diff --git a/src/topupopt/problems/esipp/blocks/prices.py b/src/topupopt/problems/esipp/blocks/prices.py
index 48aae65e479ff7737c9096bc039c55ad87bc0582..8fc17ca0d1f5df77e235b10251cdd385d81422b3 100644
--- a/src/topupopt/problems/esipp/blocks/prices.py
+++ b/src/topupopt/problems/esipp/blocks/prices.py
@@ -205,7 +205,7 @@ def price_block_other(
# if not convex_price_function:
# # delta variables
- # model.var_delta_glqpks = pyo.Var(
+ # model.var_active_segment_glqpks = pyo.Var(
# model.set_GLQPKS, within=pyo.Binary
# )
@@ -214,7 +214,7 @@ def price_block_other(
# return (
# m.var_if_glqpks[(g,l,q,p,k,s)] <=
# m.param_v_max_glqpks[(g,l,q,p,k,s)]*
- # m.var_delta_glqpks[(g,l,q,p,k,s)]
+ # m.var_active_segment_glqpks[(g,l,q,p,k,s)]
# )
# model.constr_empty_segment_if_delta_zero_imp = pyo.Constraint(
# model.set_GLQPKS_imp, rule=rule_constr_empty_segment_if_delta_zero_imp
@@ -225,7 +225,7 @@ def price_block_other(
# return (
# m.var_ef_glqpks[(g,l,q,p,k,s)] <=
# m.param_v_max_glqpks[(g,l,q,p,k,s)]*
- # m.var_delta_glqpks[(g,l,q,p,k,s)]
+ # m.var_active_segment_glqpks[(g,l,q,p,k,s)]
# )
# model.constr_empty_segment_if_delta_zero_exp = pyo.Constraint(
# model.set_GLQPKS_exp, rule=rule_constr_empty_segment_if_delta_zero_exp
@@ -236,8 +236,8 @@ def price_block_other(
# if s == len(m.set_S)-1:
# return pyo.Constraint.Skip
# return (
- # m.var_delta_glqpks[(g,l,q,p,k,s)] >=
- # m.var_delta_glqpks[(g,l,q,p,k,s+1)]
+ # m.var_active_segment_glqpks[(g,l,q,p,k,s)] >=
+ # m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]
# )
# model.constr_delta_summing_logic = pyo.Constraint(
# model.set_GLQPKS, rule=rule_constr_delta_summing_logic
@@ -247,8 +247,8 @@ def price_block_other(
# if s == len(m.set_S)-1:
# return pyo.Constraint.Skip
# return (
- # 1-m.var_delta_glqpks[(g,l,q,p,k,s)] >=
- # m.var_delta_glqpks[(g,l,q,p,k,s+1)]
+ # 1-m.var_active_segment_glqpks[(g,l,q,p,k,s)] >=
+ # m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]
# )
# model.constr_delta_next_zeros = pyo.Constraint(
# model.set_GLQPKS, rule=rule_constr_delta_next_zeros
@@ -256,20 +256,261 @@ def price_block_other(
# *************************************************************************
# *************************************************************************
+
+
+# *****************************************************************************
+# *****************************************************************************
+
+# def price_other2(
+# model: pyo.AbstractModel,
+# convex_price_function: bool = False,
+# enable_default_values: bool = True,
+# enable_validation: bool = True,
+# enable_initialisation: bool = True
+# ):
+
+# # set of price segments
+# model.set_S = pyo.Set(model.set_GL_exp_imp, model.set_QPK)
+
+# # set of GLQKS tuples
+# def init_set_GLQPKS(m):
+# return (
+# (g, l, q, p, k, s)
+# # for (g,l) in m.set_GL_exp_imp
+# # for (q,k) in m.set_QK
+# for (g, l, q, p, k) in m.set_S
+# for s in m.set_S[(g, l, q, p, k)]
+# )
+
