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specialty journal of electronic and computer sciences
Volume 5, 2019, Issue 1
Electricity Market Planning by capacity collusion of ‎Distribution considering Fuzzy Theory
Seyed Mostafa Tabatabaei, Mehrdad Setayesh Nazar
Pages: 41-57

Abstract

In recent decades, with the orientation of the power network ‎towards changing and re-structuring in the market and industry ‎mechanisms,‎‏ ‏Reactive power services are independent of other ‎services as one of the topics of investment for different ‎companies.‎ As a result of these changes, the creation of an efficient model ‎that covers more sections of the problem of reactive power ‎planning,‎‏ ‏One of the most important principles of reactive ‎power planning.‎ For this reason, in this paper, the modeling of reactive power ‎planning in order to reduce network losses,‎‏  ‏Increasing voltage ‎stability, increasing network reliability and reducing investment ‎costs are considered as an opposite multi-goal problem.‎ The reason for the contradiction is because of the different ‎nature of the cost function, the loss, and the voltage‏ ‏You can not ‎summarize all of these parameters in an objective function.‎‏ ‏The ‎motivation for this article is to find an appropriate market ‎approach and regulatory approach The management of reactive ‎power is a long-term and non-linear problem in the studied ‎system.‎ A market design is proposed in which all available sources of ‎reactive power are considered for participation.‎‏ ‏To solve the ‎proposed problem, a multi-objective honey bee mating method ‎‎(HBMO) has been used based on chaos theory.‎‏ ‏Also, the ‎nonlinear sorting system and fuzzy mechanism are used to ‎determine the best solution based on the set of solutions ‎generated from the Pareto space.‎ The proposed method has been discussed on various systems and ‎the results have been compared with other methods.‎‏ ‏Finding the ‎right answer, upgrading the best answer, and intersection of the ‎generations are the hallmarks of this method‎.



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specialty journal of electronic and computer sciences
Issue 1, Volume 7, 2021