Short Term Electric Load Forecasting using ANN in MATLAB
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- Опубликовано: 26 авг 2024
- The video discusses short-term load forecasting using artificial neural networks (ANN) in MATLAB.
The importance of load forecasting in maintaining a balance between energy production and consumption is highlighted.
Various factors such as weather conditions (rainfall, wind speed, air pressure, humidity, temperature) impact energy consumption.
The video mentions the use of the Levenberg-Marquardt training function for ANN and compares the results with other literature.
The presenter discusses their objectives, including studying different research papers, increasing the number of inputs, and testing the model on weekly and daily load data.
Detailed Description:
Electrical load forecasting is a significant issue and problem in our everyday electric power systems operations and management. It is one of the crucial tasks to be solved in order to maintain economic and sufficient power generation and reliable system operating conditions. However, with the growth and development of complex electrical power systems and a more diversified environment for providing energy services, the problem has now faced many new challenges.
Numerous load forecasting techniques and approaches have been proposed in the past, but researchers have found neural networks-based methods more reliable while producing fewer forecasting errors because of their capacity to adjust appropriately to the hidden characteristics of the connection among the output and input load data. Due to the non-linear characteristics between the changing behaviour of the load patterns and effective-parameters on it and complex relation between load design changes and their parameters, researchers have accepted NN methods more than any other conventional techniques.
Artificial Neural Networks based series short-term load forecasting (STLF) method is broadly utilized in power business. STLF can be performed utilizing other procedures such as regression-models, fuzzy-logic, expert-systems, etc. But applications of ANN have overcome the limitations in the areas of forecasting. Electrical load demands primarily depend on several weather conditions like temperature, humidity, rain, air pressure, wind speed etc.
The major aim of my project was to implement and explore the performance of ANN based approaches for daily and weekly short term load prediction (STLF). A back-propagation feedforward NN configuration was selected for training model on our dataset and compare the outcomes with multiple-linear-regression (MLR) technique. ISO New England hourly load dataset of previous four-and a half-year was utilized in training and testing neural network model. The main focus was given on daily 24-hour load predictions. Hourly load data was taken as the target data while other parameters like hour, dew point, dry bulb, working days, holidays and previous hour, day, week load is taken as input data. Simulations were carried out in MATLAB to get the better accomplishments of our designed network. The outcomes displayed that as compared to the regression technique, the performance of our designed setup was best.
hello sir , can you please provide me ur code and england training data ... i am currently pursuing my msc thesis in STLF. it would be of great help.
Sir would you like to share your Matlab code !
Sure. Just give me a reminder. There are so many emails.
Hello sir, can you pleaae share the code? I want to try it in my city
Hi. You can email me.
Hei Brother, Did you get code?
I think you send me an email but i am not sure i replied or not. If i didnt respond, kindly give me a reminder.
This code will really help me in my research. Will you help to provide me the code, i will really be very thankful.
Sure. First Subscribe my Channel and then email me on hralex102020@gmail.com.
I'll just sent you an email about your code.
Sure. Just give me a reminder. There are so many emails.
Sir, can you share the code by mail?
Contact me via email.
bro, Did you get this code?
Can you please share the code?
Sure. Just give me a reminder. There are so many emails.
Create job brother. It's very informative!!
Can you check your email please ? I need your help for designing my Hybrid model for laod forecasting. I am getting some errors and unable to remove them. It would be great if we can discuss there. Thanks
Sure. I will check my email.
Your code is ready and errors are removed. Check the updated code on your email.
The work you have done is greatly inspiring and informative.
Dear check you email. I need some modifications in my code even Imcan pay you the fee for hlping me out in my research work. I am stuck in my code from previous one month, i had tried enough to remove the errors but unluckily couldn't solve the issues yet. I am hopeful that you will help me in my research.
I checked your code for errors. It need some changes to fix the issues. You can pay the relevant amount and inform me to start working on it. Thank you