Backbone is a generic energy network optimization tool written in [GAMS](https://www.gams.com/). It has been designed to be highly adaptable in different dimensions: temporal, spatial, technology representation and market design. The model can represent stochastics with a model predictive control method [1], with short-term forecasts and longer-term statistical uncertainties. Backbone can support multiple different models due to the modifiable temporal structure and varying lengths of the time steps.
Backbone is a generic energy network optimization tool written in [GAMS](https://www.gams.com/). It has been designed to be highly adaptable in different dimensions: temporal, spatial, technology representation and market design. The model can represent stochastics with a [model predictive control method](https://doi.org/10.1016/j.automatica.2008.03.002), with short-term forecasts and longer-term statistical uncertainties. Backbone can support multiple different models due to the modifiable temporal structure and varying lengths of the time steps.
[1] Nolde, K., Uhr, M., & Morari, M. (2008). Medium term scheduling of a hydro-thermal system using stochastic model predictive control. Automatica, 1585-1594.
If you use Backbone in a published work, please cite the [following publication](https://doi.org/10.3390/en12173388), which describes the Backbone energy systems modelling framework.
## Getting Started
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@@ -10,7 +10,9 @@ Make sure that you have [Git](https://git-scm.com/) version control system and a
In order to get a copy of the Backbone project, you need to clone it using Git. Copy and paste the URL of the original Backbone repository and select the directory where you want Backbone to be cloned. The URL of the original Backbone repository is https://gitlab.vtt.fi/backbone/backbone.
You should now have *Backbone.gms*, a few additional files and three subdirectories in the directory where you cloned Backbone. Note that you need to manually create two additional subdirectories in order to get Backbone working. These subdirectories should be named *input* and *output* and they should be created in the same directory where *Backbone.gms* is.
You should now have *Backbone.gms*, a few additional files and five subdirectories in the directory where you cloned Backbone.
Small example input datasets are provided online in the [wiki](https://gitlab.vtt.fi/backbone/backbone/wikis/Example-data-sets).
## Model File Structure
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* 2d_constraints.gms - Contains definitions for constraint equations.
**Model Definition Files* - Contains GAMS definitions for different models, essentially lists the equations (constraints) that apply. Current files include *schedule.gms*, *building.gms* and *invest.gms*.
* 3a_periodicInit.gms - Initializes various data and sets for the solve loop.
* 3b_inputsLoop.gms- Instructions for possible data import inside the solve loop, as well as forecast in-the-loop improvements.
* 3c_periodicLoop.gms - Contains instructions for the forecast-time structure of the desired model.
* 3b_periodicLoop.gms- Contains instructions for the forecast-interval structure of the desired model.
* 3c_inputsLoop.gms - Contains instructions for updating the forecast data, optional forecast improvements, aggregating time series data for the time intervals, and other input data processing.
* 3d_setVariableLimits.gms - Defines the variable boundaries for each solve.
* 3e_solve.gms - Contains the GAMS solve command for using the solver.
* 3f_afterSolve.gms - Fixes some variable values after solve.
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@@ -45,7 +47,7 @@ Most of these files are under *\inc* in the Backbone folder, except for the mode
* timeAndSamples.inc - Contains definitions for the time, forecast and sample index ranges.
* modelsInit.gms - Contains model parameters for the solve (or a link to a template under *\defModels* to be used). Useful for any additional GAMS scripting.
Backbone folder contains three template files *1_options_temp.gms*, *timeAndSamples_temp.inc*, and *modelsInit_temp.gms* to provide examples of the input format. These files can be copied into *\input* and renamed to *1_options.gms*, *timeAndSamples.inc*, and *modelsInit.gms*.
Backbone folder contains template files *1_options_temp.gms*, *timeAndSamples_temp.inc*, and *modelsInit_temp.gms* to provide examples of the input format. These files can be copied into *\input* and renamed to *1_options.gms*, *timeAndSamples.inc*, and *modelsInit.gms*.
