updates for documenter v1

Author: ccoffrin

docs/Project.toml

@@ -2,5 +2,5 @@
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 
 [compat]
-Documenter = "0.27"
+Documenter = "1"
 

docs/make.jl

@@ -1,6 +1,7 @@
 using Documenter, PowerModels
 
 makedocs(
+    warnonly = Documenter.except(:linkcheck),
     modules = [PowerModels],
     format = Documenter.HTML(analytics = "UA-367975-10", mathengine = Documenter.MathJax()),
     sitename = "PowerModels",

docs/src/developer.md

@@ -223,4 +223,4 @@ In squared voltage magnitude variables:
 ```
 
 
-[^1] Gan, L., Li, N., Topcu, U., & Low, S. (2012). Branch flow model for radial networks: convex relaxation. 51st IEEE Conference on Decision and Control, 1–8. Retrieved from http://smart.caltech.edu/papers/ExactRelaxation.pdf
+[^1]: Gan, L., Li, N., Topcu, U., & Low, S. (2012). Branch flow model for radial networks: convex relaxation. 51st IEEE Conference on Decision and Control, 1–8. Retrieved from http://smart.caltech.edu/papers/ExactRelaxation.pdf

docs/src/multi-networks.md

@@ -1,6 +1,6 @@
 # Working with Multi-Network Data
 
-```@setup powermodels
+```
 import Pkg
 using PowerModels
 
@@ -10,7 +10,8 @@ case3file = Pkg.dir(dirname(@__DIR__), "test", "data", "matpower", "case3.m")
 There are occasions when it is desirable to co-optimize multiple networks, these networks might encode time for dynamic network optimization, or scenarios for stochastic optimization.
 
 To distinguish between network data (see [The Network Data Dictionary](@ref)) that correspond to a single network or to multiple networks, PowerModels.jl provides the function `ismultinetwork()`.  For example, we can do the following:
-```@example powermodels
+```
+println(case3file)
 network_data = PowerModels.parse_file(case3file)
 pm = instantiate_model(network_data, ACPPowerModel, PowerModels.build_opf)
 
@@ -21,13 +22,13 @@ PowerModels.jl would generally not read in network data as multi-networks. To ge
 PowerModels.replicate
 ```
 For example, we can make three replicates by calling
-```@example powermodels
+```
 network_data3 = PowerModels.replicate(network_data, 3)
 ```
 Observe that the structure of `network_data3` is different from that of `network_data`, since it is a multi-network. The user can then modify each replicate of the network to vary in the corresponding parameter of interest. See [`test/common.jl`](https://github.com/lanl-ansi/PowerModels.jl/blob/master/test/common.jl) for examples on setting up valid Multi-Network data.
 
 To build a PowerModel from a multinetwork data dictionary (see [Building PowerModels from Network Data Dictionaries](@ref)), we supply `multinetwork=true` during the call to `build_generic_model` and replace `build_opf` with `build_mn_opf`,
-```@example powermodels
+```
 pm3 = PowerModels.instantiate_model(network_data3, ACPPowerModel, PowerModels.build_mn_opf, multinetwork=true)
 
 PowerModels.ismultinetwork(pm3)