Document Type : Original Article
School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
Department of Mechanical engineering, University of Mohaghegh Ardabili, Ardabil, Iran
Wind energy is one of the most important renewable energies in the present and future. However, one of the significant challenges is offering amount of generation and generation price in the next-day market because, on one hand, this energy has nonlinear behavior, and on the other hand any imbalance between forecast and generation results in the generation unit being fined. In this paper, a method is presented to propose wind turbine generation by increasing the forecast accuracy and combination with flexible load and uncertainties. This increases the revenue of the wind generator companies and consumers and guarantees the connection of wind generators. In fact, in this paper, the agreed price between the wind and load is flexible so that this agreed performance will be beneficial to both wind generation and the elastic load. In this modeling, first, the system equations in the market are written and merged. To increase the revenue, the uncertainties are considered, and it is shown that their effect can change the gain in wind turbine and load. The price and wind prediction will be conducted using one of the previous methods, and the primary purpose here is to increase the system revenue. In sum up, this paper introduces the integrated offering strategy model for wind turbines and demand response to support of wind turbines in power market is proposed. the main of this strategy is increasing of renewable generations and demands profits in day ahead market which in this paper the suggestions including; integrated offering of power, uncertainties modelling, using neural fuzzy model for predictions, flexible loads and etc are proposed to achieve the optimal profits. Modeling is done using the MATLAB application to calculate Spain's wind and price information in Spain, and the performance output results are demonstrated thoroughly.