Scenario analysis using Bayesian networks: A case study in energy sector

This paper provides a general overview of creating scenarios for energy policies using Bayesian Network (BN) models. BN is a useful tool to analyze the complex structures, which allows observation of the current structure and basic consequences of any strategic change. This research will propose a decision model that will support the researchers in forecasting and scenario analysis fields. The proposed model will be implemented in a case study for Turkey. The choice of the case is based on complexities of a renewable energy resource rich country. Turkey is a heavy energy importer discussing new investments. Domestic resources could be evaluated under different scenarios aiming the sustainability. Achievements of this study will open a new vision for the decision makers in energy sector.

[1]  R. K Agrawal,et al.  Energy allocations for cooking in UP households (India): A fuzzy multi-objective analysis , 2001 .

[2]  Kamil Kaygusuz,et al.  Renewable energy potential and utilization in Turkey. , 2003 .

[3]  Alejandro Quintero,et al.  A multi-agent approach for planning activities in decentralized electricity markets , 2007, Knowl. Based Syst..

[4]  E. Aktas,et al.  An Integrated Transportation Decision Support System for Transportation Policy Decisions: The Case of Turkey , 2007 .

[5]  Füsun Ülengin,et al.  Using neural networks and cognitive mapping in scenario analysis: The case of Turkey's inflation dynamics , 2004, Eur. J. Oper. Res..

[6]  Zhonghua Yang,et al.  Agent that models, reasons and makes decisions , 2002, Knowl. Based Syst..

[7]  B. Bowerman,et al.  Forecasting, time series, and regression : an applied approach , 2005 .

[8]  Chunyan Miao,et al.  A cognitive approach for agent-based personalized recommendation , 2007, Knowl. Based Syst..

[9]  Elcin Kentel,et al.  Renewable energy potential as an alternative to fossil fuels in Turkey , 1999 .

[10]  Y. Mulugetta,et al.  Power sector scenarios for Thailand: An exploratory analysis 2002-2022 , 2007 .

[11]  Paolo Trucco,et al.  A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation , 2008, Reliab. Eng. Syst. Saf..

[12]  Prakash P. Shenoy,et al.  A causal mapping approach to constructing Bayesian networks , 2004, Decis. Support Syst..

[13]  Adam Hawkes,et al.  On policy instruments for support of micro combined heat and power , 2008 .

[14]  Kamil Kaygusuz,et al.  Energy Situation, Future Developments, Energy Saving, and Energy Efficiency in Turkey , 1999 .

[15]  Hiroyuki Mori,et al.  Risk Quantification for ANN Based Short-Term Load Forecasting , 2006 .

[16]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[17]  Chang-Hwan Lee Improving classification performance using unlabeled data: Naive Bayesian case , 2007, Knowl. Based Syst..

[18]  Seong-Pyo Cheon,et al.  Bayesian networks based rare event prediction with sensor data , 2009, Knowl. Based Syst..

[19]  Reinhard Madlener,et al.  Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis , 2009, Eur. J. Oper. Res..

[20]  G. Palermo,et al.  Constructing Bayesian networks for criminal profiling from limited data , 2008, Knowl. Based Syst..

[21]  Ethem Alpaydin,et al.  Introduction to machine learning , 2004, Adaptive computation and machine learning.

[22]  Prakash P. Shenoy,et al.  A Bayesian network approach to making inferences in causal maps , 2001, Eur. J. Oper. Res..

[23]  Jose L. Salmeron,et al.  Augmented fuzzy cognitive maps for modelling LMS critical success factors , 2009, Knowl. Based Syst..

[24]  Xia Chang-liang,et al.  Wind energy in China: Current scenario and future perspectives , 2009 .

[25]  Reginald L. Hobbs,et al.  A Scenario-directed Computational Framework To Aid Decision-making And Systems Development , 2005 .

[26]  Gordon H. Huang,et al.  Identification of optimal strategies for energy management systems planning under multiple uncertainties , 2009 .

[27]  Tetsuo Tezuka,et al.  Implications of capacity expansion under uncertainty and value of information: The near-term energy planning of Japan , 2007 .

[28]  Keng Siau,et al.  Improving the quality of conceptual modeling using cognitive mapping techniques , 2005, Data Knowl. Eng..

[29]  Füsun Ülengin,et al.  A decision support system to improve the efficiency of resource allocation in healthcare management , 2007 .

[30]  Norman E. Fenton,et al.  Making decisions: using Bayesian nets and MCDA , 2001, Knowl. Based Syst..

[31]  Ayhan Demirbas,et al.  Energy balance, energy sources, energy policy, future developments and energy investments in Turkey , 2001 .

[32]  Colin Eden,et al.  Analyzing cognitive maps to help structure issues or problems , 2004, Eur. J. Oper. Res..

[33]  Volker Krey,et al.  Compromises in energy policy--Using fuzzy optimization in an energy systems model , 2008 .

[34]  Sumeet Gupta,et al.  Linking structural equation modeling to Bayesian networks: Decision support for customer retention in virtual communities , 2008, Eur. J. Oper. Res..

[35]  Steven A. Gabriel,et al.  Solving stochastic complementarity problems in energy market modeling using scenario reduction , 2009, Eur. J. Oper. Res..

[36]  Keith Johnson,et al.  Crossover Applications , 2009, 2009 IEEE Virtual Reality Conference.

[37]  Fredric C. Olds The energy situation , 1972 .

[38]  S P Potter,et al.  Energy supply. , 1973, Science.

[39]  Hakan S. Soyhan,et al.  Sustainable energy production and consumption in Turkey: A review , 2009 .

[40]  T. Muneer,et al.  Energy supply, its demand and security issues for developed and emerging economies , 2007 .

[41]  Xiaoyi Jiang,et al.  Structure identification of Bayesian classifiers based on GMDH , 2009, Knowl. Based Syst..

[42]  Pedro Larrañaga,et al.  Probabilistic graphical models in artificial intelligence , 2011, Appl. Soft Comput..

[43]  Peter Duchessi,et al.  A Bayesian Belief Network for IT implementation decision support , 2006, Decis. Support Syst..

[44]  Mohit Goyal,et al.  Introduction of Renewable Energy Certificate in the Indian scenario , 2009 .

[45]  Toufic Mezher,et al.  Energy resource allocation using multi-objective goal programming: the case of Lebanon , 1998 .

[46]  Siret Talve,et al.  Estonian electricity supply scenarios for 2020 and their environmental performance , 2007 .

[47]  Petros A. Pilavachi,et al.  Multicriteria evaluation of power plants impact on the living standard using the analytic hierarchy process , 2008 .

[48]  Fengzhan Tian,et al.  A Selective Classifier for Incomplete Data , 2008, PAKDD.

[49]  Hyeonsang Eom,et al.  A compound framework for sports results prediction: A football case study , 2008, Knowl. Based Syst..