Transformer Optimization and Capacity Planning of Electrical Infrastructure at Takoradi Technical University

The growing need for stable delivery of electrical energy in academic institutions requires innovative solutions for optimal utilization of these assets, especially in a resource constrained environment. This research aims to identify the problem of operational inefficiencies in the electrical distribution network of Takoradi Technical University (TTU) by proposing a parallel transformer optimization framework. Using a tri-phasic methodology, which includes bibliometric analysis, empirical field monitoring, and stochastic load forecasting, the research evaluates the transition from the independent operation of a 315 kVA and a 500 kVA unit to a synchronized parallel configuration. Technical evaluation results show that although there is a nameplate mismatch, the circulating currents are safe with 20.0 A. Implementation results prove a 30% load equity improvement with 8% technical losses reduction and 1.20% of voltage regulation. The economic analysis brings a quick payback of 1.48 years. Furthermore, the framework incorporates uncertainty quantification for load growth and sensitivity analysis for impedance-based load sharing to ensure system resilience. This study provides a scalable blueprint for institutions in developing economies to achieve energy security and operational reliability through cost-effective asset optimization. This research is responsible for offering a scaling approach for institutions with limited access to financial resources to implement an efficient use of existing assets while delaying costly capital growth.

Transformer optimization, Capacity planning, Parallel operation, Load balancing, Electrical infrastructure

1. P. Torres-Bermeo et al., "Sizing and Characterization of Load Curves of Distribution Transformers," Energies vol. 18, no. 7, 2025. [Google Scholar] [Crossref]

2. M. H. Hashemi and U. Kilic, "Multi-objective design optimization of sealed core type of distribution transformers," Engineering Science and Technology, vol. 55, no. 2024. [Google Scholar] [Crossref]

3. J. Z. Balanta et al. "Replacement Strategies of Power Transformers: Literature Review" Energies, vol. 16, no. 11, 2023. [Google Scholar] [Crossref]

4. M. Toren, "Optimization of transformer parameters using combined grey wolf-whale algorithm," Industry, Engineering and Science Trans., vol. 43, no. 1, pp. 1-10, Jan. 2023. [Google Scholar] [Crossref]

5. H. Haro-Larrode, "Variable Reactance Criteria To Mitigate Deviations In Power Transformers Voltage," Machines, vol. 11 no8 2023. [Google Scholar] [Crossref]

6. Azizah, A., Purnomo, R., Shamsuri, N., Bayati, N., Nance, C., & Jiong, W. (2020). [6] Failure to account for load heterogeneity in transformer sizing. J. Elec. Eng. 12 2020. [Google Scholar] [Crossref]

7. J. Shiles et al. Adaptive Protection for Modern Distribution Systems WPRC, 2017. [Google Scholar] [Crossref]

8. R. Yang et al., "Two-layer Optimization Methodology for Distribution Network," Chinese Journal of Electrical Engineering, vol. 11, no. 1, 2025. [Google Scholar] [Crossref]

9. R. O. Oliyide and L. M. Cipcigan Adaptive thermal model for loading of transformers in Sub-Saharan Africa Scientific African 2023 vol 20 [Google Scholar] [Crossref]

10. A. A. Taheri et al, "Normal cyclic overloading strategy for indoor distribution transformers," IET Generation, Transmission & Distribution, vol. 14, 2020. [Google Scholar] [Crossref]

11. F. Saeed, S. Al-Marjaily, E. Saidu, and D. Habib, "SmartFormer: Graph-based transformer model for energy load forecasting" in Sustainable Energy Technologies, vol. 73, pp. 1, 2025. [Google Scholar] [Crossref]

12. O. N. Igbogidi, A. A. Dahunsi, "Enhancement of Power Supply with Paralleling of Transformers," IRJET vol. 7, 2020. [Google Scholar] [Crossref]

13. S. M. Miraftabzadeh et al., "Deep Learning in Power Systems: A Bibliometric Analysis," in the journal "IEEE Access," vol. 12, number 2014. [Google Scholar] [Crossref]

14. S. Wang et al. Optimal Capacity Planning for Detachable Transformer Modules. in: SSR Tranon. ed. ins. Comm. in Electr. Sci. Eur. Trans. A. Soc. IEEE Vol. 60, pp. 1 149. doi:10. [Google Scholar] [Crossref]

15. P. Pandiyan et al., "A review of the developed advancements of the green IoT in the field of smart grids," Energy Reports, vol. 11, 2024. [Google Scholar] [Crossref]

16. H. V. Newscott, R. in paper tigers look whimsical, ibsn, vol. Ijasbh ija ilio da eyem. [Google Scholar] [Crossref]

17. R. A. Moise and A. Fratu, "Parallel Working of the Transformers with Different Voltage Ratios," RECENT, vol. 23, 2022. [Google Scholar] [Crossref]

18. O. Z. Lin, C. C. Myint, "Modified Techniques for Reliability Improvement by Parallel Operation," JEET, vol. 13, 2019. [Google Scholar] [Crossref]

19. V. N. Ogar, "Load Frequency Control Using the Particle Swarm Optimisation," Journal of Engineering Research. [Google Scholar] [Crossref]

20. E. Zientek, "Loading in Consideration When Paralleling Transformers," Schneider Electric Whitepaper, 2011. [Google Scholar] [Crossref]

• The Impact Of UI/UX Design on User Trust and Task Completion in Civic Tech Platforms
• Solar Cell Photovoltaic Model Shell Sp 75
• Development of an Intelligent Traffic Management System to Address Visibility Obstruction at Urban Intersections: A Case Study of Ibadan Metropolis
• Optimum Placement of Facts Devices on an Interconnected Power Systems Using Particle Swarm Optimisation Technique
• Assessing Construction Transformation and Implication on Future Production Flow System