How to Troubleshoot Apps for the Modern Connected Worker
A Solver Manager for energy systems planning within a Stochastic Optimization Framework
1. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
A Solver Manager for energy systems
planning within a Stochastic
Optimization Framework
Emilio L. Cano1
Antonio Alonso Ayuso1
Javier M. Moguerza1
Felipe Ortega1
1
DEIO, Universidad Rey Juan Carlos, Madrid
10th
International Conference on Computational Management 1/34
2. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Outline
1 Introduction
Energy Systems in Buildings
The EnRiMa Project
2 Strategic Model
Strategic Decisions
Operational Decisions
3 Solver Manager
4 Numerical Example
10th
International Conference on Computational Management 2/34
3. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Outline
1 Introduction
Energy Systems in Buildings
The EnRiMa Project
2 Strategic Model
Strategic Decisions
Operational Decisions
3 Solver Manager
4 Numerical Example
10th
International Conference on Computational Management 3/34
4. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Energy Systems in Buildings
Liberalisation of energy markets.
Global targets, e.g. 20/20/20.
Regulations:
Emissions.
Efficiency.
Technologies: Generation, ICT.
10th
International Conference on Computational Management 4/34
5. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Energy Systems in Buildings
Liberalisation of energy markets.
Global targets, e.g. 20/20/20.
Regulations:
Emissions.
Efficiency.
Technologies: Generation, ICT.
Decisions at the building level
Strategic: Energy Systems Deployment
Operational: Energy Systems Use
10th
International Conference on Computational Management 4/34
6. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
EnRiMa Objective
http://www.enrima-project.eu
10th
International Conference on Computational Management 5/34
7. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
EnRiMa Objective
Objective
The overall objective of EnRiMa is to develop
a decision-support system (DSS) for operators
of energy-efficient buildings and spaces of
public use.
http://www.enrima-project.eu
10th
International Conference on Computational Management 5/34
8. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
EnRiMa Consortium
10th
International Conference on Computational Management 6/34
9. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
EnRiMa DSS Outline
10th
International Conference on Computational Management 7/34
10. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Symbolic Model Specification
The SMS contains the mathematical
representation of all relevant energy
subsystems and their interactions. Is
composed of sets, variables, parameters
and equations.
In the project deliverables D4.2 (initial)
and D4.3 (updated).
10th
International Conference on Computational Management 8/34
11. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Decision Scope
EnRiMaDSS
Strategic
Module
Operational
Module
StrategicDVs
Strategic
Constraints
Upper-Level
Operational DVs
Upper-Level
Energy-Balance
Constraints
Lower-Level
Energy-Balance
Constraints
Lower-Level
Operational DVs
10th
International Conference on Computational Management 9/34
12. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Scenario Tree
2
1
3 4 6
8 9 10 12
PT1
= 0 PT2
= 1 PT3
= 2 PT4
= 3 PT5
= PT6
= PT7
= 4
PT8
= 1 PT9
= 2 PT10
= 3 PT11
= PT12
= PT13
= 4
PR1
= 1
0 < PR2
= PR3
= PR4
< 1
PR5
PR12
5
7
11
13
PR6
PR7
0 < PR8
= PR9
= PR10
< 1
PR11
PR13
First Stage Second Stage Third Stage
10th
International Conference on Computational Management 10/34
13. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Outline
1 Introduction
Energy Systems in Buildings
The EnRiMa Project
2 Strategic Model
Strategic Decisions
Operational Decisions
3 Solver Manager
4 Numerical Example
10th
International Conference on Computational Management 11/34
14. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Model Sets
Time
v Tree node; v ∈ V.
m Representative profile; m ∈ M.
t Short-term period. t ∈ T .
Node parameters and functions
PRv
Probability of the node;
Pa(v) Parent of the node;
PTv
Period of the node.
10th
International Conference on Computational Management 12/34
15. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Model Sets (cont.)
Other features
i Energy technology (equipment);
i ∈ I = IGen ∪ ISto ∪ IPU .
k Energy type; k ∈ K.
n Energy tariff; n ∈ N.
l Pollutant. l ∈ L.
