code: def convex_comb_agg(model,a,b):
      
      K = len(a)-1
      w,z = {},{}
      for k in range(K+1):
          w[k] = model.addVar(lb=0, ub=1, vtype="C")
      for k in range(K):
          z[k] = model.addVar(vtype="B")
      X = model.addVar(lb=a[0], ub=a[K], vtype="C")
      Y = model.addVar(lb=-model.infinity(), vtype="C")
  
      model.addCons(X == quicksum(a[k]*w[k] for k in range(K+1)))
      model.addCons(Y == quicksum(b[k]*w[k] for k in range(K+1)))
      model.addCons(w[0] <= z[0])
      model.addCons(w[K] <= z[K-1])
      for k in range(1,K):
          model.addCons(w[k] <= z[k-1]+z[k])
      model.addCons(quicksum(w[k] for k in range(K+1)) == 1)
      model.addCons(quicksum(z[k] for k in range(K)) == 1)
      return X,Y,z
docs: convex_comb_agg -- add piecewise relation convex combination formulation -- non-disaggregated.
      Parameters:
          - model: a model where to include the piecewise linear relation
          - a[k]: x-coordinate of the k-th point in the piecewise linear relation
          - b[k]: y-coordinate of the k-th point in the piecewise linear relation
      Returns the model with the piecewise linear relation on added variables X, Y, and z.