Tracker¶
Production Cost Models (PCM) computes the time-varying dispatch schedules for each resource using
simplified models. Emerging resources including IESs and industrial demand response
need to determine the optimal operations strategy to track their market dispatch
signal. The Tracker
formulates these decisions as a model predictive control
(MPC) problem. The figure below shows an example of the optimal tracking from an
integrated energy system which consists of a thermal generator and an energy storage.
The figure shows that to track the dispatch (load) the energy system can optimally
use power output from charging and discharging cycle.
- class idaes.apps.grid_integration.tracker.Tracker(tracking_model_object, tracking_horizon, n_tracking_hour, solver)[source]¶
Wrap a model object to track the market dispatch signals. This class interfaces with the DoubleLoopCoordinator.
- formulate_tracking_problem()[source]¶
Formulate the tracking optimization problem by adding necessary parameters, constraints, and objective function.
- Parameters
None –
- Returns
None
- get_last_delivered_power()[source]¶
Returns the last delivered power output.
- Parameters
None –
- Returns
None
- record_results(**kwargs)[source]¶
Record the operations stats for the model.
- Parameters
kwargs – key word arguments that can be passed into tracking model object’s record result function.
- Returns
None
- track_market_dispatch(market_dispatch, date, hour)[source]¶
Solve the model to track the market dispatch signals. After solving, record the results from the solve and update the model.
- Parameters
market_dispatch – a list that contains the market dispatch signals
date – current simulation date
hour – current simulation hour
- Returns
None