Abstract
The uncertainty of wind resources is one of the main reasons for wind abandonment. Considering the uncertainty of wind power prediction, a robust optimal dispatching model is proposed for the wind fire energy storage system with advanced adiabatic compressed air energy storage (AA-CAES) technology. Herein, the operation constraints of the power plant and constraints of the reserved capacity are defined according to the operation characteristics of AA-CAES. Based on the limited scenario method, a solution framework is proposed to achieve the optimal robustness and economical operation of the system, which provides a new way for the application of the intelligent algorithm in the robust optimal dispatching. Specifically, a novel equilibrium optimization algorithm is employed to solve the optimal dispatching problem, which has good global search performance. The proposed solution is validated through simulations based on the IEEE-39 node system. The simulation results verify the effectiveness of the proposed dispatching model and the intelligent solver.
Highlights
Facing the challenge of global warming and energy crisis, wind power generation has been rapidly developed in recent years (Song et al, 2021b)
Combining adiabatic compressed air energy storage (AA-CAES) with renewable energy, a robust optimal scheduling model is established for the wind fire energy storage system, in which the limited scenario method is used to represent the uncertainty of wind power prediction
In order to prove the effectiveness of the established robust optimal dispatching model and the proposed solution framework, the improved IEEE-39 node based on a real power grid case is used
Summary
Facing the challenge of global warming and energy crisis, wind power generation has been rapidly developed in recent years (Song et al, 2021b). Combining AA-CAES with renewable energy, a robust optimal scheduling model is established for the wind fire energy storage system, in which the limited scenario method is used to represent the uncertainty of wind power prediction. The limited scenario method is used to establish the robust optimal dispatching model of wind fire energy storage system, and the objective function and related constraints are presented. Considering the high-dimensional and multi constraint characteristics of this optimization problem, the intelligent algorithm solver proposed in this paper solves a singlestep time series and takes the optimal scheduling output at the current time as the input of the time, which can effectively reduce the solution time while ensuring the solution accuracy. In order to prove the effectiveness of the established robust optimal dispatching model and the proposed solution framework, the improved IEEE-39 node based on a real power grid case is used. The predicted power generation curve and load curve of the wind farm are shown in Figure 2B, the minimum load is 800 MW, and the maximum load is 1600 MW
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