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.
1. Introduction
Adaptation actions come from different kinds: structural, social,
and institutional (Noble et al., 2014).
The actions have
associated features:
• Investment costs
• Diverse degrees of effectiveness to reduce impacts
• Short- / long-term effects, etc.
How to choose the best options for adaptation in energy sector?
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.
1. Introduction
Climate chage
Local Comunities
Economic Sector
Mining
Energy
Oil&Gas
2. Methodological process for optimum
selection of adaptation measures
2.1. Theoretical background
Most used methods for prioritization
and selection of measures:
(Dogulu & Kentel, 2015)
•
•
•
•
Expert judgment,
Cost Benefit Analysis,
Cost Effectiveness Analysis
Multi-Criteria Analysis
Analytic Hierarchy Process – AHP (Saaty, 2008)
2. Methodological process for optimum
selection of adaptation measures
2.2. Sector Analysis
To identify:
• Risks of CC that can affect the
activities of the energy sector.
• Adaptation measures that are more
convenient to reduce them.
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
we assign W weights
2.3. Decision model
1) Decision criteria
Facilitation
M1
M2
Sinergy
2.3. Decision model
1) Decision criteria
MA
MB
Potential contradiction
MC
MD
2) Restrictions
• Dependency relations
Precondition
M1
M2
(Taeihagh et al., 2013)
Contradiction
MC
MD
2. Methodological process for optimum
selection of adaptation measures (7/9)
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
2.3. Decision model
Maximize
Effectiveness to reduce climate risk impacts
in Short term and Long term
+ ∆ Effectiveness by facilitating
+ ∆ Effectiveness by synergy
1) Decision criteria
- ∆ Effectiveness by potential contrad.
2) Restrictions
Precondition
Restrictions
3) Formulation
Contradiction
Binary variable
Budget
2. Methodological process for optimum
selection of adaptation measures
2.3. Decision model
1) Decision criteria
2) Restrictions
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
Thanks
40th Annual IAEE International Conference
2017
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. Biblioteca
Carolina/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.