load shedding/ power systemsupply authority point of viewBox-Jenkins methodtemperature variationscontrolled demand database loadtemperature-induced loaduncontrolled demand curveThe ability to predict accurately the short-term demand on a power system is important to its optimal operation. We have studied ...
This paper presents a combinative method of power system load forecasting based on quantum behavior particle swarm optimization and chaotic neural network. Based on the quantum behavioral characteristics of the particle swarm,and using the identical particle system to update the particle's position,the ...
In this paper, a new combination prediction approach was proposed and applied to improve the middle-term electric load forecasting precision. Firstly, the load sequences were decomposed into a limited number of load sub-temporal sequences with different characteristics, which avoids the large computing...
power distribution load forecasting by neural networks[ J ] . E n ergy C onversion and M anag ement ,2 0 0 5 ,4 6 ( 9 1 0 ) :13 9 3 — 1 4 0 5 . r 5] BA HMA N K ER MA N S HA HI ,HIRo S HI IW A MIYA .U p to ...
power distribution load forecasting by neural networks[ J ] . E n ergy C onversion and M anag ement ,2 0 0 5 ,4 6 ( 9 1 0 ) :13 9 3 — 1 4 0 5 . r 5] BA HMA N K ER MA N S HA HI ,HIRo S HI IW A MIYA .U p to year 2020 load forecasting using neural...
To extract strong correlations between different energy loads and improve the interpretability and accuracy for load forecasting of a regional integrated energy system (RIES), an explainable framework for load forecasting of an RIES is proposed. This includes the load forecasting model of RIES and its...
In this paper, an efficient method is proposed to deal with short-term load forecasting with the Gaussian Processes. Short-term load forecasting plays a ke... M Ohmi,H Mori - 《Ieej Transactions on Power & Energy》 被引量: 8发表: 2006年 Power system load forecasting based upon combination...
Decision support in power systems based on load forecasting models and influence analysis of climatic and socio-economic factors This paper presents a decision support system for power load forecast and the learning of influence patterns of the socio- economic and climatic factors on... CA Rocha,F...
aAccurate forecasting of power system short –term load has been one of the most important issues in the electricity industry. And the forecasting accuracy is influenced by many unpredicted factors. Because of the non-linear features of short–term power load, the paper uses support vector machine...
A short-term load forecasting model of power system based on particle swarm optimization(deep neural network,DNN)is proposed in this paper.The DNN used the multi-layer hidden layer toperform the nonlinear mapping transformation of the original input databy adding feedforward link network,enhanced ex...