From a4b3fb3747706b5efc8def62f203f09509890eb7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Pedro=20L=2E=20Magalh=C3=A3es?= <pmlpm@posteo.de>
Date: Fri, 26 Jul 2024 01:01:23 +0200
Subject: [PATCH] Implemented the price functions using a block component.
---
src/topupopt/problems/esipp/blocks/prices.py | 626 +++++--------------
src/topupopt/problems/esipp/model.py | 11 +-
src/topupopt/problems/esipp/problem.py | 12 +-
tests/test_esipp_prices.py | 2 +-
4 files changed, 177 insertions(+), 474 deletions(-)
diff --git a/src/topupopt/problems/esipp/blocks/prices.py b/src/topupopt/problems/esipp/blocks/prices.py
index 404c852..870a71e 100644
--- a/src/topupopt/problems/esipp/blocks/prices.py
+++ b/src/topupopt/problems/esipp/blocks/prices.py
@@ -1,10 +1,12 @@
# imports
import pyomo.environ as pyo
+import math
+
# *****************************************************************************
# *****************************************************************************
-def add_prices_block(
+def add_price_functions(
model: pyo.AbstractModel,
**kwargs
):
@@ -12,18 +14,18 @@ def add_prices_block(
# *************************************************************************
# *************************************************************************
- # model.node_price_block = pyo.Block(model.set_QPK)
-
- price_other(model, **kwargs)
- # price_block_other(model, **kwargs)
+ # price_other(model, **kwargs)
+ price_other_block(model, **kwargs)
+
+ # *************************************************************************
+ # *************************************************************************
# *****************************************************************************
# *****************************************************************************
-# TODO: try to implement it as a block (might make things look cleaner)
-def price_block_other(
+def price_other_block(
model: pyo.AbstractModel,
- convex_price_function: bool = True,
+ # convex_price_function: bool = True,
enable_default_values: bool = True,
enable_validation: bool = True,
enable_initialisation: bool = True
@@ -31,485 +33,177 @@ def price_block_other(
# auxiliary set for pyomo
model.set_GLQPK = model.set_GL_exp_imp*model.set_QPK
+
+ # create a block for a transshipment node during a given time interval
+ def rule_block_prices(b, g, l, q, p, k):
+
+ # *********************************************************************
+ # *********************************************************************
+
+ # sets
+
+ # set of price segments
+ b.set_S = pyo.Set()
+
+ # TODO: introduce a set of price segments for non-convex tariffs
+ # def init_set_S_nonconvex(b, s):
+ # return (s for s in b.set_S if b.param_price_function_is_convex)
+ # b.set_S_nonconvex = pyo.Set(within=b.set_S, initialize=init_set_S_nonconvex)
+
+ # *********************************************************************
+ # *********************************************************************
+
+ # parameters
- # set of price segments
- model.set_S = pyo.Set(model.set_GLQPK)
-
- # 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)
- )
-
- # *************************************************************************
- # *************************************************************************
-
- # parameters
-
- # resource prices
+ # resource prices
+ b.param_p_s = pyo.Param(b.set_S, within=pyo.NonNegativeReals)
+
+ # price function convexity
+ b.param_price_function_is_convex = pyo.Param(within=pyo.Boolean)
- model.param_p_glqpks = pyo.Param(model.set_GLQPKS, within=pyo.NonNegativeReals)
+ # maximum resource volumes for each prices
+ b.param_v_max_s = pyo.Param(b.set_S, within=pyo.NonNegativeReals)
- # price function convexity
-
- model.param_price_function_is_convex = pyo.Param(
- model.set_GLQPK,
- within=pyo.Boolean
+ # *********************************************************************
+ # *********************************************************************
+
+ # variables
+
+ # *********************************************************************
+ # *********************************************************************
+
+ # TODO: consider replacing None in the bounds with inf in the parameter
+
+ # import and export flows
+ def bounds_var_trans_flows_s(b, s):
+ if s in b.param_v_max_s:
+ # predefined finite capacity
+ return (0, b.param_v_max_s[s])
+ else:
+ # infinite capacity
+ return (0, None)
+ b.var_trans_flows_s = pyo.Var(
+ b.set_S,
+ within=pyo.NonNegativeReals,
+ bounds=bounds_var_trans_flows_s
)
-
- # maximum resource volumes for each prices
-
- model.param_v_max_glqpks = pyo.Param(
- model.set_GLQPKS,
- within=pyo.NonNegativeReals
+
+ # *********************************************************************
+ # *********************************************************************
+
+ # import flow costs and export flow revenues
+ def rule_constr_trans_monetary_flows(b):
+ if (g,l) in b.parent_block().set_GL_imp:
+ return (
+ sum(b.var_trans_flows_s[s]*b.param_p_s[s]
+ for s in b.set_S)
+ == b.parent_block().var_ifc_glqpk[(g,l,q,p,k)]
+ )
+ else:
+ return (
+ sum(b.var_trans_flows_s[s]*b.param_p_s[s]
+ for s in b.set_S)
+ == b.parent_block().var_efr_glqpk[(g,l,q,p,k)]
+ )
