Probabilistic SCUC Considering Implication of ‎Compressed Air Energy Storage on Redressing Intermittent Load and Stochastic Wind Generation

Abstract

There are various sources of uncertainty in power systems. Solar and wind forecasting inaccuracies, price forecasting errors, load and demand response forecasting volatilities are some types of uncertainty. In addition, the possibility of outage of power system components such as lines, generating units, and loads can deteriorate the operation condition and compromise the security of power system. Hence, in order to reach a more secure operation, the uncertainties must be included in the scheduling to enhance the robustness and resiliency of power system against possible imbalances and contingencies. The inclusion of probabilistic concepts into the security-constrained unit commitment (SCUC) makes the solution of this problem more complex. However, incorporation of them into the SCUC ensures the secure operation of the power system and inhibits drastic detriments. Furthermore, the compressed air energy storage (CAES) technology is utilized to mitigate the intermittencies and uncertainties. The uncertainties are modeled by using scenario generation techniques. The simulation of a large number of stochastic scenarios considering a variety of uncertainties inclines the results to the most probable condition of realization. The results show that even though the stochastic approaches have higher operational cost but it maintains the security of the system for withstanding against plausible uncertainties and contingencies, which may occur due to whether inaccurate forecasting and consequently inappropriate scheduling or maintaining inadequate generation reserve or transmission capacity. In addition, the integration of CAES units has diminished the total cost of operation and has improved the penetration of renewable resources regard to the congestion of the system, especially at peak hours.