Planificación de Inversiones en Sistemas de Distribución Bajo Incertidumbre en el Contexto de la Transición Energética: �Un Enfoque Multiescenario.

Premio AMBAR 2025

Autores:

Carlos Andrés García Montoya, PhD, EPM - UNAL

Tomas Gomes San Román, PhD, UPC (IIT)

Carlos Mateo Domingo, PhD, UPC (IIT)

Nov 26 de 2025

Tema

Capitular

Acknowledgments and recognition

AMBAR Award 2025

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This project is the result of a collaborative postdoctoral research project between:

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Project recognized as Technological Development and Innovation in Call for Proposals 904 of 2021.

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Outline

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Source: Developed by the author.

Why distribution planning considering uncertainty?

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What investments does the system require to meet the challenges of the transition?

Source: https://www.iea.org/reports/world-energy-investment-2025

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Outline

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How to plan a distribution system under conditions of uncertainty?

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The traditional way of

system planning

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Elements of uncertainty considered:

• Demand uncertainty.
• Fulfillment with regulatory requirements.
• Asset remuneration.
• Continuity of supply.
• Macroeconomic variations.
• DERs integration
• Electric mobility impacts.
• Effectiveness of incorporated technologies.
• Expected losses.
• And others…

Source: Developed by the author

Planning Framework Developed

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Source: Adapted by the author

Planning Framework Developed

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Note: Data obtained from real utility information

Definition of probable scenarios:

Scenario reduction: by means of Sequential Monte-Carlo Simulation.

Option modeling, optimization and valuation:

Definition of alternatives under the real options approach and optimization

Data loading, preprocessing forecast

Benefits vs Value investment

Optimized decisions

Decision making requires an optimization technique, dynamic optimization or stochastic dynamics can be used.

Decision making under uncertainty

Source: Developed and adapted by the author

Network reconfiguration (GA).

Optimal New Feeders.

Optimal location of Substations / New Transformers.

Outline

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Colombian Case Study

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General Dimensions test System:

- 40.502 buses.

- 20.063 lines.

• 7.880 transformers / demands.
• 27.76 MW Peak Demand

A section of the system was modeled on Digsilent.

This corresponds to a region called "Occidente" in the west of Antioquia, Colombia.

Colombian Case Study

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Demand Forecast and uncertainty associated.

Uncertainty modeled using Sequential Monte Carlo Simulation (SMCS)

Demand growth uncertainty is modeled as a normal distribution on the SMCS

Colombian Case Study

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Note: Data obtained from real utility information

Definition of probable scenarios:

Scenario reduction:

EV and GD growth uncertainty is modeled as a Gompertz Model and SMCS

EV and GD adoption uncertainty is modeled as a Logistic model and SMCS

Network modeling according to Resulting Scenarios

Gompertz model

Logistic model

Colombian Case Study

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Option modeling, optimization and valuation:

Colombian Case Study

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Summary of results for decision making

Outline

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Conclusions

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• This paper addresses the uncertainty associated with the energy transition when incorporating or adopting technologies such as DG and EV.
• This framework enables system planners to define the uncertainty of consumer behavior and the expected ranges, and to propose solutions that can meet demand and account for uncertainty.
• The developed smart planning framework is versatile and can be applied to companies in the electricity sector as well as to system planners and regulators.
• It further enables the analysis of the impact and necessity of investments under uncertainty in distribution systems by regulatory or state planning entities.
• The inclusion of additional benefits that may be intangible, such as CO2 emissions, wasted or unconsumed energy, and/or energy not supplied, among others, is proposed.
• Finally, future work could allow the planning framework to be adapted to other environments or variables, thus expanding its potential applications in the electrical industry.

¡Gracias!

Carlos Andrés García Montoya�PhD MsC IngE ⁽¹⁾⁽²⁾�⁽¹⁾carlos.garcia.montoya@epm.com.co�⁽²⁾ www.linkedin.com/in/carlos-andres-garcia-montoya-72a25135.