Long –term load forecasting of power systems using Artificial Neural Network and ANFIS
Load forecasting is very important for planning and operation in power system energy management. It reinforces the energy efficiency and reliability of power systems. Problems of power systems are tough to solve because power systems are huge complex graphically, widely distributed and influenced by...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Asian Research Publishing Network (ARPN)
2018
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| Online Access: | http://eprints.uthm.edu.my/2484/ http://eprints.uthm.edu.my/2484/1/AJ%202019%20%2826%29.pdf |
| _version_ | 1848887750035505152 |
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| author | Ammar, Naji Sulaiman, Marizan Mohamad Nor, Ahmad Fateh |
| author_facet | Ammar, Naji Sulaiman, Marizan Mohamad Nor, Ahmad Fateh |
| author_sort | Ammar, Naji |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Load forecasting is very important for planning and operation in power system energy management. It reinforces the energy efficiency and reliability of power systems. Problems of power systems are tough to solve because power systems are huge complex graphically, widely distributed and influenced by many unexpected events. It has taken into consideration the various demographic factors like weather, climate, and variation of load demands. In this paper, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models were used to analyse data collection obtained from the Metrological Department of Malaysia. The data sets cover a seven-year period (2009- 2016) on monthly basis. The ANN and ANFIS were used for long-term load forecasting. The performance evaluations of both models that were executed by showing that the results for ANFIS produced much more accurate results compared to ANN model. It also studied the effects of weather variables such as temperature, humidity, wind speed, rainfall, actual load and previous load on load forecasting. The simulation was carried out in the environment of MATLAB software. |
| first_indexed | 2025-11-15T19:59:21Z |
| format | Article |
| id | uthm-2484 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:59:21Z |
| publishDate | 2018 |
| publisher | Asian Research Publishing Network (ARPN) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-24842021-10-20T03:23:15Z http://eprints.uthm.edu.my/2484/ Long –term load forecasting of power systems using Artificial Neural Network and ANFIS Ammar, Naji Sulaiman, Marizan Mohamad Nor, Ahmad Fateh TK3001-3521 Distribution or transmission of electric power Load forecasting is very important for planning and operation in power system energy management. It reinforces the energy efficiency and reliability of power systems. Problems of power systems are tough to solve because power systems are huge complex graphically, widely distributed and influenced by many unexpected events. It has taken into consideration the various demographic factors like weather, climate, and variation of load demands. In this paper, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models were used to analyse data collection obtained from the Metrological Department of Malaysia. The data sets cover a seven-year period (2009- 2016) on monthly basis. The ANN and ANFIS were used for long-term load forecasting. The performance evaluations of both models that were executed by showing that the results for ANFIS produced much more accurate results compared to ANN model. It also studied the effects of weather variables such as temperature, humidity, wind speed, rainfall, actual load and previous load on load forecasting. The simulation was carried out in the environment of MATLAB software. Asian Research Publishing Network (ARPN) 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/2484/1/AJ%202019%20%2826%29.pdf Ammar, Naji and Sulaiman, Marizan and Mohamad Nor, Ahmad Fateh (2018) Long –term load forecasting of power systems using Artificial Neural Network and ANFIS. ARPN Journal of Engineering and Applied Sciences, 13 (3). pp. 828-834. ISSN 1819-6608 http://www.arpnjournals.com/jeas/volume_03_2018.htm |
| spellingShingle | TK3001-3521 Distribution or transmission of electric power Ammar, Naji Sulaiman, Marizan Mohamad Nor, Ahmad Fateh Long –term load forecasting of power systems using Artificial Neural Network and ANFIS |
| title | Long –term load forecasting of power systems using Artificial Neural Network and ANFIS |
| title_full | Long –term load forecasting of power systems using Artificial Neural Network and ANFIS |
| title_fullStr | Long –term load forecasting of power systems using Artificial Neural Network and ANFIS |
| title_full_unstemmed | Long –term load forecasting of power systems using Artificial Neural Network and ANFIS |
| title_short | Long –term load forecasting of power systems using Artificial Neural Network and ANFIS |
| title_sort | long –term load forecasting of power systems using artificial neural network and anfis |
| topic | TK3001-3521 Distribution or transmission of electric power |
| url | http://eprints.uthm.edu.my/2484/ http://eprints.uthm.edu.my/2484/ http://eprints.uthm.edu.my/2484/1/AJ%202019%20%2826%29.pdf |