Comparison of conventional and meta-heuristic methods for security-constrained OPF analysis

Development and implementation of accurate, robust and computationally efficient analytical and modelling tolls is very important for the anticipated transformation of existing networks into the future "smart grids". These tools for network analysis are used at both planning and operating stages, in order to ensure optimal design and configuration of power supply systems, in terms of the requirements for higher flexibility, increased security and improved overall techno-economic performance of modelled networks. In this context, particularly important are "smart grid" applications requiring (close to) real-time controls of large and interconnected power supply systems under serious contingency scenarios and other "highly stressed" network operating conditions. This paper provides a detailed discussion and analysis of both conventional and meta-heuristic methods for security-constrained optimal power flow (SCOPF) studies. The comparison of performance of two conventional SCOPF methods and three meta-heuristic SCOPF algorithms is illustrated on IEEE 14-bus and IEEE 30-bus test networks. The analysis and optimization of objective functions in considered SCOPF methods include minimization of constraint violations in post-contingency states, as well as minimization of fuel costs, active power losses, and CO2 emissions.