TY  - JOUR
AU  - Mo, Yuchang
AU  - Chynybaev, Mirlan
AU  - Chymyrov, Akylbek
AU  - Wu, Wen
AU  - Li, Yunfei
AU  - He, Xi
AU  - Ma, Shuaisen
PY  - 2026
DA  - 2026/07/08
TI  - Coordinated Electricity Tariff and Import Planning for Kyrgyzstan Using Rolling MILP Optimization Under Seasonal Hydropower Constraints
JO  - ICCK Transactions on Systems Safety and Reliability
T2  - ICCK Transactions on Systems Safety and Reliability
JF  - ICCK Transactions on Systems Safety and Reliability
VL  - 2
IS  - 3
SP  - 176
EP  - 191
DO  - 10.62762/TSSR.2026.468829
UR  - https://www.icck.org/article/abs/TSSR.2026.468829
KW  - Kyrgyzstan power system
KW  - electricity tariff
KW  - electricity import planning
KW  - mixed-integer linear programming
KW  - hydropower
KW  - rolling optimization
KW  - supply reliability
AB  - Kyrgyzstan relies heavily on hydropower generation, which results in a pronounced seasonal mismatch between electricity supply and demand, posing significant challenges to power system reliability and supply security. During winter, reduced hydropower availability and increased electricity consumption often lead to power shortages and a growing dependence on electricity imports. To support more effective operational planning, this study proposes a mixed-integer linear programming (MILP) model for the coordinated optimization of electricity tariffs and import procurement under seasonal supply constraints. The proposed model incorporates tariff-responsive demand, domestic generation limits, electricity imports from neighboring countries, affordability requirements, and revenue adequacy constraints. A rolling optimization framework is developed to support annual, quarterly, and monthly planning updates. The model is applied to a case study of the Kyrgyz power system using publicly available electricity statistics for 2025 and seasonally adjusted monthly scenarios. Results indicate that coordinated tariff and import planning can alleviate winter supply pressure and improve system reliability, as measured by the Energy Not Supplied (ENS) indicator, compared with a benchmark planning approach. Under the studied scenarios, the optimized strategy reduces annual import requirements and lowers import expenditures while maintaining affordability and revenue-related constraints. The rolling optimization framework also provides greater flexibility for adapting to changing hydrological conditions and import market uncertainties. The proposed approach offers a practical decision-support tool for hydropower-dominated power systems facing seasonal electricity shortages and increasing import dependence.
SN  - 3069-1087
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Mo2026Coordinate,
  author = {Yuchang Mo and Mirlan Chynybaev and Akylbek Chymyrov and Wen Wu and Yunfei Li and Xi He and Shuaisen Ma},
  title = {Coordinated Electricity Tariff and Import Planning for Kyrgyzstan Using Rolling MILP Optimization Under Seasonal Hydropower Constraints},
  journal = {ICCK Transactions on Systems Safety and Reliability},
  year = {2026},
  volume = {2},
  number = {3},
  pages = {176-191},
  doi = {10.62762/TSSR.2026.468829},
  url = {https://www.icck.org/article/abs/TSSR.2026.468829},
  abstract = {Kyrgyzstan relies heavily on hydropower generation, which results in a pronounced seasonal mismatch between electricity supply and demand, posing significant challenges to power system reliability and supply security. During winter, reduced hydropower availability and increased electricity consumption often lead to power shortages and a growing dependence on electricity imports. To support more effective operational planning, this study proposes a mixed-integer linear programming (MILP) model for the coordinated optimization of electricity tariffs and import procurement under seasonal supply constraints. The proposed model incorporates tariff-responsive demand, domestic generation limits, electricity imports from neighboring countries, affordability requirements, and revenue adequacy constraints. A rolling optimization framework is developed to support annual, quarterly, and monthly planning updates. The model is applied to a case study of the Kyrgyz power system using publicly available electricity statistics for 2025 and seasonally adjusted monthly scenarios. Results indicate that coordinated tariff and import planning can alleviate winter supply pressure and improve system reliability, as measured by the Energy Not Supplied (ENS) indicator, compared with a benchmark planning approach. Under the studied scenarios, the optimized strategy reduces annual import requirements and lowers import expenditures while maintaining affordability and revenue-related constraints. The rolling optimization framework also provides greater flexibility for adapting to changing hydrological conditions and import market uncertainties. The proposed approach offers a practical decision-support tool for hydropower-dominated power systems facing seasonal electricity shortages and increasing import dependence.},
  keywords = {Kyrgyzstan power system, electricity tariff, electricity import planning, mixed-integer linear programming, hydropower, rolling optimization, supply reliability},
  issn = {3069-1087},
  publisher = {Institute of Central Computation and Knowledge}
}