Abstract: In an embodiment, a method comprises: obtaining input data including a plurality of parameters related to an energy system design; reducing the input data to a subset of the input data; in a first stage: feeding the subset of input data into a reduced version of a model for estimating an energy system configuration; estimating, using the reduced version of the model, a first energy system configuration and a lower bound solution for the first energy system configuration based on the subset of input data; and in a second stage following the first stage: feeding the input data and the lower bound solution into a full version of the model; and estimating, using the full version of the model, a second energy system configuration based on the input data and the lower bound solution.

Abstract: The disclosed embodiments combine an energy balance (e.g., averaged energy profiles) with original time series data having smaller time steps to establish an energy balance (e.g., averaged profiles) and a power balance (e.g., smaller time step with original time series data) for a Distributed Energy Resources (DER), microgrid, or other energy system. In an embodiment, a method comprises: solving, with at least one processor, a first optimization problem on time series data related to energy system planning, the first optimization including applying a power balancing framework to the time series data that captures intra-hour variability; and selecting, with the at least one processor, technology assets and sizing for the energy system based on an average hourly and sub-hourly datasets.

Abstract: The disclosed embodiments combine an energy balance (e.g., averaged energy profiles) with original time series data having smaller time steps to establish an energy balance (e.g., averaged profiles) and a power balance (e.g., smaller time step with original time series data) for a Distributed Energy Resources (DER), microgrid, or other energy system. In an embodiment, a method comprises: solving, with at least one processor, a first optimization problem on time series data related to energy system planning, the first optimization including applying a power balancing framework to the time series data that captures intra-hour variability; and selecting, with the at least one processor, technology assets and sizing for the energy system based on an average hourly and sub-hourly datasets.

Abstract: In an embodiment, a method comprises: obtaining input data including a plurality of parameters related to an energy system design; reducing the input data to a subset of the input data; in a first stage: feeding the subset of input data into a reduced version of a model for estimating an energy system configuration; estimating, using the reduced version of the model, a first energy system configuration and a lower bound solution for the first energy system configuration based on the subset of input data; and in a second stage following the first stage: feeding the input data and the lower bound solution into a full version of the model; and estimating, using the full version of the model, a second energy system configuration based on the input data and the lower bound solution.