+# model.set_GLQPKS = pyo.Set(
+# dimen=6, initialize=(init_set_GLQPKS if enable_initialisation else None)
+# )
+
+# def init_set_GLQPKS_exp(m):
+# return (
+# glqpks for glqpks in m.set_GLQPKS if glqpks[1] in m.set_L_exp[glqpks[0]]
+# )
+
+# model.set_GLQPKS_exp = pyo.Set(
+# dimen=6, initialize=(init_set_GLQPKS_exp if enable_initialisation else None)
+# )
+
+# def init_set_GLQPKS_imp(m):
+# return (
+# glqpks for glqpks in m.set_GLQPKS if glqpks[1] in m.set_L_imp[glqpks[0]]
+# )
+
+# model.set_GLQPKS_imp = pyo.Set(
+# dimen=6, initialize=(init_set_GLQPKS_imp if enable_initialisation else None)
+# )
+
+# # *************************************************************************
+# # *************************************************************************
+
+# # parameters
+
+# # resource prices
+
+# model.param_p_glqpks = pyo.Param(model.set_GLQPKS, within=pyo.NonNegativeReals)
+
+# # maximum resource volumes for each prices
+
+# model.param_v_max_glqpks = pyo.Param(
+# model.set_GLQPKS,
+# within=pyo.NonNegativeReals
+# )
+
+# # *************************************************************************
+# # *************************************************************************
+
+# # variables
+
+# # *************************************************************************
+# # *************************************************************************
+
+# # exported flow
+
+# # TODO: validate the bounds by ensuring inf. cap. only exists in last segm.
+
+# def bounds_var_ef_glqpks(m, g, l, q, p, k, s):
+# if (g, l, q, p, k, s) in m.param_v_max_glqpks:
+# # predefined finite capacity
+# return (0, m.param_v_max_glqpks[(g, l, q, p, k, s)])
+# else:
+# # infinite capacity
+# return (0, None)
+
+# model.var_ef_glqpks = pyo.Var(
+# model.set_GLQPKS_exp, within=pyo.NonNegativeReals, bounds=bounds_var_ef_glqpks
+# )
+
+# # imported flow
+
+# def bounds_var_if_glqpks(m, g, l, q, p, k, s):
+# if (g, l, q, p, k, s) in m.param_v_max_glqpks:
+# # predefined finite capacity
+# return (0, m.param_v_max_glqpks[(g, l, q, p, k, s)])
+# else:
+# # infinite capacity
+# return (0, None)
+
+# model.var_if_glqpks = pyo.Var(
+# model.set_GLQPKS_imp, within=pyo.NonNegativeReals, bounds=bounds_var_if_glqpks
+# )
+
+# # *************************************************************************
+# # *************************************************************************
+
+# # exported flow revenue
+# def rule_constr_exp_flow_revenue(m, g, l, q, p, k):
+# return (
+# sum(
+# m.var_ef_glqpks[(g, l, q, p, k, s)]
+# * m.param_p_glqpks[(g, l, q, p, k, s)]
+# for s in m.set_S[(g, l, q, p, k)]
+# )
+# == m.var_efr_glqpk[(g, l, q, p, k)]
+# )
+
+# model.constr_exp_flow_revenue = pyo.Constraint(
+# model.set_GL_exp, model.set_QPK, rule=rule_constr_exp_flow_revenue
+# )
+
+# # imported flow cost
+# def rule_constr_imp_flow_cost(m, g, l, q, p, k):
+# return (
+# sum(
+# m.var_if_glqpks[(g, l, q, p, k, s)]
+# * m.param_p_glqpks[(g, l, q, p, k, s)]
