A multiobjective interactive approach to determine the optimal electricity mix in Andalucía (Spain)

It seems clear that energy production is one of the key aspects of global sustainability. Economic, social and environmental aspects must be taken into account in order to design appropriate policies and thus, multicriteria analysis becomes a very adequate tool to deal with real problems of this kind. This study was directed by the Regional Ministry of Environment of Andalucía, who wanted to know the impact on the cost and on the environmental damage of a potential mix, more focused on renewable sources. Some authorities of the Ministry acted as decision maker in the interactive process. As a result, we have built a linear multiobjective model, in order to determine the optimal electrical mix for the Spanish region of Andalucía. Namely, we determine how much electricity power should be installed and produced, by each of the eight generation systems considered (lignite, other coals, oil, natural gas, nuclear, photovoltaic, wind and mini-hydro). Apart from the economic criterion (yearly cost), we have considered the vulnerability (in terms of percentage of imported fuel) as a strategic criterion, and 12 environmental criteria, which have been derived using the Life Cycle Analysis method on the different production systems. The interactive system PROMOIN was used to solve the multiobjective problem. PROMOIN allows the decision maker to choose how to give preference information to the system, and enables changing it anytime during the solution process, which gives more flexibility to the decision maker and increases the confidence of the decision maker in the final solution.

[1]  Pekka J. Korhonen,et al.  Evaluation of Cost Efficiency in Finnish Electricity Distribution , 2003, Ann. Oper. Res..

[2]  Kaisa Miettinen,et al.  Global formulation for interactive multiobjective optimization , 2011, OR Spectr..

[3]  Kaisa Miettinen,et al.  Introduction to Multiobjective Optimization: Noninteractive Approaches , 2008, Multiobjective Optimization.

[4]  Pekka Korhonen,et al.  A pareto race , 1988 .

[5]  Ignacy Kaliszewski,et al.  Out of the mist--towards decision-maker-friendly multiple criteria decision making support , 2004, Eur. J. Oper. Res..

[6]  James S. Dyer,et al.  A Time-Sharing Computer Program for the Solution of the Multiple Criteria Problem , 1973 .

[7]  Yasumasa Fujii,et al.  Decision analysis under uncertain CO 2 regulation policies with a global energy model and its implication for power system planning , 1998 .

[8]  Arthur M. Geoffrion,et al.  An Interactive Approach for Multi-Criterion Optimization, with an Application to the Operation of an Academic Department , 1972 .

[9]  Wlodzimierz Ogryczak,et al.  On Multiple Criteria Decision Support for Suppliers on the Competitive Electric Power Market , 2003, Ann. Oper. Res..

[10]  Theodor J. Stewart,et al.  Multiple Criteria Decision Analysis , 2001 .

[11]  Andrzej P. Wierzbicki,et al.  The Use of Reference Objectives in Multiobjective Optimization , 1979 .

[12]  R. Benayoun,et al.  Linear programming with multiple objective functions: Step method (stem) , 1971, Math. Program..

[13]  Pekka Korhonen,et al.  Behavioral Issues in MCDM: Neglected Research Questions , 1996 .

[14]  B. W. Ang,et al.  Decision analysis in energy and environmental modeling , 1995 .

[15]  Giuseppe Munda,et al.  Multiple Criteria Decision Analysis and Sustainable Development , 2005 .

[16]  S. Zionts,et al.  An Interactive Multiple Objective Linear Programming Method for a Class of Underlying Nonlinear Utility Functions , 1983 .

[17]  John Buchanan,et al.  A naïve approach for solving MCDM problems: the GUESS method , 1997 .

[18]  E. Løken.  Use of multicriteria decision analysis methods for energy planning problems , 2007 .

[19]  Kaisa Miettinen,et al.  NAUTILUS method: An interactive technique in multiobjective optimization based on the nadir point , 2010, Eur. J. Oper. Res..

[20]  Jamal O. Jaber,et al.  Evaluation of conventional and renewable energy sources for space heating in the household sector , 2008 .

