scholarly journals An Optimal Load Disaggregation Method Based on Power Consumption Pattern for Low Sampling Data

2019 ◽  
Vol 11 (1) ◽  
pp. 251 ◽  
Author(s):  
Huijuan Wang ◽  
Wenrong Yang ◽  
Tingyu Chen ◽  
Qingxin Yang
Keyword(s):  
Power Consumption ◽  
Optimization Model ◽  
Smart Grids ◽  
Large Scale ◽  
Reactive Power ◽  
Low Frequency ◽  
Performance Comparison ◽  
Consumption Pattern ◽  
Frequency Data ◽  
Load Disaggregation

In recent years, Smart Grids have been developing globally. Since smart meters only acquire low-frequency data, non-intrusive load monitoring technology using the signature extracted from high-frequency data needs an additional measurement device to be installed, so it is not suitable for promotion to the smart grid environment. However, methods using low-frequency features are poorly-suited when several appliances are switched on at the same time, or devices with similar power values are used. In response to these problems, this paper proposes a load disaggregation method based on the power consumption patterns of appliances, combining an improved mathematical optimization model and optimized bird swarm algorithm (OBSA) for load disaggregation. Experiments show that the method can effectively identify the operating states of appliances, and deal with situations in which multiple instruments have similar power characteristics or are simultaneously switching. The performance comparison proves that the improved model is more efficient than the traditional active and reactive power (PQ) optimization model in load disaggregation performance and computation time, and also verifies the robustness of the proposed method and the convergence of OBSA. As an inexpensive method without extra measurement hardware installed, the process is suitable for large-scale applications in smart grids.

scholarly journals Non-Intrusive Load Disaggregation Based on a Multi-Scale Attention Residual Network

2020 ◽  
Vol 10 (24) ◽  
pp. 9132
Author(s):  
Liguo Weng ◽  
Xiaodong Zhang ◽  
Junhao Qian ◽  
Min Xia ◽  
Yiqing Xu ◽  
...  
Keyword(s):  
Smart Grids ◽  
Recognition Rate ◽  
Low Frequency ◽  
Attention Mechanism ◽  
Learning Ability ◽  
Residual Network ◽  
Multi Scale ◽  
Energy Disaggregation ◽  
Benchmark Datasets ◽  
Load Disaggregation

Non-intrusive load disaggregation (NILD) is of great significance to the development of smart grids. Current energy disaggregation methods extract features from sequences, and this process easily leads to a loss of load features and difficulties in detecting, resulting in a low recognition rate of low-use electrical appliances. To solve this problem, a non-intrusive sequential energy disaggregation method based on a multi-scale attention residual network is proposed. Multi-scale convolutions are used to learn features, and the attention mechanism is used to enhance the learning ability of load features. The residual learning further improves the performance of the algorithm, avoids network degradation, and improves the precision of load decomposition. The experimental results on two benchmark datasets show that the proposed algorithm has more advantages than the existing algorithms in terms of load disaggregation accuracy and judgments of the on/off state, and the attention mechanism can further improve the disaggregation accuracy of low-frequency electrical appliances.

scholarly journals Green Computing

2016 ◽  
Vol 7 (2) ◽  
pp. 7-26 ◽  
Author(s):  
Jagwinder Singh
Keyword(s):  
Power Consumption ◽  
Large Scale ◽  
Electronic Devices ◽  
Green Computing ◽  
Consumption Pattern ◽  
Environment Friendly ◽  
Star Rating ◽  
Healthy Environment ◽  
The Past ◽  
Technology Resources

Green Computing is the concept to improve environmental conditions. Green Computing has begun to spread in the past few years, gaining increasingly popularity. It includes manufacturing, designing and efficiently using computers and associated subsystems- such as LED,RAM, Processor, Mouse and Keyboard with minimum impact on the environment. We are doing the study and practice of developing Information Technology resources in an environment friendly manner such that our environment get protected. As we all know usage of electronic devices is very popular these days, of which Laptops and Tabs are the most common. Surveys were conducted to analyze power consumption, pattern of devices, components like RAM, Rom processors and LED displays. Furthermore recommendations were made to make them more energy efficient. To promote the idea of green computing, energy star rating were introduced for electronic devices. The more is the star rating, the less is the power consumption. This type of computing can facilitate us to safe and make healthy environment all over the world. Present study will help us to take some initiatives to save vast amount of power which is wasted on very large scale currently under the field of computers/ electronics industry.

