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Energy management in microgrid using load response programs

Number of pages: 52 File Format: word File Code: 32273
Year: 2014 University Degree: Master's degree Category: Electrical Engineering
Tags/Keywords: Controller - Demand response - Electricity supply - Energy management - Energy management - Load response programs - Microgrid - Optimization - power plant - transmission networks
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  • Summary of Energy management in microgrid using load response programs

    dissertation for receiving a master's degree in the field of electricity

    Tension: power

    abstract

    The concept of a microgrid is a set of loads, sources of energy production and storage that act as a controllable load or generator and can provide power and heat for a local area to do Management of production power in microgrid is one of the main current topics in the design and operation of microgrid. The presence of scattered production resources has caused the management of a microgrid to deal with new and new topics. Depending on the level of exchanges between a microgrid and the main network, microgrid operation situations can be classified as independent or connected to the network. In order to properly exploit a microgrid, using an energy management system is essential. The goal of energy management is to provide power at the lowest cost in order to respond optimally to the load. This study examines the microgrid energy management system in two working modes, separated from the grid and connected to the grid.

    In this thesis, the problem of energy management is implemented by load response programs. Load response is one of the new developments in the field of energy management, which means the participation of consumers in improving the energy consumption pattern. The use of load response programs has many financial and practical benefits for both the consumer and the network itself, which include reducing the amount of outages, reducing operating costs, smoothing the load curve, etc. In this regard, Interruptible/Reducible Program (I/C) and Capacity Market Program (CAP) have been used. In these programs, rewards and fines are considered for customers in situations where the response to load reduction is not received in different scenarios. In this study, the economic model of load response is used to implement load response programs. This model uses the price elasticity of demand, which shows a more accurate behavior of customers' consumption for factors affecting demand, including electricity prices, rewards and penalties. By applying this model to the microgrid, the cost of operation in both working modes of the microgrid is significantly reduced. Optimization of exact programming (MIP) has been used for this purpose, and GAMS software is used to solve it.

    Key words - microgrid, optimization, demand response, energy management

    Chapter One

    Research overview

    1-1- Introduction

    Electricity supply in traditional networks is done by large power plants that are centrally located in specific points
    The generated energy must be transferred to consumption points by transmission and distribution networks. The above-mentioned power system has many problems, among which we can mention the reduction of reliability and availability due to the wear and tear of the infrastructure of the electrical system and the imposition of high costs of losses in the transmission of energy to the load points. With the growth of electric energy consumption and the demand for higher quality of consumed electricity, the power industry has been driven to use new technologies. On the other hand, the growing trend of privatization, the competitiveness of the electricity market, and the transformation of large investors into small investors, prompts the managers of the electricity industry to pay more attention to increasing the production capacity and network equipment with maximum energy efficiency and minimum operating costs.

    puts Basically, consumption management programs seek to achieve various goals, the most important of which are improving the efficiency of energy systems, increasing the load factor, reducing the need for investment to build and postponing the construction of new power plants, reducing the negative effects on the environment, reducing the costs of supplying electricity to customers, compensating for the lack of supply and reducing the excess demand for electricity, improving the reliability and quality of power, promoting the development of the energy economy, creating a culture of saving and effective support for customers[3].

    1-2- Statement of the problem

    Energy management changes the electricity consumption pattern of customers. This change is done in order to achieve the optimal consumption curve. By using energy management, by reducing consumption in time periods in addition to the appropriate load curve, it reduces the cost of operation and planning. The purpose of the energy management system [1] (EMS) is to decide on the best use of generators to produce power and heat in the microgrid, the best scheduling of the storage system, proper load management, proper purchase and sale from the power grid [4]. Load response programs are used in this thesis to implement energy management on the microgrid. Load response programs also mean the implementation of activities that lead to the reduction of peak demand in the short term and are raised in a short period of time. The American Energy Regulatory Commission [2] has divided load response programs into two main categories: incentive-based programs and time-based (tariff-based) programs. In order to better understand this issue, in the second chapter, the second part of the thesis introduces and examines various aspects of load response programs. nationwide in order to reduce operating costs. In this study, this type of control is used for the energy management system. In decentralized control, each microgrid is controlled by a controller. Decentralized control is a possible solution for many control and energy management problems in microgrids. This type of control is shown in figure (1-3).

    Figure 1-3: Decentralized control[5]

    One ??of the best candidates for decentralized control of microgrids is using the concept of multi-agent systems[3]. In this method, each agent uses his intelligence to determine the leading activities and make decisions independently from other agents. 1-3- The importance and necessity of research The purpose of the research is to solve the problem of energy management and optimal planning of the microgrid in two modes connected to the network and disconnected from the network using load response programs. In the off-grid state, the operator's goal is to minimize the operating cost, and in the grid-connected state, since the microgrid has the ability to exchange power with the national grid, the operator's goal is to optimize the exchange power in order to reduce operating costs. In this thesis, the issue of energy management is implemented by load response programs. Load response programs are aimed at reducing costs and solving the problem of consumption density. The system operator reduces the amount of demand by implementing load response programs and by using the centralized control of the microgrid, under these conditions, it issues the signals required by the production units for the purpose of optimization.