[21]  K. Miettinen,et al.  Interactive bundle-based method for nondifferentiable multiobjeective optimization: nimbus § , 1995 .

[22]  Manfred Grauer,et al.  Interactive Decision Analysis , 1984 .

[23]  Ignacy Kaliszewski.  Erratum to "Out of the mist - Towards decision-maker-friendly multiple criteria decision making support" [Eur. J. Oper. Res. 158(2004) 293-307] , 2007, Eur. J. Oper. Res..

[24]  B. W. Ang,et al.  Decision analysis in energy and environmental modeling: An update , 2006 .

[25]  Jürgen Branke,et al.  Interactive Multiobjective Optimization from a Learning Perspective , 2008, Multiobjective Optimization.

[26]  Hirotaka Nakayama,et al.  Satisficing Trade-off Method for Multiobjective Programming , 1984 .

[27]  Ralph E. Steuer,et al.  An interactive weighted Tchebycheff procedure for multiple objective programming , 1983, Math. Program..

[28]  Balho H. Kim,et al.  A Study on the Generation Expansion Planning System Under the Cost Based Pool , 2009 .

[29]  Jian-Bo Yang,et al.  PROJECT Method for Multiobjective Optimization Based on Gradient Projection and Reference Points , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[30]  Yacov Y. Haimes,et al.  The Interactive Surrogate Worth Trade-Off (ISWT) Method for Multiobjective Decision-Making , 1978 .

[31]  Andrea Calì,et al.  State of the Art Survey , 2006 .

[32]  Pekka Korhonen,et al.  A Visual Interactive Method for Solving the Multiple-Criteria Problem , 1986 .

[33]  Stig-Inge Gustafsson,et al.  Multi-Criteria Evaluation of Residential Energy Supply Systems , 2007 .

[34]  H. Kunzi,et al.  Lectu re Notes in Economics and Mathematical Systems , 1975 .

[35]  Derek W. Bunn,et al.  Multiple Criteria Problem Solving , 1979 .

[36]  S. Jalilzadeh,et al.  Studying influence of two effective parameters on network losses in transmission expansion planning using DCGA , 2008 .

[37]  Mariano Luque,et al.  Modified interactive chebyshev algorithm (MICA) for non-convex multiobjective programming , 2010, Optimization Letters.

[38]  Carlos Romero,et al.  Aggregation of preferences in an environmental economics context: a goal-programming approach , 2002 .

[39]  Mariano Luque,et al.  Promoin: An Interactive System for Multiobjective Programming , 2002, Int. J. Inf. Technol. Decis. Mak..

[40]  Kalyanmoy Deb,et al.  Multiobjective optimization , 1997 .

[41]  Ming Yang,et al.  Integrated resource strategic planning: Case study of energy efficiency in the Chinese power sector , 2010 .

[42]  Mariano Luque,et al.  Equivalent Information for Multiobjective Interactive Procedures , 2007, Manag. Sci..

[43]  A.T. Almeida,et al.  A decision support system for power generation expansion planning with a case study , 1990, 29th IEEE Conference on Decision and Control.

[44]  Christopher J. Koroneos,et al.  Multi-objective optimization in energy systems: the case study of Lesvos Island, Greece , 2004 .

[45]  R. S. Laundy,et al.  Multiple Criteria Optimisation: Theory, Computation and Application , 1989 .

[46]  Masatoshi Sakawa,et al.  Interactive multiobjective decision making by the sequential proxy optimization technique: SPOT , 1982 .

[47]  Niki Frantzeskaki,et al.  Sustainable energy planning by using multi-criteria analysis application in the island of Crete , 2009 .

[48]  Carlos Henggeler Antunes,et al.  MCDA and Energy Planning , 2005 .

[49]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[50]  Carlos Romero,et al.  A multiple criteria decision making approach for electricity planning in Spain: economic versus environmental objectives , 2000, J. Oper. Res. Soc..