Release History

0.6.10 (2023-01-18)

changed backwards-incompatible Updated to Numpy v1.23, Pandas v1.5, Pyomo v6.4, Ruamel.yaml v0.17, Scikit-learn v1.2, Xarray v2022.3, GLPK v5. This enables Calliope to be installed on Apple Silicon devices, but changes the result of algorithmic timeseries clustering. In scikit-learn version 0.24.0, the method of random sampling for K-Means clustering was changed. This change will lead to different optimisation results if using K-Means clustering in your model.

changed backwards-incompatible Removed support for Python version 3.7 since some updated dependencies are not available in this version.

changed Installation instructions for developers have changed since we no longer duplicate pinned packages between the developement/testing requirements file (requirements.yml) and the package requirements file (requirements.txt). See the documentation for updated instructions.

fixed Set ordering in the model dataset is consistent before and after optimising a model with clustered timeseries. Previously, the link between clusters and timesteps would become mixed following optimisation, so running would yield a different result.

0.6.9 (2023-01-10)

changed Updated to Python 3.9, with compatibility testing continuing for versions 3.8 and 3.9. Multi-platform CI tests are run on Python 3.9 instead of Python 3.8. CI tests on a Linux machine are also run for versions 3.7 and 3.8. This has been explicitly mentioned in the documentation.

changed Updated to Click 8.0.

changed Updated CBC Windows binary link in documentation to version 2.10.8.

fixed SPORES mode scoring will ignore technologies with energy capacities that are equal to their minimum capacities (i.e., energy_cap_min) or which have fixed energy capacities (energy_cap_equals).

fixed SPORE number is retained when continuing a model run in SPORES mode when solutions already exist for SPORE >= 1. Previously, the SPORE number would be reset to zero.

fixed Malformed carrier-specific group constraints are skipped without skipping all subsequent group constraints.

fixed Spurious negative values in storage_inital in operate mode are ignored in subsequent optimisation runs (#379). Negative values are a result of optimisation tolerances allowing a strictly positive decision variable to end up with (very small in magnitude) negative values. Forcing these to zero between operate mode runs ensures that Pyomo doesn’t raise an exception that input values are outside the valid domain (NonNegativeReals).

fixed om_annual investment costs will be calculated for technologies with only an om_annual cost defined in their configuration (#373). Previously, no investment costs would be calculated in this edge case.

0.6.8 (2022-02-07)

new run configuration parameter to enable relaxation of the demand_share_per_timestep_decision constraint.

new storage_cap_min/equals/max group constraints added.

changed Updated to Pyomo 6.2, pandas 1.3, xarray 0.20, numpy 1.20.

changed backwards-incompatible parameters defaulting to False now default to None, to avoid confusion with zero. To ‘switch off’ a constraint, a user should now set it to ‘null’ rather than ‘false’ in their YAML configuration.

changed INFO logging level includes logs for dataset cleaning steps before saving to NetCDF and for instantiation of timeseries clustering/resampling (if taking place).

fixed demand_share_per_timestep_decision constraint set includes all expected (location, technology, carrier) items. In the previous version, not all expected items were captured.

fixed Mixed dtype xarray dataset variables, where one dtype is boolean, are converted to float if possible. This overcomes an error whereby the NetCDF file cannot be created due to a mixed dtype variable.

0.6.7 (2021-06-29)

new spores run mode can skip the cost-optimal run, with the user providing initial conditions for spores_score and slack system cost.

new Support for Pyomo’s gurobi_persistent solver interface, which enables a more memory- and time-efficient update and re-running of models. A new backend interface has been added to re-build constraints / the objective in the Gurobi persistent solver after updating Pyomo parameters.

new A scenario can now be a mix of overrides and other scenarios, not just overrides.

new model.backend.rerun() can work with both spores and plan run modes (previously only plan worked). In the spores case, this only works with a built backend that has not been previously run (i.e., but allows a user to update constraints etc. before running the SPORES method.

