Generation expansion planning with power flow constraints – Evolutionary strategy approach

This paper presents the application of an Improved Evolutionary Strategy (IES) to least cost Generation Expansion Planning (GEP) problem with transmission line flow and location of the generating units as constraints. Optimal Power Flow (OPF) algorithm is used to check transmission line flow constraint. Least cost GEP is a non-linear combinatorial optimization problem with several constraints. Several conventional non-linear optimization methods have been used to solve the GEP problem. These methods may fail to give global optima due to handling of discrete variables in the constraints. Recently Evolutionary Computation (EC) techniques are used to solve the combinatorial optimization GEP problems, due to global search characteristic. In this paper Dynamic Programming (DP), Tunnel Constrained Dynamic Programming (TCDP) and IES methods are applied to solve the GEP problem for a modified IEEE-30 bus system with 6 years planning horizon. The cost comparison between simple GEP and GEP with transmission line flow constraints using DP, TCDP and IES are also illustrated.