Control of Dual Stator Induction Generator Based Wind Energy Conversion System

Ibrahim, Abdul-Wahab; Abubakar, Adamu Saidu; Olaniyan, A.A.; Sadiq, Bashir Olaniyi; Faskari, Shehu A.

doi:10.1109/nigercon54645.2022.9803100

Cited by 3 publications

(10 citation statements)

References 13 publications

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“…𝐼 𝑖 ≤ 𝐼 𝑖 𝑚𝑎𝑥 (5) where, 𝐼 𝑖 , 𝐼 𝑖 𝑚𝑎𝑥 and Ri are the current in ith branch, thermal limit of ith branch and resistance of the system respectively. V k is the voltage at kth bus and Vksp is the specified voltage of kth bus.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Perform contingency analysis to evaluate the system's robustness under various fault scenarios. Ensure that the selected bus numbers and generator ratings can handle contingencies [5].…”

Section: Power Flow Analysismentioning

confidence: 99%

“…However, generation of electricity from these sources ( oil, gas, coal, etc.) has negative impact on the environment in addition to continuous changes in fuel prices [4,5]. This has increased the urge of researchers and governments in countries to generate electricity from renewable energy sources [6].…”

Section: Introductionmentioning

confidence: 99%

“…The distribution system's operations were investigated, and a sensitivity analysis was created to determine the best location and DG unit size for an unbalanced radial distribution system. Reference [5] conducted research on the effects of adding dispersed generators to the electrical power supply. Distributed generation was included in the DN in order to reduce voltage drop and power losses in the network.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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: Problem Formulationmentioning

confidence: 99%

“…Perform contingency analysis to evaluate the system's robustness under various fault scenarios. Ensure that the selected bus numbers and generator ratings can handle contingencies [5].…”

Section: Power Flow Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

Timta,

Umar,

Timta

et al. 2024

PakJET

View full text Add to dashboard Cite

show abstract

“…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]. To ensure improved installation of more effective wind turbines in windy zones, different types of generators and various wind turbine concepts are being developed [4].…”

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)

Self Cite

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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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2023

JESTR

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Concerns surrounding the environment along with inadequate energy supply and high cost of same are responsible for pollution, high energy demand, unpredictable and uneconomical power generation. These have contributed to the widespread agreement that sustainable renewable energy sources (RES) must be developed, particularly in isolated villages where expanding the grid may be challenging and financially unviable for power corporations. As a result, in order to effectively and cheaply utilize the plentiful renewable energy resources, an optimal sizing approach is required. This study is aimed at investigating the economic performance of the hybrid system of a stand-alone Small Hydropower/PV/Diesel generator with battery electricity production. The cost function was minimized using Dragonfly Algorithm (DA) in order to minimize the Cost of Energy (COE) generation. The decision variables are the number of small hydro turbines (NSHP), number of solar panels (NPV), number of batteries (NBATT) and the capacity of Diesel generator (PDG). The developed method is applied to a typical Kiri village in Shelleng Local Government area of Adamawa State. For uniformity, the hourly solar irradiance data were created by converting the monthly average solar irradiance data. A dragonfly optimization technique was utilized to reach an optimum solution for the hybrid system. The result obtained showed that the system components: small Hydropower, solar PV and Diesel generator were able to generate electrical power of 5,783,600 W, 56,259 W and 5.2941e-05 W respectively to meet the energy demand. Results obtained from the developed scheme were compared with those obtained when TORSCHE algorithm was used in optimizing the hybrid system. It was observed that a total energy cost of $5,224,500 was obtained for the developed technique while $5,839,600 was obtained as the total cost for the TORSCHE model. This showed that the developed scheme outperformed the system output from the TORSCHE algorithm in terms of cost of energy by 89.46%.

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Control of Dual Stator Induction Generator Based Wind Energy Conversion System

Cited by 3 publications

References 13 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

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