changed backwards-incompatible Carrier-specific group constraints are only allowed in isolation (one constraint in the group).

changed If ensure_feasibility is set to True, unmet_demand will always be returned in the model results, even if the model is feasible. Fixes issue #355.

changed Updated to Pyomo 6.0, pandas 1.2, xarray 0.17.

changed Update CBC Windows binary link in documentation.

fixed AttrDict now has a __name__ attribute, which makes pytest happy.

fixed CLI plotting command has been re-enabled. Fixes issue #341.

fixed Group constraints are more robust to variations in user inputs. This entails a trade-off whereby some previously accepted user configurations will no longer be possible, since we want to avoid the complexity of processing them.

fixed demand_share_per_timestep_decision now functions as expected, where it previously did not enforce the per-timestep share after having decided upon it.

fixed Various bugs squashed in running operate mode.

fixed Handle number of timesteps lower than the horizon length in operate mode (#337).

0.6.6 (2020-10-08)

new spores run mode now available, to find Spatially-explicit Practically Optimal REsultS (SPORES)

new New group constraints carrier_con_min, carrier_con_max, carrier_con_equals which restrict the total consumed energy of a subgroup of conversion and/or demand technologies.

new Add ability to pass timeseries as dataframes in calliope.Model instead of only as CSV files.

new Pyomo backend interfaces added to get names of all model objects (get_all_model_attrs) and to attach custom constraints to the backend model (add_constraint).

changed Parameters are assigned a domain in Pyomo based on their dtype in model_data

changed Internal code reorganisation.

changed Updated to Pyomo 5.7, pandas 1.1, and xarray 0.16

fixed One-way transmission technologies can have om costs

fixed Silent override of nested dicts when parsing YAML strings

0.6.5 (2020-01-14)

new New group constraints energy_cap_equals, resource_area_equals, and energy_cap_share_equals to add the equality constraint to existing min/max group constraints.

new New group constraints carrier_prod_min, carrier_prod_max, and carrier_prod_equals which restrict the absolute energy produced by a subgroup of technologies and locations.

new Introduced a storage_discharge_depth constraint, which allows to set a minimum stored-energy level to be preserved by a storage technology.

new New group constraints net_import_share_min, net_import_share_max, and net_import_share_equals which restrict the net imported energy of a certain carrier into subgroups of locations.

changed backwards-incompatible Group constraints with the prefix supply_share are renamed to use the prefix carrier_prod_share. This ensures consistent naming for all group constraints.

changed Allowed ‘energy_cap_min’ for transmission technologies.

changed Minor additions made to troubleshooting and development documentation.

changed backwards-incompatible The backend interface to update a parameter value (Model.backend.update_param()) has been updated to allow multiple values in a parameter to be updated at once, using a dictionary.

changed Allowed om_con cost for demand technologies. This is conceived to allow better representing generic international exports as demand sinks with a given revenue (e.g. the average electricity price on a given bidding zone), not restricted to any particular type of technology.

changed backwards-incompatible model.backend.rerun() returns a calliope Model object instead of an xarray Dataset, allowing a user to access calliope Model methods, such as get_formatted_array.

changed Carrier ratios can be loaded from file, to allow timeseries carrier ratios to be defined, e.g. carrier_ratios.carrier_out_2.heat: file=ratios.csv.

changed Objective function options turned into Pyomo parameters. This allows them to update through the Model.backend.update_param() functionality.

changed All model defaults have been moved to defaults.yaml, removing the need for model.yaml. A default location, link and group constraint have been added to defaults.yaml to validate input model keys.

changed backwards-incompatible Revised internal logging and warning structure. Less critical warnings during model checks are now logged directly to the INFO log level, which is displayed by default in the CLI, and can be enabled interactively by calling calliope.set_log_verbosity() without any options. The calliope.set_log_level function has been renamed to calliope.set_log_verbosity and includes the ability to easily turn on and off the display of solver output.

changed All group constraint values are parameters so they can be updated in the backend model

fixed Operate mode checks cleaned up to warn less frequently and to not be so aggressive at editing a users model to fit the operate mode requirements.