Research on Supporting Effect of Dynamic Var Compensation to the Security of Large-Scale Wind Power Integration

2013 ◽  
Vol 391 ◽  
pp. 265-270
Author(s):  
Xiang Li ◽  
Peng Li ◽  
Ning Bo Wang ◽  
De Zhi Chen ◽  
Xiao Rong Zhu ◽  
...  
Keyword(s):  
Large Scale ◽  
Reactive Power ◽  
Power Grid ◽  
Low Frequency ◽  
Wind Farms ◽  
Northwest China ◽  
Reactive Power Compensation ◽  
Simulation Software ◽  
Low Frequency Oscillation ◽  
Load Mode

There are security and stability problems happened in northwest china power grid connected with jiuquan large-scale wind farms in practice, such as voltage rising and low-frequency oscillation. Analyzing data is the high load mode of Northwest Power Grid in the winter of 2012 in this paper. On this basis, simulation was implemented by using BPA simulation software to analyze the support and improvement of dynamic reactive power compensation equipment on security problems happened in jiuquan. Analysis results show that: dynamic reactive power compensation equipment has characteristics as automatic, fast regulation of reactive power. The security and stability of power grid connected with jiuquan large-scale wind farms can be enhanced effectively when these characteristics are full used.

Particle Swarm Optimization Solving Nonlinear Programming Problems in Power System

2013 ◽  
Vol 760-762 ◽  
pp. 1183-1186
Author(s):  
Li Kang ◽  
Xiao Guang Li
Keyword(s):  
Nonlinear Programming ◽  
Power System ◽  
Computational Efficiency ◽  
Optimization Model ◽  
Large Scale ◽  
Voltage Stability ◽  
Reactive Power ◽  
Voltage Control ◽  
Stability Control

In order to improve the control capability of the power system voltage stability and to enhance spatial and temporal coordination of voltage control means, it is essential to establish the model of emergency voltage control that can globally mobilize reactive power support and voltage control potential. Focus on the long-term voltage stability of power system, the paper introduce nonlinear programming into emergency voltage control, settle the problem that how to establish the model of emergency voltage control. Based on detailed models of power system, the receding optimization model of long-term voltage stability control is established under framework of model predictive control. In order to improve the computational efficiency and reduce feedback delays, nonlinear programming sensitivity algorithm is proposed to solve receding optimization model. The proposed method can improve computational efficiency significantly which creates the condition for the emergency voltage control application to large-scale systems.

scholarly journals Research on an invasive and low-frequency power consumption data acquisition method

2021 ◽  
Vol 2078 (1) ◽  
pp. 012059
Author(s):  
Weijia Sun ◽  
Hui Wang ◽  
Yongfeng Liu
Keyword(s):  
Power Consumption ◽  
Data Acquisition ◽  
Large Scale ◽  
Time Synchronization ◽  
Low Frequency ◽  
Acquisition Scheme ◽  
Reliability Issue ◽  
Local Storage ◽  
Scale Compatibility ◽  
Low Frequency Power

Abstract Aiming at the large-scale, compatibility and reliability problems faced by the data acquisition engineering for power consumption in the industrial field, for reducing the complexity and cost of the data acquisition engineering, and improving the quality, maintainability, scalability and manageability of the data acquisition, an engineering-oriented, intrusive, low-frequency data acquisition scheme for power consumption is proposed. The scheme leverages multi-agent networking technology to solve the large-scale problem, utilizes the communication driver of the dynamic loading adapter mode to tackle the compatibility trouble. Furthermore, the local storage, breakpoint retransmission, flow control, automatic recovery, automatic connection, and time synchronization are combined to solve the reliability issue. Engineering tests show that the proposed scheme possesses the significant backward compatibility characteristics, which can effectively reduce the complexity and cost of data acquisition engineering for power consumption, and significantly improve the quality, maintainability, scalability and manageability of data acquisition.

Power Efficient Implementation of Low Noise CMOS LC VCO using 32nm Technology for RF Applications

2018 ◽  
Vol 6 (8) ◽  
pp. 53
Author(s):  
Shitesh Tiwari ◽  
Sumant Katiyal ◽  
Parag Parandkar
Keyword(s):  
Power Consumption ◽  
Phase Noise ◽  
Tuning Range ◽  
Low Voltage ◽  
Performance Comparison ◽  
Low Noise ◽  
Center Frequency ◽  
Voltage Controlled Oscillator ◽  
Low Phase Noise ◽  
Lc Vco

Voltage Controlled Oscillator (VCO) is an integral component of most of the receivers such as GSM, GPS etc. As name indicates, oscillation is controlled by varying the voltage at the capacitor of LC tank. By varying the voltage, VCO can generate variable frequency of oscillation. Different VCO Parameters are contrasted on the basis of phase noise, tuning range, power consumption and FOM. Out of these phase noise is dependent on quality factor, power consumption, oscillation frequency and current. So, design of LC VCO at low power, low phase noise can be obtained with low bias current at low voltage.  Nanosize transistors are also contributes towards low phase noise. This paper demonstrates the design of low phase noise LC VCO with 4.89 GHz tuning range from 7.33-11.22 GHz with center frequency at 7 GHz. The design uses 32nm technology with tuning voltage of 0-1.2 V. A very effective Phase noise of -114 dBc / Hz is obtained with FOM of -181 dBc/Hz. The proposed work has been compared with five peer LC VCO designs working at higher feature sizes and outcome of this performance comparison dictates that the proposed work working at better 32 nm technology outperformed amongst others in terms of achieving low Tuning voltage and moderate FoM, overshadowed by a little expense of power dissipation. 

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