A Course of Twelve Elementary Lectures on Galvanism;
Observations On A Series Of Electrical Experiments
Observations On A Series Of Electrical Experiments
An Optimal Mppt Using Harmony Search Algorithm in Pv System
This Book proposes a New Harmony Search (HS) algorithm for improving the Optimization and performance of Maximum Power Point Tracking in PV System. The Harmony Search (HS) algorithm technique has been applied for multi junction solar cell system. The solar panels are made up of different materials and give constant output from Boost converter. The main aim of Harmony Search (HS) algorithm is to find out duty cycle to the Boost converter to maintain constant output voltage irrespective of power produced by solar panels. This proposed harmony search algorithm (HSA) is also used to minimizing active power loss, voltage deviation and voltage stability index. A detailed simulation of the proposed method has been simulated in Matlab/Simulink. The simulation result shows that this design can be effectively realized in practical applications.
Easy Electrical Experiments and How to Make Them;
Easy Electrical Experiments and How to Make Them;
A Treatise On Electricity In Theory And Practice
Classical Electrodynamics
Classical Electrodynamics captures Schwinger's inimitable lecturing style, in which everything flows inexorably from what has gone before. This anniversary edition offers a refreshing update while still maintaining Schwinger's voice.
On the Electromagnetic Effect of Convection-currents
Harnessing Hybrid Energy with a Floating Waterwheel System
The Hydro and Wind Energy Monitoring System is an IoT-integrated solution using Arduino to track and analyze renewable energy generation from hydro and wind sources. The system monitors the voltage generated by wind turbines and hydroelectric generators, storing the harvested energy in a battery for later use. Real-time data, including generated voltage and water flow rate, is uploaded to the Thing Speak cloud for remote access and monitoring. A flow sensor is used to measure the rate of water flow, which directly impacts hydro energy generation. Wind energy is monitored by tracking the turbine's rotational speed and output voltage. The system leverages machine learning to predict future energy generation based on historical data stored in Thing Speak, enabling proactive energy management and optimization. Using random forest algorithm, predictive analytics of system can estimate power output under different environmental conditions, improving efficiency and reliability. The IoT integration ensures continuous data collection and remote visualization, making it an effective renewable energy management system.