Hadar is a adequacy python library for deterministic and stochastic computation
Each kind of network has a needs of adequacy. On one side, some network nodes need to consume items such as watt, litter, package. And other side, some network nodes produce items. Applying adequacy on network, is tring to find the best available exchanges to avoid any lack at the best cost.
For example, a electric grid can have some nodes that can produce more power than they need and some nodes that do not produce enough power.
Above example is simple, but problem become very tricky with 10, 20 or 500 nodes !
Moreover all have a price ! Node can have many type of production, and each kind of production has its unit cost. Node can have also many consumptions with specific unavailability cost. Links between node have also max capacity and cost.
Network adequacy is not simple.
Hadar computes adequacy from simple to complex network. For example, to compute above network, just few lines need:
import hadar as hd
study = hd.Study(horizon=3)\
.network()\
.node('a')\
.consumption(cost=10 ** 6, quantity=[20, 20, 20], name='load')\
.production(cost=10, quantity=[30, 20, 10], name='prod')\
.node('b')\
.consumption(cost=10 ** 6, quantity=[20, 20, 20], name='load')\
.production(cost=10, quantity=[10, 20, 30], name='prod')\
.link(src='a', dest='b', quantity=[10, 10, 10], cost=2)\
.link(src='b', dest='a', quantity=[10, 10, 10], cost=2)\
.build()
optimizer = hd.LPOptimizer()
res = optimizer.solve(study)And few more lines to display graphics results.
plot = hd.HTMLPlotting(agg=hd.ResultAnalyzer(study, res),
node_coord={'a': [2.33, 48.86], 'b': [4.38, 50.83]})
plot.network().node('a').stack()
plot.network().map(t=0, zoom=2.5)Get more information and examples at https://www.hadar-simulator.org/