Simultaneous location of distributed production sources and switches in the distribution network considering the possibility of island operation and load model

Number of pages: 121 File Format: word File Code: 32121
Year: 2013 University Degree: Master's degree Category: Electrical Engineering
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  • Summary of Simultaneous location of distributed production sources and switches in the distribution network considering the possibility of island operation and load model

    Master's Thesis in Electrical-Power Engineering

    Abstract

    The importance of the energy issue has increased the need to use new energy sources as a producer of electrical energy. Today, one of the suitable options for providing electrical energy is distributed production sources. The use of distributed generation has many positive effects, such as increasing the free capacity of lines, reducing power losses, improving the voltage profile, and improving reliability indicators. In addition, the use of separator keys in the distribution network can play an effective role in improving the reliability of the system. Also, using the keys and distributed production resources at the same time can increase the reliability of the system through the formation of intentional islands. In order to use these equipments optimally and increase the benefits obtained from them, the optimal location and capacity should be determined for them. Extensive research has been done in the field of locating distributed production resources and keys. In most of these researches, the location of one of these equipments is considered fixed and the optimal placement for the other equipment is done. In this direction, in this thesis, the simultaneous placement of keys and scattered production resources in the distribution network is done. For this problem, a cost-based objective function has been introduced and the aforementioned goals, including reducing losses and improving reliability, have been included in it as a cost. Assuming a study period of several years, economic coefficients have been used to convert costs into current value at the time of investment. In the proposed plan, the time variable of the network loads has been taken into account using the annual load continuity curve and the multi-level load model. This load model has a great influence on the selection of islands and determining the optimal location of installation of switches. Another aspect of variable load is related to its dependence on voltage. Considering the voltage-dependent load model is effective in calculating bus voltage and losses. In addition, the different outage cost for different loads of the network causes a kind of prioritization in the supply of loads. Finally, the genetic algorithm is used to solve the placement problem. The reason for using this algorithm is its ability to search in parallel from several points of the search space and avoid getting caught in local optima through the use of various operators. To help the convergence of the genetic algorithm and to reach the global optimal solution, additional operators have been defined and proposed according to the type of problem. By designing different study cases and performing simulations, the efficiency and applicability of the proposed method has been checked and confirmed.

    Distributed production resources, key, placement, load model, genetic algorithm.

    Chapter 1-Introduction

    1-1-Preface

    In the past, due to economic reasons, the size of power plants were often large and their capacity was in the range of 150 to It was 1000 MW. It is clear that such huge power plants require a lot of facilities, including land, personnel required for work, and high capital. In addition, since these large power plants cannot be built close to load centers due to some reasons, high voltage transmission lines[1] or ultra high voltage[2] and transmission stations are needed. Similar to power plants, these transmission lines and substations need sufficient capital for design, construction, operation and maintenance.

    The long structure of these transmission lines makes them vulnerable to natural hazards such as strong wind, blizzard and lightning. In some cases, these natural hazards lead to a partial or complete blackout of the power system due to the outage of some transmission lines. In recent years, these conditions, along with environmental and economic pressures, have changed the common methods for energy production.Some of the problems related to the use of large power plants are:

    Environmental effects

    Transmission line right-of-way problems

    High investment and long-term planning

    Land required for power plant construction

    One ??of the important features of DG is that this production is on a small scale and can be easily located near the point of consumption. Currently, the electricity industry tends to move towards a restructured electricity market where competition is established in generation, transmission and distribution. In this situation, DGs are very desirable products in the electricity market. People interested in having electricity production facilities, by building and operating these facilities, can meet their needs and even sell their surplus production in the market. In this case, reducing the government's burden from investing in the production sector can lead to a reduction in the price of electricity and an improvement in the quality of supply.

    Various benefits and business environment in the electricity industry are in favor of the use of DGs. However, there are many issues that must be considered before these sources can be used in power systems. For example, where DG should be placed to benefit from its maximum technical benefits such as low losses, increased reliability, increased load capacity and improved voltage profile. Apart from this, there are also problems related to the use of DGs, such as stability and protection problems [1]. In these cases, a single-index objective function has been used [2, 3]. In some other more complex objective functions have been used. In these cases, besides the power loss index, other indices such as voltage profile and reliability are also considered [4, 5, 6, 35].

    The reliability of the power system is an important issue that has attracted the attention of many researchers. The number of errors in the distribution network is significant compared to other parts of the power network. By using switching equipment such as sectioners [4], breakers [5] and reclosing switches along with DGs, it is possible to reduce the recovery time of switched off loads. As a result of this, the reliability of the system increases. Due to the high cost of these equipments, their usage should be maximized by locating them properly [7].

    In this regard, a research has been done to locate the isolating keys[6]. The objective function of this research usually considers indicators of reliability improvement and cost reduction. This equipment is used to isolate the defect area and feed other areas. The feeding of loads can be done through direct connection to the main network or through maneuvering points or feeding by DGs [7-15].