+# for s in m.set_S[(g, l, q, p, k)]
+# )
+# == m.var_ifc_glqpk[(g, l, q, p, k)]
+# )
+
+# model.constr_imp_flow_cost = pyo.Constraint(
+# model.set_GL_imp, model.set_QPK, rule=rule_constr_imp_flow_cost
+# )
+
+# # exported flows
+# def rule_constr_exp_flows(m, g, l, q, p, k):
+# return sum(
+# m.var_v_glljqk[(g, l_star, l, j, q, k)]
+# * m.param_eta_glljqk[(g, l_star, l, j, q, k)]
+# for l_star in m.set_L[g]
+# if l_star not in m.set_L_exp[g]
+# for j in m.set_J[(g, l_star, l)] # only directed arcs
+# ) == sum(m.var_ef_glqpks[(g, l, q, p, k, s)] for s in m.set_S[(g, l, q, p, k)])
+
+# model.constr_exp_flows = pyo.Constraint(
+# model.set_GL_exp, model.set_QPK, rule=rule_constr_exp_flows
+# )
+
+# # imported flows
+# def rule_constr_imp_flows(m, g, l, q, p, k):
+# return sum(
+# m.var_v_glljqk[(g, l, l_star, j, q, k)]
+# for l_star in m.set_L[g]
+# if l_star not in m.set_L_imp[g]
+# for j in m.set_J[(g, l, l_star)] # only directed arcs
+# ) == sum(m.var_if_glqpks[(g, l, q, p, k, s)] for s in m.set_S[(g, l, q, p, k)])
+
+# model.constr_imp_flows = pyo.Constraint(
+# model.set_GL_imp, model.set_QPK, rule=rule_constr_imp_flows
+# )
+
+# # *************************************************************************
+# # *************************************************************************
+
+# # non-convex price functions
+
+# if not convex_price_function:
+
+# # delta variables
+# model.var_active_segment_glqpks = pyo.Var(
+# model.set_GLQPKS, within=pyo.Binary
+# )
+
+# # segments must be empty if the respective delta variable is zero
+# def rule_constr_empty_segment_if_delta_zero_imp(m, g, l, q, p, k, s):
+# return (
+# m.var_if_glqpks[(g,l,q,p,k,s)] <=
+# m.param_v_max_glqpks[(g,l,q,p,k,s)]*
+# m.var_active_segment_glqpks[(g,l,q,p,k,s)]
+# )
+# model.constr_empty_segment_if_delta_zero_imp = pyo.Constraint(
+# model.set_GLQPKS_imp, rule=rule_constr_empty_segment_if_delta_zero_imp
+# )
+
+# # segments must be empty if the respective delta variable is zero
+# def rule_constr_empty_segment_if_delta_zero_exp(m, g, l, q, p, k, s):
+# return (
+# m.var_ef_glqpks[(g,l,q,p,k,s)] <=
+# m.param_v_max_glqpks[(g,l,q,p,k,s)]*
+# m.var_active_segment_glqpks[(g,l,q,p,k,s)]
+# )
+# model.constr_empty_segment_if_delta_zero_exp = pyo.Constraint(
+# model.set_GLQPKS_exp, rule=rule_constr_empty_segment_if_delta_zero_exp
+# )
+
+# # if delta var is one, previous ones must be one too
+# # if delta var is zero, the next ones must also be zero
+# def rule_constr_delta_summing_logic(m, g, l, q, p, k, s):
+# if s == len(m.set_S[(g,l,q,p,k)])-1:
+# # last segment, skip
+# return pyo.Constraint.Skip
+# return (
+# m.var_active_segment_glqpks[(g,l,q,p,k,s)] >=
+# m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]
+# )
+# model.constr_delta_summing_logic = pyo.Constraint(
+# model.set_GLQPKS, rule=rule_constr_delta_summing_logic
+# )
+
+# # if a segment is not completely used, the next ones must remain empty
