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Optimal pricing strategy in wholesale electricity market using dynamic pso algorithm based on gso

Number of pages: 90 File Format: word File Code: 32145
Year: Not Specified University Degree: Master's degree Category: Electrical Engineering
Tags/Keywords: Algorithm - Electricity industry - Optimal strategy - Power systems - pricing - pso dynamic algorithm - Wholesale electricity market
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  • Summary of Optimal pricing strategy in wholesale electricity market using dynamic pso algorithm based on gso

    Dissertation for Master's degree (M.Sc)

    Electrical field, power trend

    Abstract

    With the restructuring of the electricity industry, the producers of the electricity industry appear as independent entities in the electricity market. In fact, the power plants must supply their produced electricity to the electricity market, and the financial settlement is done through the electricity market. In this research, the issue of optimal pricing strategy for a manufacturer has been raised. The main goal of the problem plan is to obtain the maximum possible profit from the sale of electricity in a period of market implementation. The technical limitations of the power plant, such as the physical limitation of production, the limitation of the rate of output changes, the limitation of the off/on time are also included in the definition of the problem. To consider the strategy of other competitors in the market, the probabilistic model for the market price has also been used. A hybrid algorithm is used to solve the existing optimization problem. The basis of the desired algorithm is PSO, in which the logic of the GSO algorithm is used to improve the efficiency of this algorithm. In the numerical control section, the desired problem has been solved for a sample producer in Iran's electricity market. The results of numerical studies show that the proposed method is able to propose a suitable strategy in the electricity market. In addition, the profit of the generator has been positive in all hours. Also, in the hours when the electricity market price changes were high, the offered prices were lower than the average value, and in the hours when the market price changes were low, the offered prices were higher than the average market price.   

    Keywords: optimal pricing strategy, electricity industry, pso dynamic algorithm

    1- Introduction

    With the development of power systems, environmental and economic considerations on the one hand and the issue of security and the continuity of reliable system work on the other hand, there are challenges for planners. designers and operators of the system. These issues have led researchers to investigate solving these challenges in the electricity industry in recent decades.

    In the past, power systems had a vertical structure[1], which means that the production of electrical energy, its transmission and distribution in an area, was carried out by a control unit. Small and large consumers bought the energy they needed from the government, and the electricity market system was monopolar [2] (monopoly). In fact, the governments managed the electricity market by building small and large power plants in different parts of the country or region and transferring it to the places of consumption and distribution, and they supervised the entire system by a central unit. With the increasing expansion of electrical energy systems and the optimal use of resources, economic competition and environmental restrictions, the trend towards a multipolar (competitive) market developed and the need for it made governments encourage companies and enterprises to invest and participate in the electricity industry. This change in laws and the application of government economic incentives to control the increasing growth of the electricity industry was proposed as deregulation[3].

    This, which leads to the privatization of the electricity industry in the production and sales sectors, took place in Chile in 1982, in Argentina in 1992, and then in the countries of Bolivia, Peru, Guatemala, Colombia, El Salvador, Panama, Brazil, Mexico, Scotland, and Ireland. North, Norway, England, Spain, Holland and parts of the United States of America have been implemented in different ways[1]. By providing better service and cheaper energy, more buyers are attracted, which brings more profit to the supplier, and on the other hand, the buyers also get more benefits. Energy suppliers are brokers [4] who sell energy to customers. Although they may not be producers, they can buy the production share of power plants. This new structure of the power system challenges the concepts of the past. In the past, the focus of research was on the formulation of some practical limitations such as bus voltage range, production limitations, transmission line capacity, possible limitations, environmental considerations and such issues..

    In order to guarantee the free access[5] of suppliers and buyers to the transmission system, the operation of the transmission system requires independence from the market shares[6]. Independent system operators [7] play the role of central coordinator, and fulfill their important responsibility by providing security and reliability of the system. Also, ISO guarantees the quality and security of the system.

    Transmission and distribution environments in competitive systems with open access and the issues related to them are of undeniable importance. In network management structures, whether as a combination of system operator [8] and market operator [9] or as an independent system operator, transmission systems have a special role as energy transmission highways. In the SO+MO system, the management of the competitive market and all matters related to the purchase and sale contracts are separate from the network operator, but in the ISO structure, both of the mentioned items are performed by the independent network operator. 2- The traditional structure of the electricity industry. This industry operated as an integrated monopoly with a vertical structure, and the ownership of all production, transmission and distribution facilities was in the hands of the national or local electricity company, and only this company was allowed to produce, transmit, distribute and sell electricity in its service territory, and was also obliged to meet the needs of all consumers, not necessarily those that make a profit. The operational and business practices of these companies should be in accordance with the guidelines and rules provided by the government supervisors, and the rates of the electricity company should be in accordance with the government regulations.

