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

In restructured electricity markets, an effective transmission pricing method is required to address transmission issues and to generate correct economic signals. Transmission line constraints can result in variations in energy prices throughout the network. These prices depend on generator bids, load levels and transmission network limitations. Locational Marginal Pricing (LMP) is a dominant approach in energy market operation and planning to identify nodal prices and manage transmission congestion. This paper presents a Genetic Algorithm (GA) based security constrained economic dispatch (SCED) approach to evaluate LMP’s at all buses while minimizing total system fuel cost for a constrained transmission system, with and without considering system losses. The proposed GA based SCED approach is applied to EEE 14 bus, 75 bus Indian power system and New England 39 bus system. The results obtained are compared with conventional Linear Programming based DCOPF using Power World Simulator. Both fixed and linear bids are considered for generators. The load is assumed to be inelastic. The proposed GA based SCED for LMP calculation is proved to be very simple, reliable and efficient in all the studied cases. Further, the optimal redispatch of generators using GA leads to overall reduction in generation fuel cost.