Citylearn

This release added a grid cost to the CityLearn Challenge 2022. The grid score is the average of a ramping and (1 - load factor) scores evaluated at the aggregated district net electricity consumption level. The purpose of adding this grid score is to encourage participants to seek a cooperative multi-agent solution in order to achieve grid-level objectives.

**Full Changelog**: https://github.com/intelligent-environments-lab/CityLearn/compare/v1.3.5...v1.3.6

This release addresses 2 main issues:

1. The long simulation time as a result of time series variables being recalculated every time step has been solved.2. Simulations, especially with RBCs are much noticeably faster to complete.
2. There was a bug in the calculation of the battery energy balance that overestimated the energy balance during discharge.
3. Other minor issues.

Credits to ludwigbald for finding and proffering solutions to the issues.

**Full Changelog**: https://github.com/intelligent-environments-lab/CityLearn/compare/v1.3.4...v1.3.5

CityLearn Challenge 2022 sixth release with bug fixes.

**Full Changelog**: https://github.com/intelligent-environments-lab/CityLearn/compare/v1.3.3...v1.3.4

CityLearn Challenge 2022 fifth release with bug fixes.

**Full Changelog**: https://github.com/intelligent-environments-lab/CityLearn/compare/v1.3.2...v1.3.3

CityLearn Challenge 2022 fourth release with bug fixes.

**Full Changelog**: https://github.com/intelligent-environments-lab/CityLearn/compare/v1.3.1...v1.3.2

CityLearn Challenge 2022 third release with bug fixes.

**Full Changelog**: https://github.com/intelligent-environments-lab/CityLearn/compare/v1.3.0...v1.3.1