  • Contents & References of Optimal pricing strategy in wholesale electricity market using dynamic pso algorithm based on gso

    List:

    Abstract 1

    Chapter One: Introduction to the process of restructuring and electricity market

    1-1- Introduction. 3

    1-2- The traditional structure of the electricity industry. 5

    1-2-1- Criteria of the traditional structure of the electricity industry. 6

    1-3- Restructuring in the electricity industry. 7

    1-3-1- Incentives for the restructuring of the electricity industry. 7

    1-3-2- Factors affecting the restructuring process. 8

    1-3-3- executive models in the modern structure of the electricity industry. 9

    1-3-3-1- vertical integrated monopoly model. 9

    1-3-3-2- buyer monopoly model. 9

    1-3-3-3- Competition in the wholesale market. 10

    1-3-3-4- model of full customer discretion in choosing the electricity supplier. 10

    1-4- The eight stages of restructuring in the electricity industry. 11

    1-4-1- Isolation and segregation of the traditional structure. 11

    1-4-2- Restructuring and creating the electricity wholesale market. 12

    1-4-3- Ensuring access to the transmission network and open access. 13

    1-5- secondary stages in the modern structure of the electricity industry. 15

    1-5-1- Risk management 15

    1-5-2- Congestion management. 15

    1-5-3- Development planning. 15

    1-5-4- Ancillary services. 16

    1-5-5- open and simultaneous information system. 17

    1-6- The process of restructuring in other countries 17

    1-6-1- Restructuring in the electricity industry of California 18

    1-6-2- Restructuring in the electricity industry of South Africa. 19

    1-6-3- Restructuring in Turkish electricity industry. 19

    1-6-4- Restructuring in the electricity industry of Kazakhstan 20

    1-6-5- The process of restructuring in Iran. 20

    1-6-6- Characteristics of Iran's electricity market. 21

    1-6-7- Pillars of Iran's electricity market. 22

    Chapter Two: Review of articles presented in the field of optimal pricing proposal

    2-1- Introduction. 25

    2-2- review of articles. 25

    2-3- Comparison of articles in terms of mathematical definition and problem solving method. 32

    Chapter three: Defining the problem of optimal pricing strategy conceptually and mathematically

    3-1- Introduction. 35

    3-2- Classification of articles. 35

    3-3- Expressing the problem conceptually. 37

    3-3-1 unknowns of the problem (control variables of the problem). 38

    3-3-2- Objective function of the problem. 39

    3-3-3- Limitations of the problem. 39

    3-4- Including other players' strategy changes in the market price. 41

    3-5- Selecting the market execution model. 43

    3-6- Defining the problem as an optimization problem. 43

    3-6-1- Objective function. 43

    3-6-2- Restrictions. 45

    3-6-2-1- The limitation of generators production 45

    3-6-2-2- The stipulation of the minimum time of generators being off and on 45

    3-6-2-3- The stipulation related to the rate of output changes. 46

    Chapter four: Introduction of GSO-based pso algorithm

    4-1- Particle community optimization method. 48

    4-2- Basic PSO method. 48

    4-2-1 background. 48

    4-3- Basic PSO. 49

    4-4- Discrete PSO. 53

    4-5- PSO algorithm based on GSO. 54

    4-6- fitness function. 55

    4-6-1- considering the restrictions. 55

    Chapter Five: Numerical Studies

    5-1- Introducing the manufacturer 57

    5-2- Study results. 57

    5-3- Comparing the performance of the desired algorithm with the PSO algorithm. 70

    Chapter Six: Summary and Conclusion

    6-1- Conclusion. 72

    Resources and sources. 73

    English abstract. 76

     

     

    Source:

     

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    [2] Ghahrani, Siamak. 1382. Restructuring literature and types of ISO. A series of specialized seminars on the electricity market, Khuzestan region electricity company. [3] System studies research group. 2013. Restructuring of electricity industry in the world. The first and second volumes, the report of the first stage of the project "Investigation and research regarding restructuring in the electricity industry", pages 2 to 20 of the Electricity Research Institute, Niro Research Institute.

    [19] Lajordi, Hassan. 2012. Restructuring steps in the electricity industry. The series of specialized seminars of the electricity market, Khuzestan region electricity company.

    [5] System studies research group. 1380. Risk management and impact of contracts. The report of the second stage of the project "Investigation and research regarding the restructuring in the electricity industry", pages 9-30, Electricity Research Institute, Power Research Institute.

