Efficient sensitivity based assessment of impact of uncertainties in multi-objective framework

This paper presents a novel Primal–Dual Interior Point Method (PDIPM) based sensitivity approach for efficient assessment of the impact of uncertainties in Multi-objective Optimization (MO). This shall aid in robust decision making. The MO problem considered, in this paper, is the Environmental–Economic dispatch (EED) problem. The two objectives, i.e. the emission and economic cost, are continuous convex functions. The uncertainties in the system parameters such as loads (or injections) and limits on line flows and voltage magnitudes, are assumed to be of fuzzy type, more specifically in an interval. Results for the IEEE 30 bus system have been obtained using the proposed approach and compared with those obtained by Monte Carlo Simulations (MCS) and Particle Swarm Optimization (PSO) based on Harmony Search (HSPSO). The results obtained provide interesting insights on how uncertainties in input data can affect decision making in MO.