A Stator Current Vector Orientation Based Multi-objective Integrative Suppressions of Flexible Load Vibration and Torque Ripple for PMSM Considering Electrical Loss

To store energy from the grid into spiral torsion spring(STS)smoothly and efficiently via PMSM,a multi-objective control problem of flexible load’s vibration,PMSM’s torque ripple,and electrical loss is raised,where the current studies on vibration and torque ripple are mostly addressed separately,not to mention electrical loss.This research attempts to propose a multi-objective integrative control scenario that can simultaneously solve these problems satisfactorily in a unitary nonlinear control framework.Firstly,a dynamic mathematical model of PMSM is built under stator current vector orientation,and then the model of PMSM is combined with the vibration model of STS to establish the overall system model of STS driven by PMSM with considering motor’s electrical loss.Then,a backstepping control principle-based multi-objective integrative control approach is proposed to realize the suppression of flexible load’s vibration and the reduction of PMSM’s torque ripple and electrical loss concurrently.Meanwhile,this research also designs a wide range speed identification method based on the least square algorithm with a forgetting factor.Simulation and experimental results have verified that the proposed integrative control method enables the state variables to track their respective references quickly and accurately,both torque ripple and load vibration are effectively suppressed,and the operating efficiency of the whole system is improved.

Accommodation of curtailed wind power by electric water heaters based on a new hybrid prediction approach

Wind power curtailment is of great importance with the increase of large-scale wind power connected to the grid. A new concept of redundant wind power accommodated by dispatching electric water heaters(EWHs) is developed in the paper. Precise predictions of wind power and EWHs load power are the basis for this work. A hybrid multi-kernel prediction approach integrating an adaptive fruit fly optimization algorithm(AFOA)and multi-kernel relevance vector machine(MKRVM) is proposed to deal with the sample distribution of multisource heterogeneous features uncovered by an energy entropy method, where AFOA is used to determine the kernel parameters in MKRVM adaptively and avoid the arbitrariness. For the large computation of the prediction approach, parallel computation based on the Hadoop cluster is used to accelerate the calculation. Then, an economic dispatching model for accommodating wind power is built taking into account the penalty of curtailed wind power and the operation cost of EWHs. The proposedscheme is implemented in an intelligent residential district.The results show that the optimization performance of the hybrid prediction approach is superior to those of four usual optimization algorithms in this case. Regular or orderly scheduling of EWHs enables accommodation of superfluous wind power and reduces dispatch cost.

Accommodation of Curtailed Wind Power by Electric Boilers Equipped in Different Locations of Heat-supply Network for Power System with CHPs

Electric boilers (EBs) provide an alternative method to deal with the accommodation of curtailed wind power. To pursue the minimum coal consumption in the system, a dispatching model integrating combined-heat-and-power (CHP) plants and EBs in different locations is developed, and the penalty of wind power curtailment and cost of EB employment are also incorporated in the model. The transmission loss and transportation lag of heat-supply network as well as the elasticity of heat load are considered in this paper. A kind of constrained programming with stochastic and fuzzy parameters is applied to deal with the uncertainties. A case in East Inner Mongolia in China demonstrates that the EBs are able to absorb curtailed wind power and supply the heat. The results indicate that the utility of EBs in the primary or secondary heat-supply network to accommodate curtailed wind power is mainly related to the efficiency of heat transmission and the elasticity of heat load.

Control Design and Implementation of a Spiral Spring Energy Storage System Connected to a Grid via PMSG

For an innovative spiral spring energy storage system,the permanent magnet synchronous generator(PMSG)is utilized as the energy conversion device due to its simple structure,low weight and high torque.During power generation,the output torque and moment of inertia of the spiral spring are changing continuously and simultaneously and the parameters of the PMSG show uncertainties.Furthermore,the DC link voltage of the converter should be stable and the power injected into the grid needs to be controlled.First,the change features of the external power source and the uncertainties of the generator’s internal parameters are expressed as the comprehensive disturbances,which are introduced into the dynamic model of the PMSG and also modify the dynamic model.Then,the high gain observers are utilized to estimate the comprehensive disturbances,and an improved robust backstepping control scheme integrating L2 gain and high gain observers is proposed.Secondly,the gridside inverter controller for the DC voltage loop and reactive power loop is designed based on the backstepping theory.Finally,hardware implementation is fulfilled to verify the presented algorithm.The results show that high gain observers are able to accurately estimate the external and internal interferences;the proposed control scheme can effectively suppress the external and internal interferences and guarantees output current,operating speed of the PMSG and output reactive power to correctly track respective references,and effectively stabilize the DC link voltage.

Hybrid Control Strategy for Air-conditioning Loads Participating in Peak Load Reduction Through Wide-range Transport Model

This paper proposes a hybrid control strategy of air-conditioning loads(ACLs)for participating in peak load reduction.The hybrid control strategy combines the temperature setpoint adjustment(TSA)control and on/off control together to make full use of response potentials of ACLs.The primary free transport model of ACLs has been established in literature at or near a fixed temperature setpoint.In this paper,a wide-range transport(WRT)model suitable for larger value of TSA is proposed.The WRT model can be constructed easily through the parameter of devices and indoor and outdoor temperature.To modulate the aggregate response characteristics of ACLs more friendly to the power grid,the safe protocol(SP)is adopted and integrated into the WRT model,which achieves a good unification of oscillation suppression and efficient modeling.Moreover,the hybrid control strategy is implemented based on the WRT model,and the model predictive control(MPC)controller is designed considering the tracking error and control switch cost.At last,the superiority of the hybrid control strategy is verified and the performance of ACLs for peak load reduction under this controller is simulated.The simulation results show that the hybrid control strategy could exploit the load reduction potential of ACLs fully than the TSA mode and track the reference signal more accurately.

Improved Model Predictive Control with Prescribed Performance for Aggregated Thermostatically Controlled Loads

Aggregate thermostatically controlled loads(AT-CLs)are a suitable candidate for power imbalance on demand side to smooth the power fluctuation of renewable energy.A new control scheme based on an improved bilinear aggregate model of ATCLs is investigated to suppress power imbalance.Firstly,the original bilinear aggregate model of ATCLs is extended by the second-order equivalent thermal parameter model to optimize accumulative error over a long time scale.Then,to ensure the control performance of tracking error,an improved model predictive control algorithm is proposed by integrating the Lyapunov function with the error transformation,and theoretical stability of the proposed control algorithm is proven.Finally,the simulation results demonstrate that the accuracy of the improved bilinear aggregate model is enhanced;the proposed control algorithm has faster convergence speed and better tracking accuracy in contrast with the Lyapunov function-based model predictive control without the prescribed performance.