Stochastic scheduling of compressed air energy storage in DC SCUC framework for high wind penetration

Abstract

High intermittent wind generation necessitates integration of bulk energy storage systems (ESSs) for maintaining security and reliability in power system operation. Considering this, stochastic security constrained unit commitment (SCUC) including compressed air energy storage (CAES) as bulk ESS for high wind penetration and with wind uncertainty modelling is addressed. Network constraints for pre- and post-line contingency are modelled using DC power flow. Injection sensitivity factors (ISFs) are conventionally used in power flow equations which, however, make N -1 network security constrained formulation huge and computationally demanding for the proposed stochastic model. Therefore, this study proposes a line outage distribution factor (LODF) to reduce the number of coefficients of post contingency DC power flow equations. This is a compact formulation with the lower computational requirement. Wind uncertainty is modelled as probable scenarios. The proposed SCUC is a complex mixed integer linear programming problem and solved using Benders decomposition technique for IEEE 30-bus and 118-bus system. Simulation results to analyse the impact of CAES, wind uncertainty and line contingency with ISF and LODF on overall operation costs, CAES scheduling, wind curtailment, locational marginal price and computational time. Results show that the proposed model is computationally efficient for system operation under high wind penetration.