+# def rule_constr_fill_up_segment_before_next(m, g, l, q, p, k, s):
+# if s == len(m.set_S[(g,l,q,p,k)])-1:
+# # last segment, skip
+# return pyo.Constraint.Skip
+# if (g,l) in m.set_GL_imp:
+# return (
+# m.var_if_glqpks[(g,l,q,p,k,s)] >=
+# m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]*
+# m.param_v_max_glqpks[(g,l,q,p,k,s)]
+# )
+# else:
+# return (
+# m.var_ef_glqpks[(g,l,q,p,k,s)] >=
+# m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]*
+# m.param_v_max_glqpks[(g,l,q,p,k,s)]
+# )
+# # return (
+# # m.var_if_glqpks[(g,l,q,p,k,s)]/m.param_v_max_glqpks[(g,l,q,p,k,s)] >=
+# # m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]
+# # )
+# # return (
+# # m.param_v_max_glqpks[(g,l,q,p,k,s)]-m.var_if_glqpks[(g,l,q,p,k,s)] <=
+# # m.param_v_max_glqpks[(g,l,q,p,k,s)]*(1- m.var_active_segment_glqpks[(g,l,q,p,k,s+1)])
+# # )
+# model.constr_fill_up_segment_before_next = pyo.Constraint(
+# model.set_GLQPKS, rule=rule_constr_fill_up_segment_before_next
+# )
# *****************************************************************************
# *****************************************************************************
def price_other(
model: pyo.AbstractModel,
- convex_price_function: bool = False,
+ convex_price_function: bool = True,
enable_default_values: bool = True,
enable_validation: bool = True,
enable_initialisation: bool = True
):
+
+ # auxiliary set for pyomo
+ model.set_GLQPK = model.set_GL_exp_imp*model.set_QPK
# set of price segments
- model.set_S = pyo.Set(model.set_GL_exp_imp, model.set_QPK)
+ model.set_S = pyo.Set(model.set_GLQPK)
# set of GLQKS tuples
def init_set_GLQPKS(m):
@@ -285,24 +526,6 @@ def price_other(
dimen=6, initialize=(init_set_GLQPKS if enable_initialisation else None)
)
- def init_set_GLQPKS_exp(m):
- return (
- glqpks for glqpks in m.set_GLQPKS if glqpks[1] in m.set_L_exp[glqpks[0]]
- )
-
- model.set_GLQPKS_exp = pyo.Set(
- dimen=6, initialize=(init_set_GLQPKS_exp if enable_initialisation else None)
- )
-
- def init_set_GLQPKS_imp(m):
- return (
- glqpks for glqpks in m.set_GLQPKS if glqpks[1] in m.set_L_imp[glqpks[0]]
- )
-
- model.set_GLQPKS_imp = pyo.Set(
- dimen=6, initialize=(init_set_GLQPKS_imp if enable_initialisation else None)
- )
-
# *************************************************************************
# *************************************************************************
@@ -311,6 +534,13 @@ def price_other(
# resource prices
model.param_p_glqpks = pyo.Param(model.set_GLQPKS, within=pyo.NonNegativeReals)
+
+ # price function convexity
+
+ model.param_price_function_is_convex = pyo.Param(
+ model.set_GLQPK,
+ within=pyo.Boolean
+ )
# maximum resource volumes for each prices
@@ -327,172 +557,129 @@ def price_other(
# *************************************************************************
# *************************************************************************
- # exported flow
-
- # TODO: validate the bounds by ensuring inf. cap. only exists in last segm.
