Keywords: dynamic programming, TEP, NSGAII, fuzzy decision.

Introduction

Transmission Expansion Planning (TEP) is one of the main parts of planning development power systems aiming at identifying time, place and number of new transmission lines to optimize construction cost and efficiency of these lines In order to achieve the adequacy of the power to the centers of load. TEP is usually classified into dynamic and static. In static planning the number and spots of needed power lines are determined for one year, while in dynamic planning, the needed construction time is also considered  \cite{Latorre_2003}. TEP is a nonlinear and complex problem one which is getting more complicated by increasing of the studied network scale. It was started by L. L. Grinver in 1970 to minimize efficiency cost and taking account generation constraints of power plants and power lines capacity using linear planning  \cite{Risheng_Fang_2003} . But in the recent year, most studies have been done on reconstructed power systems. The major difference between the TEPs in exclusive and competitive environments is that the main problem in exclusive environments include generation, transmission, and distribution all together while in competitive environments these sections are considered separately \cite{styczynski1999,shahidehpour2002}. Another important difference is that unlike exclusive environments which mostly include definite data, competitive environments include uncertainty data as a main parameter \cite{Tor_2008,de_J_Silva_2005}. Objective function of exclusive environment is based on minimal cost while in competitive environment the objective function is maximum profit. Also, TEP solutions in competitive and traditional environments are classified into innovative optimization such as linear programming \cite{de_J_Silva_2005}, dynamic programming \cite{Alguacil_2003}, nonlinear programming \cite{kalyanmoy2003} in mathematical optimization and mathematical methods such as genetic algorithm \cite{Kim_1988}, objective-oriented models \cite{Xie_2007}, metal plating \cite{Romero_1996}, expert systems \cite{Teive_1998} and fuzzy theory \cite{Hongsik_Kim}.
The purpose of this paper is to study the effects of distributed generation on TEP in reconstructed environments. Since there is no contribution between generation companies and transmission companies in reconstructed environments, TEP needs to predict producers' behaviors. In this study, generation valuing method was used to predict producers' behaviors and planning was researched using dynamic approach in a five-year period. Moreover, the effects of distributed generation of windy and solar powers on TEP in reconstructed environments are considered. The rest of the paper is organized as follows: market exploitation model is introduced in section 2. Problem formulation and planning indexes is discussed in section 3. Simulation results and conclusion have been presented in section 4 and section 5.