Cost analysis of a power system using probabilistic optimal power flow with energy storage integration and wind generation

This paper examines the storage application and its optimal placement for the social cost and transmission congestion relief of wind integration. Probability density functions (PDFs) are used to characterize the uncertainties of wind speed and load. A probabilistic optimal power flow (POPF) is developed using two-point estimation which incorporates the storage system either as a variable load or as a variable generator. Storage systems are optimally placed and adequately sized using a particle swarm optimization (PSO) to minimize the sum of operation and congestion costs over a scheduling period. A technical assessment framework is developed to enhance the efficiency of wind integration and evaluate the economics of storage technologies and conventional gas-fired alternatives. The proposed method is used to carry out a cost-benefit analysis for the IEEE 24-bus system and determine the most economical technology. Optimal storage distribution and its potential to relieve the transmission congestion are evaluated for higher wind penetration levels.