fixed Documentation distinctly renders inline Python, YAML, and shell code snippets.

fixed Tech groups are used to filter technologies to which group constraints can be applied. This ensures that transmission and storage technologies are included in cost and energy capacity group constraints. More comprehensive tests have been added accordingly.

fixed Models saved to NetCDF now include the fully built internal YAML model and debug data so that Model.save_commented_model_yaml() is available after loading a NetCDF model from disk

fixed Fix an issue preventing the deprecated charge_rate constraint from working in 0.6.4.

fixed Fix an issue that prevented 0.6.4 from loading NetCDF models saved with older versions of Calliope. It is still recommended to only load models with the same version of Calliope that they were saved with, as not all functionality will work when mixing versions.

fixed backwards-incompatible Updated to require pandas 0.25, xarray 0.14, and scikit-learn 0.22, and verified Python 3.8 compatibility. Because of a bugfix in scikit-learn 0.22, models using k-means clustering with a specified random seed may return different clusters from Calliope 0.6.5 on.

0.6.4 (2019-05-27)

new New model-wide constraint that can be applied to all, or a subset of, locations and technologies in a model, covering:

  • demand_share, supply_share, demand_share_per_timestep, supply_share_per_timestep, each of which can specify min, max, and equals, as well as energy_cap_share_min and energy_cap_share_max. These supersede the group_share constraints, which are now deprecated and will be removed in v0.7.0.

  • demand_share_per_timestep_decision, allowing the model to make decisions on the per-timestep shares of carrier demand met from different technologies.

  • cost_max, cost_min, cost_equals, cost_var_max, cost_var_min, cost_var_equals, cost_investment_max, cost_investment_min, cost_investment_equals, which allow a user to constrain costs, including those not used in the objective.

  • energy_cap_min, energy_cap_max, resource_area_min, resource_area_max which allow to constrain installed capacities of groups of technologies in specific locations.

new asynchronous_prod_con parameter added to the constraints, to allow a user to fix a storage or transmission technology to only be able to produce or consume energy in a given timestep. This ensures that unphysical dissipation of energy cannot occur in these technologies, by activating a binary variable (prod_con_switch) in the backend.

new Multi-objective optimisation problems can be defined by linear scalarisation of cost classes, using run.objective_options.cost_class (e.g. {‘monetary’: 1, ‘emissions’: 0.1}, which models an emissions price of 0.1 units of currency per unit of emissions)

new Storage capacity can be tied to energy capacity with a new energy_cap_per_storage_cap_equals constraint.

new The ratio of energy capacity and storage capacity can be constrained with a new energy_cap_per_storage_cap_min constraint.

new Easier way to save an LP file with a --save_lp command-line option and a Model.to_lp method

new Documentation has a new layout, better search, and is restructured with various content additions, such as a section on troubleshooting.

new Documentation for developers has been improved to include an overview of the internal package structure and a guide to contributing code via a pull request.

changed backwards-incompatible Scenarios in YAML files defined as list of override names, not comma-separated strings: fusion_scenario: cold_fusion,high_cost becomes fusion_scenario: [‘cold_fusion’, ‘high_cost’]. No change to the command-line interface.

changed charge_rate has been renamed to energy_cap_per_storage_cap_max. charge_rate will be removed in Calliope 0.7.0.

changed Default value of resource_area_max now is inf instead of 0, deactivating the constraint by default.

changed Constraint files are auto-loaded in the pyomo backend and applied in the order set by ‘ORDER’ variables given in each constraint file (such that those constraints which depend on pyomo expressions existing are built after the expressions are built).

changed Error on defining a technology in both directions of the same link.

changed Any inexistent locations and / or technologies defined in model-wide (group) constraints will be caught and filtered out, raising a warning of their existence in the process.

changed Error on required column not existing in CSV is more explicit.

changed backwards-incompatible Exit code for infeasible problems now is 1 (no success). This is a breaking change when relying on the exit code.

