Abstract: Systems and method for optimal control of one or more energy storage systems are provided. Based on live, historical, and/or forecast data received from one or more data sources, one or more forecasts of one or more parameters relating to the operation of the one or more energy storage systems and an associated forecast uncertainty may be calculated by various forecasting techniques. Using one or more optimization techniques, an optimal dispatch schedule for the operation of the one or more energy storage systems may be created based on the forecasts. The optimal dispatch schedule may be used to determine one or more energy storage system parameters, which are used to control the operation of the energy storage systems.

Abstract: Systems and methods for optimal control of one or more energy storage systems are provided. Based on live, historical, and/or forecast data received from one or more data sources, one or more forecasts of one or more parameters relating to the operation of the one or more energy storage systems and an associated forecast uncertainty may be calculated by various forecasting techniques. Using one or more optimization techniques, an optimal dispatch schedule for the operation of the one or more energy storage systems may be created based on the forecasts. The optimal dispatch schedule may be used to determine one or more energy storage system parameters, which are used to control the operation of the energy storage systems.

Abstract: Systems and methods for optimal planning and real-time control of energy storage systems for multiple simultaneous applications are provided. Energy storage applications can be analyzed for relevant metrics such as profitability and impact on the functionality of the electric grid, subject to system-wide and energy storage hardware constraints. The optimal amount of storage capacity and the optimal operating strategy can then be derived for each application and be prioritized according to a dispatch stack, which can be statically or dynamically updated according to data forecasts. Embodiments can consist of both planning tools and real-time control algorithms.

Abstract: Systems and methods for optimal planning and real-time control of energy storage systems for multiple simultaneous applications are provided. Energy storage applications can be analyzed for relevant metrics such as profitability and impact on the functionality of the electric grid, subject to system-wide and energy storage hardware constraints. The optimal amount of storage capacity and the optimal operating strategy can then be derived for each application and be prioritized according to a dispatch stack, which can be statically or dynamically updated according to data forecasts. Embodiments can consist of both planning tools and real-time control algorithms.

Abstract: Systems and methods for optimal planning and real-time control of energy storage systems for multiple simultaneous applications are provided. Energy storage applications can be analyzed for relevant metrics such as profitability and impact on the functionality of the electric grid, subject to system-wide and energy storage hardware constraints. The optimal amount of storage capacity and the optimal operating strategy can then be derived for each application and be prioritized according to a dispatch stack, which can be statically or dynamically updated according to data forecasts. Embodiments can consist of both planning tools and real-time control algorithms.

Abstract: Systems and methods for optimal planning and real-time control of energy storage systems for multiple simultaneous applications are provided. Energy storage applications can be analyzed for relevant metrics such as profitability and impact on the functionality of the electric grid, subject to system-wide and energy storage hardware constraints. The optimal amount of storage capacity and the optimal operating strategy can then be derived for each application and be prioritized according to a dispatch stack, which can be statically or dynamically updated according to data forecasts. Embodiments can consist of both planning tools and real-time control algorithms.

Abstract: Systems and methods for optimal planning and real-time control of energy storage systems for multiple simultaneous applications are provided. Energy storage applications can be analyzed for relevant metrics such as profitability and impact on the functionality of the electric grid, subject to system-wide and energy storage hardware constraints. The optimal amount of storage capacity and the optimal operating strategy can then be derived for each application and be prioritized according to a dispatch stack, which can be statically or dynamically updated according to data forecasts. Embodiments can consist of both planning tools and real-time control algorithms.