A multiyear dynamic transmission expansion planning model using a discrete based EPSO approach

This paper presents a multiyear dynamic transmission expansion planning, TEP, model aiming at minimizing operation and investment costs along the entire planning horizon while ensuring an adequate quality of service and enforcing constraints modeling the operation of the network along the planning horizon. The developed model profits from the experience of planners when preparing a list of possible branch (lines and transformers) additions each of them associated to the corresponding investment cost. The objective of solving a TEP problem is to select a number of elements of this list and provide its scheduling along the planning horizon such that one is facing a mixed integer optimization problem. In this case, this problem was solved using a discrete evolutionary particle swarm optimization algorithm, DEPSO, based on already reported EPSO approaches but particularly suited to treat discrete problems. Apart from detailing the developed DEPSO, this paper describes the mathematical formulation of the TEP problem and the adopted solution algorithm. It also includes results of the application of the DEPSO to the TEP problem using two test networks widely used by other researchers on this area.

► Mixed integer optimization model of the transmission expansion planning, TEP, problem.
► Dynamic multiperiod TEP model.
► Consideration of penalties over excessive losses and non-zero PNS for N − 1 contingencies.
► Enhancement of the EPSO algorithm, to accommodate discrete variables, DEPSO.
► Application of the developed tool to Case Studies.