each of which examines a part of the power system. For example, to check the reliability of the production system, regardless of any complexity [4] in the transmission and distribution systems, the amount of production and the probability [5] of availability [6] of each power plant unit are used as criteria for judging and calculating reliability. However, in a broader view and considering the transmission system, only the availability of power plant production units, to access their production, is not a criterion for judging reliability; But the probability of accessibility to transmission lines also plays a role in calculating reliability. The broadest view in calculating the reliability in the power system is a comprehensive look at the production, transmission and distribution sectors to calculate the reliability in the power system.

    The HL1 study level examines only the reliability and availability of the production system.

    The HL2 study level, in addition to the availability of the production system, also considers the limitations of the transmission system.

    The HL3 study level deals with the comprehensive study of the power system.

    The above division is one of the categories in the study of reliability in the power system. The scope of the author's view in this research is the study of reliability within the scope of distribution systems.

    Different parameters play a role in calculating the reliability of a system. For example, in power systems, reliability increases with the increase of power plant units. Of course, it should be noted that the increase in production by itself will not increase the reliability, but the possibility of the availability of the added production is important.

    Today, with the advances made in power electronics, as well as the increasing importance of environmental concerns and air pollution, as well as the increase in the price of fossil fuels, the approach to production based on renewable energy has increased. This issue has created a phenomenon called distributed production in the distributed network sector. Dispersed production sources include wind turbines, solar cells and combined heat-power units [7] (CHP). Electric cars with the ability to connect to the power grid are also scattered from other sources.In addition to this issue, the role of phasor measurement devices in calculating reliability will also be investigated. 1-2 statement of the problem and the need for research, although reliability in power systems is not a new concept and has long been of interest to designers [8] and planners [9] of power systems, however, the creation of new equipment in power systems such as smart measuring devices [10] and Also, distributed generation resources as well as new power switches with high maneuverability require designers to define new reliability. In more precise terms, with the more advanced hardware in the power system and the significant presence of these equipments, the need to investigate their effects on reliability concepts and indicators seems important.

    For example, the presence of scattered production resources in the distribution network sector, perhaps at first glance, results in an unquestionable increase in reliability in the power system. Because it adds production resources to distribution networks and increasing production according to traditional reliability calculations [11] is a way to increase reliability in the power system. While the unlimited presence of these resources in distribution networks causes accidents, which incidentally leads to a decrease in reliability in power systems.

  • Contents & References of Reliability assessment of smart microgrid considering the impact of electric vehicles and PMU

    List:

    Page

    Abstract 1

    Chapter One: Research Overview

    1-1 Introduction. 3

    1-2 statement of the problem and necessity of research. 5

    1-2-2 reliability in mathematical language. 9

    1-2-3 solutions to increase reliability in a system[1]. 11

    1-2-4 different methods of power system reliability evaluation[1]. 12

    1-2-5 of the cars 13

    1-3 Phasor measurement units (PMU) 18

    1-3-1 Synchronization of sampling moments. 18

    1-3-2 Structure of phasor measurement units. 18

    1-3-3 Types of messages 19

    1-3-4 Transient response of phasor measurement units. 19

    1-3-5 Data transmission timing 20

    1-3-6 Applications of phasor measurement units. 20

    1-4 research objectives. 23

    1-5 research hypotheses. 24

    1-6 The process of presenting materials. 24

    Chapter Two: An overview of the conducted research (literature and documentation, frameworks and basis, history and background of the research)

    2-1 An overview of the past research in the field of cars. 26

    2-2 An overview of the research conducted in the study of the effect of distributed production resources on reliability. 37

    Chapter 3: Method of conducting research

    3-1 Introduction. 45

    2-3 Electric vehicle modeling. 56

    3-3 phasor measurement unit. 56

    3-4 reliability assessment method in the distribution system. 58

    3-4-1 Advantages and disadvantages of analytical and random methods. 58

    3-5 reliability indicators in the distribution network. 59

    3-5-1 Common Axis Indexes 60

    3-5-1-1 System Outage Average Fluctuation Index (SAIFI) 60

    3-5-1-2 System Outage Average Duration Index (SAIDI) 61

    3-5-1-3 Average Outage Subscribers Index (CAIDI) 61

    3-5-1-4 Average system availability index (ASAI) 62

    3-5-2 Reliability indicators with load criterion 62

    3-6 Summary and conclusion. 62

    Chapter Four: Implementation and Results

    4-1 Introduction. 64

    4-2 The studied network. 64

    4-3 network component information. 66

    4-4 reliability calculation algorithm. 68

    4-5 estimation of electric vehicle production. 69

    4-6 How to model the PMU measurement system in reliability calculations. 70

    4-7 Implementation of the proposed algorithm. 71

    4-7-1 Scenario 1: Absence of scattered production sources and pmu system in the network. 71

    2-4-7-2 second scenario: the presence of scattered production sources including electric cars in the network and the absence of pmu. 71

    4-7-3 presence of distributed generation resources and pmu in the network. 72

    4-8 Conclusion. 73

    Chapter Five: Conclusions and Suggestions

    5-1 Introduction. 75

    5-2 Conclusion. 75

    3-5 suggestions. 76

    Sources

    Non-Persian sources..78

    English abstract..80

    Source:

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    [1] Sheldon S. Williamson, Energy Management Strategies for Electric and Plug-in Hybrid Electric Vehicles, first edition, Springer, 2013.

