Risk Assessment with Generic Energy Storage under Exogenous and Endogenous Uncertainty

TL;DR

This paper introduces a probabilistic model for generic energy storage that accounts for both external and internal uncertainties, highlighting the importance of considering endogenous uncertainty in risk assessment for energy systems.

Contribution

It redefines generic energy storage to include probabilistic reserves and develops a data-driven model incorporating exogenous and endogenous uncertainties for improved risk evaluation.

Findings

Endogenous uncertainty increases risk compared to exogenous uncertainty.

Distribution system risk is higher when considering endogenous uncertainty.

System operators should adopt new strategies to manage endogenous uncertainty.

Abstract

Current risk assessment ignores the stochastic nature of energy storage availability itself and thus lead to potential risk during operation. This paper proposes the redefinition of generic energy storage (GES) that is allowed to offer probabilistic reserve. A data-driven unified model with exogenous and endogenous uncertainty (EXU & EDU) description is presented for four typical types of GES. Moreover, risk indices are proposed to assess the impact of overlooking (EXU & EDU) of GES. Comparative results between EXU & EDU are illustrated in distribution system with day-ahead chance-constrained optimization (CCO) and more severe risks are observed for the latter, which indicate that system operator (SO) should adopt novel strategies for EDU uncertainty.