An Improved Analytical Method For Optimal Sizing And Placement Of Power Electronic Based Distributed Generation Considering Harmonic Limits

Abubakar, Adamu Saidu; Olaniyan, A.A.; Ibrahim, Abdul-Wahab; Sulaiman, Sulaiman H

doi:10.1109/powerafrica.2019.8928658

Cited by 6 publications

(5 citation statements)

References 11 publications

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“…The success rate of a CSA is generally evaluated based on its ability to find high-quality solutions within a reasonable amount of time, convergence speed, and robustness across different problem types. Assessment of success rates is done using benchmark problems, real-world applications, or mathematical functions that serve as a standard to compare the performance of different optimization algorithms [2].…”

Section: Cuckoo Search Algorithmmentioning

confidence: 99%

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Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

Timta,

Umar,

Timta

et al. 2024

PakJET

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This work presents an improved cuckoo search algorithm based on Success Rate (CSA-SR) for optimal allocation of Distributed Generation (DG). This is necessary in order to improve the power quality of the distribution system by minimizing power loss and improving voltage stability. Voltage Stability Index (VSI) is applied to identify restricted unhealthy buses/areas in the distribution networks. The work is implemented on standard IEEE 33 Bus test systems. Newton Raphson Power Flow (NRPF) technique is used in MATLAB R2019b environment for the power flow analysis. The overall IEEE 33 Bus system real power loss obtained from the simulation result is found to be 202.7071MW at the base case. Following the application of 3 DGs using CSA-SR, the real power loss is found to be 113.9630 MW which shows a reduction of 88.441MW which is equivalent to 43.77% as related to the base case. The results minimized the system losses while significantly enhancing the voltage profile of the bus voltages as a result of optimal siting and sizing of the DG. These show that the CSA-SR technique outperformed PSO, which was used to ascertain the effectiveness of the developed scheme.

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Section: Cuckoo Search Algorithmmentioning

confidence: 99%

“…Energy demand grows at a faster pace than electricity generation due to continuous growth in population, enhanced industrialization and improvement in living standards [1,2]. Electricity generation from fossil fuels still remains the main source of energy generation [3].…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

Timta,

Umar,

Timta

et al. 2024

PakJET

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“…Electrical energy plays an important role in the development of any nation. This is because, the level of energy consumed or generated is a great determinant in measuring the development of modern civilization [1,2]. Recently, generating electrical energy from renewable sources to meet load demand has been regarded as an alternative to the conventional sources of energy generation [3].…”

Section: Introductionmentioning

confidence: 99%

Non-Linear Model Predictive Speed Control of Six Phase Squirrel Cage Generator in Wind Energy System

Umar Musa,

Sarip,

Mas'ud

et al. 2023

2023 IEEE 6th International Conference on Electrical, Electronics and System Engineering (ICEESE)

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Due to the intermittent nature of wind, varying wind speed causes imbalance in the current of the six phase squirrel cage induction generator (SCIG). These changes in the input signal create inbalance in the current and therefore causes deviations in the torque and flux of the generator. Therefore, this work develops non-linear model predictive control (NMPC) scheme for the generator to ensure that uncertainties in the input of the wind energy conversion system (WECS) have little effect in the quality of output power supplied to the grid. Simulation results obtained when NMPC technique was used in controlling the generator in the WECS showed the effectiveness of the aforementioned technique. The results obtained from the developed scheme were compared with those obtained when backstepping controller was used in controlling the six phase SCIG. It was observed that the developed scheme outperformed the backstepping technique in terms of electromagnetic torque by 16.844%, while a 61.1% improvement was observed in terms of settling time for the rotor flux of the developed technique over that of the backstepping. Finally, the results obtained for the DC link voltage output showed an improvement in terms of overshoot and settling time respectively.

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“…lectrical power generated or consumed in a country plays significant role on the level of development of that country (Abdulwahab et al, 2020;Shankar & Mukherjee 2016). Due to continuous increase in the price of fuel and growing concerns over global climate change, countries are deploying alternative means of generating electricity (Abdulwahab et al, 2021;Abubakar et al, 2019;Jibril et al, 2019). Renewable energy sources (RES) include: wind, solar, biomass, bio-fuel and geothermal energy (Wang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

Abdulwahab¹,

Faskari²,

Belgore³

et al. 2021

FUOYEJET

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This paper presents an improved hybrid micro-grid load frequency control scheme for an autonomous system. The micro-grid system comprises of renewable and non-renewable energy-based Power Generating Units (PGU) which consist of Solar Photovoltaic, WT Generator, Solar Thermal Power Generator, Diesel Engine Generator, Fuel Cell (FC) with Aqua Electrolizer (AE). However, power produce from renewable sources in microgrid are intermittent in supply, hence make it difficult to maintain power balance between generated power and demand. Therefore, Battery energy storage system, ultra-capacitor and flywheel energy storage systems make up the energy storage units. These separate units are selected and combined to form two different scenarios in this study. This approach mitigates frequency fluctuations during disturbances (sudden load changes) by ensuring balance between the generated power and demand. For each scenario, Moth flame optimization algorithm optimized Proportional-Integral controllers were utilized to control the micro-grid (to minimize fluctuations from the output power of the non-dispatchable sources and from sudden load change). The results of the developed scheme were compared with that of Quasi-Oppositional Harmony Search Algorithm for overshoot and settling time of the frequency deviation. From the results obtained, the proposed scheme outperformed that of the quasi-oppositional harmony search algorithm optimized controller by an average percentage improvement of 35.95% and 28.76% in the case of overshoot and settling time when the system step input was suddenly increased. All modelling analysis were carried out in MATLAB R2019b environment. Keywords—Frequency Deviation, Micro-grid, Moth flame optimization algorithm, Quasi-Oppositional Harmony Search Algorithm.

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An Improved Analytical Method For Optimal Sizing And Placement Of Power Electronic Based Distributed Generation Considering Harmonic Limits

Cited by 6 publications

References 11 publications

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

Non-Linear Model Predictive Speed Control of Six Phase Squirrel Cage Generator in Wind Energy System

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

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