Browsing by Author "Hajibandeh, Neda"
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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.
- Investigation on electricity market designs enabling demand response and wind generationPublication . Hajibandeh, Neda; Catalão, João Paulo da Silva; Mariano, Sílvio José Pinto Simões; Shafie-khah, MiadrezaDemand Response (DR) comprises some reactions taken by the end-use customers to decrease or shift the electricity consumption in response to a change in the price of electricity or a specified incentive payment over time. Wind energy is one of the renewable energies which has been increasingly used throughout the world. The intermittency and volatility of renewable energies, wind energy in particular, pose several challenges to Independent System Operators (ISOs), paving the way to an increasing interest on Demand Response Programs (DRPs) to cope with those challenges. Hence, this thesis addresses various electricity market designs enabling DR and Renewable Energy Systems (RESs) simultaneously. Various types of DRPs are developed in this thesis in a market environment, including Incentive-Based DR Programs (IBDRPs), Time-Based Rate DR Programs (TBRDRPs) and combinational DR programs on wind power integration. The uncertainties of wind power generation are considered through a two-stage Stochastic Programming (SP) model. DRPs are prioritized according to the ISO’s economic, technical, and environmental needs by means of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The impacts of DRPs on price elasticity and customer benefit function are addressed, including the sensitivities of both DR parameters and wind power scenarios. Finally, a two-stage stochastic model is applied to solve the problem in a mixed-integer linear programming (MILP) approach. The proposed model is applied to a modified IEEE test system to demonstrate the effect of DR in the reduction of operation cost.