    Among the things that are effective in determining more realistic optimal solutions for placement problems, we can mention the load model. In the simplest case, the load model is considered as a peak load and constant power model [2, 3, 4, 6, 36]. In some researches, the time-varying aspect of the amount of consumed loads is considered [12, 16, 17]. In some others, the aspect of being dependent on the voltage of the power of the loads is taken into consideration [9, 12, 18]. In some, both aspects are considered [19].

    One ??of the most important effects of using DG in the distribution network is reducing losses. Also, the placement of isolating switches in the distribution network, in the presence or without the presence of DG, is done in order to improve reliability. In order to have the two advantages of reducing losses and improving reliability, disconnector switches and DGs can be used at the same time. In this case, DGs along with isolating switches can provide part of the loads by forming intentional islands when a fault occurs. In such a situation, the discussion of simultaneous placement of separator keys and DGs is raised. In some studies, the location of DGs is considered fixed and only the placement of keys is done [20].

  • Contents & References of Simultaneous location of distributed production sources and switches in the distribution network considering the possibility of island operation and load model

    List:

    List of tables D

    List of figures and

    Chapter 1- Introduction. 2

    1-1- Preface 2

    1-2- Thesis structure. 5

    Chapter 2- An overview of the problem of locating distributed production sources and separator keys in the distribution network. 8

    2-1- Introduction. 8

    2-2-    Objectives of placement of distributed generation sources and isolating switches 9

    2-2-1-     Power losses. 9

    2-2-1-1- Effect of distributed generation on power losses. 9

    2-2-1-2- How to evaluate the power loss index. 9

    2-2-2-     Reliability 10

    2-2-2-1- The effect of scattered production and separator keys on reliability 10

    2-2-2-2- How to evaluate the reliability index. 11

    2-2-3- Network voltage profile. 15

    2-2-3-1- Effect of distributed generation on voltage and network voltage regulation. 15

    2-2-3-2- How to evaluate the voltage profile index 16

    2-2-4-     Network voltage stability. 17

    2-2-4-1- The effect of distributed generation on voltage stability 17

    2-2-4-2- How to evaluate the voltage stability index 17

    2-2-5- Short circuit current 18

    2-2-5-1- The effect of scattered generation on short circuit current 18

    2-2-5-2- How to evaluate the short circuit current index 18

    2-3-   Restrictions. 19

    2-3-1- Load distribution restrictions 19

    2-3-2- Network voltage restrictions. 20

    2-3-3- Line capacity requirement. 20

    2-3-4- Production Capacity Production Capacity 21

    2-3-5- Scattered Production Ce on 21

    2-4- Scattered Production Production and Keys 22

    2-4-1- Analytical Methods. 22

    2-4-2- Numerical methods. 23

    2-4-3- Evolutionary computing methods. 25

    2-4-3-1- Ant population algorithm. 25- 2-5- Investigating several examples of the objective function for the problem of locating scattered production and separating keys 27- 2-6- Summarizing and concluding. 35

    Chapter 3- Proposed method for simultaneous deployment of distributed generation resources and disconnecting keys. 37

    3-1- Introduction. 37

    3-2- Problem modeling. 38

    3-2-1- Load model. 38

    3-2-1-1- Variable load model with time. 38

    3-2-1-2- Voltage dependent load model 39

    3-2-2-     Distributed generation model 40

    3-2-3-     Objective function. 40

    3-2-4- Limitations 45

    3-3- Suggested optimization method. 46

    3-3-1- Problem coding (chromosome definition) 47

    3-3-2- Fitness function 47

    3-3-3- Selection. 49

    3-3-4- Intersection operator 49

    3-3-5- Mutation operator 51

    3-3-6-     Generation of random population. 53

    3-3-7- Termination condition 54

    3-4- Problem solving process. 54

    3-5- Summarizing and concluding. 56

    Chapter 4- Implementation of the proposed algorithm and case studies. 58

    4-1- Introduction. 58

    4-2- Validation of reliability assessment. 59

    4-3-    Characteristics of the 33 bus network under study. 61

    4-4- Determining candidate locations for installing distributed production resources and keys 61

    4-5-    Data and parameter values ??used in the proposed algorithm. 64

    4-6- Simulation results for study cases. 67

    4-6-1- First study case. 69

    4-6-2- Second study case. 71

    4-6-1- The third study case. 74

    4-6-1- Fourth study case. 76

    4-6-2- Fifth case study. 78

    4-6-3- The sixth study case. 81

    4-6-4- The seventh study case. 82

    4-6-1- Eighth study case. 85

    4-6-1-     The ninth study case. 87

    4-6-2- Tenth study case. 88

    4-7-    Overall comparison and analysis of the results. 91

    4-8- Summarizing and concluding. 97

    Chapter 5- Summary, conclusion and suggestions 100

    5-1- Summary and conclusion. 100

    5-2-    Suggestions 102

    List of references 106

    Source:

    Nadarajah, Than Oo, and Le Van Phu. "Distributed generator placement in power distribution system using genetic algorithm to reduce losses." Thammasat International Journal of Science and Technology, vol.9, no. 3 (2004): 55-62.

