Research on user-side flexible load scheduling method based on greedy algorithm

Ge, Peiran; Sun, Liang; Wang, Fuwang

doi:10.1016/j.egyr.2022.10.352

Cited by 6 publications

(2 citation statements)

References 3 publications

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“…After crossover and mutation operations, obvious infeasible solutions can be quickly eliminated according to the power and energy constraints. From the comparison, it can be seen that the method proposed in this paper was significantly faster than the binary particle swarm optimization [32], the differential evolution algorithm [33], the simulated annealing algorithm [34], and the traversal solving algorithm [35], of which the results obtained using the traversal solving algorithm could be regarded as the benchmark. Through comparison, it was found that the algorithm proposed in this paper can find a solution very close to the optimal solution in a relatively short period of time.…”

Section: Island Partition Schemementioning

confidence: 99%

Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation

Hao,

Huang,

et al. 2023

Energies

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More and more distributed generation (DG) and energy storage (ES) devices are being connected to the distribution network (DN). They have the potential of maintaining a stable supply load during failure periods when using islanding operations. Therefore, DG and ES have capacity value, i.e., improving the power supply capability of the system. However, there are strong fluctuations in DG outputs, and the operations of ES devices have sequential characteristics. The same capacity of DG has different load-bearing capabilities compared to conventional thermal or hydroelectric units. This paper proposes a method for evaluation of power supply capability improvement in DNs. First, the temporal fluctuation in both power source and load demand during fault periods is considered. A DN island partition model considering the secondary power outage constraint is established. Then, a modified genetic algorithm is designed. The complex island partition model is solved to achieve accurate power supply reliability evaluation. And the incremental power supply capability associated to DG and ES devices is calculated. Finally, a case study is conducted on the PG&E 69-bus system to verify the effectiveness of the proposed method. It is found that with a 20% configuration ratio of ES devices, the power supply capability improvement brought about by 6 MW DG can reach about 773 kW.

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Section: Island Partition Schemementioning

confidence: 99%

Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation

Hao,

Huang,

et al. 2023

Energies

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“…The Pearson correlation coefficient plays a pivotal role in the optimization of the K-means clustering algorithm, particularly by quantifying linear relationships, enhancing K-means clustering, and optimizing cluster representation. Calculate the Pearson correlation coefficient of the selected daily wind power output data, and use the Greedy Algorithm to find the output curve with the lowest correlation as the clustering center [19]. Then, use K-means for clustering and repeat several times to find the clustering result corresponding to the maximum silhouette coefficient [12].…”

mentioning

confidence: 99%

Feature Extraction Approach for Distributed Wind Power Generation Based on Power System Flexibility Planning Analysis

Hu,

Yang,

Wang

et al. 2024

Electronics

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This study addresses the integral role of typical wind power generation curves in the analysis of power system flexibility planning. A novel method is introduced for extracting these curves, integrating an enhanced K-means clustering algorithm with advanced optimization techniques. The process commences with thorough data cleaning, filtering, and smoothing. Subsequently, the refined K-means algorithm, augmented by the Pearson correlation coefficient and a greedy algorithm, clusters the wind power curves. The optimal number of clusters is ascertained through the silhouette coefficient. The final stage employs particle swarm and whale optimization algorithms for the extraction of quintessential wind power output curves, essential for flexibility planning in power systems. This methodology is validated through a case study involving wind power output data from a new energy-rich provincial power grid in North China, spanning from 1 January 2019, to 31 December 2022. The resultant curves proficiently mirror wind power fluctuations, thereby laying a foundational framework for power system flexibility planning analysis.

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Optimizing Art Studio Connectivity: A Haversine and Greedy Algorithm Approach for Navigation in Cirebon Indonesia

Permana,

Arlovin,

Hidayat

et al. 2023

2023 17th International Conference on Telecommunication Systems, Services, and Applications (TSSA)

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Research on user-side flexible load scheduling method based on greedy algorithm

Cited by 6 publications

References 3 publications

Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation

Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation

Feature Extraction Approach for Distributed Wind Power Generation Based on Power System Flexibility Planning Analysis

Optimizing Art Studio Connectivity: A Haversine and Greedy Algorithm Approach for Navigation in Cirebon Indonesia

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