…ow plot

…-pse into adam-a-a-price-taker-model

… functions to add constraints through pyomo blocks

…y argument for ramping func

…or ramping function

… blk

…ion gets called

…times

Removed some unused variables. Beautified some of the code. Made all documentation for functions consistent and more useful. Added a few ToDo's for new functionality to be added to the class.

Updated the formatting in the initialization of the PriceTakerModel. Added a check to the seed setter for integer inputs. Also added a check to the horizon_length setter for integer inputs.

Added function description and Args/Returns statements for the 'generate_daily_data' function.

Corrected the mathematical expressions for the constraints for ramping rates and startup/shutdown expressions. Namely, the expressions now appropriately constrain power ramp rates under all scenarios. Also, design decisions to build and it's impact on whether an equipment can turn on or not has been fixed. Minimum downtime constraint was also fixed. Also, I added a check to make sure that the up_time and down_time inputs are valid under the assumptions.

Added tests to check the seed, horizon_length, and minimum up_time/down_time inputs. All tests pass. As a note, the tests for clustering the LMP data need to change as they are failing. Parsed data is passed instead of raw data. I am looking into this.

Added validity checks to make sure kmin and kmax >= 0 and are integer values. Also, kmin < kmax. Also, added tests to ensure that each edge case is appropriately handled.

Fixed a few typos and made language more clear.

Added checks that the ramping rates as inputs are between 0 and 1 (fractions of the maximum capacity). Also added tests for each of these scenarios.

Code used 1-based indexing but test used 0-based. Fixed the mistmatch.

Added an attribute to the CONFIG of OperationModelData that will be True by default. The attribute, append_lmp_data, will work with building the multiperiod_model so that LMP data will automatically be populated. Old way required a dummy value for m.LMP at the operational level and the user updated LMP manually for each time period.

Also removed some hard-coded values in the append_lmp_data() function.

Updated code to be more modern and follow new Pyomo paradigms. Removed warnings for constructing both the ramping rate and startup/shutdown/min uptime/min downtime constraints. Also edited a few lines to beautify.

The set 'range_time_steps' was defined in both the ramping rate and startup/shutdown function. Also, wrote the try/except statement with the hasattr() function instead since it is one line and much neater.

Added a check to make sure that n_clusters is feasible. Also added tests to capture edge cases.

Disaggregated the unit tests for logger messages. Should make it easier to debug later.

Removed duplicate deepgetattr function and added it as an import to the __init__.py file in the idaes.apps.grid_integration tree. Also, added a test for deepgetattr's error message.

Added a check and test for n_clusters being a valid value for cluster_lmp_data. Also added a check to see if the horizon length exceed the raw_data length, meaning an empty data frame would be returned.

Removed reconfigure data as it was poor coding practice (i.e., all functionality was done by generate_daily_data). Updated all tests to accommodate. Updated all functions in price_taker_model to accommodate. Also added warning messages for when sheet and column are not defined along with test for these warning messages.

Updated lmp_data to allow for non-integer columns to be used. Ultimately, the user should be responsible for column naming and correlating LMP data. Code is now more general.

Found a case where the warning message should play (and added comments that a few test could be deleted as functions work properly but output may depend on external packages of kneed and scikit-learn).

Also fixed up get_optimal_n_clusters and cluster_lmp_data as there were some unnecessary loops, lines of code, and if statements to test.

Updated the ability to make hourly cashflows. Now the user can provide all cashflows associated with all operation block models and the total cost and total revenue for each time point is generated to be used in the build cashflow function for the objective function. Still need to add tests for each of the logger messages (but the function appears to be working correctly).

Added tests for some of the logger warning messages from the build_hourly_cashflows and build_cashflows functions.

Through these tests, most of the building code has also been tested. Remaining are two cases that will cover the rest of the build cases, options for the operational block, and the nonlinear case studies.

Also, I am considering adding a function to add the capacity limitation (both linear and nonlinear w/ and w/o linearization).

Ran black to adhere to code formatting guidelines.

Finished running black on a missed file from last commit.

Broken file tests fixed for other systems. Also fixed a typo in the startup/shutdown assignment constraint.

This test may produce different results based on what machine it is run from. Removed, but this will cause a couple lines of code to be uncovered.

Incorporated changes recommended by lbianchi-lbl to avoid conflicts and to correct an uncommitted change to the price_taker_model file.

Updated the plot test to now plt.show() the figure. Instead, the user will use plt.show() if desired.

Ran black to format recent changes. Trying to make sure current tests succeed on the builds.

Made a new test and fixed another. Wanted to cover some stray lines of code that were not run from the tests originally.

Added a function to add capacity limits for a given commodity. This was originally meant to be a user activity with linearization called at the operation_and_design_models level, however it appears it would be better in the price-taker-class itself. Discussions with Krishna have led us to use a NotImplementedError for a couple other things as well. All code now tested (except multi-year time horizons). Final testing offline for model format and finishing docstrings.

Finished adding docstrings to all complex functions.

Ran black to reformat the changed files.

Fixed a big where I accidentally called the lower bound twice instead of the lower bound AND the upper bound. Code has been tested and lines up with solutions done in a more "by-hand" fashion.

Decided to let multiyear LMP analysis to rest on the user instead of generalizing that example within the price-taker-class.

…wn_formulation_NEW.csv

Removed extraneous file added by accident.

Should resolve sphinx warnings.

Co-authored-by: Ludovico Bianchi <[email protected]>

Removed design_blk and assume the user will take care of this as an additional argument in the 'model_args' keyword.

As discussed, replacing the borrowed deepgetattr function with the more "Pyomothonic" find_component method.

Updated the test dependence to be on .csv files, per request.

Updated the borrowed deepgetattr() function to be more "Pyomothonic" with the native find_component() function.

Also updated .xlsx dependency of the test functions to be dependent on .csv file types as requested.

…-pse into price-taker-model

Removed .xlsx dependency for testing and removed deprecated .xlsx test files. Added a shortened .csv file to replace the shortened .xlsx file.

Updating to fix Sphinx build issues.

Using lighter weight parent class for design and operation model blocks.

Made sklearn and kneed optional imports to perform clustering. Logger messages and import errors added for when functions are called that use these packages. Updated setup.py to reflect that these are no longer new dependencies.

Updated tests for optional imports. Moved plotting test to within a separate function.

Ran black on all code.

Split tests so that optional import tests are now all separated from tests that do not use optional imports.

This reverts commit 46a3331.