10th
International Conference on Computational Management 13/34
16. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Strategic Model
EnRiMaDSS
Strategic
Module
Operational
Module
StrategicDVs
Strategic
Constraints
Upper-Level
Operational DVs
Upper-Level
Energy-Balance
Constraints
Lower-Level
Energy-Balance
Constraints
Lower-Level
Operational DVs
The strategic model is used in order to make
strategic decisions concerning which
technologies to install and/or decommission in
the long term. It includes a simplified version
of operational energy-balance constraints.
10th
International Conference on Computational Management 14/34
17. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Strategic Decisions
Decision Variables
hv
k,n Tariff choice;
xiv
i Technologies to install;
xdv,a
i Technologies to decommission;
xv,a
i Technologies installed;
xcv
i Available capacity of technologies.
10th
International Conference on Computational Management 15/34
18. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Strategic Decisions (cont.)
Relations
xv,a
i = xv ,a−1
i − xdv,a
i
xcv
i = Gi ·
a∈AAges(i,v)
AGa
i · xv,a
i
n∈NPur(k)
hv
k,n = 1
. . .
10th
International Conference on Computational Management 16/34
19. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Embedded Operational Model
EnRiMaDSS
Strategic
Module
Operational
Module
StrategicDVs
Strategic
Constraints
Upper-Level
Operational DVs
Upper-Level
Energy-Balance
Constraints
Lower-Level
Energy-Balance
Constraints
Lower-Level
Operational DVs
The model includes the realisation of
short-term decisions (t) that are scaled to a
long-term period (PTv
) through a
representative profile (m).
10th
International Conference on Computational Management 17/34
20. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Operational Decisions
Decision Variables
ev,m,t
Primary energy consumed;
rv,m,t
i,k Energy stored;
riv,m,t
i,k Energy input to storage;
rov,m,t
i,k Energy output from storage;
uv,m,t
k,n Energy to purchase;
wv,m,t
k,n Energy to sell;
yv,m,t
i,k Energy generator input;
zv,m,t
i,k Energy generator output;
10th
International Conference on Computational Management 18/34
21. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Operational Decisions (cont.)
Relations
i∈IGen
zv,m,t
i,k −
i∈IGen
yv,m,t
i,k +
n∈NPur(k)
uv,m,t
k,n −
n∈NS(k)
wv,m,t
k,n
+
i∈ISto
rov,m,t
i,k − riv,m,t
i,k = Dv,m,t
k ·
1 −
i∈IPU
ODv
i,k · xcv
i
10th
International Conference on Computational Management 19/34
22. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Operational Decisions (cont.)
Strategic & Operational link
zv,m,t
i,k ≤ DTm
· AFv,m,t
i · xcv
i
OAv
i,k · xcv
i ≤ rv,m,t
i,k ≤ OBv
i,k · xcv
i
uv,m,t
k,n ≤ hv
k,n · MEk,n · DTm
10th
International Conference on Computational Management 20/34
23. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Further constraints
Emmissions limit;
Efficiency limit;
Budget limit.
10th
International Conference on Computational Management 21/34
24. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Objective
minimize
v∈V
(1 + DR)
PTv
· PR
v
·
i∈I
CI
v
i − SU
v
i · Gi · xi
v
i +
a∈AAges(i,v)
CD
v,a
i · Gi · xd
v,a
i
+
a∈AAges(i,v)
CM
v,a
i · Gi · x
v,a
i
+
m∈M
DM
m
·
t∈TTm(m,t)
n∈NPur(k,n)
PP
v,m,t
k,n
· u
v,m,t
k,n
−
n∈NS(k,n)
SP
v,m,t
k,n
· w
v,m,t
k,n
+
i∈IGen ,k∈KOut(i,k)
CO
v
i,k · z
v,m,t
i,k
+
i∈ISto ,k∈KPo(i,k)
CO
v
i,k · r
v,m,t
i,k
10th
International Conference on Computational Management 22/34
25. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Outline
1 Introduction
Energy Systems in Buildings
The EnRiMa Project
2 Strategic Model
Strategic Decisions
Operational Decisions
3 Solver Manager
4 Numerical Example
10th
International Conference on Computational Management 23/34
26. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Solver Manager
The initial concept of“Stochastic
Optimisation”within the project has evolved
to a so-called“Solver Manager”.