+ b.constr_trans_monetary_flows = pyo.Constraint(
+ rule=rule_constr_trans_monetary_flows
)
- \
- # price block
- model.price_block = pyo.Block(model.set_GLQPK)
-
- # *************************************************************************
- # *************************************************************************
-
- # variables
-
- # *************************************************************************
- # *************************************************************************
-
- # 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_trans_flows_glqpks = pyo.Var(
- model.set_GLQPKS, within=pyo.NonNegativeReals, bounds=bounds_var_trans_flows_glqpks
- )
-
- # *************************************************************************
- # *************************************************************************
-
- # 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:
+
+ # imported and exported flows
+ def rule_constr_trans_flows(b):
+ if (g,l) in b.parent_block().set_GL_imp:
+ return sum(
+ b.parent_block().var_v_glljqk[(g,l,l_star,j,q,k)]
+ for l_star in b.parent_block().set_L[g]
+ if l_star not in b.parent_block().set_L_imp[g]
+ for j in b.parent_block().set_J[(g,l,l_star)] # only directed arcs
+ ) == sum(b.var_trans_flows_s[s] for s in b.set_S)
+ else:
+ return sum(
+ b.parent_block().var_v_glljqk[(g,l_star,l,j,q,k)]
+ * b.parent_block().param_eta_glljqk[(g,l_star,l,j,q,k)]
+ for l_star in b.parent_block().set_L[g]
+ if l_star not in b.parent_block().set_L_exp[g]
+ for j in b.parent_block().set_J[(g,l_star,l)] # only directed arcs
+ ) == sum(b.var_trans_flows_s[s] for s in b.set_S)
+ b.constr_trans_flows = pyo.Constraint(rule=rule_constr_trans_flows)
+
+ # *********************************************************************
+ # *********************************************************************
+
+ # non-convex price functions
+
+ # delta variables
+ b.var_active_segment_s = pyo.Var(b.set_S, within=pyo.Binary)
+
+ # segments must be empty if the respective delta variable is zero
+ def rule_constr_empty_segment_if_delta_zero(b, s):
+ if len(b.set_S) == 1 or b.param_price_function_is_convex:
+ # single segment, skip
+ # convex, skip
+ return pyo.Constraint.Skip
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)]
+ b.var_trans_flows_s[s] <=
+ b.param_v_max_s[s]*b.var_active_segment_s[s]
)
- == m.var_ifc_glqpk[(g, l, q, p, k)]
+ b.constr_empty_segment_if_delta_zero = pyo.Constraint(
+ b.set_S, rule=rule_constr_empty_segment_if_delta_zero
)
- else:
+
+ # 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(b, s):
+ if s == len(b.set_S)-1 or b.param_price_function_is_convex:
+ # last segment, skip
+ # convex, skip
+ return pyo.Constraint.Skip
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)]
+ b.var_active_segment_s[s] >=
+ b.var_active_segment_s[s+1]
)
- == m.var_efr_glqpk[(g, l, q, p, k)]
+ b.constr_delta_summing_logic = pyo.Constraint(
+ b.set_S, rule=rule_constr_delta_summing_logic
)
- model.constr_trans_monetary_flows = pyo.Constraint(
- model.set_GLQPK, rule=rule_constr_trans_monetary_flows
- )
-
- # 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_trans_flows = pyo.Constraint(
- model.set_GLQPK, rule=rule_constr_trans_flows
- )
-
- # *************************************************************************
- # *************************************************************************
-
- # non-convex price functions
- # 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)]
- )
- 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)]
- )
- 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)]
+ # if a segment is not completely used, the next ones must remain empty
+ def rule_constr_fill_up_segment_before_next(b, s):
+ if s == len(b.set_S)-1 or b.param_price_function_is_convex:
+ # last segment, skip
+ # convex, skip
+ return pyo.Constraint.Skip
+ return (
+ b.var_trans_flows_s[s] >=
+ b.var_active_segment_s[s+1]*
+ b.param_v_max_s[s]
+ )
+ b.constr_fill_up_segment_before_next = pyo.Constraint(
+ b.set_S, rule=rule_constr_fill_up_segment_before_next
)
- # 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
- )
- # *************************************************************************
- # *************************************************************************
-
- # # 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
- # def rule_constr_delta_summing_logic(m, g, l, q, p, k, s):
- # if s == len(m.set_S)-1:
- # 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 delta var is zero, subsequent ones must also be zero
- # def rule_constr_delta_next_zeros(m, g, l, q, p, k, s):
- # if s == len(m.set_S)-1:
- # return pyo.Constraint.Skip
- # return (
- # 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
- # )
+ model.block_prices = pyo.Block(model.set_GLQPK, rule=rule_block_prices)
# *************************************************************************
# *************************************************************************
-
-
+
+# *****************************************************************************
+# *****************************************************************************
+# *****************************************************************************