-
- def bounds_var_ef_glqpks(m, g, l, q, p, k, s):
+ # import and export flows
+ def bounds_var_trans_flows_glqpks(m, g, l, q, p, k, s):
if (g, l, q, p, k, s) in m.param_v_max_glqpks:
# predefined finite capacity
return (0, m.param_v_max_glqpks[(g, l, q, p, k, s)])
else:
# infinite capacity
return (0, None)
-
- model.var_ef_glqpks = pyo.Var(
- model.set_GLQPKS_exp, within=pyo.NonNegativeReals, bounds=bounds_var_ef_glqpks
- )
-
- # imported flow
-
- def bounds_var_if_glqpks(m, g, l, q, p, k, s):
- if (g, l, q, p, k, s) in m.param_v_max_glqpks:
- # predefined finite capacity
- return (0, m.param_v_max_glqpks[(g, l, q, p, k, s)])
- else:
- # infinite capacity
- return (0, None)
-
- model.var_if_glqpks = pyo.Var(
- model.set_GLQPKS_imp, within=pyo.NonNegativeReals, bounds=bounds_var_if_glqpks
+ model.var_trans_flows_glqpks = pyo.Var(
+ model.set_GLQPKS, within=pyo.NonNegativeReals, bounds=bounds_var_trans_flows_glqpks
)
# *************************************************************************
# *************************************************************************
- # exported flow revenue
- def rule_constr_exp_flow_revenue(m, g, l, q, p, k):
- return (
- sum(
- m.var_ef_glqpks[(g, l, q, p, k, s)]
- * m.param_p_glqpks[(g, l, q, p, k, s)]
- for s in m.set_S[(g, l, q, p, k)]
+ # import flow costs and export flow revenues
+ def rule_constr_trans_monetary_flows(m, g, l, q, p, k):
+ if (g,l) in m.set_GL_imp:
+ return (
+ sum(
+ m.var_trans_flows_glqpks[(g, l, q, p, k, s)]
+ * m.param_p_glqpks[(g, l, q, p, k, s)]
+ for s in m.set_S[(g, l, q, p, k)]
+ )
+ == m.var_ifc_glqpk[(g, l, q, p, k)]
)
- == m.var_efr_glqpk[(g, l, q, p, k)]
- )
-
- model.constr_exp_flow_revenue = pyo.Constraint(
- model.set_GL_exp, model.set_QPK, rule=rule_constr_exp_flow_revenue
- )
-
- # imported flow cost
- def rule_constr_imp_flow_cost(m, g, l, q, p, k):
- return (
- sum(
- m.var_if_glqpks[(g, l, q, p, k, s)]
- * m.param_p_glqpks[(g, l, q, p, k, s)]
- for s in m.set_S[(g, l, q, p, k)]
+ else:
+ return (
+ sum(
+ m.var_trans_flows_glqpks[(g, l, q, p, k, s)]
+ * m.param_p_glqpks[(g, l, q, p, k, s)]
+ for s in m.set_S[(g, l, q, p, k)]
+ )
+ == m.var_efr_glqpk[(g, l, q, p, k)]
)
- == m.var_ifc_glqpk[(g, l, q, p, k)]
- )
-
- model.constr_imp_flow_cost = pyo.Constraint(
- model.set_GL_imp, model.set_QPK, rule=rule_constr_imp_flow_cost
+ model.constr_trans_monetary_flows = pyo.Constraint(
+ model.set_GLQPK, rule=rule_constr_trans_monetary_flows
)
- # exported flows
- def rule_constr_exp_flows(m, g, l, q, p, k):
- return sum(
- m.var_v_glljqk[(g, l_star, l, j, q, k)]
- * m.param_eta_glljqk[(g, l_star, l, j, q, k)]
- for l_star in m.set_L[g]
- if l_star not in m.set_L_exp[g]
- for j in m.set_J[(g, l_star, l)] # only directed arcs
- ) == sum(m.var_ef_glqpks[(g, l, q, p, k, s)] for s in m.set_S[(g, l, q, p, k)])
-
- model.constr_exp_flows = pyo.Constraint(
- model.set_GL_exp, model.set_QPK, rule=rule_constr_exp_flows
- )
-
