In smart grids, customers are promoted to change their energy consumption patterns by
electricity prices. In fact, in this environment, the electricity price and load consumption are …

Introduction to Nature-Inspired Optimization brings together many of the innovative
mathematical methods for non-linear optimization that have their origins in the way various …

Electricity price forecasting has nowadays become a significant task to all market players in
deregulated electricity market. The information obtained from future electricity helps market …

Electricity pricing approaches are generally categorized into flat-rate and dynamic pricing
models. Flat-rate pricing charges a fixed rate regardless of market conditions, whereas …

This paper presents two intelligent classifier schemes for classifying the faults in a series
capacitor compensated transmission line (SCCTL). The first proposed intelligent classifier …

In this paper, a novel speed control method for Homopolar Brushless DC (HBLDC) motor
based on the adaptive nonlinear internal-model control (ANIMC) is presented. Rotor position …

Accurate electricity price prediction is key to the orderly operation of the electricity market.
However, the uncertain, stochastic and fluctuant characteristics of electricity pricees make …

Building a new power system is an important measure taken by China to cope with climate
change problems. Establishing a flexible and perfect electricity market and price mechanism …

This thesis extends the use of artificial neural networks (ANNs) optimisation and training
algorithms including the Powell-Beale conjugate gradient (PBCG), scaled conjugate …

This paper presents a novel hybrid algorithm to forecast day-ahead prices in the electricity
market. Seeking for more accurate price forecasting techniques, this hybrid price-forecasting …