Strategies for Power Systems Expansion Planning in a Competitive Electrical Market

Andreoni, Alberto Mario; Garcia-Agreda, A.; Strada, T. J.; Saraiva, João Tomé

doi:10.1007/s00202-006-0022-6

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…Substituting it into Equation (18), the objective function can be converted as follows, min f (P ω t , P dis t ,…”

Section: Model Solvingmentioning

confidence: 99%

“…In [16], on the premise of that the wind speed obeys the Rayleigh distribution, a cooperative dispatching model for the hybrid system of EVs, wind power, photovoltaics, and energy storage is constructed. Utilizing a fuzzy optimization method [17,18], the wind power is processed and the wind power model is solved by mixed integer programming. However, it is quite difficult to obtain the accurate distribution and parameters of wind energy.…”

Section: Introductionmentioning

confidence: 99%

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IGDT-Based Wind–Storage–EVs Hybrid System Robust Optimization Scheduling Model

et al. 2019

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Wind power has features of uncertainty. When wind power producers (WPPs) bid in the day-ahead electricity market, how to deal with the deviation between forecasting output and actual output is one of the important topics in the design of electricity market with WPPs. This paper makes use of a non-probabilistic approach—Information gap decision theory (IGDT)—to model the uncertainty of wind power, and builds a robust optimization scheduling model for wind–storage–electric vehicles(EVs) hybrid system with EV participations, which can make the scheduling plan meet the requirements within the range of wind power fluctuations. The proposed IGDT robust optimization model first transforms the deterministic hybrid system optimization scheduling model into a robust optimization model that can achieve the minimum recovery requirement within the range of wind power output fluctuation, and comprehensively considers each constraint. The results show that the wind–storage–EVs hybrid system has greater operational profits and less impact on the safe and stable operation of power grids when considering the uncertainty of wind power. In addition, the proposed method can provide corresponding robust wind power fluctuation under different expected profits of the decision-maker to the wind–storage–EVs hybrid system.

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“…Substituting it into Equation (18), the objective function can be converted as follows, min f (P ω t , P dis t ,…”

Section: Model Solvingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%