Simulation on Supplier Side Bidding Strategy at Day-ahead Electricity Market Using Ant Lion Optimizer

Jain, Kunal; Saxena, Akash

doi:10.47852/bonviewjcce2202160

Cited by 27 publications

(14 citation statements)

References 25 publications

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“…To verify the advantages of the proposed algorithm, a comparative experiment is designed in this section. Referring to the comparative experimental methods used in the literature figure [28,29], combined with the actual travel experiences of tourists, the algorithms commonly used for map route searching are selected as the control group in the experiment. The proposed algorithm is set as the experimental group.…”

Section: Route Methods Comparison and Analysis (1) Selection Of Compa...mentioning

confidence: 99%

POI Route Recommendation Model Based on Symmetrical Naive Bayes Classification Spatial Accessibility and Improved Cockroach Swarm Optimization Algorithm

Zhou,

Zhang,

Liang

et al. 2024

Symmetry

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The commonly used POI route recommendation methods usually ignore the effects of tourists’ interests and transportation geographical conditions, and so may not output the optimal results. To solve the problems, we propose a POI route recommendation model based on symmetrical Naive Bayes classification spatial accessibility (NBCSA) and an improved cockroach swarm optimization algorithm (ICSOA), aiming to recommend POI routes that satisfy tourists’ interests and have the lowest travel costs under tourism transportation geographical conditions. Using the historical POIs visited by tourists as the training set, we construct an improved symmetrical Naive Bayes classification algorithm (NBCA), and the POIs in the destination city are divided into categories by tourists’ preferences. Then we propose an improved NBCSA model to calculate the spatial accessibility field strength (SAFS) for each category’s POIs. Based on the recommended POIs, we propose the ICSOA to recommend optimal POI routes. The experiment verifies that the proposed algorithm can effectively classify the POIs and recommend POIs that best match the tourists’ interests and produce the lowest travel costs. Compared with the TCA and GDA method, the proposed algorithm can output the POI routes with lower travel costs and has higher algorithm execution efficiency. Among the output optimal routes, the proposed algorithm can reduce costs by 5.62% at the lowest and 52.25% at the highest.

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Section: Route Methods Comparison and Analysis (1) Selection Of Compa...mentioning

confidence: 99%

POI Route Recommendation Model Based on Symmetrical Naive Bayes Classification Spatial Accessibility and Improved Cockroach Swarm Optimization Algorithm

Zhou,

Zhang,

Liang

et al. 2024

Symmetry

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show abstract

“…In spoofing attacks, attackers can rearrange data in the system, causing sensors or controllers to receive false data, resulting in the system not functioning properly [27]. Considering Spoofing attacks, Bernoulli random variables are used for statistics [28]. The output measurement value under Spoofing attacks is � y ¼ aðtÞðzðtÞ À yðtÞÞ þ yðtÞ, combined with Spoofing attacks and DoS attacks, interconnected power LFC model actual output under mixed attack is shown in Eq (25).…”

Section: Plos Onementioning

confidence: 99%

“…A controller is designed as shown in Eq (27) to converge the system onto the desired surface, as shown in Eq (28).…”

Section: Plos Onementioning

confidence: 99%

Security load frequency control model of interconnected power system based on deception attack

Sun,

Tang,

2024

PLoS ONE

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The interconnected power system connects the power grids of different regions through transmission lines, achieving power interconnection and resource sharing. However, data is transmitted through open power networks and is more susceptible to network attacks. To improve the stability of interconnected power systems under deception attacks, three scenarios of system security load frequency control were studied. Based on the construction of a dynamic model of load frequency control, an event-triggered strategy was used to reduce the communication frequency between nodes, resulting in a reduction in the amount of network transmission data. A sliding mode controller was constructed to solve the problem of event-triggered sliding mode security load frequency control. Elastic event-triggered sliding mode load frequency control for interconnected power systems under mixed attacks. The simulation results showed that using the load frequency control model triggered by events, the load frequency deviation of the interconnected power system can be stabilized at around 12 seconds, effectively saving the cost of network resources. Under the regulation of the load frequency control model based on sliding mode control, the interconnected power system stabilized in 10 seconds, reducing the load of network transmission. The elastic event-triggered sliding mode load frequency control model can ensure stable transmission of power data under various attacks and has good anti-interference performance. The results of this study have played an important role in achieving the stability of power resource supply. Compared with previous studies on individual power systems, this study solves the attack problem of interconnected power systems and considers the frequency control problem of system security loads under mixed attacks, enabling the system to recover stability faster.

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“…Intelligent optimization algorithms imitate the behavior of biological groups such as predation and hunting to find the optimal solution. It can be searched by imitating the population characteristics of different organisms [20]. The research, improvement, and application of intelligent optimization algorithms have also been popular.…”

Section: Introductionmentioning

confidence: 99%

Optimization Strategy of Classification Model Based on Weighted Implicit Optimal Extreme Learning Machine

Zhang,

Wang

2024

IEEE Access

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Classification algorithms are one of the important research topics in the artificial intelligence, widely applied in various scientific and engineering fields. Extreme learning machine is a single hidden layer feed-forward neural network algorithm. Compared with traditional neural network models, the training speed and the generalization ability are also better. In terms of methodology, this study first innovatively improves the traditional Grey Wolf Optimization (GWO) algorithm to enhance its convergence and search ability. Specific improvement measures include implementing the reverse learning strategy to reduce the initial dependence of the algorithm on population distribution, and adding exploration perception strategy to enhance the global search ability of the algorithm by calculating heuristic factors, so as to identify the global optimal solution more effectively. The results showed that the improved W-DH-ELM model had excellent performance on multiple standard data sets. In particular, the average accuracy was more than 90%, which was significantly higher than other benchmark classification models. In terms of operation efficiency, the running time of the new model on different data sets was significantly reduced, accounting for less than 25%, and the lowest running time was only 4.89%. These experimental indicators verify the effectiveness of the introduced intelligent optimization algorithm in improving the performance of traditional ELM model without changing the original model structure. The improved W-DH-ELM model not only maintains the fast training characteristics of ELM, but also has higher accuracy and stability, which shows its superiority in dealing with complex classification tasks. In summary, the weighted double hidden layer extreme learning machine optimized by the improved GWO proposed in this study has significant advantages in classification problems, providing a new perspective for future machine learning applications and research.

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Simulation on Supplier Side Bidding Strategy at Day-ahead Electricity Market Using Ant Lion Optimizer

Cited by 27 publications

References 25 publications

POI Route Recommendation Model Based on Symmetrical Naive Bayes Classification Spatial Accessibility and Improved Cockroach Swarm Optimization Algorithm

POI Route Recommendation Model Based on Symmetrical Naive Bayes Classification Spatial Accessibility and Improved Cockroach Swarm Optimization Algorithm

Security load frequency control model of interconnected power system based on deception attack

Optimization Strategy of Classification Model Based on Weighted Implicit Optimal Extreme Learning Machine

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