Dynamic grouping control of electric vehicles based on improved k-means algorithm for wind power fluctuations suppression

To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs based on an improved k-means algorithm.First,a swing door trending(SDT)algorithm based on compression result feedback was designed to extract the feature data points of wind power.The gating coefficient of the SDT was adjusted based on the compression ratio and deviation,enabling the acquisition of grid-connected wind power signals through linear interpolation.Second,a novel algorithm called IDOA-KM is proposed,which utilizes the Improved Dingo Optimization Algorithm(IDOA)to optimize the clustering centers of the k-means algorithm,aiming to address its dependence and sensitivity on the initial centers.The EVs were categorized into priority charging,standby,and priority discharging groups using the IDOA-KM.Finally,an two-layer power distribution scheme for EVs was devised.The upper layer determines the charging/discharging sequences of the three EV groups and their corresponding power signals.The lower layer allocates power signals to each EV based on the maximum charging/discharging power or SOC equalization principles.The simulation results demonstrate the effectiveness of the proposed control strategy in accurately tracking grid power signals,smoothing wind power fluctuations,mitigating EV degradation,and enhancing the SOC balance.

Wind Power Fluctuation Compensation by Variable Speed Pumped Storage Plants in Grid Integrated System:Frequency Spectrum Analysis

Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations and stability of the power grid system.The fluctuation of the grid frequency problem,for example,is more pronounced.The fluctuation of the frequency in turn impacts even the collapse of the power system.To minimize such problems,a droop-vector control strategy applied on a doubly-fed induction machine based(DFIM)variable speed pumped storage(VSPS)system is proposed in this paper.This method is should be used as a wind power fluctuation compensation solution in the wind farm-grid integration system.The system model is made on the basis of the technique called a phasor model.The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation.The software platform MATLAB/Simulink is used for verifying the performance of the proposed system.The results show that the method of the frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirements in large power networks.The control strategy proposed in this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves a well-controlled power flow and stable grid frequency with the deviations being in acceptable ranges.

Analytic Mechanism for the Cumulative Effect of Wind Power Fluctuations from Single Wind Farm to Wind Farm Cluster

The use of wind power is rapidly growing worldwide as a means of reducing carbon emissions for the energy sector.China has the world’s largest wind power installation and multiple large-scale wind farm clusters,each comprising dozens of wind farms.For the planning and operation of the power system,it is important to understand the power fluctuation characteristics of wind farm clusters.Several studies demonstrate that the relative power fluctuation of a wind farm cluster is less than that of a single wind farm.Is this decreasing trend a random occurrence or does it have a regular pattern?This scientific question is addressed by investigating the mechanism of the cumulative effect of a wind farm cluster.In this study,a cumulative model is proposed by examining the spatiotemporal relationships of wind power variations and wind farm dispersion.Structural gain function and critical cumulative frequency are defined as the foundations to analytically describing the cumulative effect.By investigating the cumulative effect mechanism,the relationship between power fluctuation and spatiotemporal parameters of the wind farm cluster are revealed.The power fluctuation of a cluster can be predicted using the cumulative model even before it is completely built.The mechanism of the cumulative effect is validated on the basis of the data of two actual wind farm clusters.

Demand-side Management Based on Model Predictive Control in Distribution Network for Smoothing Distributed Photovoltaic Power Fluctuations

With the rapid increase of distributed photovoltaic(PV) power integrating into the distribution network(DN), the critical issues such as PV power curtailment and low equipment utilization rate have been caused by PV power fluctuations. DN has less controllable equipment to manage the PV power fluctuation. To smooth the power fluctuations and further improve the utilization of PV, the regulation ability from the demandside needs to be excavated. This study presents a continuous control method of the feeder load power in a DN based on the voltage regulation to respond to the rapid fluctuation of the PV power output. PV power fluctuations will be directly reflected in the point of common coupling(PCC), and the power fluctuation rate of PCCs is an important standard of PV curtailment.Thus, a demand-side management strategy based on model predictive control(MPC) to mitigate the PCC power fluctuation is proposed. In pre-scheduling, the intraday optimization model is established to solve the reference power of PCC. In real-time control, the pre-scheduling results and MPC are used for the rolling optimization to control the feeder load demand. Finally,the data from the field measurements in Guangzhou, China are used to verify the effectiveness of the proposed strategy in smoothing fluctuations of the distributed PV power.

A demand side controller of electrolytic aluminum industrial microgrids considering wind power fluctuations

Direct wind power purchase for large industrial users is a meaningful way to improve wind power consumption and decrease industrial production costs.Short-term wind power fluctuations may lead to large-scale wind power curtailment problems.To promote use of wind energy,a demand side control method is proposed based on output regulator theory for a grid-connected industrial microgrid with electrolytic aluminum loads to continuously track and respond to wind power fluctuations.The control model of the EALs and the dominant frequencies of the wind power fluctuation signals are analyzed and incorporated into the demand side control plant.The feedback control signals with active power deviations on the tie-line are used to design the demand side controller.Simulations are conducted for an actual industrial microgrid to validate the feasibility and effectiveness of the proposed method.The results demonstrate that the proposed controller based on output regulator theory is able to effectively track wind power fluctuations.

Probability distribution of wind power volatility based on the moving average method and improved nonparametric kernel density estimation

In the process of large-scale,grid-connected wind power operations,it is important to establish an accurate probability distribution model for wind farm fluctuations.In this study,a wind power fluctuation modeling method is proposed based on the method of moving average and adaptive nonparametric kernel density estimation(NPKDE)method.Firstly,the method of moving average is used to reduce the fluctuation of the sampling wind power component,and the probability characteristics of the modeling are then determined based on the NPKDE.Secondly,the model is improved adaptively,and is then solved by using constraint-order optimization.The simulation results show that this method has a better accuracy and applicability compared with the modeling method based on traditional parameter estimation,and solves the local adaptation problem of traditional NPKDE.

