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The rapid development of renewable energy sources such as wind power has brought great challenges to the power grid. Wind power penetration can be improved by using hybrid energy storage (ES) to mitigate wind power fluctuation. We studied the strategy of smoothing wind power fluctuation and the strategy of hybrid ES power distribution. Firstly, an effective control strategy can be extracted by comparing constant-time low-pass filtering (CLF), variable-time low-pass filtering (VLF), wavelet packet decomposition (WPD), empirical mode decomposition (EMD) and model predictive control algorithms with fluctuation rate constraints of the identical grid-connected wind power. Moreover, the mean frequency of ES as the cutoff frequency can be acquired by the Hilbert Huang transform (HHT), and the time constant of filtering algorithm can be obtained. Then, an improved low-pass filtering algorithm (ILFA) is proposed to achieve the power allocation between lithium battery (LB) and supercapacitor (SC), which can overcome the over-charge and over-discharge of ES in the traditional low-pass filtering algorithm (TLFA). In addition, the optimized LB and SC power are further obtained based on the SC priority control strategy combined with the fuzzy control (FC) method. Finally, simulation results show that wind power fluctuation can be effectively suppressed by LB and SC based on the proposed control strategies, which is beneficial to the development of wind and storage system.

The area‐level coordination of regulation capacity by automatic generation control (AGC) is an effective approach to mitigate wind power fluctuations in interconnected power system with high wind penetration. However, the applicability of this method is restricted by the existing AGC strategy. For this reason, power systems in China are experiencing serious wind curtailments to meet the power balance. In this study, a distributed coordination AGC strategy based on regulation marginal cost (RMC) is proposed for coordinating regulation capacity in different areas to remove frequency deviations. Detailed regulating characteristics of the AGC strategy in the existing power systems are discussed. Based on the above analysis, a distributed coordination RMC controller is designed to meet the proposed multi‐area coordination rule using a partial primal‐dual sub‐gradient algorithm. In this proposed controller, the coordination signal containing RMC is exchanged with adjacent controllers through communication networks. The simulation results prove that the distributed coordination RMC strategy can economically coordinate the regulation capacity of an interconnected power system and satisfy the frequency control performance standard. [ABSTRACT FROM AUTHOR]

The transition to a low carbon energy portfolio necessitates a reduction in the demand of fossil-fuel and an increase in renewable energy generation and penetration. Wind energy in particular is ubiquitous, yet the stochastic nature of wind energy hinders its wide-spread adoption into the electric grid. Numerous techniques (improved wind forecasting, improved wind turbine design and improved power electronics) have been proposed to increase the penetration of wind energy, yet only a few have addressed the challenges of wind intermittency, grid stability and flexibility simultaneously. The problem of excess wind energy results in wind curtailment and has plagued large scale wind integration. NREL's HOMER software is used to show that a strong negative correlation exists between the cycles to failure of a storage device and the excess wind energy on the system. A 1 MJ magnesium-diboride superconducting magnetic energy storage (SMES) system is designed to alleviate momentary interruptions (lasting from a few milli-seconds to a few minutes) in wind turbines. The simulation results establish the efficacy of SMES coupled with wind turbines improve output power quality and show that a 1 MJ SMES alleviated momentary interruptions for ∼50 s in 3 MW wind turbines. These studies suggest that SMES when coupled to wind turbines could be ideal storage devices that improve wind power quality and electric grid stability. [ABSTRACT FROM AUTHOR]

Wind farm power fluctuations resulted from the wind random nature bring a significant challenge to the wind turbine generators operating in the maximum power point tracking. Furthermore, the smoothing process of a large wind farm in which the Battery Energy Storage System (BESS) is used, needs a considerable initial investment cost. Utilizing Smart Parking Lots (SPLs) can be considered as an applicable solution. In this paper, assuming conventional parking lots in Tehran converted to an SPL set in a near future and thus establishing an enormous charging/discharging capacity, the smoothing process is performed on a 51 MW wind farm. For this purpose, a coordinated control system based on two control algorithms is proposed. The first proposed algorithm chooses eligible SPLs for charging/discharging activity before receiving a new sample of the wind farm output power. Afterwards, the second proposed algorithm determines qualified vehicles in selected SPLs. The main aim is to minimize the number of SPLs (vehicles) taking part in the process. According to the simulation results, the required BESS capacity in the power smoothing process of a typical wind farm decreases considerably when the proposed approach is applied. Thus, the investment cost of BESS is reduced significantly. [ABSTRACT FROM AUTHOR]