@@ -11,12 +11,12 @@ The following algorithms are available in this repository:
7) Algorithm combining 4) and 5)
The src/ directory includes three scripts, namely:
The src directory includes three scripts, namely:
- algorithms.jl, which implements algorithms 1) - 7)
- algorithms.jl, which implements algorithms 1. - 7.
- utilities.jl, which includes useful auxiliary functions
- main.jl, from which algorithms can be run
The data/ directory includes some toy data on which the algorithms can be tested. The data come from a renewable power plant siting problem, where a user-specified number of onshore wind sites (k) must be selected out of 3609 candidate sites in Europe so as to minimise the occurrence of simultaneous low electricity production events relative to a user-specified threshold (e.g., such that at least c sites produce simultaneously). Hourly-sampled meteorological data from the ERA5 database was transformed into so-called capacity factor data (reflecting the amount of electricity that each candidate site may produce during each hour, based on the type of power generation technology that may be deployed there). In total, capacity factor data are available for 744 hours (one month) and each candidate site. These data are stored in capacity_factors_matrix.p, which is a pickled file. Electricity demand data are stored in demand_vector.p, while technical potential (i.e., the maximum amount of capacity that may be deployed at a given site) data are stored in potential.p. The capacity factor, electricity demand and technical potential data are used to construct the D matrix.
The data directory includes some toy data on which the algorithms can be tested. The data come from a renewable power plant siting application, where a user-specified number of onshore wind sites (k) must be selected out of 3609 candidate sites in Europe so as to minimise the occurrence of simultaneous low electricity production events relative to a user-specified threshold (e.g., such that at least c sites produce simultaneously). Hourly-sampled wind speed data from the ERA5 database were transformed into so-called capacity factor data (reflecting the amount of electricity that each candidate site may produce during each hour, based on the type of power generation technology that may be deployed there). In total, capacity factor data are available for 744 hours (one month) and each candidate site. These data are stored in capacity_factors_matrix.p, which is a pickled file (the data can be extracted with functions provided in the utilities.jl script). Electricity demand data are stored in demand_vector.p, while technical potential (i.e., the maximum amount of capacity that may be deployed at a given site) data are stored in potential.p. The capacity factor, electricity demand and technical potential data are used to construct the D matrix, which is used in the MIP formulations of max k-multicover and is also used to compute the objective value in other algorithms.
Please feel free to email any requests or comments to mathias.berger@alumni.duke.edu.
