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Virtual power plant (VPP) provides a flexible solution to distributed energy resources integration by aggregating renewable generation units, conventional power plants, energy storages, and flexible demands. This paper proposes a novel model for determining the optimal offering strategy in the day-ahead energy-reserve market and the optimal selfscheduling plan. It considers exogenous uncertainties (or called decision-independent uncertainties, DIUs) associated with market clearing prices and available wind power generation, as well as the endogenous uncertainties (or called decision-dependent uncertainties, DDUs) pertaining to real-time reserve deployment requests. A tractable solution method based on strong duality theory, McCormick relaxation, and the Benders' decomposition to solve the proposed stochastic adaptive robust optimization with DDUs formulation is developed. Simulation results demonstrate the applicability of the proposed approach.

Grid-side electrochemical battery energy storage systems (BESS) have been increasingly deployed as a fast and flexible solution to promoting renewable energy resources penetration. However, high investment cost and revenue risk greatly restrict its grid-scale applications. As one of the key factors that affect investment cost, the cycle life of battery heavily depends on its charging/discharging actions during the operation, particularly in the presence of uncertain renewable generation. In this context, it is necessary to consider the operation-dependent cycle life of batteries in optimal BESS sizing, which imposes great challenges to the modeling and solving of the planning problems. In this paper, we propose a novel two-level optimal sizing model for grid-scale BESS, considering its operation under uncertainties induced by volatile wind generation. In the lower level, a long-term chronological operation simulation of BESS is processed with an accurate cycle life model of batteries; in the upper level, marginal economic utility analysis and BESS size reforming are conducted to approach the optimal size of BESS. An iterative algorithm is designed to solve the model effectively. The proposed method is verified on a modified IEEE RTS-24 system and a real provincial power grid of China. INDEX TERMS battery energy storage, optimal sizing, cycle life, marginal utility analysis I. INTRODUCTION A. BACKGROUND VOLUME 4, 2016 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

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