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.vscode/settings.json

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+{
+}

LICENSE.md

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 MIT License
 
-Copyright © 2021-2023 by Evelise de G. Antunes, Nabil Sadou and Pierre Haessig
+Copyright © 2021-2023 by Evelise de G. Antunes, Nabil Sadou Pierre Haessig and Jean Fructhieu NIKIEMA
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

Optimization/BB_toolbox.jl

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+using Microgrids
+using NLopt
+
+
+"Multi-objective criterion for microgrid performance: lcoe, shedding rate"
+function obj_multi(x= X,capex=capex_def,dispatch=dispatch_1,load=Pload,cf_pv=Ppv1k,cf_wind=cf_wind)
+         mg=new_microgrid(Sizing((1000*x)...),capex,ini_filling_state,load,cf_wind,cf_pv)
+    mg,traj,stats, costs = simulate_double(mg,capex,dispatch)
+    # Extract KPIs of interest
+    lcoe = costs.lcoe # $/kWh
+    shed_rate = stats.shed_rate; # in [0,1]
+    return lcoe, shed_rate
+end
+
+"""Mono-objective criterion: LCOE + penalty if shedding rate > `shed_max`
+
+with signature adapted to NLopt with `grad` as 2nd argument
+
+load shedding penalty threshold `shed_max` should be in  [0,1[
+"""
+function obj(x,grad, shed_max,capex=capex_def,dispatch=dispatch_1, w_shed_max=1e5,load=Pload,cf_pv=Ppv1k,cf_wind=cf_wind)
+    lcoe, shed_rate =  obj_multi(x,capex,dispatch,load,cf_pv,cf_wind)
+    over_shed = shed_rate - shed_max
+    if over_shed > 0.0
+        penalty = w_shed_max*over_shed
+    else
+        penalty = 0.0
+    end
+    J = lcoe + penalty
+end
+
+"""Optimize sizing of microgrid based on the `obj` function
+
+Parameters:
+- `x0`: initial sizing (for the algorithms which need them)
+- `shed_max`: load shedding penalty threshold (same as in `obj`)
+- `algo` could be one of LN_SBPLX, GN_DIRECT, GN_ESCH...
+- `maxeval`: maximum allowed number of calls to the objective function,
+  that is to the microgrid simulation
+- `xtol_rel`: termination condition based on relative change of sizing, see NLopt doc.
+- `srand`: random number generation seed (for algorithms which use some stochastic search)
+
+"""
+function optim_mg(x0, shed_max, xmin,xmax, algo=:GN_CRS2_LM, maxeval=1000, xtol_rel=1e-8, srand=1,load=Pload,cf_pv=Ppv1k,cf_wind=cf_wind)
+    nx = length(x0) # number of optim variables
+    opt = Opt(algo, nx)
+    NLopt.srand(srand)
+
+    opt.lower_bounds = xmin
+    opt.upper_bounds = xmax
+    opt.min_objective = (x, grad) -> obj(x, grad, shed_max,capex_def,Microgrids.dispatch_1,1e5,load,cf_pv,cf_wind)
+    opt.xtol_rel = xtol_rel
+    opt.maxeval = maxeval
+
+    (fopt, xopt, ret) = optimize(opt, x0)
+    return xopt, ret, opt.numevals
+end