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Kaberere, Keren K.
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Electrical & Electronics Engineering

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Improving frequency regulation for future low inertia power grids: a review Wamukoya, Brian K.; Muriithi, Christopher M.; Kaberere, Keren K.
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5873

Abstract

The modern power system is witnessing an unprecedented increase in the penetration of renewable variable generation (VG) sources. Increased uptake of converter interfaced VG like solar PV and wind power while replacing conventional synchronous generators (SGs) introduces new challenges to grid operators in terms of dynamically handling frequency stability and regulation. Reducing the number of SGs while increasing non-synchronous, inertia-less converter interfaced VG reduces grid natural inertia, which is critical for maintaining frequency stability. To cure inertia deficiency, researchers, broadly, have proposed implementing supplemental control strategies to VG sources or energy storage systems to emulate natural inertia (virtual inertia (VI)). Alternatively, VG sources can be operated below their maximum power point (deloaded mode), making available a reserve margin which can rapidly be deployed in case of a contingency with the help of power electronic devices, to provide fast frequency response. This paper reviews recent solutions proposed in literature to address the low inertia problem to improve frequency stability. Additionally, it highlights the formulation of an optimization problem for VI sizing and placement as well as techniques applied in solving the optimization problem. Finally, gaps in literature that require further research were identified
Optimization of dynamic transmission network expansion planning using binary particle swarm optimization algorithm Inyanga, Faith Eseri; Muisyo, Irene N.; Kaberere, Keren K.
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8944

Abstract

Increasing power demand is usually met by the expansion of generation capacity. The transmission network should be expanded in tandem to ensure power is evacuated from generation points to the load centres. Inadequate power capacity causes congestion. Congestion results due to under-voltages and violation of transmission lines’ loading limits. Constructing additional transmission lines is required to alleviate the congestion after measures of increasing the transmission line’s transfer capability are exploited. Transmission network expansion planning (TNEP) determines the transmission lines to be added to a power system at minimal construction cost, without violating network constraints. In this research, voltage limit violations are penalized in a constrained dynamic TNEP problem for a 10-year planning horizon. The optimal location and number of new transmission lines required at minimal construction cost, and transmission losses associated with the transmission network operations are determined. Improved binary particle swarm optimization (IBPSO) algorithm is applied to optimize the dynamic transmission network expansion planning (DTNEP) results. The developed model is tested on Garver’s 6-bus system using MATLAB. The construction cost for new transmission lines is minimized, and transmission losses reduced when compared to other published works without violating voltage limits (±5%) and transmission lines’ thermal capacities. The transmission network system adequacy is improved.
Co-Authors Inyanga, Faith Eseri Muisyo, Irene N. Muriithi, Christopher M. Wamukoya, Brian K.