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

Number of pages: 88 File Format: word File Code: 31377
Year: 2014 University Degree: Master's degree Category: Electronic Engineering
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    Continued Master's Thesis in Electrical Engineering (M.Sc.)

    Tension: Power

    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.

    Key words: reliability, smart car, intelligent measurement unit, power system

    1-1  Introduction

    Reliability is a basic concept in the planning, design and construction of 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 the calculation of reliability in the power system is also a comprehensive look at the production, transmission and distribution sectors to calculate the reliability in the power system. Figure 1-1 shows the different levels of reliability checks in power systems. As it is known, the study levels are divided into HL1, HL2 and HL3 fields.

    Figure 1-1

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

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

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

    The above classification 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. Along with this issue, the role of phasor measurement devices in calculating reliability will also be investigated.

    1-2 Statement of the problem and necessity of research

    Although reliability in power systems is not a new concept and has long been the concern of designers [8] and planners [9] of power systems, however, the creation of new equipment in power systems such as smart measuring devices [10] as well as distributed production sources 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 examine 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 the distribution networks causes accidents, which incidentally leads to a decrease in the reliability of the power systems. The presence of these resources in the power system, which are mostly connected to the power system in the distribution systems sector, have changed the distribution sector from passive [12] to active networks [13] and in other words, they have made the power flow two-way. At first glance, one can expect an increase in reliability in a system due to an increase in production in these sources, but the random nature [14] of these sources and the uncertainty [15] in the predicted production [16] of these sources can cause an uncertain dependence of production on these sources.

    On the other hand, the same two-way flow direction and the possibility of interference in the protection system [17] can lead to unnecessary power outages in the power system. Because with the change of power flow caused by the presence of these sources in the network, the amount of fault current changes before and after the entry of these sources into the network, and if the penetration coefficient of these sources in the network is higher, it means that the capacity of scattered sources installed in the power system will increase, the protection system and the fault current will be more and more affected by the presence of these sources and the result will be the creation of insecurity in the system.

    Dispersed generation sources have other effects as a result of which reliability is not only increased but also decreased. will have As another example of these effects, we can create power quality phenomena [18] caused by the disconnection and connection of these equipments or the presence of inverters [19] in the structure of these sources.

    Therefore, examining the effect of each scattered source in the power system and expressing solutions and safety tips for the safe presence of these sources in the network, and simultaneously preventing[20] the occurrence of disturbances[21] caused by the inappropriate placement[22] of these sources are points that point to the importance of studying in this field. Add.

    One of the other changes that have occurred in today's power systems is the possibility of checking and monitoring the system status by measuring equipment such as phasor measurement units [23] (PMU) or smart measurement systems (SMS) [24]. Equipment that are placed in strategic positions [26] of the network for the purpose of real-time monitoring of the amount of production, consumption, current passing through the lines, the amount of voltage stability [25] in the buses, as well as the evaluation of power quality phenomena in each feeder, and by measuring in real time [27], they help the regional electricity management and consumers in the best possible exploitation of the electric network.

    The presence of these electrical devices, although it has no direct effect on the amount of production or consumption, but the information from They inform the network operator of the current and future status of the network and also inform consumers of current consumption and current electricity prices. Therefore, it causes two actions in power networks.

    Preventive action[28]

    Corrective action[29]

    The first action is caused by the actions of the network operator and at the head of it is the regional power management, which informs the state of the system both from the present time, and from the not too distant future of the system through measurement and estimation of the state of the measuring devices[30] and causes the necessary measures to be taken to prevent Accidents happen. It is natural that the prevention of these incidents leads to a decrease in the amount of outages and as a result the reliability of the system increases.

    The second action can also be created by the consumers. Modifying the consumption pattern can be one of these actions in a long time. Of course, the network operator can also check the information obtained from these measuring devices, and try to fix the problems and deficiencies that previously existed in the system.

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

    List:

    Table of Contents

    Title

    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 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 research done (literature and documents, frameworks and basis, history and background of the research)

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

    2-2 An overview of the research carried out 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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Reliability assessment of smart microgrid considering the impact of autonomous vehicles and PMU