Differential Evolution Optimization Algorithm Based on Generation Systems Reliability Assessment Integrated with Wind Energy

Kadhem, Athraa Ali; Wahab, Noor Izzri Abdul; Abdalla, Ahmed N.

doi:10.1109/pgsret.2019.8882705

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…The designs of the variable control values for the proposed DEOA algorithm was documented as displayed in Table 1 [26], during applied at the "Test System-79 & 96" The DEOA algorithm was applied for 100 iterations run consecutively in matching conditions as previously stated, to verify the robustness and confidence of this algorithm. The results of the various implementations are presented in Table 2.…”

Section: Run I: Valuation Of Algorithm Performance For the "Rts-79" Smentioning

confidence: 99%

The Contribution of Wind Energy Capacity on Generation Systems Adequacy Reliability using Differential Evolution Optimization Algorithm

Kadhem¹,

Wahab²,

Abdalla³

2020

Adv. sci. technol. eng. syst. j.

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Currently, increasing penetration of the Wind Energy Conversion System (WECs) in Power generation systems has influenced the supply of electrical power reliability for the consumer in comparison with other traditional sources. In this paper, the performance and efficiency of a new optimization approach referred to as the "Differential Evolution Optimization Algorithm" (DEOA) to measure the reliability of power adequacy systems (RPAs). The proposed intelligent algorithm which relies on the Population-based Intelligent Search (PBIs) technique is viewed as a feasible alternative for the Monte Carlo simulation (MCS) method in the assessment of the non-chronological system. The benefit of utilizing this algorithm is apparent in the manner it expedites the calculation and achieves greater precision with less calculation effort. Additionally, there is a deeper understanding of the effect of the increasing levels of wind energy on generation adequacy from the WECs sources to satisfy future power electricity demands. In addition, the effectiveness of the suggested algorithm in assessing the RPAs was compared to the analytical and MCS method.

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Section: Run I: Valuation Of Algorithm Performance For the "Rts-79" Smentioning

confidence: 99%

The Contribution of Wind Energy Capacity on Generation Systems Adequacy Reliability using Differential Evolution Optimization Algorithm

Kadhem¹,

Wahab²,

Abdalla³

2020

Adv. sci. technol. eng. syst. j.

Self Cite

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show abstract

“…Another vein of study is to assess the reliability of power generating plants since the availability of reliable power supply is important. Assessing the reliability power generation system usually done through simulation or analytical methods with the various reliability indices, for example, loss of load frequency, loss of energy expectation, and loss of load expectation [18]. Simulation techniques may result in high computational burden in complex system [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Preventive Maintenance and Forced Outages in Power Plants in Korea

et al. 2020

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Maintaining high facility reliability in power plants is essential to secure long-term electricity supply. This paper applies the survival analysis to the actual unit level power generation data in Korea to estimate the relationship between facility reliability and the preventive maintenance. Duration of generators between forced outages is used to measure plant reliability. the empirical analysis shows that preventive maintenance cost, planned outage for maintenance, use rate, and reserve margin lead to the longer duration of generators and, in turn, the lower forced outage rates. We uncover that the marginal benefit of the preventive maintenance cost is decreasing at an increasing rate. It indicates that the marginal benefit of the “current” maintenance cost is minimal. Results in the paper imply that power plants in Korea might be spending unnecessarily high maintenance costs considering already having world’s lowest forced outage rates.

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Effects of Unavailability of Conventional Energy Units on Power Generation System Adequacy

Ali Kadhem,

Abdul Wahab

2024

JST

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Presently, aside from conventional power, wind energy is considered an important power source in electrical power supply systems. The prime factor affecting electrical power supply systems is the blackout of electrical power for load demand-supply. Therefore, the safe operation of interconnected large power systems integrated with wind energy cannot be carried out without understanding the system’s behavior during abnormal and emergencies. In power generation systems, failure of the conventional generating units (CGUs) and wind turbine generating units (WTGUs) will lead to service interruption and subsequent disconnection of load points. This paper analyzes the impact of frequent failures of the CGUs and WTGUs on the output power systems. A Sequential Monte Carlo Simulation (SMCS) method and the Frequency and Duration (F&D) method are extremely effective for estimating the variation of risk indices when additional wind turbine generators are incorporated into the generation system. The results demonstrate the variation of reliability indices in the adequacy systems when additional WTGUs are incorporated into the generation system.

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Differential Evolution Optimization Algorithm Based on Generation Systems Reliability Assessment Integrated with Wind Energy

Cited by 3 publications

References 30 publications

The Contribution of Wind Energy Capacity on Generation Systems Adequacy Reliability using Differential Evolution Optimization Algorithm

The Contribution of Wind Energy Capacity on Generation Systems Adequacy Reliability using Differential Evolution Optimization Algorithm

Preventive Maintenance and Forced Outages in Power Plants in Korea

Effects of Unavailability of Conventional Energy Units on Power Generation System Adequacy

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