changed get_formatted_array improved in both speed and memory consumption.

changed model and run configurations are now available as attributes of the Model object, specifically as editable dictionaries which automatically update a YAML string in the model_data xarray dataset attribute list (i.e. the information is stored when sending to the solver backend and when saving to and loading from NetCDF file)

changed All tests and example models have been updated to solve with Coin-CBC, instead of GLPK. Documentation has been updated to reflect this, and aid in installing CBC (which is not simple for Windows users).

changed Additional and improved pre-processing checks and errors for common model mistakes.

fixed Total levelised cost of energy considers all costs, but energy generation only from supply, supply_plus, conversion, and conversion_plus.

fixed If a space is left between two locations in a link (i.e. A, B instead of A,B), the space is stripped, instead of leading to the expectation of a location existing with the name ` B`.

fixed Timeseries efficiencies can be included in operate mode without failing on preprocessing checks.

fixed Name of data variables is retained when accessed through model.get_formatted_array()

fixed Systemwide constraints work in models without transmission systems.

fixed Updated documentation on amendments of abstract base technology groups.

fixed Models without time series data fail gracefully.

fixed Unknown technology parameters are detected and the user is warned.

fixed Loc::techs with empty cost classes (i.e. value == None) are handled by a warning and cost class deletion, instead of messy failure.

0.6.3 (2018-10-03)

new Addition of flows plotting function. This shows production and how much they exchange with other locations. It also provides a slider in order to see flows’ evolution through time.

new calliope generate_runs in the command line interface can now produce scripts for remote clusters which require SLURM-based submission (sbatch...).

new backwards-incompatible Addition of scenarios, which complement and expand the existing overrides functionality. overrides becomes a top-level key in model configuration, instead of a separate file. The calliope run command has a new --scenario option which replaces –override_file, while calliope generate_runs has a new --scenarios option which replaces –override_file and takes a semicolon-separated list of scenario names or of group1,group2 combinations. To convert existing overrides to the new approach, simply group them under a top-level overrides key and import your existing overrides file from the main model configuration file with import: ['your_overrides_file.yaml'].

new Addition of calliope generate_scenarios command to allow automating the construction of scenarios which consist of many combinations of overrides.

new Added --override_dict option to calliope run and calliope generate_runs commands

new Added solver performance comparison in the docs. CPLEX & Gurobi are, as expected, the best options. If going open-source & free, CBC is much quicker than GLPK!

new Calliope is tested and confirmed to run on Python 3.7

changed resource_unit - available to supply, supply_plus, and demand technologies - can now be defined as ‘energy_per_area’, ‘energy’, or ‘energy_per_cap’. ‘power’ has been removed. If ‘energy_per_area’ then available resource is the resource (CSV or static value) * resource_area, if ‘energy_per_cap’ it is resource * energy_cap. Default is ‘energy’, i.e. resource = available_resource.

changed Updated to xarray v0.10.8, including updates to timestep aggregation and NetCDF I/O to handle updated xarray functionality.

changed Removed calliope convert command. If you need to convert a 0.5.x model, first use calliope convert in Calliope 0.6.2 and then upgrade to 0.6.3 or higher.

changed Removed comment persistence in AttrDict and the associated API in order to improve compatibility with newer versions of ruamel.yaml

fixed Operate mode is more robust, by being explicit about timestep and loc_tech indexing in storage_initial preparation and resource_cap checks, respectively, instead of assuming an order.

fixed When setting ensure_feasibility, the resulting unmet_demand variable can also be negative, accounting for possible infeasibility when there is unused supply, once all demand has been met (assuming no load shedding abilities). This is particularly pertinent when the force_resource constraint is in place.

fixed When applying systemwide constraints to transmission technologies, they are no longer silently ignored. Instead, the constraint value is doubled (to account for the constant existence of a pair of technologies to describe one link) and applied to the relevant transmission techs.

fixed Permit groups in override files to specify imports of other YAML files

fixed If only interest_rate is defined within a cost class of a technology, the entire cost class is correctly removed after deleting the interest_rate key. This ensures an empty cost key doesn’t break things later on. Fixes issue #113.

fixed If time clustering with ‘storage_inter_cluster’ = True, but no storage technologies, the model doesn’t break. Fixes issue #142.

