Photovoltaic Model for Smart Grid Applications
Primary Faculty Mentor’s Name
Dr. Adel el Shahat
Proposal Track
Student
Session Format
Poster
Abstract
At any moment, there are millions of customers consuming megawatts of power. At the same instance of time, dozens of power plants are producing exactly the right amount of power to satisfy all of the demand while the distribution lines are sending the power from the power plants to the consumers.
It is not easy to store electricity for extended periods of time; so most of the generated power is used within a short time period of being produced. At the push of a button, the grid routes power wherever it is needed. It sidesteps bottlenecks and hiccups that might slow the flow. This system works great, and it can be highly reliable for years at a time as long as the transmission lines are maintained and are not over capacity. Exceeding capacity generates heat which causes sag and breakage. This can create phase and voltage fluctuations. Longer lines have less capacity than shorter ones. If certain parts of the grid are carrying electricity at capacity, a small shift in the power flow can trip circuit breakers, which sends larger flows onto neighboring lines to start a chain-reaction failure. The interconnected nature of the grid makes the entire system vulnerable to collapse.
With the yearly average of brownouts and blackouts increasing due to a growing rate of power consumption with an ever increasing population; the costs of U.S. outages are running into the billions. In response, the U.S. data centers are being forced to innovate and adapt to meet the new demands of the power grid. Greener power sources like photovoltaic systems are being implemented in conjunction with great advancements in power distribution and management of the power grid itself.
Our research proposes general and specific modeling and simulation for Schott ASE-300-DGF PV panel for Smart Grid applications. This is done, with the aid of MATLAB environment and Artificial Neural Network (ANN). First modeling of PV cell module at nominal conditions at 25°C, and 1KW/m2 with I-V curves at (0°C, 25°C, 50°C, 75°C), also power and irradiance. Then, we propose general modeling and simulation at more probable situations for variable values of temperature and irradiance. The simulation results at each irradiance value with various temperature values and corresponding characteristics are well depicted in 3-D figures. Later, the ANN model for the proposed range of irradiance and temperature as model inputs, with the corresponding values of voltages, currents, and power as outputs is presented. Finally, algebraic equations for the ANN model are deduced.
Keywords
Smart grid, Photovoltaic cell, Solar energy, Power, Artificial neural network, Modeling, Schott, Green energy, FACTS, Temperature and irradiance
Award Consideration
1
Location
Concourse/Atrium
Presentation Year
2014
Start Date
11-15-2014 2:55 PM
End Date
11-15-2014 4:10 PM
Publication Type and Release Option
Presentation (Open Access)
Recommended Citation
Jones, Bradley and Vultaggio, Quentin, "Photovoltaic Model for Smart Grid Applications" (2014). Georgia Undergraduate Research Conference (2014-2015). 123.
https://digitalcommons.georgiasouthern.edu/gurc/2014/2014/123
Photovoltaic Model for Smart Grid Applications
Concourse/Atrium
At any moment, there are millions of customers consuming megawatts of power. At the same instance of time, dozens of power plants are producing exactly the right amount of power to satisfy all of the demand while the distribution lines are sending the power from the power plants to the consumers.
It is not easy to store electricity for extended periods of time; so most of the generated power is used within a short time period of being produced. At the push of a button, the grid routes power wherever it is needed. It sidesteps bottlenecks and hiccups that might slow the flow. This system works great, and it can be highly reliable for years at a time as long as the transmission lines are maintained and are not over capacity. Exceeding capacity generates heat which causes sag and breakage. This can create phase and voltage fluctuations. Longer lines have less capacity than shorter ones. If certain parts of the grid are carrying electricity at capacity, a small shift in the power flow can trip circuit breakers, which sends larger flows onto neighboring lines to start a chain-reaction failure. The interconnected nature of the grid makes the entire system vulnerable to collapse.
With the yearly average of brownouts and blackouts increasing due to a growing rate of power consumption with an ever increasing population; the costs of U.S. outages are running into the billions. In response, the U.S. data centers are being forced to innovate and adapt to meet the new demands of the power grid. Greener power sources like photovoltaic systems are being implemented in conjunction with great advancements in power distribution and management of the power grid itself.
Our research proposes general and specific modeling and simulation for Schott ASE-300-DGF PV panel for Smart Grid applications. This is done, with the aid of MATLAB environment and Artificial Neural Network (ANN). First modeling of PV cell module at nominal conditions at 25°C, and 1KW/m2 with I-V curves at (0°C, 25°C, 50°C, 75°C), also power and irradiance. Then, we propose general modeling and simulation at more probable situations for variable values of temperature and irradiance. The simulation results at each irradiance value with various temperature values and corresponding characteristics are well depicted in 3-D figures. Later, the ANN model for the proposed range of irradiance and temperature as model inputs, with the corresponding values of voltages, currents, and power as outputs is presented. Finally, algebraic equations for the ANN model are deduced.