## When Simply Using Backbone
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* --- Define Time Step Intervals ----------------------------------------------
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@@ -78,6 +82,10 @@ if (mType('invest'),
// Define the number of forecasts used by the model
mSettings('invest', 'forecasts') = 0;
// Define which nodes and timeseries use forecasts
//Option clear = gn_forecasts; // By default includes everything, so clear first
//gn_forecasts('wind', 'XXX', 'ts_cf') = yes;
// Define forecast properties and features
mSettings('invest', 't_forecastStart') = 0; // At which time step the first forecast is available ( 1 = t000001 )
mSettings('invest', 't_forecastLengthUnchanging') = 0; // Length of forecasts in time steps - this does not decrease when the solve moves forward (requires forecast data that is longer than the horizon at first)
// Define the number of forecasts used by the model
mSettings('schedule', 'forecasts') = 3;
// Define which nodes and timeseries use forecasts
//Option clear = gn_forecasts; // By default includes everything, so clear first
//gn_forecasts('wind', 'XXX', 'ts_cf') = yes;
// Define forecast properties and features
mSettings('schedule', 't_forecastStart') = 1; // At which time step the first forecast is available ( 1 = t000001 )
mSettings('schedule', 't_forecastLengthUnchanging') = 36; // Length of forecasts in time steps - this does not decrease when the solve moves forward (requires forecast data that is longer than the horizon at first)
q_maxDownward(grid, node, unit, mType, s, f, t) "Downward commitments will not undercut power plant minimum load constraints or maximum elec. consumption"
q_maxUpward(grid, node, unit, mType, s, f, t) "Upward commitments will not exceed maximum available capacity or consumed power"
q_reserveProvision(restype, up_down, grid, node, unit, s, f, t) "Reserve provision limited for units"
q_maxDownward(grid, node, unit, mType, s, f, t) "Downward commitments (v_gen and online v_reserve) will not undercut minimum (online) production capacity (+) or maximum (online) consumption capacity (-)"
q_maxDownwardOfflineReserve(grid, node, unit, mType, s, f, t) "Downward commitments (v_gen and all v_reserve) will not undercut zero production (+) or maximum consumption capacity (-)"
q_maxUpward(grid, node, unit, mType, s, f, t) "Upward commitments (v_gen and online v_reserve) will not exceed maximum (online) production capacity (+) or minimum (online) consumption capacity (-)"
q_maxUpwardOfflineReserve(grid, node, unit, mType, s, f, t) "Upward commitments (v_gen and all v_reserve) will not exceed maximum production capacity (+) or zero consumption (-)"
q_reserveProvision(restype, up_down, grid, node, unit, s, f, t) "Reserve provision limited for units with investment possibility"
q_reserveProvisionOnline(restype, up_down, grid, node, unit, s, f, t) "Reserve provision limited for units that are not capable of providing offline reserve"
q_startshut(mType, s, unit, f, t) "Online capacity now minus online capacity in the previous interval is equal to started up minus shut down capacity"
q_startuptype(mType, s, starttype, unit, f, t) "Startup type depends on the time the unit has been non-operational"
q_onlineOnStartUp(s, unit, f, t) "Unit must be online after starting up"
and not gnuOfflineRescapable(restype, grid, node, unit)
},
+ v_reserve(restype, 'down', grid, node, unit, s, f+df_reserves(grid, node, restype, f, t), t) // (v_reserve can be used only if the unit is capable of providing a particular reserve)
and not gnuOfflineRescapable(restype, grid, node, unit)
},
+ v_reserve(restype, 'up', grid, node, unit, s, f+df_reserves(grid, node, restype, f, t), t) // (v_reserve can be used only if the unit is capable of providing a particular reserve)
and not gnuOfflineRescapable(restype, grid, node, unit)
},
+ v_reserve(restype, 'down', grid, node, unit, s, f+df_reserves(grid, node, restype, f, t), t) // (v_reserve can be used only if the unit is capable of providing a particular reserve)
) // END sum(nuRescapable)
/ p_stepLength(m, f, t)
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@@ -2532,7 +2691,7 @@ q_boundCyclic(gnss_bound(gn_state(grid, node), s_, s), m)
and tSolveFirst = mSettings(m, 't_start')
}..
// Initial value of the state of the node at the start of the sample
// Initial value of the state of the node at the start of the sample s
