Workflow

Generally, the workflow requires three steps:

• load data
• clustering
• optimization

CEP Specific Workflow

The input data is distinguished between time series independent and time series dependent data. They are kept separate as just the time series dependent data is used to determine representative periods (clustering).

Example Workflow

using ClustForOpt

# load data (electricity price day ahead market)
ts_input_data, = load_timeseries_data("DAM", "GER";K=365, T=24) #DAM

# run standard kmeans clustering algorithm to cluster into 5 representative periods, with 1000 initial starting points
clust_res = run_clust(ts_input_data;method="kmeans",representation="centroid",n_clust=5,n_init=1000)

# battery operations optimization on the clustered data
opt_res = run_opt(clust_res)