10th
International Conference on Computational Management 24/34
27. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
SM Interface
The SM Interface allows to separate
communication tasks and other interaction
features from the core features of the Solver
Manager
10th
International Conference on Computational Management 25/34
28. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Solver Manager Process Flow
1 Retrieve data from Scenario Generator
and GUI;
2 Create data objects with the instance;
3 Create the instance for a given
optimisation software;
4 Run the optimisation software, usin a
given solver;
5 Check and analyse the solution;
6 Update data objects with the solution;
7 Deliver the solution to the rest of the
modules;
10th
International Conference on Computational Management 26/34
29. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Outline
1 Introduction
Energy Systems in Buildings
The EnRiMa Project
2 Strategic Model
Strategic Decisions
Operational Decisions
3 Solver Manager
4 Numerical Example
10th
International Conference on Computational Management 27/34
30. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Scenario Tree
1
PTv = 0
4
PTv = 1
5
PTv = 2
Scenario 2
PR v
=
0.5
2
PTv = 1
3
PTv = 2
Scenario 1
PR
v =
0.5
10th
International Conference on Computational Management 28/34
31. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Sets
A = {0, 1, 2}
I = {PV}
K = {electricity, radiation}
L = {∅}
N = {normalRTEp, touRTEp}
V = {1, 2, 3, 4, 5}
M = {profile1, profile2, profile3, profile4}
T = {time1, time2, time3, time4, time5,
time6}
10th
International Conference on Computational Management 29/34
33. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Solution
0
50
100
150
200
0
50
100
150
200
scenario1scenario2
1 2
Period
Units
a
0
1
Available units
profile1 profile2 profile3 profile4
0
50
100
150
200
0
50
100
150
200
0
50
100
150
200
0
50
100
150
200
0
50
100
150
200
Node1Node2Node3Node4Node5
time1
time2
time3
time4
time5
time6
time1
time2
time3
time4
time5
time6
time1
time2
time3
time4
time5
time6
time1
time2
time3
time4
time5
time6
t
Supply(kWh)
n
normalRTEp
touRTEp
Electricity purchases
10th
International Conference on Computational Management 31/34
34. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Summary
New challenges for building managers.
EnRiMa stochastic strategic model.
Solver Manager: flexible and extensible.
10th
International Conference on Computational Management 32/34
35. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Summary
New challenges for building managers.
EnRiMa stochastic strategic model.
Solver Manager: flexible and extensible.
Outlook
Include operational model.
DSS modules integration
Solvers, alogorithms and benchmarking.
10th
International Conference on Computational Management 32/34
36. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Acknowledgements
This work has been partially funded by the
project Energy Efficiency and Risk
Management in Public Buildings (EnRiMa)
EC’s FP7 project (number 260041)
We also acknowledge the projects:
OPTIMOS3 (MTM2012-36163-C06-06)
Project RIESGOS-CM: code S2009/ESP-1685
HAUS: IPT-2011-1049-430000
EDUCALAB: IPT-2011-1071-430000
DEMOCRACY4ALL: IPT-2011-0869-430000
CORPORATE COMMUNITY: IPT-2011-0871-430000
CONTENT & INTELIGENCE: IPT-2012-0912-430000
10th
International Conference on Computational Management 33/34
37. Energy Systems
Planning
10th
CMS’13
Emilio L. Cano
Introduction
Energy Systems in Buildings
EnRiMa Project
Strategic Model
Strategic Decisions
Operational Decisions
Solver Manager
Numerical Example
Summary
Discussion
Thanks !
emilio.lopez@urjc.es
@emilopezcano
10th
International Conference on Computational Management 34/34