Browsing by Author "Petinrin, J. O."

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Microgrids: a decentralized alternative for rural electrification in Nigeria
(2020) Petinrin, J. O.; Petinrin, M. O.; Johnson, D. O.
Poor electricity services remain a major obstacle to growth in Nigeria, as inadequate and epileptic power supply undermines investment opportunity, economic growth, social and infrastructure developments. Centralized power generation, transmission and distribution system operations in Nigeria can no longer deliver competitively cheap and reliable electricity to remote customers on and off the national grid. Anticipated development in generation with a balanced combination of ongrid and off-grid power projects is very achievable in Nigeria. A balanced approach could potentially lead to an accelerated journey to full electrification in the country. This would in turn result in a significant boost of the country’s economy, as power has been proven to be an enabler of other sectors of the economy. This paper presents micro grids as a decentralized alternative for rural electrification in Nigeria. The paper reviews the electrification status in Nigeria, power management of micro grid and prospect of renewable energy for rural energy provision. The benefits, challenges and future prospects of micro grid are also discussed. Implementation of decentralized micro grid across 774 local governments of Nigeria with five (5) micro grids installed in each local government will not only improve the wellbeing of Nigerian rural dwellers, but also enhance Nigeria's energy and economic prospects for potential global investment.
Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm
(2021-02) Ogunsina, A. A.; Petinrin, M. O.; Petinrin, O. O.; Offornedo, E. N.; Petinrin, J. O.; Asaolu, G. O.
A system of power generation whereby the generating equipment is located close to the point of usage, thereby reducing losses and operation cost is called distributed generation (DG). However, it is imperative that DGs are sited such that the quality of power delivered is optimized and the total real power loss within the system minimized. This paper proposes an approach for optimum sizing and siting of DGs sizing in a power distribution system using Ant Colony Optimization (ACO) algorithm. To validate the algorithm the IEEE 30 bus standard test system was employed. A 92% decrease in real power loss within the system relative to the value before the connection of DGs was observed, while the minimum bus voltage increased from 0.656 per unit to 0.965 per unit. The results obtained from ACO are further verified by creating an ETAP model of the IEEE 30 bus system and simulating the impact of DG on the system. A significant reduction in total real power losses within the system and improvement in voltage profile was observed when the DGs are placed at the ACO derived sites relative to at other locations. Therefore, Ant Colony Algorithm can be used in deriving the optimum sites and sizes of DGs in a power distribution system.
Voltage control in distribution feeders with high penetration of wind energy
(2017-07) Petinrin, J. O.; Shaaban, M.; Petinrin, M. O.
The recent drift towards balancing generation and consumption, along with increasing demands of high power quality and reliability, require the deployment of energy storage and application of demand response in the smart grid. The potential for using energy storage and demand response promise to have a major impact on schemes for voltage control in a smart grid. This paper presents a comprehensive optimisation architecture that do not only take into consideration the coordination of VAr control devices, but also manages storage facilities and demand response in an hourly operation fashion. An integrated framework on hybrid Particle Swarm Optimisation/Gravitational Search Algorithm (PSOGSA) is used for VAr control devices, energy storage and demand response optimisation scheduling. The effectiveness of the proposed method is validated through a quasi-time sequence analysis over a 24-hourly simulation period. Test results show that the smart coordinated operation among the control devices causes reduction in system losses and enhances system capability to maintain voltages within the prescribed bounds.