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 (saarango@unal.edu.co)

Diana Carolina Ríos Echeverri, M.Sc. Student (dcrios@unal.edu.co)Patricia Jaramillo Álvarez Ph.D., Associate Profesor (gpjarami@unal.edu.co)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 (saarango@unal.edu.co)

Diana Carolina Ríos Echeverri, M.Sc. Student (dcrios@unal.edu.co)Patricia Jaramillo Álvarez Ph.D., Associate Profesor (gpjarami@unal.edu.co)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.