    [2] Singh, Deependra, and K. S. Verma. "Multiobjective optimization for DG planning with load models." Power Systems, IEEE Transactions on 24.1 (2009): 427-436. [3] Wang, Caisheng, and M. Hashem Nehrir. "Analytical approaches for optimal placement of distributed generation sources in power systems." Power Systems, IEEE Transactions on 19, no. 4 (2004): 2068-2076.

    [4] Moradi, M. H., M. Abedinie, and H. Bagheri Tolabi. "Optimal multi-distributed generation location and capacity by genetic algorithms." In IPEC, 2010 Conference Proceedings, pp. 614-618. IEEE, 2010.

    [5] Willis, H. Lee. "Analytical methods and rules of thumb for modeling DG-distribution interaction." In Power Engineering Society Summer Meeting, 2000. IEEE, vol. 3, pp. 1643-1644. IEEE, 2000.

    [6] Ghosh, Sudipta, S. P. Ghoshal, and Saradindu Ghosh. "Optimal sizing and placement of distributed generation in a network system." International Journal of Electrical Power & Energy Systems 32, no. 8 (2010): 849-856.

    [7] Moradi, Adel, and M. Fotuhi-Firuzabad. "Optimal switch placement in distribution systems using trinary particle swarm optimization algorithm." Power Delivery, IEEE Transactions on 23.1 (2008): 271-279. [8] Falaghi, Hamid, M-R. Haghifam, and Chanan Singh. "Ant colony optimization-based method for placement of sectionalizing switches in distribution networks using a fuzzy multiobjective approach." Power Delivery, IEEE Transactions on 24.1 (2009): 268-276.

    [9] Abiri-Jahromi, Amir, Mahmud Fotuhi-Firuzabad, Masood Parvania, and Mohsen Mosleh. "Optimized sectionalizing switch placement strategy in distribution systems." Power Delivery, IEEE Transactions on 27, no. 1 (2012): 362-370.

    [10] Vahidnia, Arash, Gerard Ledwich, Arindam Ghosh, and Edward Palmer. "An improved genetic algorithm and graph theory based method for optimal sectionalizer switch placement in distribution networks with DG." In Universities Power Engineering Conference (AUPEC) 2011 21st Australasian, pp. 1-7. IEEE, 2011.

    [11] Bezerra, Jose Roberto, Giovanni Cordeiro Barroso, and Ruth PS Leao. "Switch placement algorithm for reducing customer outage impacts on radial distribution networks." In TENCON 2012-2012 IEEE Region 10 Conference, pp. 1-6. IEEE, 2012.

    [12] Tadayon, M., and S. Golestani. "A new method for optimal RCS placement in distribution power system considering DG islanding impact on reliability." In Transmission & Distribution Conference & Exposition: Asia and Pacific 2009, pp. 1-4. IEEE, 2009.

    [13] Jalilzadeh, Elshan, Seyyed Majid Miri-Larimi, and M-R. Haghifam. "Optimal placement of sectionalizing switches in distribution network with presence of renewable energy resources." CIRED 2012 Workshop: Integration of Renewables into the Distribution Grid, January 2012 page 348.

    [14] Chen, Chao-Shun, Chia-Hung Lin, Hui-Jen Chuang, Chung-Sheng Li, Ming-Yang Huang, and Chia-Wen Huang. "Optimal placement of line switches for distribution automation systems using immune algorithm." Power Systems, IEEE Transactions on 21, no. 3 (2006): 1209-1217.

    [15] Tsao, Teng-Fa, Ying-pin Chang, and Wen-Kung Tseng. "Reliability and costs optimization for distribution system placement problem." In Transmission and Distribution Conference and Exhibition: Asia and Pacific 2005 IEEE/PES, pp. 1-6. IEEE, 2005.

    [16] Raoofat, M. "Simultaneous allocation of DGs and remote controllable switches in distribution networks considering multilevel load model." International Journal of Electrical Power & Energy Systems 33.8 (2011): 1429-1436. [17] de Souza, Benemar A., ??and Jo?o MC de Albuquerque. "Optimal placement of distributed generator networks using evolutionary programming." In Transmission & Distribution Conference and Exposition: Latin America, 2006. TDC'06. IEEE/PES, pp. 1-6. IEEE, 2006. [18] A.M.

Simultaneous location of distributed production sources and switches in the distribution network considering the possibility of island operation and load model