Browsing by Author "Shafie-khah, Miadreza"
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- Demand Response-Based Operation Model in Electricity Markets With High Wind Power PenetrationPublication . Hajibandeh, Neda; Shafie-khah, Miadreza; Talari, Saber; Dehghan, Shahab; Amjady, Nima; Mariano, S.; Catalão, JoãoThe issue of climate change has received considerable attention in recent decades. Therefore, renewable energies and especially wind units have become a central point of attention. To cope with the uncertainties of wind power generation, resulting from the intermittent nature of this kind of energy, this paper proposes a Demand Response (DR) based operation approach. In other words, unlike the previous models in the literature that considered a supplementary role for the DR, this paper introduces the main role for the DR in the operation of future electricity markets. This approach focuses on a comprehensive modeling of the Demand Response Programs (DRPs) for the operational scheduling of electricity markets, considering the uncertainties of the generation of wind turbines, aiming at increasing the network security and decreasing the operation cost. The incorporation of market-based DRPs such as Demand Bidding (DB) and Ancillary Service Demand Response (ASDR) is also considered. Two novel quantitative indices are introduced to analyze the success of DRPs regarding efficiency and wind integration. Numerical results obtained on two IEEE test systems indicate the effectiveness of the proposed model.
- Real-Time Scheduling of Demand Response Options Considering the Volatility of Wind Power GenerationPublication . Talari, Saber; Shafie-khah, Miadreza; Chen, Yue; Wei, Wei; Gaspar, Pedro Dinis; Catalão, J. P. S.In this paper, a new methodology to unleash the potential of demand response (DR) in real-time is presented. Customers may tend to apply their DR potential in the real-time market in addition to their scheduled potential in the day-ahead stage. Thus, the proposed method facilitates balancing the realtime market via DR aggregators (DRAs). It can be vital once the stochastic variables of the network such as production of wind power generators (WPG) do not follow the forecasted production in real-time and have some distortions. Two-stage stochastic programming is employed to schedule some DR options in both day-ahead and real-time markets. DR options in real-time are scheduled based on possible scenarios that reflect the behaviors of wind power generation and are generated through Monte-Carlo simulation method. The merits of the method are demonstrated in a 6-bus case study and in the IEEE RTS-96, which shows a reduction in total operation cost.