0.6.2 (2018-06-04)

new units_max_systemwide and units_equals_systemwide can be applied to an integer/binary constrained technology (capacity limited by units not energy_cap, or has an associated purchase (binary) cost). Constraint works similarly to existing energy_cap_max_systemwide, limiting the number of units of a technology that can be purchased across all locations in the model.

new backwards-incompatible primary_carrier for conversion_plus techs is now split into primary_carrier_in and primary_carrier_out. Previously, it only accounted for output costs, by separating it, om_con and om_prod are correctly accounted for. These are required conversion_plus essentials if there’s more than one input and output carrier, respectively.

new Storage can be set to cyclic using run.cyclic_storage. The last timestep in the series will then be used as the ‘previous day’ conditions for the first timestep in the series. This also applies to storage_inter_cluster, if clustering. Defaults to False, with intention of defaulting to True in 0.6.3.

new On clustering timeseries into representative days, an additional set of decision variables and constraints is generated. This addition allows for tracking stored energy between clusters, by considering storage between every datestep of the original (unclustered) timeseries as well as storage variation within a cluster.

new CLI now uses the IPython debugger rather than built-in pdb, which provides highlighting, tab completion, and other UI improvements

new AttrDict now persists comments when reading from and writing to YAML files, and gains an API to view, add and remove comments on keys

fixed Fix CLI error when running a model without transmission technologies

fixed Allow plotting for inputs-only models, single location models, and models without location coordinates

fixed Fixed negative om_con costs in conversion and conversion_plus technologies

0.6.1 (2018-05-04)

new Addition of user-defined datestep clustering, accessed by clustering_func: file=filename.csv:column in time aggregation config

new Added layout_updates and plotly_kwarg_updates parameters to plotting functions to override the generated Plotly configuration and layout

changed Cost class and sense (maximize/minimize) for objective function may now be specified in run configuration (default remains monetary cost minimization)

changed Cleaned up and documented Model.save_commented_model_yaml() method

fixed Fixed error when calling --save_plots in CLI

fixed Minor improvements to warnings

fixed Pure dicts can be used to create a Model instance

fixed AttrDict.union failed on all-empty nested dicts

0.6.0 (2018-04-20)

Version 0.6.0 is an almost complete rewrite of most of Calliope’s internals. See New in v0.6.0 for a more detailed description of the many changes.

Major changes

changed backwards-incompatible Substantial changes to model configuration format, including more verbose names for most settings, and removal of run configuration files.

new backwards-incompatible Complete rewrite of Pyomo backend, including new various new and improved functionality to interact with a built model (see New in v0.6.0).

new Addition of a calliope convert CLI tool to convert 0.5.x models to 0.6.0.

new Experimental ability to link to non-Pyomo backends.

new New constraints: resource_min_use constraint for supply and supply_plus techs.

changed backwards-incompatible Removal of settings and constraints includes subset_x, subset_y, s_time, r2, r_scale_to_peak, weight.

changed backwards-incompatible system_margin constraint replaced with reserve_margin constraint.

changed backwards-incompatible Removed the ability to load additional custom constraints or objectives.

0.5.5 (2018-02-28)

  • fixed Allow r_area to be non-zero if either of e_cap.max or e_cap.equals is set, not just e_cap.max.

  • fixed Ensure static parameters in resampled timeseries are caught in constraint generation

  • fixed Fix time masking when set_t.csv contains sub-hourly resolutions

0.5.4 (2017-11-10)

Major changes

  • fixed r_area_per_e_cap and r_cap_equals_e_cap constraints have been separated from r_area and r_cap constraints to ensure that user specified r_area.max and r_cap.max constraints are observed.

