Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050

Dimitry Diassy; Fatma Sow; Mouhamadou Sam; Jacques Joachim Faye; Mamadou Lamine Samb

doi:doi:10.11648/j.ijepe.20261501.12

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Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050

Dimitry Diassy, Fatma Sow, Mouhamadou Sam, Jacques Joachim Faye, Mamadou Lamine Samb^*

Published in International Journal of Energy and Power Engineering (Volume 15, Issue 1)

Received: 27 November 2025 Accepted: 4 January 2026 Published: 20 January 2026

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Abstract

This study develops a Pyomo-based Mixed Integer Linear Programming (MILP) model to optimize electricity tariffs in Senegal, aiming to design a framework that is economically efficient, socially equitable, and environmentally sustainable. The model integrates generation, storage, and dynamic pricing mechanisms into a unified optimization structure covering the period 2022–2050. Five tariff scenarios are simulated - Reference, Progressive, Feed-in Tariff, Static Hybrid, and Dynamic Hybrid -allowing a comparative assessment of their technical and financial performance. Results demonstrate that the Dynamic Hybrid scenario achieves the most favorable outcomes. By 2050, renewable energy reaches 80% of the total generation mix, while the average cost of electricity decreases by 18% (from 83.8 to 68.9 FCFA/kWh). Public subsidies fall dramatically, from 27.5%to 6.8% of sector revenues. Dynamic hourly pricing reduces peak demand by 12–15%, limits reliance on thermal generation, and improves system flexibility through expanded energy storage (10% of the mix by 2050). Moreover, the social lifeline tariff (65 FCFA/kWh for the first 50 kWh/month) remains fiscally sustainable, ensuring protection for low-income households. Overall, the study highlights that dynamic tariff optimization, enabled by open-source algorithmic tools such as Pyomo, can serve as a strategic instrument for predictive regulation and sustainable energy governance. Policy recommendations are proposed for institutional strengthening, data-driven tariff setting, and regional integration within ECOWAS, positioning Senegal as a potential model for resilient energy transition in West Africa.

Published in	International Journal of Energy and Power Engineering (Volume 15, Issue 1)
DOI	10.11648/j.ijepe.20261501.12
Page(s)	27-36
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Pyomo, Dynamic Pricing, Energy Optimization, Renewable Energy, Senegal

References

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[5]	J. Freier and V. von Loessl, (2022). “Dynamic electricity tariffs: Designing reasonable pricing schemes for private households,” Energy Economics, vol. 112, p. 106146. https://doi.org/10.1016/j.eneco.2022.106146
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[11]	C. Hao, X. Zhang, Y. Li, C. Li, and X. Hu,(2024) “Dynamic pricing in consumer-centric electricity markets: A systematic review and thematic analysis,” Electric Power Systems Research, vol. 226, p. 110091. https://doi.org/10.1016/j.esr.2024.101349
[12]	M. Ansarin, A. Azimi, and B. Mousavi, (2022) “A review of equity in electricity tariffs in the renewable era,” Renewable and Sustainable Energy Reviews, vol. 165,p. 112577. https://doi.org/10.1016/j.rser.2022.112577
[13]	Hart, W. E., Watson, J.-P., & Woodruff, D. L. (2017). Pyomo: Optimization Modeling in Python. 2nd Edition, Springer. https://doi.org/10.1007/978-3-319-58821-6 1
[14]	Khanh, N. et al. (2025). A Review of Open-Source Energy System Modelling Tools. International Journal of Advances in Applied Sciences, 14(2), 469–480. https://doi.org/10.11591/ijaas.v14.i2.pp469-480
[15]	El Barkouki, B., Cherkaoui, M., & El Hammouchi, R.(2023). An Economic Dispatch for a Shared Energy Storage System Using MILP Optimization: A Case Study of a Moroccan Microgrid. Energies, 16(12), 4601. https://doi.org/10.3390/en16124601
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[19]	Ministry of Petroleum and Energy (MPE). (2014). Emergency Plan for Senegal - National Strategy for the Integration of Renewable Energy. Government of Senegal, Dakar. Available at: https://www.finances.gouv.sn
[20]	Diassy, D., Samb, M. L., Ngom, A., et al. (2025). Comparative Modeling of Electricity Tariff Schemes in Senegal and Implications for the Energy Transition by 2050. International Journal of Advanced Research, 13(10), 904–918. https://dx.doi.org/10.21474/IJAR01/21983
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Diassy, D., Sow, F., Sam, M., Faye, J. J., Samb, M. L. (2026). Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050. International Journal of Energy and Power Engineering, 15(1), 27-36. https://doi.org/10.11648/j.ijepe.20261501.12

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ACS Style

Diassy, D.; Sow, F.; Sam, M.; Faye, J. J.; Samb, M. L. Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050. Int. J. Energy Power Eng. 2026, 15(1), 27-36. doi: 10.11648/j.ijepe.20261501.12