    In this thesis, the interruptible/reducible program (I/C) and the capacity market program (CAP) are used, which are incentive-based programs. In these programs, rewards and penalties are considered for customers in situations where the load reduction response is not received, in different scenarios. By applying these scenarios, the amount of demand has been determined for each hour. In this thesis, the economic model of the load is used to implement load response programs. In this model, the price elasticity of demand is used, which shows a more accurate behavior of the subscribers' consumption for the factors affecting the demand, including electricity price, reward and penalty, which by applying it to the microgrid, the operating costs are reduced to a considerable extent.

    1-4- Objectives of the dissertation

    be:

    The main purpose of this study is energy management in microgrid in two working modes such as island mode and grid connected mode.

  • Contents & References of Energy management in microgrid using load response programs

    List:

    Abstract 1

    Chapter One: Research overview. 2

    1-1- Introduction. 3

    1-2- statement of the problem. 4

    1-3- The importance and necessity of research. 5

    1-4- Objectives of the thesis. 6

    1-5- hypothesis. 6

    1-6- The overall structure of the thesis. 6

    The second chapter: an overview of the research done 8

    The first part. 8

    2-1- Microgrid. 9

    2-1-1- Introduction. 9

    2-1-2- Definition of CERTS microgrid. 10

    2-1-3- Microgrid structure. 11

    2-1-3-1- distributed energy sources 12

    2-1-3-2- connection interfaces. 12

    2-1-3-3- Microgrid loads. 13

    2-1-3-4- management systems. 14

    2-1-3-5- control structure. 15 2-1-4- Planning and operation of micro-grids 17 2-1-5 Technical and economic advantages of micro-grids 17 2-1-6 Challenges of developing micro-grids: 18 2-1-7 Presence of micro-grids in the electricity market. 18

     

     

    Part II. 18

    2-2- Load response programs 18

    2-2-1- Introduction. 18

    2-2-2- Concepts of demand side management 19

    2-2-3- Types of load response programs 22

    2-2-3-1- Classification of load response program from the point of view of FERC. 22

    2-2-3-2- Classification of load response program from the perspective of NERC. 24

    2-2-3-3-   Burden response programs at NYISO. 24

    2-2-4- Benefits of using load response programs 25

    2-2-4-1- Benefits of load response from the point of view of consumers. 25

    2-2-4-2- Benefits of load response from market and network perspective. 25

    2-2-5- The costs of answering the burden 30

    Part three. 31

    2-3- review of articles. 31

    Chapter three: materials and methods of research implementation. 33

    Mathematical modeling of the energy management system of a microgrid. 34

    3-1- Introduction. 34

    3-2- The concept of price elasticity of demand 36

    3-3- Price elasticity of demand 38

    3-3-1- Modeling single period elastic loads. 39

    3-3-2- Modeling of multi-period elastic loads. 40

    3-3-3- Load economic model 41

    3-4- Objective functions of microgrid production planning problem. 41

    3-5- Constraints of the problem of planning the participation of microgrid units. 42

    3-5-1- Power balance adverb. 42

    3-5-2- The balance clause of reward and penalty. 42

    3-5-3- The requirement of minimum and maximum production. 42

    3-5-4- binary adverb of on-off mode. 43

    3-5-5- Non-negative adverb. 43

    3-6- The final modeling of the problem. 43

    3-6-1- The first mode: operation in the mode separated from the network (island mode) 43

    3-6-2- The second mode: operation in the mode connected to the network. 44

    Chapter Four: Data Analysis 45

    4-1- Introduction. 46

    4-2- The studied system. 46

    4-3- Studying the implementation of load response programs 48

    4-3-1- Scenario 1. 48

    4-3-2- Scenario 2. 49

    4-3-3- Scenario 3. 49

    4-4- Optimum simulation of microgrid in different operating conditions. 50

    4-4-1- The first mode: separate mode from the network (island mode) 50

    4-4-2 The second mode: the mode connected to the network. 53

    Chapter five: conclusions and suggestions. 56

    5-1- Conclusion. 57

    5-2- Suggestions. 57

    List of sources. 58

     

    Source:

     [1]    “Strategic Plan For The IEA Demand-Side Management Program” 2008-2012

     

    [2]   “Demand Side Management Best Practices Guidebook for Pacific Island Power Utilities” July 2006

     

    [3]    Peter Palensky, Senior Member, IEEE, and Dietmar Dietrich, Senior Member, IEEE "Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads" IEEE Transactions on Industrial Informatics, VOL.  7, NO.  3, AUGUST 2011

