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Bus Basis Model Applied to the Chilean Power System: A Detailed Look at Chilean Electric Demand

Author

Listed:
  • Carlos Benavides

    (Energy Center, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370450, Chile)

  • Sebastián Gwinner

    (Energy Center, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370450, Chile)

  • Andrés Ulloa

    (Facultad de Ciencias Económicas y Administrativas, Universidad Católica de la Santísima Concepción, Concepción 4090541, Chile)

  • José Barrales-Ruiz

    (Center of Economics for Sustainable Development (CEDES), Faculty of Economics and Government, Universidad San Sebastian, Concepción 4080871, Chile)

  • Vicente Sepúlveda

    (Energy Center, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370450, Chile)

  • Manuel Díaz

    (Energy Center, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago 8370450, Chile)

Abstract

This paper presents a methodology to forecast electrical demand for the Chilean Electrical Power System considering a national, regional, district and bus spatial disaggregation. The methodology developed was based on different kinds of econometric models and end-use models to represent the massification of low carbon emission technologies such as electromobility, electric heating, electric water heating, and distributed generation. In addition, the methodology developed allows for the projection of the electric demand considering different kinds of clients as regulated and non-regulated clients, and different economic sectors. The model was applied to forecast the long-term electricity demand in Chile for the period 2022–2042 for 207 districts and 474 buses. The results include projections under the base case and low carbon scenarios, highlighting the significant influence of new technologies on future demand.

Suggested Citation

  • Carlos Benavides & Sebastián Gwinner & Andrés Ulloa & José Barrales-Ruiz & Vicente Sepúlveda & Manuel Díaz, 2024. "Bus Basis Model Applied to the Chilean Power System: A Detailed Look at Chilean Electric Demand," Energies, MDPI, vol. 17(14), pages 1-28, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3448-:d:1434477
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    References listed on IDEAS

    as
    1. Zhao, Zhenyu & Zhang, Yao & Yang, Yujia & Yuan, Shuguang, 2022. "Load forecasting via Grey Model-Least Squares Support Vector Machine model and spatial-temporal distribution of electric consumption intensity," Energy, Elsevier, vol. 255(C).
    2. Luzia, Ruan & Rubio, Lihki & Velasquez, Carlos E., 2023. "Sensitivity analysis for forecasting Brazilian electricity demand using artificial neural networks and hybrid models based on Autoregressive Integrated Moving Average," Energy, Elsevier, vol. 274(C).
    3. Rizzati, Massimiliano & De Cian, Enrica & Guastella, Gianni & Mistry, Malcolm N. & Pareglio, Stefano, 2022. "Residential electricity demand projections for Italy: A spatial downscaling approach," Energy Policy, Elsevier, vol. 160(C).
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