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AMA Style

Diassy D, Sow F, Sam M, Faye JJ, Samb ML. Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050. Int J Energy Power Eng. 2026;15(1):27-36. doi: 10.11648/j.ijepe.20261501.12

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@article{10.11648/j.ijepe.20261501.12,
  author = {Dimitry Diassy and Fatma Sow and Mouhamadou Sam and Jacques Joachim Faye and Mamadou Lamine Samb},
  title = {Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050
},
  journal = {International Journal of Energy and Power Engineering},
  volume = {15},
  number = {1},
  pages = {27-36},
  doi = {10.11648/j.ijepe.20261501.12},
  url = {https://doi.org/10.11648/j.ijepe.20261501.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20261501.12},
  abstract = {This study develops a Pyomo-based Mixed Integer Linear Programming (MILP) model to optimize electricity tariffs in Senegal, aiming to design a framework that is economically efficient, socially equitable, and environmentally sustainable. The model integrates generation, storage, and dynamic pricing mechanisms into a unified optimization structure covering the period 2022–2050. Five tariff scenarios are simulated - Reference, Progressive, Feed-in Tariff, Static Hybrid, and Dynamic Hybrid -allowing a comparative assessment of their technical and financial performance. Results demonstrate that the Dynamic Hybrid scenario achieves the most favorable outcomes. By 2050, renewable energy reaches 80% of the total generation mix, while the average cost of electricity decreases by 18% (from 83.8 to 68.9 FCFA/kWh). Public subsidies fall dramatically, from 27.5%to 6.8% of sector revenues. Dynamic hourly pricing reduces peak demand by 12–15%, limits reliance on thermal generation, and improves system flexibility through expanded energy storage (10% of the mix by 2050). Moreover, the social lifeline tariff (65 FCFA/kWh for the first 50 kWh/month) remains fiscally sustainable, ensuring protection for low-income households. Overall, the study highlights that dynamic tariff optimization, enabled by open-source algorithmic tools such as Pyomo, can serve as a strategic instrument for predictive regulation and sustainable energy governance. Policy recommendations are proposed for institutional strengthening, data-driven tariff setting, and regional integration within ECOWAS, positioning Senegal as a potential model for resilient energy transition in West Africa.
},
 year = {2026}
}

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TY  - JOUR
T1  - Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050

AU  - Dimitry Diassy
AU  - Fatma Sow
AU  - Mouhamadou Sam
AU  - Jacques Joachim Faye
AU  - Mamadou Lamine Samb
Y1  - 2026/01/20
PY  - 2026
N1  - https://doi.org/10.11648/j.ijepe.20261501.12
DO  - 10.11648/j.ijepe.20261501.12
T2  - International Journal of Energy and Power Engineering
JF  - International Journal of Energy and Power Engineering
JO  - International Journal of Energy and Power Engineering
SP  - 27
EP  - 36
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20261501.12
AB  - This study develops a Pyomo-based Mixed Integer Linear Programming (MILP) model to optimize electricity tariffs in Senegal, aiming to design a framework that is economically efficient, socially equitable, and environmentally sustainable. The model integrates generation, storage, and dynamic pricing mechanisms into a unified optimization structure covering the period 2022–2050. Five tariff scenarios are simulated - Reference, Progressive, Feed-in Tariff, Static Hybrid, and Dynamic Hybrid -allowing a comparative assessment of their technical and financial performance. Results demonstrate that the Dynamic Hybrid scenario achieves the most favorable outcomes. By 2050, renewable energy reaches 80% of the total generation mix, while the average cost of electricity decreases by 18% (from 83.8 to 68.9 FCFA/kWh). Public subsidies fall dramatically, from 27.5%to 6.8% of sector revenues. Dynamic hourly pricing reduces peak demand by 12–15%, limits reliance on thermal generation, and improves system flexibility through expanded energy storage (10% of the mix by 2050). Moreover, the social lifeline tariff (65 FCFA/kWh for the first 50 kWh/month) remains fiscally sustainable, ensuring protection for low-income households. Overall, the study highlights that dynamic tariff optimization, enabled by open-source algorithmic tools such as Pyomo, can serve as a strategic instrument for predictive regulation and sustainable energy governance. Policy recommendations are proposed for institutional strengthening, data-driven tariff setting, and regional integration within ECOWAS, positioning Senegal as a potential model for resilient energy transition in West Africa.