     

    [4] Alireza Bagherian, S. M. Moghaddas Tafreshi" A developed Energy Management System for a Micro grid in the Competitive Electricity Market" 978-1-4244-2235-7/09/$25. 00 2009 IEEE

     

    [5]     Wencong Su and Jianhui Wang “Energy Management Systems in Micro grid Operations” October 2012, Vol.  25, Issue 8

     

     

    [6] N. W. A. ??Lidula, A. D. Rajapakse" Microgrids research: A review of Rajapakse "Microgrids research: A review of experimental micro grids and test systems" doi:10. 1016/j. rser. 2010. 09. 041 Accepted 15 September 2010

    [7] S. Chowdhury, S. P. Chowdhury and P. Crossley" Microgrids and Active Distribution Networks" Published by the Institution of Engineering and Technology, London, United Kingdom © 2009 the Institution of Engineering and Technology

    [8] Charles K. Sao, Member, IEEE, and Peter W. Lehn, Senior Member, IEEE "Control and Power Management of Converter Fed Micro grids" IEEE Transactions on Power Systems, Vol.  23, No.  3, August 2008

    [9] John Stevens, Sandia National Laboratories; Harry Vollkommer P. E., David Klapp, American Electric Power “CERTS Micro grid System Tests” 1-4244-1298-6/07/$25. 00 ©2007 IEEE.

    [10] American National Standards Institute “IEEE Guide For Monitoring, Information Exchange, And Control Of Distributed Resources Interconnected With Electric Power Systems” Approved 17 May 2007

    [11] G. Pepermans, J. Driesen, D. Haeseldonckx, W.  D'haeseleer And R. Belmans" Distributed Generation: Definition, Benefits And Issues" 19 August 2003

    [12]     by Imre Gyuk, Pramod Kulkarni, Joseph H.  Sayer, John D.  Boyes, Garth P.  Corey, and Georgianne H.  Peek ”The United States Of Storage” March/April 2005

    [13] John H. Doudna, P. E, Senior Member, IEEE" Overview of California ISO Summer 2000 Demand Response Programs" 0-7803-6672-7/01/$10. 00 (C) 2001 IEEE [14] Robert H. Lasseter, Project Leader Paolo Piagi University of Wisconsin-Madison “Control and Design of Micro grid Components” January 2006 [15] Farid Katiraei, Reza Irvani, Nikos Hatziargyriou, Aris Dimeas “Microgrid Management” 1540-7977/08/$25. 00©2008 IEEE

    [16] Aris L. Dimeas, Student Member, IEEE, and Nikos D. Hatziargyriou, Senior Member, IEEE "Operation of a Multiagent System for Microgrid Control" IEEE Transactions On Power Systems, Vol.  20, No.  3, August 2005

    [17] J. Oyarzabal, J. Jimeno, J. Ruela, A. Engler and C. Hardt “Agent based Micro Grid Management System” No ENK5-CT2002-00610

    [18] A. L. Dimeas, Student Member IEEE, N. D. Hatziargyriou, Senior Member.  IEEE" Agent based control of Virtual Power Plants" Contract No ENK 5-CT-200200610

     

    [19] Chris Marnay, Hiroshi Asano, Stavros Papathanassiou, Goran Strbac "Policymaking For Microgrid" 1540-7977/08/$25. 00©2008 IEEE

    [20] Antonis G. Tsikalakis, Student Member, IEEE, and Nikos D. Hatziargyriou, Senior Member, IEEE “Centralized Control for Optimizing Micro grids Operation” IEEE Transactions On Energy Conversion, Vol.  23, No.  1, March 2008

    [21] Clark W. Gellings “The Concept Of Demand Side Management For Electric Utilities” Proceedings Of The IEEE, Vol.  73, No.  10, October 1985

     

    [22] North American Electric Reliability Corporation “Winter Reliability Assessment” 2012/2013

     

    [23]     Federal Energy Regulatory Commission “Assessment of Demand Response and Advanced Metering” December 2012

     

    [24]     U. S. Department Of Energy "Benefits Of Demand Response In Electricity Markets And Recommendations For Achieving Them" February 2006

    [25] Daniel E. Olivares, Student Member, IEEE, Claudio A. Caٌizares, Fellow, IEEE and Mehrdad Kazerani, Senior Member, IEEE "A Centralized Energy Management System for Isolated MicroGrids" IEEE Transactions on Smart Grid, Vol.  5, No.  4, July 2014

    [26] H. S. V. S. Kumar Nunna, Suryanarayana Doolla," Energy Management in Microgrids Using Demand Response and Distributed Storage—A Multiagent Approach" IEEE Transactions on Power Delivery, Vol.  28, No.

Energy management in microgrid using load response programs
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