Optimal re-dispatch of generator for congestion management using PSO

Mahala, Hemant; Kumar, Y. V. Pavan

doi:10.1109/icgccee.2014.6922307

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…This reflects that in actual grid operation, the output of thermal generators may increase from the planned value due to grid congestion. The constraint in (12) selects the thermal generators that are not to be curtailed based on the sum of the sensitivity values to the congested lines. In addition, (2)-( 9) described in Section 3.1, are also considered as constraints.…”

Section: Thermal Power Output Curtailment Considering Sensitivitymentioning

confidence: 99%

“…Table IV lists the settings of the two comparison methods in Case 2. All of these methods determine the output curtailment rate of each thermal generator based on the objective function in (11) under the constraints in ( 2)-( 9) and (12). Furthermore, they minimize the output curtailment of REs based on the constraints in ( 2)-( 9) and the objective function in (13) Fig.…”

Section: Case 2: Evaluation Of Output Curtailment Of Res Based On Sen...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…In previous studies, the output curtailment was determined to minimize the cost of an operation as well as the amount of curtailment of generators, and consequently the effectiveness was verified [12][13][14][15][16][17][18][19]. For instance, methods for determining the output curtailment rate were proposed to minimize the above objective functions based on quasi-optimization methods such as particle swarm optimization (PSO) and multi-objective particle swarm optimization (MOPSO) [12][13][14]. Further, methods to minimize the amount of output curtailment and reduce the output adjustment cost by considering the effect of mitigating grid congestion through sensitivity analysis were proposed as well [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Mitigation of Grid Congestion by Curtailment of Thermal Generators and Renewable Energies Based on Sensitivity Analysis

Tanno

Kaneko

Hayashi

et al. 2022

IEEJ Transactions Elec Engng

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Grid congestion is expected owing to the interconnection of massive renewable energies within the transmission system. Power system operators need to resolve the problem by controlling the output of thermal and renewable generators, such as curtailment, which should be the smallest possible for efficient utilization. Moreover, the equality of generation opportunities should be maintained among renewable energies. However, achieving the two objectives simultaneously is challenging, because the output curtailment effect on grid congestion in a loop system varies depending on its configuration. Further, the thermal generators are curtailed before renewable energies in the merit order scheme necessitating adjustments in the thermal generator output considering the renewable energy curtailment. This study proposed a method to determine the output curtailment ratio of thermal power and renewable energies employing sensitivity analysis, aiming to ensure equality, and maximize the power generation opportunities of renewable energies for the mitigation of grid congestion. The effectiveness of the proposed method was verified via numerical simulations using a power system model based on an actual power system in the northern Tohoku area of Japan. The results indicate that the proposed method can reduce the total amount of curtailment and improve the equality of generation opportunities.

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Section: Thermal Power Output Curtailment Considering Sensitivitymentioning

confidence: 99%

Section: Case 2: Evaluation Of Output Curtailment Of Res Based On Sen...mentioning

confidence: 99%