  • changed technologies and location subsets are now communicated with the solver as a combined location:technology subset, to reduce the problem size, by ignoring technologies at locations in which they have not been allowed. This has shown drastic improvements in Pyomo preprocessing time and memory consumption for certain models.

Other changes

  • fixed Allow plotting carrier production using calliope.analysis.plot_carrier_production if that carrier does not have an associated demand technology (previously would raise an exception).

  • fixed Define time clustering method (sum/mean) for more constraints that can be time varying. Previously only included r and e_eff.

  • changed storage technologies default s_cap.max to inf, not 0 and are automatically included in the loc_tech_store subset. This ensures relevant constraints are not ignored by storage technologies.

  • changed Some values in the urban scale MILP example were updated to provide results that would show the functionality more clearly

  • changed technologies have set colours in the urban scale example model, as random colours were often hideous.

  • changed ruamel.yaml, not ruamel_yaml, is now used for parsing YAML files.

  • fixed e_cap constraints for unmet_demand technologies are ignored in operational mode. Capacities are fixed for all other technologies, which previously raised an exception, as a fixed infinite capacity is not physically allowable.

  • fixed stack_weights were strings rather than numeric datatypes on reading NetCDF solution files.

0.5.3 (2017-08-22)

Major changes

  • new (BETA) Mixed integer linear programming (MILP) capabilities, when using purchase cost and/or units.max/min/equals constraints. Integer/Binary decision variables will be applied to the relevant technology-location sets, avoiding unnecessary complexity by describing all technologies with these decision variables.

Other changes

  • changed YAML parser is now ruamel_yaml, not pyyaml. This allows scientific notation of numbers in YAML files (#57)

  • fixed Description of PV technology in urban scale example model now more realistic

  • fixed Optional ramping constraint no longer uses backward-incompatible definitions (#55)

  • fixed One-way transmission no longer forces unidirectionality in the wrong direction

  • fixed Edge case timeseries resource combinations, where infinite resource sneaks into an incompatible constraint, are now flagged with a warning and ignored in that constraint (#61)

  • fixed e_cap.equals: 0 sets a technology to a capacity of zero, instead of ignoring the constraint (#63)

  • fixed depreciation_getter now changes with location overrides, instead of just checking the technology level constraints (#64)

  • fixed Time clustering now functions in models with time-varying costs (#66)

  • changed Solution now includes time-varying costs (costs_variable)

  • fixed Saving to NetCDF does not affect in-memory solution (#62)

0.5.2 (2017-06-16)

  • changed Calliope now uses Python 3.6 by default. From Calliope 0.6.0 on, Python 3.6 will likely become the minimum required version.

  • fixed Fixed a bug in distance calculation if both lat/lon metadata and distances for links were specified.

  • fixed Fixed a bug in storage constraints when both s_cap and e_cap were constrained but no c_rate was given.

  • fixed Fixed a bug in the system margin constraint.

0.5.1 (2017-06-14)

new backwards-incompatible Better coordinate definitions in metadata. Location coordinates are now specified by a dictionary with either lat/lon (for geographic coordinates) or x/y (for generic Cartesian coordinates), e.g. {lat: 40, lon: -2} or {x: 0, y: 1}. For geographic coordinates, the map_boundary definition for plotting was also updated in accordance. See the built-in example models for details.

new Unidirectional transmission links are now possible. See the documentation on transmission links.

Other changes

  • fixed Missing urban-scale example model files are now included in the distribution

  • fixed Edge cases in conversion_plus constraints addressed

  • changed Documentation improvements

0.5.0 (2017-05-04)

Major changes

new Urban-scale example model, major revisions to the documentation to accommodate it, and a new calliope.examples module to hold multiple example models. In addition, the calliope new command now accepts a --template option to select a template other than the default national-scale example model, e.g.: calliope new my_urban_model --template=UrbanScale.