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    [6] Seref Soylu, ELECTRIC VEHICLES – ELECTRIC VEHICLES – MODELING AND SIMULATIONS, Edited by Seref Soylu, Published by InTech, 2011.

    [7] ELECTRIC AND HYBRID VEHICLES POWER SOURCES, MODELS, SUSTAINABILITY, INFRASTRUCTURE, First edition, ELSEVIER, 2010.

    [8] Qiuwei Wu, GRID INTEGRATION OF ELECTRIC VEHICLES IN OPEN ELECTRICITY MARKETS, FIRST EDITION, WILEY, 2013.

    [9] Casey Quinn, Daniel Zimmerle, and Thomas H. Bradley "An Evaluation of State-of-Charge Limitations andBradley "An Evaluation of State-of-Charge Limitations and Actuation Signal Energy Content on Plug-in Hybrid Electric Vehicle, Vehicle-to-Grid Reliability, and Economics", IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 1, MARCH 2012, pp. 483-491.

    [10] Saeed Rezaee, Ebrahim Farjah, Member, IEEE, and Benyamin Khorramdel "Probabilistic Analysis of Plug-In Electric Vehicles Impact on Electrical Grid Through Homes and Parking Lots", This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY.

    [11] Y. Ota, H. Taniguchi, T. Nakajima, K. M. Liyanage, JumpeiBaba, and A. Yokoyama “Autonomous Distributed V2G (Vehicle-to-Grid) Satisfying Scheduled Charging” IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 1, MARCH 2012, pp. 559-564.

    [12] Luc´?a Igualada, Cristina Corchero, Miguel Cruz-Zambrano, and F.-Javier Heredia, “Optimal Energy Management for a Residential Microgrid Including a Vehicle-to-Grid System”, IEEE TRANSACTIONS ON SMART GRID, VOL. 5, NO. 4, JULY 2014, PP.2163-2172.

    [13] C. Pang, P. Dutta, and M. Kezunovic, “BEVs/PHEVs as Dispersed Energy Storage for V2B Uses in the Smart Grid”, IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 1, MARCH 2012, PP.473-482.

    [14] Billinton. R and R. Allan, Reliability evaluation of engineering systems, 2nd Edition, Plenum Press, New York, 1992.

    [15] Roy Billinton · Rajesh Karki · Ajit Kumar Verma Editors, “Reliable and Sustainable Electric Power

    and Energy Systems Management”, Springer, 2013.

    [16] M.Al-Muhaini, G.T. Heydt, "Evaluating Future Power Distribution System Reliability Including Distributed Generation", IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 28, NO. 4, OCTOBER 2013, PP.2264-2272.

    [17] S. Bahramirad, W. Reder, A. Khodaei, "Reliability-Constrained Optimal Sizing of Energy Storage System in a Microgrid", IEEE TRANSACTIONS ON SMART GRID, VOL. 3, NO. 4, DECEMBER 2012, pp. 2056-2062.

    [18] I.Ziari, G. Ledwich, A.Ghosh and G.Platt, "Integrated Distribution Systems Planning to Improve Reliability Under Load Growth", IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 27, NO. 2, APRIL 2012, pp. 757-765.

    [19] S.Rezaee, E.Farjah, B.Khorramdel, "Probabilistic Analysis of Plug-In Electric Vehicles Impact on Electrical Grid Through Homes and Parking Lots", IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.

    [20] J. Zhao, F. Wen, Z. Y. Dong, Y. Xue, and K. P. Wong, "Optimal Dispatch of Electric Vehicles and Wind Power Using Enhanced Particle Swarm Optimization", IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 8, NO. 4, NOVEMBER 2012, pp. 889-899.

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    [22] M. Hashmi, S. Hanninen, and K. Maki, “Survey of smart grid concepts, architectures, and technological demonstrations worldwide,” in Proc. IEEE Power Energy Soc. Conf. Innovative Smart Grid Technologies (ISGT Latin America), Columbia, 2011, pp. 1–7.

    [23] P. P. Barker and R. W. de Mello, “Determining the impact of distributed generation on power systems: Part 1—Radial distribution systems,” in Proc. IEEE Power Eng. Soc. Summer Meeting, 2000, vol. 3, pp. 1645–1656.

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