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Presentation at the Computational Management Science conference, May 1-3 2013, Montreal (Canada)

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- 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
- 32. 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 Parameters profile1 profile2 profile3 profile4 0.00 0.05 0.10 0.15 0.20 0.00 0.05 0.10 0.15 0.20 0.00 0.05 0.10 0.15 0.20 0.00 0.05 0.10 0.15 0.20 0.00 0.05 0.10 0.15 0.20 12345 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 Price(EUR) n normalRTEp touRTEp Electricity price 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 Demand(kWh) Electricity Demand 10th International Conference on Computational Management 30/34
- 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