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Article
Open AccessEfficient federated learning on resource-constrained edge devices based on model pruning
Federated learning is an effective solution for edge training, but the limited bandwidth and insufficient computing resources of edge devices restrict its deployment. Different from existing methods that only ...
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Article
A multiagent deep deterministic policy gradient-based distributed protection method for distribution network
Relay protection system plays an important role in the safe and stable operation of distribution network (DN), and the traditional model-based relay protection algorithms are difficult to solve the impact of t...
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Article
Low-voltage distribution network topology identification based on constrained least square and graph theory
Network topology is essential for the safe operation of a low-voltage (LV) distribution network. This network connectivity is difficult to obtain accurately due to the complex structure and low level of automa...
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Chapter and Conference Paper
A Non-intrusive Appliances Load Monitoring Method Based on Hourly Smart Meter Data
Peak load management is very important for the electric power system. This paper analyzes the impact of residential swimming pool pumps (RSPPs) on the peak load. First, this paper analyzes the challenges of no...
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Chapter and Conference Paper
A Novel Power System Anomaly Data Identification Method Based on Neural Network and Affine Propagation
Identification of anomaly data is very important for power system state estimation. In this paper, a method of power system anomaly data identification based on neural network and affine propagation is propose...
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Chapter and Conference Paper
Data Cleaning Based on Multi-sensor Spatiotemporal Correlation
Sensor-based condition monitoring systems are becoming an important part of modern industry. However, the data collected from sensor nodes are usually unreliable and inaccurate. It is very critical to clean th...
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Chapter and Conference Paper
A Data Quality Improvement Method Based on the Greedy Algorithm
High-quality data is very important for data analysis and mining. Data quality can be indicated by many indicators, and some methods have been proposed for data quality improvement by improving one or more dat...
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Chapter and Conference Paper
Power Consumption and Coverage Test of NB-IoT in the Substation Edge Computing Environment
With the continuous development of smart grids, the application of Internet of Things technology in the substation edge computing environment is becoming more and more widespread. Traditional communication tec...
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Chapter and Conference Paper
Distributed Hierarchical Fault Diagnosis Based on Sparse Auto-Encoder and Random Forest
For the diagnosis of large-scale local devices, the traditional centralized fault diagnosis systems are becoming incompetent to meet the requirement of real-time monitoring. This paper proposes the Distributed...
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Chapter and Conference Paper
Design of Overall Framework of Self-Service Big Data Governance for Power Grid
At present, power grid companies have not formed a complete data quality control system and a comprehensive and effective data quality assurance mechanism, which restricts the deep mining of data value. In thi...
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Chapter and Conference Paper
Towards Edge Computing Based Distributed Data Analytics Framework in Smart Grids
Edge computing, as an emerging paradigm empower ...
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Chapter and Conference Paper
The Limited Mutation Particle Swarm Optimizer
Similar with other swarm algorithms, the PSO algorithm also suffers from premature convergence. Mutation is a widely used strategy in the PSO algorithm to overcome the premature convergence. This paper discuss...
