Assume-framework

Latest version: v0.5.0

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0.3.6

What's Changed
* update github actions by maurerle in https://github.com/assume-framework/assume/pull/296
* use latest github actions versions for codecov too by maurerle in https://github.com/assume-framework/assume/pull/297
* Fix tutorial 2 by nick-harder in https://github.com/assume-framework/assume/pull/299
* silence output of gurobipy by specifying an env which does not log by maurerle in https://github.com/assume-framework/assume/pull/300
* fixes writing market_dispatch and dispatch for other product_types by maurerle in https://github.com/assume-framework/assume/pull/301
* Fix datetime warning by maurerle in https://github.com/assume-framework/assume/pull/302
* Add a tutorial for the advanced order types and documentation for the complex clearing by adamsjohanna in https://github.com/assume-framework/assume/pull/303
* Fixes string conversion of paths by kim-mskw in https://github.com/assume-framework/assume/pull/307
* move dmas bidding strategies into try since pyomo is not a required d… by nick-harder in https://github.com/assume-framework/assume/pull/308


**Full Changelog**: https://github.com/assume-framework/assume/compare/v0.3.5...v0.3.6

0.3.5

We are thrilled to announce the release of v0.3.5 of ASSUME Framework. This release marks the introduction of the redispatch module, a tool for congestion management, alongside several bug fixes and improvements. Let's delve into the details of the changes:

Redispatch Module Introduction

Congestion Management
In v0.3.5, the introduction of the redispatch module significantly enhances the framework's capabilities in addressing congestion management challenges. This module is equipped to support both cost-based and market-based redispatch strategies, leveraging the PyPSA network to detect and resolve congestion effectively.

To explore its functionality, users can engage with the Example 01d, wherein a Day-Ahead Energy Market and a subsequent Redispatch Market are employed. Initially, the market is cleared using a single bidding zone, followed by a congestion management process. Furthermore, a detailed Jupyter-based tutorial will be made available to facilitate a deeper understanding of the module's application.

Cost-Based and Market-Based Redispatch
The redispatch module offers support for both cost-based and market-based redispatch strategies. This includes the implementation of "pay as bid" and "pay as clear" market methods, empowering users with versatile tools for congestion management.

Detailed Changes

Redispatch v1
Implemented by nick-harder. paragpatil39 and rqussous in [PR 279](https://github.com/assume-framework/assume/pull/279), this significant update introduces the initial version of the redispatch feature, laying the foundation for advanced congestion management.

New Strategies Allocation
nick-harder's contribution in [PR 289](https://github.com/assume-framework/assume/pull/289) brings about a crucial change in strategy allocation, now utilizing market names instead of product types, enhancing the overall clarity and usability of the framework.

Bug Fixes and Refinements
- Storage Operation Fixes: adamsjohanna addressed some bugs in storage operations, ensuring smoother functionality ([PR 291](https://github.com/assume-framework/assume/pull/291)).
- Removal of Empty Bid Method: In [PR 293](https://github.com/assume-framework/assume/pull/293), nick-harder eliminated the use of empty bid as a method of bidding strategy, streamlining the bidding process.
- EOM References Cleanup: nick-harder's contribution in [PR 294](https://github.com/assume-framework/assume/pull/294) involved the removal of hard-coded EOM references from the code base, ensuring a more flexible and maintainable code structure.
- Overall scenario loading and other quality improvements by maurerle

For a comprehensive list of changes, please refer to the [Full Changelog](https://github.com/assume-framework/assume/compare/v0.3...v0.3.5).

We encourage all users to upgrade to v0.3.5 to leverage the latest enhancements and bug fixes. Your feedback is invaluable, and we look forward to hearing about your experiences with these new features.

0.3

What's Changed

Features
- Added reuse compliance by maurerle
- Added Data Request mechanism by maurerle ([247](https://github.com/assume-framework/assume/pull/247))
- Added "Open in Collab" to notebooks by nick-harder ([258](https://github.com/assume-framework/assume/pull/258))
- Added block order and linked order and respective market clearing mechanism by adamsjohanna ([269](https://github.com/assume-framework/assume/pull/269))
- Added MASTR based OEDS loader by maurerle
- Added AMIRIS Scenario loader by maurerle

Fixes
- Fixed calculation of marginal cost and output_before by maurerle ([250](https://github.com/assume-framework/assume/pull/250))
- Changed buffer add function call by kim-mskw ([255](https://github.com/assume-framework/assume/pull/255))
- Adjusted query of reward during training by nick-harder ([256](https://github.com/assume-framework/assume/pull/256))
- Fixed calculation of flexible storage bids by maurerle ([260](https://github.com/assume-framework/assume/pull/260))
- Fixed RL evaluations by kim-mskw ([280](https://github.com/assume-framework/assume/pull/280))
- Fixed usage of license references by maurerle ([246](https://github.com/assume-framework/assume/pull/246))

Documentation
- [Tutorial] Added basic tutorial 01 and 02 by nick-harder ([257](https://github.com/assume-framework/assume/pull/257))
- [Tutorial] Added Custom Unit and Custom Strategy tutorial by Manish-Khanra ([262](https://github.com/assume-framework/assume/pull/262))
- [Tutorial] Added tutorial of EOM and LTM comparison by maurerle ([265](https://github.com/assume-framework/assume/pull/265))
- Updated dependencies and installation instructions by nick-harder ([282](https://github.com/assume-framework/assume/pull/282))
- Added additional clearing and strategy docs by maurerle ([283](https://github.com/assume-framework/assume/pull/283))

Other
- Moved scenario loaders to separate folder by maurerle ([264](https://github.com/assume-framework/assume/pull/264))
- Added an automatic assignment of RL units to one RL unit operator by kim-mskw ([276](https://github.com/assume-framework/assume/pull/276))
- Improved data_dict usage by maurerle ([274](https://github.com/assume-framework/assume/pull/274))

Full Changelog
[Full Changelog](https://github.com/assume-framework/assume/compare/v0.2.1...v0.3)

0.2.1

What's Changed
* fix loading learned strategies by nick-harder in https://github.com/assume-framework/assume/pull/219
* Workshop dach by kim-mskw in https://github.com/assume-framework/assume/pull/218
* distribute current time correctly to agents running in shadow container in different process by maurerle in https://github.com/assume-framework/assume/pull/199
* RL Documentation by kim-mskw in https://github.com/assume-framework/assume/pull/221
* Add shields badges to readme by maurerle in https://github.com/assume-framework/assume/pull/223
* add amiris scenario loader by maurerle in https://github.com/assume-framework/assume/pull/224
* fixes for running distributed scenario with mqtt by maurerle in https://github.com/assume-framework/assume/pull/222


**Full Changelog**: https://github.com/assume-framework/assume/compare/v0.2.0...v0.2.1

0.2.0

**What has changed:**
- The learning performance has been improved
- The learning can now be also performed on CUDA enabled devices
- Added tracking of evaluation periods for better learning performance evaluation
- Storage units behavior bugs have been adressed
- Now several simulation can be started in parallel
- New Grafana dashboard definitions for easier analysis
- Docker compose file now includes Renderer to save plots directly from Grafan dashboards

0.1.0

This is the initial release of assume-framework, which is published to PyPi.

The assume-framework allows to define different energy market designs and includes reinforcement learning capabilities.


market_paper
This tag is used to release a citable version of the code used for the conference paper:
"Market Abstraction of Energy Markets and Policies – Application in an Agent-Based Modeling Toolbox"

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