    [6] System Studies Research Group. 1380. Review and study of ancillary services. Step report. Report of the fifth stage of the project, "Investigation and research regarding restructuring in the electricity industry", pages 82 to 104, Electricity Research Institute, Power Research Institute.

    [7] System Studies Research Group. 1380. Review and study of system operator. The report of the second phase of the project "Investigation and research regarding restructuring in the electricity industry", Research Institute of Electricity, Research Institute of Power.

    [8] Mohammad Shahidehpour, Hatim Yamin, Zuyi Li, 2002. Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Managementg, John Wiley & Sons.

    [9] Lewington Ilka, Petrov Konstantin. 2005. Power Sector Restructuring, KEMA Consulting(ECC), JANUARY (Day 3).

    [10] Bureau of Economic Surveys and Export Development. 2016. South African market analysis. Vice President of Planning and Economic Affairs, Ministry of Energy.

    [11] Bureau of regulation and development of competition in the water and electricity market. 2017. Privatization strategy and restructuring of Turkish electricity sector. Group of Privatization and Implementation of Principal 44 Policies.

    [12] Summary of the World Bank report on Iran's electricity industry. Ministry of Energy, from the site http://www.moe.org.ir

    [13] Regulations for determining the method. 1382. Rates and terms of buying and selling electricity in the country's electricity network. [14] Deputy Planning. Additional services. Iran Electric Network Management Company, from the website http://www.igmc.ir.

    [15] Iran's Economic Survey and Export Development Office. 2016. Analysis of Kazakhstan's electricity market. Vice President of Planning and Economic Affairs, Ministry of Energy. [16] Shangyou Hao, 2000. A Study of Basic Bidding Strategy in Clearing Pricing Auctions, IEEE transactions on power systems, vol. 15, no. 3.

    [17] Fushuan Wen and A. Kumar David, 2001. Optimal Bidding Strategies and Modeling of Imperfect Information Among Competitive Generators, IEEE transactions on power systems, vol. 16, no. 1, February.

    [18] Li Yang, Fushuan Wen, Development of bidding strategies in electricity markets using possibility theory.

    [19] Antonio J. Conejo, Francisco Javier Nogales, and José Manuel Arroyo, 2002. Price-Taker Bidding Strategy Under Price Uncertainty, IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 17, NO. 4.

    [20] Vasileios P. Gountis, and Anastasios G. Bakirtzis. 2004. Bidding Strategies for Electricity Producers in a Competitive Electricity Marketplace. IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 19, NO. 1.

    [21] Ning Lu, Joe H. Chow, and Alan A. Desrochers, Pumped-Storage Hydro-Turbine Bidding Strategies in a Competitive Electricity Market.

    [22] Li Ma, Fushuan Wen, Optimal Bidding Strategies for Generation Companies in Electricity Markets with Transmission Capacity Constraints Taken into Account.

    [23] Claudia P. Rodriguez, George J. Anders. 2004. Bidding Strategy Design for Different Types of Electric Power Market Participants. IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 19, NO. 2.

    [24] Tao Li, Mohammad Shahidehpour 2005. Strategic Bidding of Transmission-Constrained

    GENCOs with Incomplete Information, IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 20, NO. 1.

    [25] Hui Niu, Ross Baldick, Guidong Zhu 2005. Supply Function Equilibrium Bidding Strategies With Fixed Forward Contracts IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 20, NO. 4.

    [26] Daniel Kirschen, Goran Strbac, 2004. Fundamentals of Power System Economics. University of Manchester Institute of Science & Technology (UMIST), UK, Copyright John Wiley & Sons, Ltd

    ]27[ Ansari, Maitham., Mojtaba Shiwai. and Mohammad Sadiq Ghazizadeh. 2019. Modeling competitive electricity markets and evaluating its parameters based on the visibility of market players' information. 25th International Electricity Conference, Power Research Institute.

    [28] Mohammadshahidehpur, Hatimyamin, Zuyi Li. 2002. Market Operation in Electric Power Systems. Copyright by John Wiley & Sons

    [29] Allen J. Wood, Bruce F. Wollenberg. Power Generation, Operation, And Control. Copyright by John Wiley & Sons. [30]. Kennedy J, Eberhart R. Particle swarm optimization. 1995. Proceedings of IEEE International Conference on Neural Networks (ICNN'95) Perth, Australia: IEEE Press; 1995. Vol. IV. p. 1942–1948.

Optimal pricing strategy in wholesale electricity market using dynamic pso algorithm based on gso
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