Optimum generation scheduling incorporating wind energy using HHO–IGWO algorithm

Dhawale, Dinesh; Kamboj, Vikram Kumar; Anand, Priyanka

doi:10.1186/s43067-022-00067-w

Cited by 11 publications

(3 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equation ( 24) provides a technical illustration of the numeric value matrix that represents the unit's on/off schedule. (24) where U art , which is the operational state of the g th unit for the h th hour, is either activated or deactivated.…”

Section: C) Implementation Criteria To Solve Ucp Using the Proposed A...mentioning

confidence: 99%

See 1 more Smart Citation

Modified Arithmetic Algorithms for Optimal Power System Operation Considering Uncertainties From Intermittent Renewable Energy and Electric Vehicles

Abdelhakeem,

Hasaneen,

Helmy

et al. 2024

IEEE Access

View full text Add to dashboard Cite

The integration of Renewable Energy Resources (RENs) and the increasing usage of Electric Light Duty Vehicles (LDVs) are considered decisive measures for meeting international commitments towards reducing greenhouse gas (GHG) emissions in pursuit of sustainability. However, the complexity that arises from the inherent instability and uncertainty associated with these measures affects power grids and significantly complicates the Unit Commitment Problem (UCP). This research paper introduces two unique optimization techniques which are the Main Arithmetic Approach (AOT) and the Modified Arithmetic Approach (IAOT) to address the optimal decisions for the UCP considering intermittent RENs and LDVs. The AOT exploits the statistical characteristics inherent in basic mathematical operators. Additionally, AOT leverages the probability distributions associated with fundamental mathematical operators to optimize its operations. Conversely, the proposed IAOT boosts effectiveness by harnessing the benefits of natural logarithms and exponential operators with high-density values for operator selection to produce a more flexible search process. Moreover, the IAOT takes advantage of the unique properties of natural logarithms and exponential operators with high-density values to achieve improved performance. Real power system data is utilized to conduct a comprehensive analysis involving four distinct UCP case studies with twelve relevant scenarios ranging from SA1 to SF2 showing the low and prominent levels of penetration of LDVs in different seasonal conditions that incorporate uncertainties of RENs. The effectiveness of the elected approaches is examined through key performance indicators including the overall operating costs per day (OCD) and the costeffectiveness ratio (CER), considering distinct LDVs profiles and levels of RENs penetration. The study shows significant insights into the scenarios analyzed. Scenario SF1 -IAOT is the most cost-effective alternative, with OCD of $528,430, closely followed by SB1 -IAOT, which costs $529,550. Conversely, Scenario SD2 -AOT has the greatest OCD of $559,667. Furthermore, the CER and OCD offer useful insights. SB1 -IAOT has the lowest OCD (20.69), whereas SD2 -AOT has the greatest OCD (21.92). In terms of CER, Scenario SE1 -AOT has the greatest value of 0.91, whereas SB1 -IAOT, SA1 -AOT, SC1 -IAOT, and SF2 -IAOT have the lowest CER of 0.86., highlighting the effectiveness of incorporating RENs and LDVs in achieving favorable financial implications for grid operators and decision-makers. The comprehensive analysis results demonstrate the elected techniques' applicability and superiority in finding the best optimal solutions to the UCP incorporating different RENs and LDVs scenarios.

show abstract

Section: C) Implementation Criteria To Solve Ucp Using the Proposed A...mentioning

confidence: 99%

“…Furthermore, integrating large-scale RENs frequently necessitates changes to existing transmission and distribution networks. This is because RENs, such as wind farms, are frequently located in distant places, far from population centers where power is required [24].…”

Section: Introductionmentioning

confidence: 99%

Modified Arithmetic Algorithms for Optimal Power System Operation Considering Uncertainties From Intermittent Renewable Energy and Electric Vehicles

Abdelhakeem,

Hasaneen,

Helmy

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Researchers continue to explore its potential and refine its techniques for various applications [28,29].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization and Performance Analysis of Bimorph Magneto-Electro-Elastic Energy Harvesters

Moory Shirbani,

Alavi

2024

FU Mech Eng

View full text Add to dashboard Cite

This study thoroughly investigates the multi-objective optimization of a magneto-electro-elastic (MEE) harvester in bimorph configurations and by the new method of Harris Hawk’s optimization (HHO). The harvesters are configured in both series and parallel connections and under harmonic excitation to explore the effects of various parameters on the performance of the harvesting system. The primary objective is to maximize the total harvested power. Optimization involves various parameters, including dimensions, relative displacement changes, voltage, and current values. The Pareto fronts from the HHO method reveal optimal points in different configurations and scenarios. Notably, the optimal points are selected based on the criterion of maximum total power. The results reveal distinct optimal points for each objective function, demonstrating trade-offs between performance metrics. These findings provide valuable insights into the design and operation of efficient energy harvesters in MEE systems. The parallel configuration outperforms the series connection in terms of the current generation. Moreover, the evaluation of the overall performance of the energy harvesters in terms of total harvested power indicated that both series and parallel connections could lead to promising outcomes. However, the series connection exhibited a more dominant effect on maximizing the total harvested power, proving its relevance in pursuing the highest possible power output.

show abstract

BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet

Luján-García,

Cardoso-Moreno,

Yáñez-Márquez

et al. 2023

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Optimum generation scheduling incorporating wind energy using HHO–IGWO algorithm

Cited by 11 publications

References 32 publications

Modified Arithmetic Algorithms for Optimal Power System Operation Considering Uncertainties From Intermittent Renewable Energy and Electric Vehicles

Modified Arithmetic Algorithms for Optimal Power System Operation Considering Uncertainties From Intermittent Renewable Energy and Electric Vehicles

Multi-Objective Optimization and Performance Analysis of Bimorph Magneto-Electro-Elastic Energy Harvesters

BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet

Contact Info

Product

Resources

About