Average Daily Optimization / Solar Powered Distributed Unit Optimization / Kan Ito

Using NRG's annual data (time series building load and solar panel output), "Go Go Green It" developed a Robust Second Order Cone Program minimizing the cost of capital and operation of a Distributed Energy Resource system consisting of energy storage, solar photovoltaic panels, access to the grid, and the building loads.

To realize a practical approach to this highly constrained problem, the team utilized chance constraints with a reliability factor to ascertain realistic results. The optimization outputs sizing for the solar panels and energy storage as well as the energy dynamics of the average day of operation. The system has certain characteristics that should be noted.

First, the grid's energy is transferable via the energy storage or the directly to the building load. Second, the system has a bidirectional flow of energy with the grid. In the case where energy is returned to the grid, Net Metering is implemented into the cost function. Furthermore, the cost function uses time of use rates (TOU) for drawing energy from the grid.

The optimization revealed significant savings with a yield of 63% savings from current practice. Because the building used large quantities of energy, the building would save costs on the order of Millions of USD.

In conclusion, incorporating statistics and data analytics provides more accurate, efficient, and profitable methods for sizing distributed energy resource (DER) assets.

Solar Powered Distributed Unit Optimization: Average Daily Optimization

Robust Second Order Cone Optimization of DER System.

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