VL  - 15
IS  - 1
ER  -

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Author Information

Dimitry Diassy

Department of Physics and Chemistry, University Iba Der Thiam of Thies, Thies, Senegal

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Fatma Sow

Department of Physics and Chemistry, University Iba Der Thiam of Thies, Thies, Senegal

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Mouhamadou Sam

Department of Physics and Chemistry, University Iba Der Thiam of Thies, Thies, Senegal

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Jacques Joachim Faye

Department of Physics and Chemistry, University Iba Der Thiam of Thies, Thies, Senegal

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Mamadou Lamine Samb

Department of Physics and Chemistry, University Iba Der Thiam of Thies, Thies, Senegal

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APA Style

Diassy, D., Sow, F., Sam, M., Faye, J. J., Samb, M. L. (2026). Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050. International Journal of Energy and Power Engineering, 15(1), 27-36. https://doi.org/10.11648/j.ijepe.20261501.12

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ACS Style

Diassy, D.; Sow, F.; Sam, M.; Faye, J. J.; Samb, M. L. Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050. Int. J. Energy Power Eng. 2026, 15(1), 27-36. doi: 10.11648/j.ijepe.20261501.12

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AMA Style

Diassy D, Sow F, Sam M, Faye JJ, Samb ML. Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050. Int J Energy Power Eng. 2026;15(1):27-36. doi: 10.11648/j.ijepe.20261501.12

Copy | Download

@article{10.11648/j.ijepe.20261501.12,
  author = {Dimitry Diassy and Fatma Sow and Mouhamadou Sam and Jacques Joachim Faye and Mamadou Lamine Samb},
  title = {Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050
},
  journal = {International Journal of Energy and Power Engineering},
  volume = {15},
  number = {1},
  pages = {27-36},
  doi = {10.11648/j.ijepe.20261501.12},
  url = {https://doi.org/10.11648/j.ijepe.20261501.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20261501.12},
  abstract = {This study develops a Pyomo-based Mixed Integer Linear Programming (MILP) model to optimize electricity tariffs in Senegal, aiming to design a framework that is economically efficient, socially equitable, and environmentally sustainable. The model integrates generation, storage, and dynamic pricing mechanisms into a unified optimization structure covering the period 2022–2050. Five tariff scenarios are simulated - Reference, Progressive, Feed-in Tariff, Static Hybrid, and Dynamic Hybrid -allowing a comparative assessment of their technical and financial performance. Results demonstrate that the Dynamic Hybrid scenario achieves the most favorable outcomes. By 2050, renewable energy reaches 80% of the total generation mix, while the average cost of electricity decreases by 18% (from 83.8 to 68.9 FCFA/kWh). Public subsidies fall dramatically, from 27.5%to 6.8% of sector revenues. Dynamic hourly pricing reduces peak demand by 12–15%, limits reliance on thermal generation, and improves system flexibility through expanded energy storage (10% of the mix by 2050). Moreover, the social lifeline tariff (65 FCFA/kWh for the first 50 kWh/month) remains fiscally sustainable, ensuring protection for low-income households. Overall, the study highlights that dynamic tariff optimization, enabled by open-source algorithmic tools such as Pyomo, can serve as a strategic instrument for predictive regulation and sustainable energy governance. Policy recommendations are proposed for institutional strengthening, data-driven tariff setting, and regional integration within ECOWAS, positioning Senegal as a potential model for resilient energy transition in West Africa.
},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Dynamic Optimization of Electricity Tariffs in Senegal: A Pyomo-Based Model for a Resilient Renewable Energy Mix Toward 2050

AU  - Dimitry Diassy
AU  - Fatma Sow
AU  - Mouhamadou Sam
AU  - Jacques Joachim Faye
AU  - Mamadou Lamine Samb
Y1  - 2026/01/20
PY  - 2026
N1  - https://doi.org/10.11648/j.ijepe.20261501.12
DO  - 10.11648/j.ijepe.20261501.12
T2  - International Journal of Energy and Power Engineering
JF  - International Journal of Energy and Power Engineering
JO  - International Journal of Energy and Power Engineering
SP  - 27
EP  - 36
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.20261501.12
AB  - This study develops a Pyomo-based Mixed Integer Linear Programming (MILP) model to optimize electricity tariffs in Senegal, aiming to design a framework that is economically efficient, socially equitable, and environmentally sustainable. The model integrates generation, storage, and dynamic pricing mechanisms into a unified optimization structure covering the period 2022–2050. Five tariff scenarios are simulated - Reference, Progressive, Feed-in Tariff, Static Hybrid, and Dynamic Hybrid -allowing a comparative assessment of their technical and financial performance. Results demonstrate that the Dynamic Hybrid scenario achieves the most favorable outcomes. By 2050, renewable energy reaches 80% of the total generation mix, while the average cost of electricity decreases by 18% (from 83.8 to 68.9 FCFA/kWh). Public subsidies fall dramatically, from 27.5%to 6.8% of sector revenues. Dynamic hourly pricing reduces peak demand by 12–15%, limits reliance on thermal generation, and improves system flexibility through expanded energy storage (10% of the mix by 2050). Moreover, the social lifeline tariff (65 FCFA/kWh for the first 50 kWh/month) remains fiscally sustainable, ensuring protection for low-income households. Overall, the study highlights that dynamic tariff optimization, enabled by open-source algorithmic tools such as Pyomo, can serve as a strategic instrument for predictive regulation and sustainable energy governance. Policy recommendations are proposed for institutional strengthening, data-driven tariff setting, and regional integration within ECOWAS, positioning Senegal as a potential model for resilient energy transition in West Africa.

VL  - 15
IS  - 1
ER  -

Copy | Download