Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network
A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-11-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/9/12/987 |
| _version_ | 1828180501573140480 |
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| author | Cheng-Ming Lee Chia-Nan Ko |
| author_facet | Cheng-Ming Lee Chia-Nan Ko |
| author_sort | Cheng-Ming Lee |
| collection | DOAJ |
| description | A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using an SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN). In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO) is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from the Taiwan Power Company (TPC). Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision compared to various RBFNNs. |
| first_indexed | 2024-04-12T05:46:26Z |
| format | Article |
| id | doaj.art-7cc174eacfd44aa194fdc48f57ca2918 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-12T05:46:26Z |
| publishDate | 2016-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-7cc174eacfd44aa194fdc48f57ca29182022-12-22T03:45:27ZengMDPI AGEnergies1996-10732016-11-0191298710.3390/en9120987en9120987Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural NetworkCheng-Ming Lee0Chia-Nan Ko1Department of Digital Living Innovation, Nan Kai University of Technology, Tsaotun, Nantou 542, TaiwanDepartment of Automation Engineering, Nan Kai University of Technology, Tsaotun, Nantou 542, TaiwanA reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using an SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN). In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO) is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from the Taiwan Power Company (TPC). Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision compared to various RBFNNs.http://www.mdpi.com/1996-1073/9/12/987short-term load forecastingradial basis function neural networksupport vector regressionparticle swarm optimizationadaptive annealing learning algorithm |
| spellingShingle | Cheng-Ming Lee Chia-Nan Ko Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network Energies short-term load forecasting radial basis function neural network support vector regression particle swarm optimization adaptive annealing learning algorithm |
| title | Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network |
| title_full | Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network |
| title_fullStr | Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network |
| title_full_unstemmed | Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network |
| title_short | Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network |
| title_sort | short term load forecasting using adaptive annealing learning algorithm based reinforcement neural network |
| topic | short-term load forecasting radial basis function neural network support vector regression particle swarm optimization adaptive annealing learning algorithm |
| url | http://www.mdpi.com/1996-1073/9/12/987 |
| work_keys_str_mv | AT chengminglee shorttermloadforecastingusingadaptiveannealinglearningalgorithmbasedreinforcementneuralnetwork AT chiananko shorttermloadforecastingusingadaptiveannealinglearningalgorithmbasedreinforcementneuralnetwork |