Assessment of a Genetic Algorithm Based Security Constrained Economic Dispatch Approach for LMP Calculation

Abstract

To address transmission issues and generate correct economic signals in restructured electricity markets, an effective transmission pricing method is required. Transmission line constraints can cause energy prices to fluctuate across the network. These prices are determined by generator bids, load levels, and transmission network constraints. Locational Marginal Pricing (LMP) is a popular method for identifying nodal prices and managing transmission congestion in the energy market.   This chapter gives a Genetic Algorithm (GA)-based security constrained economic dispatch (SCED) approach for evaluating LMPs at all buses while minimizing total system fuel cost for a constrained transmission system, both with and without system losses. The proposed GA-based SCED approach is used on the EEE 14 bus system, the 75-bus Indian power system, and the New England 39-bus system. Using Power World Simulator, the obtained results are compared to conventional Linear Programming-based DCOPF. For generators, both fixed and linear bids are considered. It is assumed that the load is inelastic.  The proposed GA-based SCED for LMP calculation has been shown to be very simple, reliable, and efficient in all of the cases studied. Furthermore, optimal redispatch of generators using GA results in an overall reduction in generation fuel cost.