A multi-attribute congestion-driven approach for evaluation of power generation plans

Summary Independent System Operator (ISO) needs to draw sufficient attention to transmission congestion management (TCM) for guaranteeing power system security when deciding about a proposed power generation plan (PGP). To this end, this paper proposes a multi-attribute decision-making approach. The proposed decision-making procedure for a considered PGP includes three major stages: (1) Obtaining different attributes of TCM for all considered scenarios, i.e. the normal operating case and contingencies due to outage of power system components before and after implementation of the PGP. (2) Identifying the effective scenarios before and after the implementation of the PGP. For this purpose, two multi-attribute decision-making approaches are applied, one of which ISO could adopt based on its managerial point of view: (a) A conjunctive approach in which scenarios meeting minimal predefined thresholds for their obtained TCM attributes are selected. (b) A pessimistic approach based on data envelopment analysis introduced by Charnes, Cooper, and Rhodes (CCR-DEA) in which the severest scenarios are selected. 3) Calculating each scenario's Degree of Severity (DOS) using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and comparing sum of the DOS of the effective scenarios before and after the implementation of the PGP. For an acceptable PGP, sum of effective scenarios' DOS after implementation of the PGP should be less than that of before. The proposed procedure is applied to the IEEE Reliability Test System (RTS) and the results are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

[1]  Yong Shi,et al.  Induced Arithmetic Average Bias Matrix Model (IAABMM) , 2013 .

[2]  M.M.A. Salama,et al.  Identify the impact of distributed resources on congestion management , 2005, IEEE Transactions on Power Delivery.

[3]  E. Stanley Lee,et al.  An extension of TOPSIS for group decision making , 2007, Math. Comput. Model..

[4]  Jose L. Ceciliano Meza,et al.  A Model for the Multiperiod Multiobjective Power Generation Expansion Problem , 2007, IEEE Transactions on Power Systems.

[5]  W. Cooper,et al.  Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software , 1999 .

[6]  J. Driesen,et al.  Influences of large penetration of distributed generation on N-1 safety operation , 2004, IEEE Power Engineering Society General Meeting, 2004..

[7]  Nima Amjady,et al.  A scenario-based multiobjective operation of electricity markets enhancing transient stability , 2012 .

[8]  Naresh Acharya,et al.  Locating series FACTS devices for congestion management in deregulated electricity markets , 2007 .

[9]  János Fülöp,et al.  Introduction to decision making methods.(Working paper of the Laboratory of Operations Research and Decision Systems. (LORDS)WP05-6.) , 2005 .

[10]  Manjaree Pandit,et al.  ANN based integrated security assessment of power system using parallel computing , 2012, International Journal of Electrical Power & Energy Systems.

[11]  A. J. Conejo,et al.  Strategic Generation Investment Under Uncertainty Via Benders Decomposition , 2012, IEEE Transactions on Power Systems.

[12]  Minghai Liu,et al.  Application of substitutability in congestion relief , 2010 .

[13]  A. Conejo,et al.  Strategic Generation Investment Using a Complementarity Approach , 2011, IEEE Transactions on Power Systems.

[14]  S. Dutta,et al.  Optimal Rescheduling of Generators for Congestion Management Based on Particle Swarm Optimization , 2008, IEEE Transactions on Power Systems.

[15]  Antonio J. Conejo,et al.  Multiperiod auction for a pool-based electricity market , 2002 .

[16]  Jamshid Aghaei,et al.  Generation Expansion Planning in pool market: A hybrid modified game theory and improved genetic algorithm , 2009 .

[17]  Gyutai Kim,et al.  Identifying investment opportunities for advanced manufacturing systems with comparative-integrated performance measurement , 1997 .

[18]  Masoud Rashidinejad,et al.  Distributed generation placement for congestion management considering economic and financial issues , 2010 .

[19]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[20]  David W. Coit,et al.  Multi-period multi-objective electricity generation expansion planning problem with Monte-Carlo simulation , 2010 .

[21]  A.J. Conejo,et al.  Congestion management ensuring voltage stability , 2008, IEEE Transactions on Power Systems.

[22]  Mohammad Shahidehpour,et al.  The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee , 1999 .

[23]  Mohammad Hossein Javidi,et al.  Coordinated decisions for transmission and generation expansion planning in electricity markets , 2013 .

[24]  F. Schneider Multiple Criteria Decision Making in Application Layer Networks , 2010 .

[25]  M. Shahidehpour,et al.  Security-Constrained Resource Planning in Electricity Markets , 2007, IEEE Transactions on Power Systems.

[26]  John S. Liu,et al.  Data envelopment analysis 1978-2010: A citation-based literature survey , 2013 .

[27]  George Mavrotas,et al.  Power generation expansion planning in an autonomous island system using multi-objective programming: the case of Milos Island , 2010, Oper. Res..

[28]  Nima Amjady,et al.  Multi-objective market clearing of joint energy and reserves auctions ensuring power system security , 2009 .

[29]  M. Shahidehpour,et al.  Market-Based Generation and Transmission Planning With Uncertainties , 2009, IEEE Transactions on Power Systems.

[30]  Jamshid Aghaei,et al.  Generation expansion planning in Pool market: A hybrid modified game theory and particle swarm optimization , 2011 .

[31]  P. Murugan,et al.  Solutions to transmission constrained generation expansion planning using differential evolution , 2009 .

[32]  Jamshid Aghaei,et al.  Reliability constrained multi-period generation expansion planning of electrical energy resources using MILP , 2013 .

[33]  S. Baskar,et al.  Application and comparison of metaheuristic techniques to generation expansion planning in the partially deregulated environment , 2007 .

[34]  Ching-Lai Hwang,et al.  Multiple attribute decision making : an introduction , 1995 .

[35]  Alexander Zerrahn,et al.  The benefit of coordinating congestion management in Germany , 2013, 2013 10th International Conference on the European Energy Market (EEM).

[36]  S. Grijalva,et al.  Assessment of distributed generation programs based on transmission security benefits , 2005, IEEE Power Engineering Society General Meeting, 2005.

[37]  J.A. Momoh,et al.  An approach to determine Distributed Generation (DG) benefits in power networks , 2008, 2008 40th North American Power Symposium.

[38]  Abit Balin,et al.  Fuzzy multicriteria selection among cogeneration systems: A real case application , 2013 .

[39]  S. Baskar,et al.  Application of NSGA-II Algorithm to Generation Expansion Planning , 2009, IEEE Transactions on Power Systems.

[40]  Luis G. Vargas,et al.  How to Make A Decision , 2012 .

[41]  Taher Niknam,et al.  Scenario-based dynamic economic emission dispatch considering load and wind power uncertainties , 2013 .