Bidder¶
Market participating resources (e.g., generators, IESs) submit energy bids
(a.k.a., bid curves) to the day-ahead and real-time markets for each trading time
period to communicate their flexibility and marginal costs. As shown in the figure
below, an energy bid is a piecewise constant function described by several energy
offer price ($/MWh) and
operating level (MW) pairs. Bid curves from each resource are inputs (i.e.,
parameters) in the market-clearing optimization problems solved by production cost models. Currently,
the Bidder
formulates a two-stage stochastic program to calculate the optimized
time-varying bid curves for thermal generators. In this stochastic program, each
uncertain price scenario has a corresponding power output. As shown in the figure,
each of these uncertain price and power output pairs formulates a segment in the
bidding curves.
- class idaes.apps.grid_integration.bidder.Bidder(bidding_model_object, n_scenario, solver, forecaster)[source]¶
Wrap a model object to bid into the market using stochastic programming.
- compute_bids(date, hour=None, **kwargs)[source]¶
Solve the model to bid into the markets. After solving, record the bids from the solve.
- Parameters
date – current simulation date
hour – current simulation hour
- Returns
None
- formulate_bidding_problem()[source]¶
Formulate the bidding optimization problem by adding necessary parameters, constraints, and objective function.
- Parameters
None –
- Returns
None
- record_bids(bids, date, hour)[source]¶
This function records the bids and the details in the underlying bidding model.
- Parameters
bids – the obtained bids for this date.
date – the date we bid into
hour – the hour we bid into
- Returns
None
- class idaes.apps.grid_integration.bidder.SelfScheduler(bidding_model_object, n_scenario, horizon, solver, forecaster, fixed_to_schedule=False)[source]¶
Wrap a model object to self schedule into the market using stochastic programming.
- compute_bids(date, hour=None, **kwargs)[source]¶
Solve the model to self-schedule into the markets. After solving, record the schedule from the solve.
- Parameters
date – current simulation date
hour – current simulation hour
- Returns
None
- formulate_bidding_problem()[source]¶
Formulate the bidding optimization problem by adding necessary parameters, constraints, and objective function.
- Parameters
None –
- Returns
None
- record_bids(bids, date, hour)[source]¶
This function records the bids (schedule) and the details in the underlying bidding model.
- Parameters
bids – the obtained bids for this date.
date – the date we bid into
hour – the hour we bid into
- Returns
None