Renewable energy resources like wind generation are being rapidly integrated into modern power systems. Energy storage systems (ESS) are being viewed as a game-changer for renewable integration due to their ability to absorb the variability and uncertainty arising from the wind generation. While abundant literature is available on system adequacy and operational reliability evaluation, operational adequacy studies considering wind and energy storage have received very little attention, despite their elevated significance. This work presents a novel framework that integrates wind power and energy storage models to a bulk power system model to sequentially evaluate the operational adequacy in the operational mission time. The analytical models are developed using a dynamic system state probability evaluation approach by incorporating a system state probability estimation technique, wind power probability distribution, state enumeration, state transition matrix, and time series analysis in order to quantify the operational adequacy of a bulk power system integrated with wind power and ESS. The loss of load probability (LOLP) is used as the operational adequacy index to quantify the spatio-temporal variation in risk resulting from the generation and load variations, their distribution on the network structure, and the operational strategies of the integrated ESS. The proposed framework is aimed to serve as a guideline for operational planning, thereby simplifying the decision-making process for system operators while considering resources like wind and energy storage facilities. The methodology is applied to a test system to quantify the reliability and economic benefits accrued from different operational strategies of energy storage in response to wind generation and other operational objectives in different system scenarios.
An Improved Integrated Cumulant Method by Probability Distribution Pre-identification in Power System with Wind Generation
