A co-optimization model between Energy and Ancillary Service (AS) products. We pull Energy and AS prices using the Gridstatus API using Pyomo for model setup and GLPK for solver.
This program optimizes the operation and bidding strategy of renewable-based Virtual Power Plants (RVPPs) under different sources of uncertainty using MILP-based flexible robust optimization approaches. The model considers RVPP participation in the Day-Ahead, Secondary Reserve, and Intra-Day Iberian electricity markets.
A script to pull Ancillary Service (AS) prices from the CAISO OASIS API. These are California electricity prices.
Downloading and storing the TenneT aFRR bid ladders at regular intervals
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