Speak of time steps in minimum "time" constraints

The constraints are actually defined in time steps.
(The documentation asked for integers before, so it
could be seen from the context.)

src/oemof/solph/_options.py

@@ -185,13 +185,13 @@ class NonConvex:
     inactivity_costs : numeric (iterable or scalar)
         Costs associated with not operating the flow.
     minimum_uptime : numeric (1 or positive integer)
-        Minimum time that a flow must be greater then its minimum flow after
-        startup. Be aware that minimum up and downtimes can contradict each
-        other and may lead to infeasible problems.
+        Minimum number of time steps that a flow must be greater then its
+        minimum flow after startup. Be aware that minimum up and downtimes
+        can contradict each other and may lead to infeasible problems.
     minimum_downtime : numeric (1 or positive integer)
-        Minimum time a flow is forced to zero after shutting down.
-        Be aware that minimum up and downtimes can contradict each
-        other and may to infeasible problems.
+        Minimum number of time steps a flow is forced to zero after
+        shutting down. Be aware that minimum up and downtimes can
+        contradict each other and may to infeasible problems.
     maximum_startups : numeric (0 or positive integer)
         Maximum number of start-ups in the optimization timeframe.
     maximum_shutdowns : numeric (0 or positive integer)