智能电网的能耗调度算法
DR StratComp stands for Demand-Response Strategies Comparator. Its purpose is
to assess the efficiency of different energy-consumption scheduling algorithms
in a smart power grid. This is the code associated with the paper
Incentive-based Energy Consumption Scheduling Algorithms for the Smart
Grid. I wrote it in
2010 during my internship with Pr George Kesidis at Penn State University.
DR StratComp requires Python 2.4+ with the matplotlib library. Execution goes
through the main.py file:
% python main.py
Look at the source code to find the different default scenarii available.
Format of the input files is rather loose. First four lines describe (in that
order) the values of L, the number of slots, C0 (constant cost) and C1 (overage
part of the cost function). Lines should look like this:
L = 3000nb_slots = 36C0 = 2.8e-6C1 = 2.8e-8
Anyway you can add anything you want after you specified the values of the
parameters. Hence, the following syntax is allowed (and recommanded):
L = 3000 kWnb_slots = 36 slots (10 min/slot)C0 = 2.8e-6 $/kW/s (slope 1 in the BC Hydro model)C1 = 2.8e-8 $/kW^2/s
Total duration is 6 hours (you can change it in scheduling.Settings.T). Energy
units are up to the test file, yet kW should be preferred. Please note that C0
and C1 must use second as “time component” of their units (this has an
incidence on the way costs are computed in scheduling.py).
Rest of the file describes the jobs. Next line indicates the number P of task
“packs”. Each of the P following lines describe a pack, and consist in two
integers and a floating point number, respectively the number of jobs, their
duration (in time slots) and their instant cost (in whatever unit you chose for
L), e.g.
51 15 462.242 30 132.1210 10 56.4210 20 17.5120 10 19.18