- # imported flows
- def rule_constr_imp_flows(m, g, l, q, p, k):
- return sum(
- m.var_v_glljqk[(g, l, l_star, j, q, k)]
- for l_star in m.set_L[g]
- if l_star not in m.set_L_imp[g]
- for j in m.set_J[(g, l, l_star)] # only directed arcs
- ) == sum(m.var_if_glqpks[(g, l, q, p, k, s)] for s in m.set_S[(g, l, q, p, k)])
+ # imported and exported flows
+ def rule_constr_trans_flows(m, g, l, q, p, k):
+ if (g,l) in m.set_GL_imp:
+ return sum(
+ m.var_v_glljqk[(g, l, l_star, j, q, k)]
+ for l_star in m.set_L[g]
+ if l_star not in m.set_L_imp[g]
+ for j in m.set_J[(g, l, l_star)] # only directed arcs
+ ) == sum(m.var_trans_flows_glqpks[(g, l, q, p, k, s)] for s in m.set_S[(g, l, q, p, k)])
+ else:
+ return sum(
+ m.var_v_glljqk[(g, l_star, l, j, q, k)]
+ * m.param_eta_glljqk[(g, l_star, l, j, q, k)]
+ for l_star in m.set_L[g]
+ if l_star not in m.set_L_exp[g]
+ for j in m.set_J[(g, l_star, l)] # only directed arcs
+ ) == sum(m.var_trans_flows_glqpks[(g, l, q, p, k, s)] for s in m.set_S[(g, l, q, p, k)])
- model.constr_imp_flows = pyo.Constraint(
- model.set_GL_imp, model.set_QPK, rule=rule_constr_imp_flows
+ model.constr_trans_flows = pyo.Constraint(
+ model.set_GLQPK, rule=rule_constr_trans_flows
)
# *************************************************************************
# *************************************************************************
# non-convex price functions
-
- if not convex_price_function:
-
- # delta variables
- model.var_delta_glqpks = pyo.Var(
- model.set_GLQPKS, within=pyo.Binary
- )
- # segments must be empty if the respective delta variable is zero
- def rule_constr_empty_segment_if_delta_zero_imp(m, g, l, q, p, k, s):
- return (
- m.var_if_glqpks[(g,l,q,p,k,s)] <=
- m.param_v_max_glqpks[(g,l,q,p,k,s)]*
- m.var_delta_glqpks[(g,l,q,p,k,s)]
- )
- model.constr_empty_segment_if_delta_zero_imp = pyo.Constraint(
- model.set_GLQPKS_imp, rule=rule_constr_empty_segment_if_delta_zero_imp
- )
-
- # segments must be empty if the respective delta variable is zero
- def rule_constr_empty_segment_if_delta_zero_exp(m, g, l, q, p, k, s):
- return (
- m.var_ef_glqpks[(g,l,q,p,k,s)] <=
- m.param_v_max_glqpks[(g,l,q,p,k,s)]*
- m.var_delta_glqpks[(g,l,q,p,k,s)]
- )
- model.constr_empty_segment_if_delta_zero_exp = pyo.Constraint(
- model.set_GLQPKS_exp, rule=rule_constr_empty_segment_if_delta_zero_exp
+ # delta variables
+ model.var_active_segment_glqpks = pyo.Var(
+ model.set_GLQPKS, within=pyo.Binary
+ )
+
+ # segments must be empty if the respective delta variable is zero
+ def rule_constr_empty_segment_if_delta_zero(m, g, l, q, p, k, s):
+ if len(m.set_S[(g,l,q,p,k)]) == 1 or m.param_price_function_is_convex[(g,l,q,p,k)]:
+ # single segment, skip
+ # convex, skip
+ return pyo.Constraint.Skip
+ return (
+ m.var_trans_flows_glqpks[(g,l,q,p,k,s)] <=
+ m.param_v_max_glqpks[(g,l,q,p,k,s)]*
+ m.var_active_segment_glqpks[(g,l,q,p,k,s)]
)
-
- # if delta var is one, previous ones must be one too
