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"Hosting Capacity Assessment Strategies and Reinforcement Learning Meth" by Jude Suchithra, Duane Robinson et al.

Increasing connection rates of rooftop photovoltaic (PV) systems to electricity distribution networks has become a major concern for the distribution network service providers (DNSPs) due to the inability of existing network infrastructure to accommodate high levels of PV penetration while maintaining voltage regulation and other operational requirements. The solution to this dilemma is to undertake a hosting capacity (HC) study to identify the maximum penetration limit of rooftop PV generation and take necessary actions to enhance the HC of the network. This paper presents a comprehensive review of two topics: HC assessment strategies and reinforcement learning (RL)-based coordinated voltage control schemes. In this paper, the RL-based coordinated voltage control schemes are identified as a means to enhance the HC of electricity distribution networks. RL-based algorithms have been widely used in many power system applications in recent years due to their precise, efficient and model-f ....

Artificial Neural Networks , Electricity Distribution Networks , Hosting Capacity , Photovoltaic Systems , Uasi Static Time Series , Reinforcement Learning , Voltage Control ,

Artificial intelligence, intelligence gathering & analysis, crime management

Artificial intelligence, intelligence gathering & analysis, crime management
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SS Bhagwat appointed director of IISER Pune

Professor Bhagwat holds a PhD in chemical technology, and is associated with many ongoing industry-sponsored projects. ....

Artificial Neural Networks , Interfacial Science , Exergy Engineering , Computer Process Simulation , Artificial Neural , Prof Rajadhyaksha Best Teacher , Ss Bhagwat Iiser , S Bhagwat Director , Iser Director , Iiser Pune , June Institute , Une News , Pune Latets News , Ndian Express , Ndian Epxress News ,

What are neural networks? Definition and examples

Neural networks are examples of machine learning. Machine learning is a part of artificial intelligence where machines learn to improve by analyzing data. ....

Artificial Neural Networks , Neural Networks , Neural Network ,

"Slope stability prediction using the Artificial Neural Network (ANN)" by Al Muhalab Al-Dughaishi, Shivakumar Karekal et al.

Slope failure is a significant risk in both civil and mining operations. This failure phenomenon is more likely to occur during the high rainfall season, areas with a high probability of seismic activity and in cold countries due to freezing-thawing. Further, a poor understanding of hydrogeology and geotechnical factors can contribute to erroneous engineering designs. Several Limit Equilibrium Methods (LEMs) and numerical modelling tools have been developed over the years. However, the highlighted success of the Artificial Neural Networks (ANNs) in other disciplines/sectors has motivated researchers to implement ANNs to forecast the Factor Of Safety (FOS). This paper aims to develop ANNs to predict the value of the FOS for slopes formed by (i) uniform one soil/rock material and (ii) formed by two soil/rock materials. Each of these slopes contains three sub-models with 6, 7 and 8 input material parameters. Thousands of FOS values were generated for each sub-model using LEMs by randomly ....

Artificial Neural Networks Anns , Limit Equilibrium Methods , Artificial Neural Networks , Factor Of Safety , Mean Square Error ,