Probabilistic multi‐objective optimization method for interline power flow controller (IPFC) allocation in power systems

Rezaeian‐Marjani, Saeed; Ebrahimi, Hasan; Tousi, Behroz

doi:10.1049/gtd2.12645

Cited by 7 publications

(5 citation statements)

References 43 publications

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“…Users can also install a client on the computer or mobile phone for access. Compared with the browser, the client supports the establishment of a local database and synchronization with the remote, so that further operations such as data and report query can be carried out offline [10].…”

Section: Data Applicationmentioning

confidence: 99%

Interval design of expressway comprehensive energy system based on multi-objective optimization

Wang,

Zhang,

et al. 2024

International Conference on Smart Transportation and City Engineering (STCE 2023)

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In order to understand the interval design of expressway comprehensive energy system, a research on interval design of expressway comprehensive energy system based on multi-objective is put forward. From the perspective of joint planning and operation, taking the planning result as the direction and the operation result as the target calculation basis, this paper establishes the relationship between planning and operation from the perspectives of annualized cost of equipment investment in the planning process, investment time value, energy use cost and operation and maintenance cost in the operation process, and realizes the integrated planning and operation optimization model of comprehensive energy system. Secondly, the optimization process, optimization goal and solving algorithm of the model are put forward. Through examples, it is proved that the load interval of electric vehicle is basically consistent with the trend of electric load. If it is not adjusted, it is easy to cause the phenomenon of "peak plus peak" of electric load. Wind power has a large output at night, and it is easy to produce wind curtailment, so we can focus on how to absorb the excess wind power in these periods.Finally, according to the actual construction needs of users, the construction scheme of comprehensive energy system under fixed investment constraints is put forward, which provides theoretical basis for solving the planning problem of comprehensive energy system.

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Section: Data Applicationmentioning

confidence: 99%

Interval design of expressway comprehensive energy system based on multi-objective optimization

Wang,

Zhang,

et al. 2024

International Conference on Smart Transportation and City Engineering (STCE 2023)

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“…In Fig. 1 , the experiment will select preliminary PN security risk evaluation indicators based on a large amount of existing literature and the principles of indicator construction 24 , 25 . Due to the huge amount of information, to ensure the comprehensiveness of the evaluation indicators, the preliminary selection of evaluation indicators is prone to the problem of huge number, which in turn leads to the distortion of the evaluation results.…”

Section: Construction Of Pnsrem Based On Lsa-svm Algorithmmentioning

confidence: 99%

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Qi,

Zhu,

et al. 2024

Sci Rep

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Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as firewalls, intrusion detection, and malicious detection technologies offer specific protection based on their unique perspectives. However, as the types and concealment of attacksincrease, these measures struggle to detect them promptly and respond accordingly. In order to meet the social demand for the accuracy and computation speed of the power network security risk evaluation model, the study develops a fusion power network security risk evaluation algorithm by fusing the flash search algorithm with the support vector machine. This algorithm is then used as the foundation for building an improved power network security risk evaluation model based on the fusion algorithm.The study's improved algorithm's accuracy is 96.2%, which is higher than the accuracy of the other comparative algorithms; its error rate is 3.8%, which is lower than the error rate of the other comparative algorithms; and its loss function curve convergence is quicker than that of the other algorithms.The risk evaluation model's accuracy is 97.8%, which is higher than the accuracy of other comparative models; the error rate is 1.9%, which is lower than the error rate of other comparative models; the computing time of the improved power network security risk evaluation model is 4.4 s, which is lower than the computing time of other comparative models; and its expert score is high. These findings are supported by empirical analysis of the improved power network security risk evaluation model proposed in the study. According to the study's findings, the fusion algorithm and the upgraded power network security risk evaluation model outperform other approaches in terms of accuracy and processing speed. This allows the study's maintenance staff to better meet the needs of the community by assisting them in identifying potential security hazards early on and taking the necessary preventative and remedial action to ensure the power system's continued safe operation.

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“…Another challenge to face in the reliability of power system planning and control is risk assessment. Currently, in this research field, machine learning algorithms are employed for state evaluation and risk assessment for relay protections, ensuring the stable operation of the power system [201], [202], [203]. Addressing high safety risks in the new integrated energy system requires sophisticated computations for safe and smart electricity consumption.…”

Section: ) Risk Assessmentmentioning

confidence: 99%

K-Means and Alternative Clustering Methods in Modern Power Systems

Miraftabzadeh,

Colombo,

Longo

et al. 2023

IEEE Access

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As power systems evolve by integrating renewable energy sources, distributed generation, and electric vehicles, the complexity of managing these systems increases. With the increase in data accessibility and advancements in computational capabilities, clustering algorithms, including K-means, are becoming essential tools for researchers in analyzing, optimizing, and modernizing power systems. This paper presents a comprehensive review of over 440 articles published through 2022, emphasizing the application of K-means clustering, a widely recognized and frequently used algorithm, along with its alternative clustering methods within modern power systems. The main contributions of this study include a bibliometric analysis to understand the historical development and wide-ranging applications of K-means clustering in power systems. This research also thoroughly examines K-means, its various variants, potential limitations, and advantages. Furthermore, the study explores alternative clustering algorithms that can complete or substitute K-means. Some prominent examples include K-medoids, Time-series K-means, BIRCH, Bayesian clustering, HDBSCAN, CLIQUE, SPECTRAL, SOMs, TICC, and swarm-based methods, broadening the understanding and applications of clustering methodologies in modern power systems. The paper highlights the wide-ranging applications of these techniques, from load forecasting and fault detection to power quality analysis and system security assessment. Throughout the examination, it has been observed that the number of publications employing clustering algorithms within modern power systems is following an exponential upward trend. This emphasizes the necessity for professionals to understand various clustering methods, including their benefits and potential challenges, to incorporate the most suitable ones into their studies.INDEX TERMS Clustering algorithms, K-means clustering, power systems. FIGURE 3. K-means clustering and power system bibliometric trend per country.

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Probabilistic multi‐objective optimization method for interline power flow controller (IPFC) allocation in power systems

Cited by 7 publications

References 43 publications

Interval design of expressway comprehensive energy system based on multi-objective optimization

Interval design of expressway comprehensive energy system based on multi-objective optimization

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

K-Means and Alternative Clustering Methods in Modern Power Systems

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