new Allow technologies to generate revenue (by specifying negative costs)

new Allow technologies to export their carrier directly to outside the system boundary

new Allow storage & supply_plus technologies to define a charge rate (c_rate), linking storage capacity (s_cap) with charge/discharge capacity (e_cap) by s_cap * c_rate => e_cap. As such, either s_cap.max & c_rate or e_cap.max & c_rate can be defined for a technology. The smallest of s_cap.max * c_rate and e_cap.max will be taken if all three are defined.

changed backwards-incompatible Revised technology definitions and internal definition of sets and subsets, in particular subsets of various technology types. Supply technologies are now split into two types: supply and supply_plus. Most of the more advanced functionality of the original supply technology is now contained in supply_plus, making it necessary to update model definitions accordingly. In addition to the existing conversion technology type, a new more complex conversion_plus was added.

Other changes

  • changed backwards-incompatible Creating a Model() with no arguments now raises a ModelError rather than returning an instance of the built-in national-scale example model. Use the new calliope.examples module to access example models.

  • changed Improvements to the national-scale example model and its tutorial notebook

  • changed Removed SolutionModel class

  • fixed Other minor fixes

0.4.1 (2017-01-12)

  • new Allow profiling with the --profile and --profile_filename command-line options

  • new Permit setting random seed with random_seed in the run configuration

  • changed Updated installation documentation using conda-forge package

  • fixed Other minor fixes

0.4.0 (2016-12-09)

Major changes

new Added new methods to deal with time resolution: clustering, resampling, and heuristic timestep selection

changed backwards-incompatible Major change to solution data structure. Model solution is now returned as a single xarray DataSet instead of multiple pandas DataFrames and Panels. Instead of as a generic HDF5 file, complete solutions can be saved as a NetCDF4 file via xarray’s NetCDF functionality.

While the recommended way to save and process model results is by NetCDF4, CSV saving functionality has now been upgraded for more flexibility. Each variable is saved as a separate CSV file with a single value column and as many index columns as required.

changed backwards-incompatible Model data structures simplified and based on xarray

Other changes

  • new Functionality to post-process parallel runs into aggregated NetCDF files in

  • changed Pandas 0.18/0.19 compatibility

  • changed 1.11 is now the minimum required numpy version. This version makes datetime64 tz-naive by default, thus preventing some odd behavior when displaying time series.

  • changed Improved logging, status messages, and error reporting

  • fixed Other minor fixes

0.3.7 (2016-03-10)

Major changes

changed Per-location configuration overrides improved. All technology constraints can now be set on a per-location basis, as can costs. This applies to the following settings:

  • techname.x_map

  • techname.constraints.*

  • techname.constraints_per_distance.*

  • techname.costs.*

The following settings cannot be overridden on a per-location basis:

  • Any other options directly under techname, such as techname.parent or techname.carrier

  • techname.costs_per_distance.*

  • techname.depreciation.*

Other changes

  • fixed Improved installation instructions

  • fixed Pyomo 4.2 API compatibility

  • fixed Other minor fixes

0.3.6 (2015-09-23)

  • fixed Version 0.3.5 changes were not reflected in tutorial

0.3.5 (2015-09-18)

Major changes

new New constraint to constrain total (model-wide) installed capacity of a technology (e_cap.total_max), in addition to its per-node capacity (e_cap.max)

changed Removed the level option for locations. Level is now implicitly derived from the nested structure given by the within settings. Locations that define no or an empty within are implicitly at the topmost (0) level.

changed backwards-incompatible Revised configuration of capacity constraints: e_cap_max becomes e_cap.max, addition of e_cap.min and e_cap.equals (analogous for r_cap, s_cap, rb_cap, r_area). The e_cap.equals constraint supersedes e_cap_max_force (analogous for the other constraints). No backwards-compatibility is retained, models must change all constraints to the new formulation. See Per-tech constraints for a complete list of all available constraints. Some additional constraints have name changes:

  • e_cap_max_scale becomes e_cap_scale

  • rb_cap_follows becomes rb_cap_follow, and addition of rb_cap_follow_mode

  • s_time_max becomes s_time.max

changed backwards-incompatible All optional constraints are now grouped together, under constraints.optional:

