Adaptation plan for the energy sector...Adaptation plan for the energy sector: participative methods...
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Transcript of Adaptation plan for the energy sector...Adaptation plan for the energy sector: participative methods...
Adaptation plan for the energy sector: participative methods for developing countries
Santiago Arango Aramburo Ph.D., Full Profesor ([email protected])
Diana Carolina Ríos Echeverri, M.Sc. Student ([email protected])Patricia Jaramillo Álvarez Ph.D., Associate Profesor ([email protected])Decision Sciences Group, Universidad Nacional de Colombia-Medellín
40th Annual IAEE International Conference
2017
Agenda
1. Introduction: the problem
2. Methodology: the approach
3. Conclusions: comments and
discussions
1. Introduction• There is a need for adaptation to the new climate
conditions.• Energy sector is vulnerable to potential climate
negative impacts on energy systems associated to resources endowment, energy supply and energy sector vulnerability (Ebinger & Vergara, 2011).
• Climate change will affect energy sector infrastructure, may cause energy supply disruptions and alter energy demand patterns (OECD, 2015).
• Jeopardize the competitiveness of the sector.
Adaptation actions come from different kinds: structural, social, and institutional (Noble et al., 2014).
It is useful to use mathematical models to make the right decisions for adaptation to climate change and to make efficient use of investment resources.
• Investment costs
• Diverse degrees of effectiveness to reduce impacts
• Short- / long-term effects, etc.
The actions have associated features:
How to choose the best options for adaptation in energy sector?
1. Introduction
1. Introduction
Climate chage
Economic SectorMiningEnergy
Oil&Gas
Local Comunities
2. Methodological process for optimum selection of adaptation measures
2.1. Theoretical background Most used methods for prioritization and selection of measures:
• Expert judgment, • Cost Benefit Analysis, • Cost Effectiveness Analysis • Multi-Criteria Analysis
Analytic Hierarchy Process – AHP (Saaty, 2008)
(Dogulu & Kentel, 2015)
To identify:
• Risks of CC that can affect the
activities of the energy sector.
• Adaptation measures that are more
convenient to reduce them.
2.2. Sector Analysis
2. Methodological process for optimum selection of adaptation measures
2.2. Sector Analysis
2. Methodological process for optimum selection of adaptation measures
2.3. Decision model It was developed a decision model based
on multi-criteria technique AHP (Saaty,
2008) and combinatorial optimization (Grötschel & Lovász, 1995)
2. Methodological process for optimum selection of adaptation measures
2.3. Decision model
1) Decision criteria
2. Methodological process for optimum selection of adaptation measures
we assign W weights
2.3. Decision model
1) Decision criteria
2) Restrictions
• Dependency relations
M1 M2
MA MB
MC MD
Facilitation
Sinergy
Potential contradiction
M1 M2
Precondition
MC MD
Contradiction
(Taeihagh et al., 2013)
2.3. Decision model
1) Decision criteria
2) Restrictions
• Dependency relations
• Budget How much $ is there to invest on adaptation?
2. Methodological process for optimum selection of adaptation measures (7/9)
2.3. Decision model
1) Decision criteria
2) Restrictions
2. Methodological process for optimum selection of adaptation measures
3) Formulation
Effectiveness to reduce climate risk impacts in Short term and Long term
Maximize
+ ∆ Effectiveness by facilitating
+ ∆ Effectiveness by synergy
- ∆ Effectiveness by potential contrad.
RestrictionsPrecondition
Contradiction
Binary variable
Budget
2.3. Decision model
1) Decision criteria
2) Restrictions
2. Methodological process for optimum selection of adaptation measures
3) Formulation
(Ríos, 2016)
3. Conclusions
• Not only risk analysis: competitiveness
• Still complicated method: need for adaptation
• Participatory methods:• World cafe for weight assignments
• Focus group for alternative's valuation
• Consistency with local and regional development plans
Adaptation plan for the energy sector: participative methods for developing countries
Santiago Arango Aramburo Ph.D., Full Profesor ([email protected])
Diana Carolina Ríos Echeverri, M.Sc. Student ([email protected])Patricia Jaramillo Álvarez Ph.D., Associate Profesor ([email protected])Decision Sciences Group, Universidad Nacional de Colombia-Medellín
40th Annual IAEE International Conference
2017
Thanks
References• Dogulu, N., & Kentel, E. (2015). Prioritization and selection of climate change adaptation measures: a review of the
literature. In 36th IAHR World Congress. The Hague, Holanda. Retrieved from file:///D:/1. BibliotecaCarolina/Downloads/86871.pdf
• Grötschel, M., & Lovász, L. (1995). Combinatorial optimization. In Handbook of Combinatorics (pp. 1541–1597).
• Noble, I. R., Huq, S., Anokhin, Y., Carmin, J., Goudou, D., Lansigan, F., … Villamizar, A. (2014). Adaptation needs and options. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change(pp. 833–868). Retrieved from http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-Chap14_FINAL.pdf
• OECD. (2015). Adapting to the impacts of climate change. Policy perspectives. Retrieved from https://www.oecd.org/env/cc/Adapting-to-the-impacts-of-climate-change-2015-Policy-Perspectives-27.10.15 WEB.pdf
• OECD, & IEA. (2015). Making the energy sector more resilient to climate change. Retrieved from https://www.iea.org/publications/freepublications/publication/COP21_Resilience_Brochure.pdf
• Ríos, D. C. (2016). Modelo de decisión para la priorización y selección de medidas de adaptación al cambio climático. Universidad Nacional de Colombia.
• Saaty, T. (2008). Decision making with the analytic hierarchy process. Int. J. Services Sciences, 1(1), 83–98.
• Taeihagh, A., Givoni, M., & Bañares-Alcántara, R. (2013). Which policy first? A network-centric approach for the analysis and ranking of policy measures. Environment and Planning B: Planning and Design, 40, 595 – 616.
