Fuzzy Models for Short Term Power Forecasting in Palestine
Short-Term Load Forecasting (STLF) is needed to efficiently manage the power systems. In this paper, two kinds of models that depend on the Fuzzy based techniques are developed to represent the STLF models in Palestine. Different types of these models have been developed using the available data se...
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| Format: | Article |
| Language: | English |
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Qubahan
2023-11-01
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| Series: | Qubahan Academic Journal |
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| Online Access: | https://journal.qubahan.com/index.php/qaj/article/view/268 |
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| author | Raed Basbous |
| author_facet | Raed Basbous |
| author_sort | Raed Basbous |
| collection | DOAJ |
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Short-Term Load Forecasting (STLF) is needed to efficiently manage the power systems. In this paper, two kinds of models that depend on the Fuzzy based techniques are developed to represent the STLF models in Palestine. Different types of these models have been developed using the available data sets that include the past electric load values and the climatic variables as inputs. It is shown that the climatic variables have a major effect on the predicted load. Various optimization techniques are used to develop the proposed models including hybrid and Backpropagation optimization techniques, Subtractive Clustering, and combining the Subtractive Clustering and Hybrid optimization techniques. The obtained results indicate the efficiency of the proposed models using the time and weather data.
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| format | Article |
| id | doaj-art-aedba60b7eac4a9e962191c7f12426ed |
| institution | Kabale University |
| issn | 2709-8206 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | Qubahan |
| record_format | Article |
| series | Qubahan Academic Journal |
| spelling | doaj-art-aedba60b7eac4a9e962191c7f12426ed2025-02-03T10:12:26ZengQubahanQubahan Academic Journal2709-82062023-11-013410.48161/qaj.v3n4a268268Fuzzy Models for Short Term Power Forecasting in PalestineRaed Basbous0Al-Quds Open University, Palestine Short-Term Load Forecasting (STLF) is needed to efficiently manage the power systems. In this paper, two kinds of models that depend on the Fuzzy based techniques are developed to represent the STLF models in Palestine. Different types of these models have been developed using the available data sets that include the past electric load values and the climatic variables as inputs. It is shown that the climatic variables have a major effect on the predicted load. Various optimization techniques are used to develop the proposed models including hybrid and Backpropagation optimization techniques, Subtractive Clustering, and combining the Subtractive Clustering and Hybrid optimization techniques. The obtained results indicate the efficiency of the proposed models using the time and weather data. https://journal.qubahan.com/index.php/qaj/article/view/268Subtractive Clustering, Fuzzy Logic, Sugeno, ANFIS, Neural Networks, Hybrid Optimization |
| spellingShingle | Raed Basbous Fuzzy Models for Short Term Power Forecasting in Palestine Qubahan Academic Journal Subtractive Clustering, Fuzzy Logic, Sugeno, ANFIS, Neural Networks, Hybrid Optimization |
| title | Fuzzy Models for Short Term Power Forecasting in Palestine |
| title_full | Fuzzy Models for Short Term Power Forecasting in Palestine |
| title_fullStr | Fuzzy Models for Short Term Power Forecasting in Palestine |
| title_full_unstemmed | Fuzzy Models for Short Term Power Forecasting in Palestine |
| title_short | Fuzzy Models for Short Term Power Forecasting in Palestine |
| title_sort | fuzzy models for short term power forecasting in palestine |
| topic | Subtractive Clustering, Fuzzy Logic, Sugeno, ANFIS, Neural Networks, Hybrid Optimization |
| url | https://journal.qubahan.com/index.php/qaj/article/view/268 |
| work_keys_str_mv | AT raedbasbous fuzzymodelsforshorttermpowerforecastinginpalestine |