Knowledge-Based Models for Smart Grid

2015 ◽  
pp. 189-210
Author(s):  
Igor B. Yadykin ◽  
Evgeny M. Maximov
Keyword(s):  
Smart Grid ◽  
Knowledge Based

scholarly journals A Knowledge-Based Path Optimization Technique for Cognitive Nodes in Smart Grid

2018 ◽  
Author(s):  
Nawab Muhammad Faseeh Qureshi ◽  
Ali Kashif Bashir ◽  
Isma Farah Siddiqui ◽  
Asad Abbas ◽  
Keehyun Choi ◽  
...  
Keyword(s):  
Smart Grid ◽  
Optimization Technique ◽  
Path Optimization ◽  
Knowledge Based

Stuck-at Fault Analytics of IoT Devices Using Knowledge-based Data Processing Strategy in Smart Grid

2018 ◽  
Vol 106 (4) ◽  
pp. 1969-1983 ◽  
Author(s):  
Isma Farah Siddiqui ◽  
Nawab Muhammad Faseeh Qureshi ◽  
Muhammad Akram Shaikh ◽  
Bhawani Shankar Chowdhry ◽  
Asad Abbas ◽  
...  
Keyword(s):  
Smart Grid ◽  
Data Processing ◽  
Processing Strategy ◽  
Knowledge Based ◽  
Iot Devices

scholarly journals Game Theoretical Demand Response Management and Short-Term Load Forecasting by Knowledge Based Systems on the basis of Priority Index

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 431 ◽  
Author(s):  
Mahnoor Khan ◽  
Nadeem Javaid ◽  
Sajjad ◽  
Abdullah ◽  
Adnan Naseem ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Demand Response ◽  
Load Forecasting ◽  
Short Term ◽  
Priority Index ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Short Term Load Forecasting ◽  
Utility Companies

Demand Response Management (DRM) is considered one of the crucial aspects of the smart grid as it helps to lessen the production cost of electricity and utility bills. DRM becomes a fascinating research area when numerous utility companies are involved and their announced prices reflect consumer’s behavior. This paper discusses a Stackelberg game plan between consumers and utility companies for efficient energy management. For this purpose, analytical consequences (unique solution) for the Stackelberg equilibrium are derived. Besides this, this paper presents a distributed algorithm which converges for consumers and utilities. Moreover, different power consumption activities on the basis of time series are becoming a basic need for load prediction in smart grid. Load forecasting is taken as the significant concerns in the power systems and energy management with growing technology. The better precision of load forecasting minimizes the operational costs and enhances the scheduling of the power system. The literature has discussed different techniques for demand load forecasting like neural networks, fuzzy methods, Naïve Bayes, and regression based techniques. This paper presents a novel knowledge based system for short-term load forecasting. The algorithms of Affinity Propagation and Binary Firefly Algorithm are integrated in knowledge based system. Besides, the proposed system has minimum operational time as compared to other techniques used in the paper. Moreover, the precision of the proposed model is improved by a different priority index to select similar days. The similarity in climate and date proximity are considered all together in this index. Furthermore, the whole system is distributed in sub-systems (regions) to measure the consequences of temperature. Additionally, the predicted load of the entire system is evaluated by the combination of all predicted outcomes from all regions. The paper employs the proposed knowledge based system on real time data. The proposed scheme is compared with Deep Belief Network and Fuzzy Local Linear Model Tree in terms of accuracy and operational cost. In addition, the presented system outperforms other techniques used in the paper and also decreases the Mean Absolute Percentage Error (MAPE) on a yearly basis. Furthermore, the novel knowledge based system gives more efficient outcomes for demand load forecasting.

scholarly journals A Modern Data-Mining Approach Based on Genetically Optimized Fuzzy Systems for Interpretable and Accurate Smart-Grid Stability Prediction

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2559
Author(s):  
Marian B. Gorzałczany ◽  
Jakub Piekoszewski ◽  
Filip Rudziński
Keyword(s):  
Data Mining ◽  
Smart Grid ◽  
Simulated Data ◽  
Fuzzy Rule ◽  
Stability Prediction ◽  
Data Set ◽  
Rule Based ◽  
Electrical Grid ◽  
Knowledge Based ◽  
Data Mining Approach

The main objective and contribution of this paper was/is the application of our knowledge-based data-mining approach (a fuzzy rule-based classification system) characterized by a genetically optimized interpretability-accuracy trade-off (by means of multi-objective evolutionary optimization algorithms) for transparent and accurate prediction of decentral smart grid control (DSGC) stability. In particular, we aim at uncovering the hierarchy of influence of particular input attributes upon the DSGC stability. Moreover, we also analyze the effect of possible "overlapping" of some input attributes over the other ones from the DSGC-stability perspective. The recently published and available at the UCI Database Repository Electrical Grid Stability Simulated Data Set and its input-aggregate-based concise version were used in our experiments. A comparison with 39 alternative approaches was also performed, demonstrating the advantages of our approach in terms of: (i) interpretable and accurate fuzzy rule-based DSGC-stability prediction and (ii) uncovering the hierarchy of DSGC-system’s attribute significance.

Is the Personal Always Political?

2017 ◽  
Vol 38 (3) ◽  
pp. 133-143 ◽  
Author(s):  
Danny Osborne ◽  
Yannick Dufresne ◽  
Gregory Eady ◽  
Jennifer Lees-Marshment ◽  
Cliff van der Linden
Keyword(s):  
Survey Data ◽  
National Survey ◽  
Negative Relationship ◽  
Openness To Experience ◽  
Political Sophistication ◽  
Knowledge Based

Abstract. Research demonstrates that the negative relationship between Openness to Experience and conservatism is heightened among the informed. We extend this literature using national survey data (Study 1; N = 13,203) and data from students (Study 2; N = 311). As predicted, education – a correlate of political sophistication – strengthened the negative relationship between Openness and conservatism (Study 1). Study 2 employed a knowledge-based measure of political sophistication to show that the Openness × Political Sophistication interaction was restricted to the Openness aspect of Openness. These studies demonstrate that knowledge helps people align their ideology with their personality, but that the Openness × Political Sophistication interaction is specific to one aspect of Openness – nuances that are overlooked in the literature.

Connectives Increase Knowledge-Based Inferences

1994 ◽  
Author(s):  
Gregory Barker ◽  
Keith Millis ◽  
Jonathan M. Golding
Keyword(s):  
Knowledge Based

The contribution of low-level sensory features versus knowledge-based factors for encoding of objects in working memory

2013 ◽  
Author(s):  
Valerio Santangelo ◽  
Simona Arianna Di Francesco ◽  
Serena Mastroberardino ◽  
Emiliano Macaluso
Keyword(s):  
Working Memory ◽  
Low Level ◽  
Knowledge Based ◽  
Sensory Features
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