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With the recent developments in energy sector, the pricing of electricity is now governed by the spot market where a variety of market mechanisms are effective. After the new legislation of market liberalization in Turkey, competition-based on hourly price has received a growing interest in the energy market, which necessitated generators and electric utility companies to add new dimensions to their...
In the paper is proposed a new neuro-wavelet based approach for the problem of short term load forecasting. The implemented neuro-wavelet based algorithm combines the potential of two soft computing techniques. The strength over other approaches appeared in literature is that firstly the hourly power load data are wavelet processed and then provided as input to an RNN. The obtained simulation results...
Load forecasting has many applications for power systems, including energy purchasing and generation, load switching, contract evaluation, and infrastructure development. In this paper, we will discuss night peak load forecasting of Algerian power system using time series back propagation neural networks, including the effect of the temperature, working days and weekends.
To resolve the problem of short-term power load forecasting, we propose a self-adapting particle swarm optimization (PSO) algorithm to optimize the error back propagation (BP) neural network model. The proposed model is called PSO-BP model which employs PSO to adjust control parameters of BP neural network. In order to verify the performance of PSO-BP, the practical datum of a city in China are selected...
This paper presents a comprehensive study of forecasting a day-ahead of load and locational marginal pricing (LMP) using artificial intelligent systems. An artificial neural network (ANN) is trained with a stochastic optimization technique called particle swarm optimization (PSO). This training algorithm works to adjust the network weights and biases as to minimize the error function. Wavelet transformed...
Wind power generation increases rapidly. The available wind energy depends on the wind speed, which is a random variable. For the wind-farm operator, this poses difficulty in the system scheduling and energy dispatching, as the schedule of the wind-power availability is not known in advance. In this paper, we propose an intelligent technique for forecasting wind speed of wind turbine. This technique...
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