Effect of Assistive Grouser Mechanism on Lightweight Rover Power Consumption Pattern on Steep Soft Sand Inclines

2018 ◽  
pp. 343-351
Author(s):  
Ahmad Najmuddin Ibrahim ◽  
Yasuhiro Fukuoka
Keyword(s):  
Power Consumption ◽  
Consumption Pattern

A Demand Based Optimum Solar Panel Orientation

2010 ◽  
Author(s):  
Mohammad H. Naraghi
Keyword(s):  
New York ◽  
New York City ◽  
Power Consumption ◽  
York City ◽  
Energy Demand ◽  
Solar Panel ◽  
Consumption Pattern ◽  
Tilted Surface ◽  
Typical Summer ◽  
Building Cooling

The clear sky and monthly clearness index models are used to evaluate the hourly and monthly insolation on unit area of a tilted surface for the entire year. The hourly power consumption of a typical municipality (for this case New York City) for typical summer and winter days are used to determine the tilt and azimuth angles of a solar panel such that the solar energy reached the panel best match the energy consumption pattern. For the example case considered, in this work New York City, the electric power consumption peaks during summers at afternoon hours, due to increase in building cooling loads. It is found that orienting the solar panel at a westward azimuth angle with a tilt angle that results in maximum annual insolation is the best orientation of the solar panel for responding to both the peak energy demand and having reasonably high overall annual power generation. Although the model is used to optimize the solar panel orientation for New York City, it can however, be used for any building at any location as long as the needed solar data and power consumption pattern are known.

scholarly journals Efficient Planning of Electrical Distribution System for Consumers in Sarawak, Malaysia

2014 ◽  
Vol 72 (1) ◽  
Author(s):  
Ibrahim S.H. ◽  
Baharun A. ◽  
Nawi M.N.M ◽  
Chai C.J.
Keyword(s):  
Power Consumption ◽  
Distribution System ◽  
Load Distribution ◽  
Consumption Pattern ◽  
Load Factor ◽  
Cluster Sampling ◽  
Distribution Transformer ◽  
Consumption Data ◽  
Efficient Planning ◽  
Load Characteristics

This study presents a method to determine power consumption pattern for several types of consumers in Sarawak, Malaysia. The power consumption data for consumers has been recorded using EDMI Mk.6 Genius polyphase electronic (E3) meters installed at their premises. The multistage cluster sampling is used to design the sample size to determine the sufficient amount of meters required. The data obtained from the meters has been analysed to obtain the pattern of power consumption for different types of consumers. This power consumption pattern has been applied to determine load factor, diversity factor for the calculation of After Diversity Maximum Demand (ADMD). ADMD is also used to determine the optimal amount of load, distribution transformer size and 11kV cable size. Temperature sensitivity analysis related to the demand has been investigated as well. It is found that power consumption pattern model is beneficial in finding the total electrical load, distribution transformer size and 11kV cable size needed by the consumers. Thus through this study the load characteristics had been determined to support utility operation and planning efficiently.

scholarly journals Application of Predictive Control in Scheduling of Domestic Appliances

2020 ◽  
Vol 10 (5) ◽  
pp. 1627 ◽  
Author(s):  
Himanshu Nagpal ◽  
Andrea Staino ◽  
Biswajit Basu
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Predictive Control ◽  
Peak Power ◽  
Mixed Integer ◽  
Consumption Pattern ◽  
Problem Model ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Peak Power Consumption

In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.

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 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.

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