Stochastic scheduling of battery energy storage system for large-scale wind power penetration

Abstract

High penetrations of wind generation have intermittency and volatility issues in deregulated power system. With increasing penetration of wind power, independent system operator (ISO) faces an enormous challenge in secure operation with intermittency and uncertainty of renewable energy resources. To handle these issues, battery energy storage system (BESS) is a probable solution for enhancing the wind penetration in the electric grid. In this regard, this article proposes a stochastic security constrained unit commitment (SCUC) with BESS considering wind uncertainty. The proposed approach is formulated and solved by Benders decomposition (BD) method which reduces computational time. The goal is to detect the optimal amount of SCUC, locational marginal price (LMP), wind curtailment, and line contingency by performing DC optimal power flow (DCOPF). Numerical case studies are investigated in detail using IEEE Reliability test system (RTS) 24-bus network and simulation results are found to be inspiring.

Keywords

• pricing
• power generation economics
• power system security
• wind power plants
• probability
• power generation scheduling
• load flow
• power generation dispatch
• power markets
• battery storage plants
• stochastic processes
• power grids
• wind uncertainty
• wind curtailment
• dc optimal power flow
• stochastic scheduling
• battery energy storage system
• large-scale wind power penetration
• wind generation
• deregulated power system
• independent system operator
• renewable energy resources
• bess
• wind penetration
• stochastic security constrained unit commitment
• electric grid
• scuc
• benders decomposition method
• bd method
• locational marginal price
• lmp
• line contingency
• dcopf
• ieee reliability test system 24-bus network