Showing 1 - 10 of 186
Accurate load forecasting is an important issue for the reliable and efficient operation of the power system. This paper presents a hybrid algorithm which combines SVR (support vector regression), RBFNN (radial basis function neural network), and DEKF (dual extended Kalamn filter) to construct a...
Persistent link: https://www.econbiz.de/10010808210
В статье осуществлены анализ и оценка характеристик финансовых состояний предприятий машиностроения. Предложен алгоритм выбора показателей для оценки...
Persistent link: https://www.econbiz.de/10011217120
This paper proposes a hybrid STLF (short-term load forecasting) framework with a new input selection method. BNN (Bayesian neural network) is used to forecast the load. A combination of the correlation analysis and ℓ2-norm selects the appropriate inputs to the individual BNNs. The correlation...
Persistent link: https://www.econbiz.de/10011209569
Persistent link: https://www.econbiz.de/10011193589
The paper presents the application of echo state network (ESN) to short-term load forecasting (STLF) problem in power systems for both 1-h and 24-h ahead predictions while using the least number of inputs: current-hour load, predicted target-hour temperature, and only for 24-h ahead forecasting,...
Persistent link: https://www.econbiz.de/10010808024
In this paper, WESN (wavelet echo state network) with a novel ESN-based reconstruction stage is applied to both STLF (short-term load forecasting) and STTF (short-term temperature forecasting). Wavelet transform is used as the front stage for multi-resolution decomposition of load or temperature...
Persistent link: https://www.econbiz.de/10010809602
Decomposition (EMD), Extended Kalman Filter (EKF), Extreme Learning Machine with Kernel (KELM) and Particle Swarm Optimization (PSO …
Persistent link: https://www.econbiz.de/10010784933
The adaptation of energy production to demand has been traditionally very important for utilities in order to optimize resource consumption. This is especially true also in microgrids where many intelligent elements have to adapt their behaviour depending on the future generation and consumption...
Persistent link: https://www.econbiz.de/10011055424
Electricity is indispensable and of strategic importance to national economies. Consequently, electric utilities make an effort to balance power generation and demand in order to offer a good service at a competitive price. For this purpose, these utilities need electric load forecasts to be as...
Persistent link: https://www.econbiz.de/10011030891
In the deregulated energy market, the accuracy of load forecasting has a significant effect on the planning and operational decision making of utility companies. Electric load is a random non-stationary process influenced by a number of factors which make it difficult to model. To achieve better...
Persistent link: https://www.econbiz.de/10011030922