Electric Power System Operation Decision Support by Expert System Built with Paraconsistent Annotated Logic

Filho, João Inácio da Silva; Onuki, Alexandre Shozo; Ferrara, Luís Fernando Pompeo; Mário, Maurício Conceição; Camargo, Jose de Melo; Garcia, Dorotéa Vilanova; Santos, Marco Antônio Cetale; Rocco, Alexandre

doi:10.5772/51379

Cited by 3 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, in a basic configuration, the preliminary analysis in a PAN produces a value of real Degree Certainty D CR and a signaled interval of certainty φ e (±), referring to a unique proposition. According to Da Silva Filho et al [23] [24] the Paraconsistent Algorithm Extractor of Contradiction effects (ParaExtr ctr ) is applied to connections of the PANNet. This configuration forms a Paraconsistent Analysis Network, which is capable of extracting the effects of the contradiction, gradually from the signals of information that come from the uncertain knowledge database source.…”

Section: Methodology For Designing Testing Software Model Analysismentioning

confidence: 99%

“…The Paraconsistent Analysis for Extraction of Contradiction effects (ParaExtr ctr ) algorithm is based on a topology that enables PANNet to represent a range of situations, where the existing (φ ext ) group of clusters of similar semantic nature elements coming from several sources of information representing a modeling PAN Kernels, according to Da Silva Filho et al [23] [24].…”

Section: Methodology For Designing Testing Software Model Analysismentioning

confidence: 99%

See 1 more Smart Citation

An Application of Paraconsistent Annotated Logic for Design Software Testing Strategies

Nascimento¹,

Dias²,

Filho³

2014

JSEA

View full text Add to dashboard Cite

Nowadays, application model systems for decision-making based on non-classical logic such asParaconsistent Logic are used successfully in the treatment of uncertainties. The method presented in this paper is based on the fundamental concepts of Paraconsistent Annotated Logic with annotation of 2 values (PAL2v). In this study, two algorithms based on PAL2v are presented gradually, to extract the effects of the contradiction in signals of information from a database of uncertain knowledge. The Paraconsistent Extractors Algorithms of Contradiction Effect-Para Extr ctr is applied to filters of networks of analyses (PANets) of signal information, where uncertain and contradictory signals may be found. Software test case scenarios are subordinated to an application model of Paraconsistent decision-making, which provides an analysis using Paraconsistent Logic in the treatment of uncertainties for design software testing strategies. This quality-quantity criterion to evaluate the software product quality is based on the characteristics of software testability analysis. The Para consistent reasoning application model system presented in this case study, reveals itself to be more efficient than the traditional methods because it has the potential to offer an appropriate treatment to different originally contradicting source information.

show abstract

Section: Methodology For Designing Testing Software Model Analysismentioning

confidence: 99%

Section: Methodology For Designing Testing Software Model Analysismentioning

confidence: 99%

An Application of Paraconsistent Annotated Logic for Design Software Testing Strategies

Nascimento¹,

Dias²,

Filho³

2014

JSEA

View full text Add to dashboard Cite

show abstract

“…The transmission system uses aerial electric transmission wires to connect generating stations to substations and load centers. The distribution system employs aerial or underground transmission wires and distributes electricity to a whole district [35].…”

Section: Metaheuristic Algorithms For Power System Applicationsmentioning

confidence: 99%

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

et al. 2023

View full text Add to dashboard Cite

Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field.

show abstract

Enhancing power system stability with AI-based relaying algorithms – A review

Rajesh¹,

Sam²

2023

JPS

View full text Add to dashboard Cite

Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies that are increasingly being used to improve various aspects of power systems. In particular, AI-based relaying algorithms have the potential to revolutionize the way power systems are protected from faults and failures. Relaying algorithms play a critical role in ensuring the stability and reliability of power systems. However, traditional relay protection algorithms face several challenges, including difficulty handling complex and dynamic systems, limited fault detection accuracy, and slow response times to changing conditions. AI-based relaying algorithms can address these challenges by leveraging the power of Artificial Intelligence and Machine Learning. This paper presents an overview of AI-based relaying algorithms and their potential applications in power systems. It explores the use of AI techniques such as Artificial Neural Networks (ANN), Decision Trees (DT), and expert systems for improving the accuracy and reliability of relay protection. It also discuss the steps involved in AI-based relaying algorithms, including feature extraction, classification, and result output. This paper highlights the importance of further research and development in this field to fully realize the benefits of AI-based relaying algorithms.

show abstract

Electric Power System Operation Decision Support by Expert System Built with Paraconsistent Annotated Logic

Cited by 3 publications

References 8 publications

An Application of Paraconsistent Annotated Logic for Design Software Testing Strategies

An Application of Paraconsistent Annotated Logic for Design Software Testing Strategies

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Enhancing power system stability with AI-based relaying algorithms – A review

Contact Info

Product

Resources

About