numerical calculation , energy indicators , distribution of electrical networks , RastrWin3


The city of Turkestan, Kazakhstan is experiencing growth leading to an increased
need for electricity. In order to meet this demand the city is upgrading its infrastructure specifically focusing on improving its 35/10 kV substations. Engineers are utilizing calculation software like RastrWin3 to design and analyze these substations.
This software offers capabilities, for modeling substations. Using RastrWin3 the ability to import data from sources like drawings AutoCad, GIS maps and other relevant resources. This imported data serves as the foundation for constructing the substation model. Engineers can easily incorporate components such as transformers, feeders, circuit breakers and busbars into the model. Each element of the model can be assigned parameters like voltage, current, resistance and power to represent real world conditions. Additionally, load profiles can be generated for analysis purposes to capture fluctuations, in energy demands throughout the day and year. Numerical calculation software plays a role, in the design and analysis of substations. It provides engineers with a toolset to achieve the following objectives:
1. Construct models of substations.
2. Simulate the behavior of substations under operational conditions.
3. Resolve issues that may arise in electrical substations.
4. Enhance the design and optimization of substations.
One notable software in this domain is RastrWin3 which offers capabilities for calculations and simulations related to electric substations. Engineers can utilize this program to evaluate power systems, in emergency and transient modes. Accounting for various factors such as non-linearity, power and reactive power losses, as well, as the influence of capacitive coupling.
Various types of loads such, as consumer loads, substation auxiliary loads and loads from protection and automation devices are considered in the modeling process. The software RastrWin3 is utilized to design and analyze 35/10 kV substations, in Turkestan. This software assists in enhancing the precision of substation design reducing the time needed for designing and developing substations improving substation efficiency and lowering maintenance costs.


Xuefeng, W., & Shengxing, L. (2022). Electric Design of 35kV Substation. IEEE 2nd International Conference on Mobile Networks and Wireless Communications, 1-20.

Alejandro, G., & Eric, W. (2022). How well do emission factors approximate emission changes from electric power system models? Environmental Science and Technology, 14701-14712.

Peter, H., Vanessa, B., & Matthias, F. (2023). Electricity accounting in life cycle assessment: the double counting problem. International Journal of Life Cycle Assessment, 771-787.

Xiang, B., Huang, M., & He, L. (2020). Data-Driven Electric Power Dispatching Equivalent Model Packing Method for Integrated Energy Systems. 2020 10th International Conference on Power and Energy Systems (ICPES), 91-99.

Johannes, A., Leach, M., &Yang, A. (2018). The impact of increased decentralised generation on the reliability of an existing electricity network. Appl Energy, 479–502.

Dawei, Z., & Luming, G. (2019). Review on modeling of photovoltaic power generation systems. 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). 608-615.

Yu, P., Qinyong, Z., & Xiaohui, Q. (2022). Power System Flexibility Indicators Considering Reliability in Electric Power System with High-Penetration New Energy. 2022 5th International Conference on Power and Energy Applications (ICPEA), 3682-3691.

Hirsch, A., & Parag, Y. (2018) A review of technologies, key drivers, and outstanding issues. Renew Sustain Energy Rev, 402, 11.

Cheng, C., Luo, B., Shen, J., & Liao, S. (2018). A modular parallelization framework for power flow transfer analysis of large-scale power systems. J. Mod. Power Syst. Clean Energy, 6(4), 679–690.

Tang, F., Xiao, C., Gao, X., Zhang, Y., Du, N., & Hu, B. (2020). Research on transmission network expansion planning considering splitting control. Sustainability, 12(5), 123-129.

Shu, D., Xie, X., Yan, Z., Dinavahi, V., & Strunz, K. (2019). A multi-domain cosimulation method for comprehensive shifted-frequency phasor DC-grid models and EMT AC-grid models. IEEE Trans. Power Electron, 34(11), 10557–10574. https://doi://10.1049/joe.2020.0099

Mitra, J., & Benidris, M. (2020). A homotopy-based method for robust computation of controlling unstable equilibrium points. IEEE Trans. Power Syst., 35(2), 1422–1431. https://doi://10.1109/TPWRS.2019.2942948

Yongping W., Weiting X., & Chang L. (2023). Evaluation Methods for the Development of New Power Systems Based on Cloud Model. 12th International Conference on Power and Energy Systems (ICPES), 60. https://doi://10.1109/ICPES56491.2022.10072835

Daniel, O., & Daniel, S. (2020). Cost-effective energy storage that reduces emissions. IEEE Transactions on Power Systems, 35 (2), 1509-1519.




How to Cite

Kalimoldayev, M. ., & Shermantayeva, Z. (2023). MODEL DEVELOPMENT AND CALCULATIONS FOR 35/10 KV ELECTRICAL SUBSTATIONS IN TURKESTAN REGION USING RASTRWIN3 PROGRAM. Scientific Journal of Astana IT University, 16(16).