- # if delta var is zero, the next ones must also be zero
- def rule_constr_delta_summing_logic(m, g, l, q, p, k, s):
- if s == len(m.set_S[(g,l,q,p,k)])-1:
- # last segment, skip
- return pyo.Constraint.Skip
- return (
- m.var_delta_glqpks[(g,l,q,p,k,s)] >=
- m.var_delta_glqpks[(g,l,q,p,k,s+1)]
- )
- model.constr_delta_summing_logic = pyo.Constraint(
- model.set_GLQPKS, rule=rule_constr_delta_summing_logic
+ model.constr_empty_segment_if_delta_zero = pyo.Constraint(
+ model.set_GLQPKS, rule=rule_constr_empty_segment_if_delta_zero
+ )
+
+ # if delta var is one, previous ones must be one too
+ # if delta var is zero, the next ones must also be zero
+ def rule_constr_delta_summing_logic(m, g, l, q, p, k, s):
+ if s == len(m.set_S[(g,l,q,p,k)])-1 or m.param_price_function_is_convex[(g,l,q,p,k)]:
+ # last segment, skip
+ # convex, skip
+ return pyo.Constraint.Skip
+ return (
+ m.var_active_segment_glqpks[(g,l,q,p,k,s)] >=
+ m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]
)
-
- # if a segment is not completely used, the next ones must remain empty
- def rule_constr_fill_up_segment_before_next(m, g, l, q, p, k, s):
- if s == len(m.set_S[(g,l,q,p,k)])-1:
- # last segment, skip
- return pyo.Constraint.Skip
- if (g,l) in m.set_GL_imp:
- return (
- m.var_if_glqpks[(g,l,q,p,k,s)] >=
- m.var_delta_glqpks[(g,l,q,p,k,s+1)]*
- m.param_v_max_glqpks[(g,l,q,p,k,s)]
- )
- else:
- return (
- m.var_ef_glqpks[(g,l,q,p,k,s)] >=
- m.var_delta_glqpks[(g,l,q,p,k,s+1)]*
- m.param_v_max_glqpks[(g,l,q,p,k,s)]
- )
- # return (
- # m.var_if_glqpks[(g,l,q,p,k,s)]/m.param_v_max_glqpks[(g,l,q,p,k,s)] >=
- # m.var_delta_glqpks[(g,l,q,p,k,s+1)]
- # )
- # return (
- # m.param_v_max_glqpks[(g,l,q,p,k,s)]-m.var_if_glqpks[(g,l,q,p,k,s)] <=
- # m.param_v_max_glqpks[(g,l,q,p,k,s)]*(1- m.var_delta_glqpks[(g,l,q,p,k,s+1)])
- # )
- model.constr_fill_up_segment_before_next = pyo.Constraint(
- model.set_GLQPKS, rule=rule_constr_fill_up_segment_before_next
+ model.constr_delta_summing_logic = pyo.Constraint(
+ model.set_GLQPKS, rule=rule_constr_delta_summing_logic
+ )
+
+ # if a segment is not completely used, the next ones must remain empty
+ def rule_constr_fill_up_segment_before_next(m, g, l, q, p, k, s):
+ if s == len(m.set_S[(g,l,q,p,k)])-1 or m.param_price_function_is_convex[(g,l,q,p,k)]:
+ # last segment, skip
+ # convex, skip
+ return pyo.Constraint.Skip
+ return (
+ m.var_trans_flows_glqpks[(g,l,q,p,k,s)] >=
+ m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]*
+ m.param_v_max_glqpks[(g,l,q,p,k,s)]
)
+ # return (
+ # m.var_if_glqpks[(g,l,q,p,k,s)]/m.param_v_max_glqpks[(g,l,q,p,k,s)] >=
+ # m.var_active_segment_glqpks[(g,l,q,p,k,s+1)]
+ # )
+ # return (
+ # m.param_v_max_glqpks[(g,l,q,p,k,s)]-m.var_if_glqpks[(g,l,q,p,k,s)] <=
+ # m.param_v_max_glqpks[(g,l,q,p,k,s)]*(1- m.var_active_segment_glqpks[(g,l,q,p,k,s+1)])
+ # )
+ model.constr_fill_up_segment_before_next = pyo.Constraint(