+# *****************************************************************************
+# *****************************************************************************
+# *****************************************************************************
+# *****************************************************************************
+# *****************************************************************************
# *****************************************************************************
# *****************************************************************************
-
-# 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 = True,
+ # convex_price_function: bool = True,
enable_default_values: bool = True,
enable_validation: bool = True,
enable_initialisation: bool = True
@@ -555,7 +249,8 @@ def price_other(
model.param_v_max_glqpks = pyo.Param(
model.set_GLQPKS,
- within=pyo.NonNegativeReals
+ within=pyo.NonNegativeReals,
+ # default=math.inf
)
# *************************************************************************
@@ -568,6 +263,7 @@ def price_other(
# import and export flows
def bounds_var_trans_flows_glqpks(m, g, l, q, p, k, s):
+ # return (0, m.param_v_max_glqpks[(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)])
@@ -693,6 +389,8 @@ def price_other(
# *****************************************************************************
# *****************************************************************************
+# TODO: implement the lambda model
+
def price_block_lambda(model: pyo.AbstractModel, **kwargs):
raise NotImplementedError
@@ -700,6 +398,8 @@ def price_block_lambda(model: pyo.AbstractModel, **kwargs):
# *****************************************************************************
# *****************************************************************************
+# TODO: implement the delta model
+
def price_block_delta(model: pyo.AbstractModel, **kwargs):
raise NotImplementedError
diff --git a/src/topupopt/problems/esipp/model.py b/src/topupopt/problems/esipp/model.py
index 62e387c..ade66bb 100644
--- a/src/topupopt/problems/esipp/model.py
+++ b/src/topupopt/problems/esipp/model.py
@@ -3,7 +3,7 @@
import pyomo.environ as pyo
from .blocks.networks import add_network_restrictions
-from .blocks.prices import add_prices_block
+from .blocks.prices import add_price_functions
# *****************************************************************************
# *****************************************************************************
@@ -57,33 +57,26 @@ def create_model(
# *************************************************************************
# set of assessments
-
model.set_Q = pyo.Set()
# TODO: use rangesets for time-related sets
# set of time step intervals for each assessment
-
model.set_K_q = pyo.Set(model.set_Q)
# set of representative evaluation periods for each assessment
-
model.set_P_q = pyo.Set(model.set_Q)
# set of networks
-
model.set_G = pyo.Set()
# set of nodes on each network
-
model.set_L = pyo.Set(model.set_G)
# set of importing nodes on each network
-
model.set_L_imp = pyo.Set(model.set_G, within=model.set_L)
# set of exporting nodes on each network
-
model.set_L_exp = pyo.Set(model.set_G, within=model.set_L)
# *************************************************************************
@@ -2163,7 +2156,7 @@ def create_model(
)
# prices
- add_prices_block(model)
+ add_price_functions(model)
# *************************************************************************
# *************************************************************************
diff --git a/src/topupopt/problems/esipp/problem.py b/src/topupopt/problems/esipp/problem.py
index 8b0dd6b..c05b664 100644
--- a/src/topupopt/problems/esipp/problem.py
+++ b/src/topupopt/problems/esipp/problem.py
@@ -2548,7 +2548,7 @@ class InfrastructurePlanningProblem(EnergySystem):
}
# maximum resource volume per segment (infinity is the default)
-
+
param_v_max_glqpks = {
(g, l, q, p, k, s): self.networks[g]
.nodes[l][Network.KEY_NODE_PRICES][(q, p, k)]
@@ -3511,6 +3511,16 @@ class InfrastructurePlanningProblem(EnergySystem):
"param_arc_sns_sos1_weights_glljqk": param_arc_sns_sos1_weights_glljqk,
# *****************************************************************
# *****************************************************************
+ "block_prices": {
+ (*gl,*qpk): {
+ 'param_price_function_is_convex': {None: param_price_function_is_convex[(*gl,*qpk)]},
+ 'set_S': {None: set_S[(*gl,*qpk)]},
+ 'param_p_s': {s: param_p_glqpks[(*gl,*qpk,s)] for s in set_S[(*gl,*qpk)]},
+ 'param_v_max_s': {s: param_v_max_glqpks[(*gl,*qpk,s)] for s in set_S[(*gl,*qpk)] if (*gl,*qpk,s) in param_v_max_glqpks},
+ }
+ for gl in set_GL_exp_imp
+ for qpk in set_QPK
+ }
}
}
diff --git a/tests/test_esipp_prices.py b/tests/test_esipp_prices.py
index 0bccfd4..9f3bf25 100644
--- a/tests/test_esipp_prices.py
+++ b/tests/test_esipp_prices.py
@@ -681,7 +681,7 @@ class TestESIPPProblem:
max_number_parallel_arcs={},
simplify_problem=False,
)
-
+ ipp.instance.pprint()
assert not ipp.has_peak_total_assessments()
assert ipp.results["Problem"][0]["Number of constraints"] == 14 # 10 before nonconvex block
assert ipp.results["Problem"][0]["Number of variables"] == 13 # 11 before nonconvex block
--
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