The Linear Formulation of Thermal Unit Commitment Problem with Uncertainties through a Computational Mixed Integer

Ahsan, Mian Khuram; Pan, Tianhong; Li, Zhengming

doi:10.4236/jpee.2018.66001

Cited by 4 publications

(1 citation statement)

References 21 publications

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“… d : Power load demand at time (  ).  The unequal constraints 1) Spinning power reserve requirement The Spinning power reserve is essential in the operation of the power system and is determined as a sufficient percentage of the PLD as follows [14] [15]:…”

Section: ( )mentioning

confidence: 99%

Optimal Unit Commitment with Renewable Energy in Regulated and Deregulated Systems

El‐Ela¹,

Allam²,

Doso³

2022

EPE

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In this paper, the impact of the wind power generation system on the total cost and profit of the system is studied by using the proposed procedure of binary Sine Cosine (BSC) optimization algorithm with optimal priority list (OPL) algorithm. As well, investigate the advantages of system transformation from a regulated system to a deregulated system and the difference in the objective functions of the two systems. The suggested procedure is carried out in two parallel algorithms; The goal of the first algorithm is to reduce the space of searching by using OPL, while the second algorithm adjusts BSC to get the optimal economic dispatch with minimum operation cost of the unit commitment (UCP) problem in the regulated system. But, in the deregulated system, the second algorithm adopts the BSC technique to find the optimal solution to the profit-based unit commitment problem (PBUCP), through the fast of researching the BSC technique. The proposed procedure is applied to IEEE 10-unit test system integrated with the wind generator system. While the second is an actual system in the Egyptian site at Hurghada. The results of this algorithm are compared with previous literature to illustrate the efficiency and capability of this algorithm. Based on the results obtained in the regulated system, the suggested procedure gives better results than the algorithm in previous literature, saves computational efforts, and increases the efficiency of the output power of each unit in the system and lowers the price of kWh. Besides, in the deregulated system the profit is high and the system is more reliable.

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Section: ( )mentioning

confidence: 99%

Optimal Unit Commitment with Renewable Energy in Regulated and Deregulated Systems

El‐Ela¹,

Allam²,

Doso³

2022

EPE

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Mitigating wind energy uncertainties and operational constraints in solving the unit commitment problem in power systems through enhanced arithmetic optimization techniques

Abdelhakeem,

Hasaneen,

Helmy

et al. 2024

Energy Reports

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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

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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.

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The Linear Formulation of Thermal Unit Commitment Problem with Uncertainties through a Computational Mixed Integer

Cited by 4 publications

References 21 publications

Optimal Unit Commitment with Renewable Energy in Regulated and Deregulated Systems

Optimal Unit Commitment with Renewable Energy in Regulated and Deregulated Systems

Mitigating wind energy uncertainties and operational constraints in solving the unit commitment problem in power systems through enhanced arithmetic optimization techniques

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

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