+ model.set_GLQPKS, rule=rule_constr_fill_up_segment_before_next
+ )
# *****************************************************************************
# *****************************************************************************
diff --git a/src/topupopt/problems/esipp/problem.py b/src/topupopt/problems/esipp/problem.py
index 5b2a5707492400360d4b7c66ff1df11c319b87f9..3659ad67caea582d20dab8d2251aa3d023987d71 100644
--- a/src/topupopt/problems/esipp/problem.py
+++ b/src/topupopt/problems/esipp/problem.py
@@ -2549,6 +2549,17 @@ class InfrastructurePlanningProblem(EnergySystem):
for s in set_S[(g, l, q, p, k)]
}
+ # price function convexity
+
+ param_price_function_is_convex = {
+ (g, l, q, p, k): (
+ self.networks[g].nodes[l][Network.KEY_NODE_PRICES][(q, p, k)].price_monotonically_increasing_with_volume()
+ if l in set_L_imp[g] else
+ self.networks[g].nodes[l][Network.KEY_NODE_PRICES][(q, p, k)].price_monotonically_decreasing_with_volume()
+ )
+ for (g, l, q, p, k) in set_S
+ }
+
# maximum resource volume per segment (infinity is the default)
param_v_max_glqpks = {
@@ -3451,6 +3462,7 @@ class InfrastructurePlanningProblem(EnergySystem):
"param_c_df_qp": param_c_df_qp,
"param_c_time_qpk": param_c_time_qpk,
"param_p_glqpks": param_p_glqpks,
+ "param_price_function_is_convex": param_price_function_is_convex,
"param_v_max_glqpks": param_v_max_glqpks,
# *****************************************************************
# converters
diff --git a/src/topupopt/problems/esipp/utils.py b/src/topupopt/problems/esipp/utils.py
index 94c3f790cc9049638b683fd2dc4443cabdc0d323..4047696c1311ed28b21307510000cd5c8638cbf9 100644
--- a/src/topupopt/problems/esipp/utils.py
+++ b/src/topupopt/problems/esipp/utils.py
@@ -99,7 +99,7 @@ def statistics(ipp: InfrastructurePlanningProblem,
imports_qpk = {
qpk: pyo.value(
sum(
- ipp.instance.var_if_glqpks[(g,l_imp,*qpk, s)]
+ ipp.instance.var_trans_flows_glqpks[(g,l_imp,*qpk, s)]
for g, l_imp in import_node_keys
# for g in ipp.networks
# for l_imp in ipp.networks[g].import_nodes
@@ -114,7 +114,7 @@ def statistics(ipp: InfrastructurePlanningProblem,
exports_qpk = {
qpk: pyo.value(
sum(
- ipp.instance.var_ef_glqpks[(g,l_exp,*qpk, s)]
+ ipp.instance.var_trans_flows_glqpks[(g,l_exp,*qpk, s)]
for g, l_exp in export_node_keys
# for g in ipp.networks
# for l_exp in ipp.networks[g].export_nodes
diff --git a/tests/test_esipp_prices.py b/tests/test_esipp_prices.py
index 31e4c55d7b5638d1a10fe0cf5896545cf1656f72..783304755c4d764ac00cd70e0ac0da3deb620f71 100644
--- a/tests/test_esipp_prices.py
+++ b/tests/test_esipp_prices.py
@@ -629,8 +629,6 @@ class TestESIPPProblem:
# the objective function should be -7.5
assert math.isclose(pyo.value(ipp.instance.obj_f), -2.0, abs_tol=1e-3)
- # TODO: trigger errors with infinite capacity segments in non-convex functions
-
# *************************************************************************
# *************************************************************************