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With growing penetration of renewable energy sources in power grids, it is increasingly important to reduce the renewable power forecasting error and variability to maintain balance of grid load and supply and participate in wholesale energy markets. Power from weather-dependent renewable sources like wind and solar are particularly subject to variability and forecasting error. In this study we propose...
We analyze the actual commuting profiles of vehicles in the US and develop a statistical model to fit the observed data. Subsequently, this model is leveraged in a simulation framework to simulate the behavior of fleets of Plug-in Electric Vehicles (PEV), analyze their impact on the grid and, compute the effective load carrying capacity (ELCC) contributed by PEVs. We develop methodologies to quantify...
The effect of integrating intermittent renewable generation such as wind and solar, as well as plug-in electric vehicles (PEVs) on a grid is an important area of study. Renewable generation depends on weather. Energy consumption, storage, and emergency usage of battery-stored power in PEVs are dependent on the spread of such vehicles in a geographical area, commute patterns, and hours of long-term...
We have developed a model for analyzing the system imbalance with different mixes of renewable generation (solar photovoltaic and wind) including in the presence of large pools of plug-in electric vehicles (PEVs) that participate in vehicle-to-grid and grid-to-vehicle operations. Our proposed model also identifies optimal compositions of renewable portfolios that minimize system imbalance reserve...
We have developed a model to identify optimal sizes of aggregate solar PV capacity in a region that maximizes the effective load carrying capacity (ELCC) of the grid in the presence of increasing number of plug-in electric vehicles (PEVs) participating in vehicle-to-grid operations. The model has been implemented using a simulation-based framework performing the following key steps: • Compute optimal...
We performed a study of plug-in electric vehicle (PEV) vehicle-to-grid (V2G) operations to characterize the behavior of effective load carrying capacity (ELCC) contributed by the PEVs. We leveraged the V2G simulation framework developed in [1] and used wider data sets in this study to perform a broader and deeper analysis.
Intermittent and uncertain nature of power output from weather-dependent renewable energy sources like solar is a major challenge in integrating them with traditional power grids that mostly consist of reliable power sources. We have created a framework for efficiently managing the weather-related uncertainty risk of solar generators and facilitating their integration into power grids while optimizing...
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