  • constraints.group_fraction.group_fraction becomes constraints.optional.group_fraction

  • constraints.ramping.ramping_rate becomes constraints.optional.ramping_rate

Other changes

  • new analysis.map_results function to extract solution details from multiple parallel runs

  • new Various other additions to analysis functionality, particularly in the analysis_utils module

  • new analysis.get_levelized_cost to get technology and location specific costs

  • new Allow dynamically loading time mask functions

  • changed Improved summary table in the model solution: now shows only aggregate information for transmission technologies, also added missing s_cap column and technology type

  • fixed Bug causing some total levelized transmission costs to be infinite instead of zero

  • fixed Bug causing some CSV solution files to be empty

0.3.4 (2015-04-27)

  • fixed Bug in construction and fixed O&M cost calculations in operational mode

0.3.3 (2015-04-03)

Major changes

changed In preparation for future enhancements, the ordering of location levels is flipped. The top-level locations at which balancing takes place is now level 0, and may contain level 1 locations. This is a backwards-incompatible change.

changed backwards-incompatible Refactored time resolution adjustment functionality. Can now give a list of masks in the run configuration which will all be applied, via time.masks, with a base resolution via time.resolution (or instead, as before, load a resolution series from file via time.file). Renamed the time_functions submodule to time_masks.

Other changes

  • new Models and runs can have a name

  • changed More verbose calliope run

  • changed Analysis tools restructured

  • changed Renamed debug.keepfiles setting to debug.keep_temp_files and better documented debug configuration

0.3.2 (2015-02-13)

  • new Run setting model_override allows specifying the path to a YAML file with overrides for the model configuration, applied at model initialization (path is given relative to the run configuration file used). This is in addition to the existing override setting, and is applied first (so override can override model_override).

  • new Run settings output.save_constraints and output.save_constraints_options

  • new Run setting parallel.post_run

  • changed Solution column names more in line with model component names

  • changed Can specify more than one output format as a list, e.g. output.format: ['csv', 'hdf']

  • changed Run setting parallel.additional_lines renamed to parallel.pre_run

  • changed Better error messages and CLI error handling

  • fixed Bug on saving YAML files with numpy dtypes fixed

  • Other minor improvements and fixes

0.3.1 (2015-01-06)

  • Fixes to time_functions

  • Other minor improvements and fixes

0.3.0 (2014-12-12)

  • Python 3 and Pyomo 4 are now minimum requirements

  • Significantly improved documentation

  • Improved model solution management by saving to HDF5 instead of CSV

  • Calculate shares of technologies, including the ability to define groups for the purpose of computing shares

  • Improved operational mode

  • Simplified time_tools

  • Improved output plotting, including dispatch, transmission flows, and installed capacities, and added model configuration to support these plots

  • r can be specified as power or energy

  • Improved solution speed

  • Better error messages and basic logging

  • Better sanity checking and error messages for common mistakes

  • Basic distance-dependent constraints (only implemented for e_loss and cost of e_cap for now)

  • Other improvements and fixes

0.2.0 (2014-03-18)

  • Added cost classes with a new set k

  • Added energy carriers with a new set c

  • Added conversion technologies

  • Speed improvements and simplifications

  • Ability to arbitrarily nest model configuration files with import statements

  • Added additional constraints

  • Improved configuration handling

  • Ability to define timestep options in run configuration

  • Cleared up terminology (nodes vs locations)

  • Improved TimeSummarizer masking and added new masks

  • Removed technology classes

  • Improved operational mode with results output matching planning mode and dynamic updating of parameters in model instance

  • Working parallel_tools

  • Improved documentation

  • Apache 2.0 licensed

  • Other improvements and fixes

0.1.0 (2013-12-10)

  • Some semblance of documentation

  • Usable built-in example model

  • Improved and working TimeSummarizer

  • More flexible masking for TimeSummarizer

  • Ability to add additional constraints without editing core source code

  • Some basic test coverage

  • Working parallel run configuration system

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