A preventive control strategy for static voltage stability based on an efficient power plant model of electric vehicles

With the increasing integration of wind farms and electric vehicles(EVs)in power systems,voltage stability is becoming more and more serious.Based on vehicle-to-grid(V2G),an efficient power plant model of EVs(E-EPP)was developed to estimate EV charging load with available corresponding response capacity under different charging strategies.A preventive control strategy based on E-EPP was proposed to maintain the static voltage stability margin(VSM)of power system above a predefined security level.Two control modes were used including the disconnection of EV charging load(‘V1G’mode)and the discharge of stored battery energy back to power grid(‘V2G’mode).A modified IEEE 14-bus system with high penetration of wind power and EVs was used to verify the effectiveness of preventive control strategy.Simulation results showed that the proposed strategy can not only improve the static voltage stability of power system with considerable wind generation,but also guarantee the travelling comfort for EV owners.

Load curve smoothing strategy based on unified state model of different demand side resources

Renewable energy based distributed generation(DG) has the potential to reach high penetration levels in the residential region. However, its integration at the demand side will cause rapid power fluctuations of the tieline in the residential region. The traditional generators are generally difficult to manage rapid power fluctuations due to their insufficient efficiency requirements and low responding speed. With an effective control strategy, the demand side resources(DSRs) including DGs, electric vehicles and thermostatically-controlled loads at thedemand side, are able to serve as the energy storage system to smooth the load fluctuations. However, it is a challenge to properly model different types of DSRs. To solve this problem, a unified state model is first developed to describe the characteristics of different DSRs. Then a load curve smoothing strategy is proposed to offset the load fluctuations of the tie-line of the residential region, where a control matrix deduced from the unified state model is introduced to manage the power outputs of different DSRs,considering the response order and the comfort levels.Finally, a residential region with households is used to validate the load curve smoothing strategy based on the unified state model, and the results show that the power fluctuation rate of the tie-line is significantly decreased.Meanwhile, comparative study results are shown to demonstrate the advantages of the unified state model based load curve smoothing strategy.

Adaptive Power Control Based on Double-layer Q-learning Algorithm for Multi-parallel Power Conversion Systems in Energy Storage Station

An energy storage station(ESS)usually includes multiple battery systems under parallel operation.In each battery system,a power conversion system(PCS)is used to connect the power system with the battery pack.When allocating the ESS power to multi-parallel PCSs in situations with fluctuating operation,the existing power control methods for parallel PCSs have difficulty in achieving the optimal efficiency during a long-term time period.In addition,existing Q-learning algorithms for adaptive power allocation suffer from the curse of dimensionality.To overcome these challenges,an adaptive power control method based on the double-layer Q-learning algorithm for n parallel PCSs of the ESS is proposed in this paper.First,a selection method for the power allocation coefficient is developed to avoid repeated actions.Then,the outer action space is divided into n+1 power allocation modes according to the power allocation characteristics of the optimal operation efficiency.The inner layer uses an actor neural network to determine the optimal action strategy of power allocations in the non-steady state.Compared with existing power control methods,the proposed method achieves better performance for both static and dynamic operation efficiency optimization.The proposed method optimizes the overall operation efficiency of PCSs effectively under the fluctuating power outputs of the ESS.