The development and deployment of grid-scale energy storage technologies have increased recently and are expected to grow due to technology improvements and supporting policies. While energy storage can help increase the penetration of renewables, reduce the consumption of fossil fuels, and increase the grid sustainability, its integration into the electric grid poses unique sustainability challenges that need to be investigated through systematic sustainability assessment frameworks. The main objective of this dissertation is to develop principles and models to assess the environmental and economic impacts of grid-scale energy storage and guide its development and deployment. The first study of this dissertation is an initial case study of energy storage to examine the role of cost-effective energy storage in supporting high penetration of wind energy and achieving emissions targets in an off-grid configuration. In this study, the micro-grid system includes wind energy integrated with vanadium redox flow battery (VRFB) as energy storage, and natural gas engine. Life cycle greenhouse gas (GHG) emissions and total cost of delivered electricity are evaluated and generation mixes are optimized to meet emissions targets at the minimum cost. The results demonstrate that while incorporating energy storage consistently reduces life cycle GHG emissions in the system by integrating more wind energy, its integration is cost-effective only under very ambitious emission targets. The insights from this case study and additional literature review led to the development of a set of twelve principles for green energy storage, presented in the second study. These principles are applicable to the wide range of energy storage technologies and grid applications, and are developed to guide the design, maintenance, and operation of energy storage systems for grid applications. The robustness of principles was tested through a comprehensive literature review and also through in-depth quantitative analyses of the VRFB off-grid system. An in-depth parametric analysis is developed in the third study to evaluate the impacts of six key parameters (e.g. energy storage service-life) that influence the environmental performance of six energy storage technologies within three specific grid applications (including time-shifting, frequency regulation, and power reliability). This study reveals that round-trip efficiency and heat rate of charging and displaced generation technologies are dominant parameters in time-shifting and regulation applications, whereas energy storage service life and production burden dominate in power reliability. Finally, an optimization model is developed in the fourth study to examine the real-world application of energy storage in bulk energy time-shifting in California grid under varying renewable penetration levels. The objective was to find the optimal operation and size of energy storage in order to minimize the system total costs (including monetized GHG emissions), while meeting the electricity load and systems constraints. Simulations were run to investigate how the operation of nine distinct storage technologies impacted system cost, given each technology’s characteristics. The results show that increasing the renewable capacity and the emissions tax would make it more cost-effective for energy storage deployment. Among storage technologies, pumped-hydro and compressed-air energy storage with lower capital costs, are deployed in more scenarios. Overall, this research demonstrates how sustainability performance is influenced by storage technology characteristics and the electric grid conditions. The systematic principles, model equations, and optimizations developed in this dissertation provide specific guidance to industry stakeholders on design and deployment choices. The targeted audience ranges from energy storage designers and manufacturers to electric power utilities.