Impact of the Intermittency of Photovoltaic Power Plants on the Frequency Management: Case of the Senegalese Electricity Grid

This paper investigates the impact of the intermittency of the photovoltaic (PV) power plants on the electric grid frequency management and the consequences that can occur. To meet these purposes, three years data of the Senegalese grid frequency are used, combined with three PV power plants data since their starting-up. Using these data, we analyzed two days of heavily disturbed operation of the Senegalese grid in order to emphasize the real impact of the presence of PV power plants on the electrical grid. Our study has highlighted that how the intermittency of photovoltaic power plants affects frequency management. It obviously appears that the PV production curves follow the irradiation variations. Instantaneous variations of PV production make it difficult to manage the grid frequency leading to more frequent load shedding as we have shown with the data after the commissioning of the PV power plants. We also estimate the power then energy losses during the load shedding induced by the PV integration on the power grid by comparing a period corresponding to one month before (February 2017) and one month after (February 2018) the integration of variable PV production.

Bi-objective Layout Optimization for Multiple Wind Farms Considering Sequential Fluctuation of Wind Power Using Uniform Design

The fluctuation of wind power brings great challenges to the secure,stable,and cost-efficient operation of the power system.Because of the time-correlation of wind speed and the wake effect of wind turbines,the layout of wind farm has a significant impact on the wind power sequential fluctuation.In order to reduce the fluctuation of wind power and improve the operation security with lower operating cost,a bi-objective layout optimization model for multiple wind farms considering the sequential fluctuation of wind power is proposed in this paper.The goal is to determine the optimal installed capacity of wind farms and the location of wind turbines.The proposed model maximizes the energy production and minimizes the fluctuation of wind power simultaneously.To improve the accuracy of wind speed estimation and hence the power calculation,the timeshifting of wind speed between the wind tower and turbines’locations is also considered.A uniform design based two-stage genetic algorithm is developed for the solution of the proposed model.Case studies demonstrate the effectiveness of this proposed model.

Optimal control and management of large-scale battery energy storage system to mitigate fluctuation and intermittence of renewable generations

Battery energy storage system(BESS)is one of the effective technologies to deal with power fluctuation and intermittence resulting from grid integration of large renewable generations.In this paper,the system configuration of a China’s national renewable generation demonstration project combining a large-scale BESS with wind farm and photovoltaic(PV)power station,all coupled to a power transmission system,is introduced,and the key technologies including optimal control and management as well as operational status of this BESS are presented.Additionally,the technical benefits of such a large-scale BESS in dealing with power fluctuation and intermittence issues resulting from grid connection of large-scale renewable generation,and for improvement of operation characteristics of transmission grid,are discussed with relevant case studies.

Day-ahead allocation of operation reserve in composite power systems with large-scale centralized wind farms

This paper focuses on the day-ahead allocation of operation reserve considering wind power prediction error and network transmission constraints in a composite power system.A two-level model that solves the allocation problem is presented.The upper model allocates operation reserve among subsystems from the economic point of view.In the upper model,transmission constraints of tielines are formulated to represent limited reserve support from the neighboring system due to wind power fluctuation.The lower model evaluates the system on the reserve schedule from the reliability point of view.In the lower model,the reliability evaluation of composite power system is performed by using Monte Carlo simulation in a multi-area system.Wind power prediction errors and tieline constraints are incorporated.The reserve requirements in the upper model are iteratively adjusted by the resulting reliability indices from the lowermodel.Thus,the reserve allocation is gradually optimized until the system achieves the balance between reliability and economy.A modified two-area reliability test system (RTS) is analyzed to demonstrate the validity of the method.

Design a Hybrid Energy-Supply for the Electrically Driven Heavy-Duty Hexapod Vehicle

Increasing the power density and overload capability of the energy-supply units(ESUs)is always one of the most challenging tasks in developing and deploying legged vehicles,especially for heavy-duty legged vehicles,in which significant power fluctuations in energy supply exist with peak power several times surpassing the average value.Applying ESUs with high power density and high overload can compactly ensure fluctuating power source supply on demand.It can avoid the ultra-high configuration issue,which usually exists in the conventional lithium-ion battery-based or engine-generator-based ESUs.Moreover,it dramatically reduces weight and significantly increases the loading and endurance capabilities of the legged vehicles.In this paper,we present a hybrid energy-supply unit for a heavy-duty legged vehicle combining the discharge characteristics of lithium-ion batteries and peak energy release/absorption characteristics of supercapacitors to adapt the ESU to high overload power fluctuations.The parameters of the lithium-ion battery pack and supercapacitor pack inside the ESU are optimally matched using the genetic algorithm based on the energy consumption model of the heavy-duty legged vehicle.The experiment results exhibit that the legged vehicle with a weight of 4.2 tons can walk at the speed of 5 km/h in a tripod gait under a reduction of 35.39%in weight of the ESU compared to the conventional lithium-ion battery-based solution.

Optimal Coordination Control Strategy of Hybrid Energy Storage Systems for Tie-line Smoothing Services in Integrated Community Energy Systems

Increasing renewable energy penetration into integrated community energy systems(ICESs)requires more efficient methods to prevent power fluctuations of the tie–line(connection of the ICESs to the main grid).In this paper,centrally-controlled air conditioners are considered as a virtual energy storage system(VESS).The optimal thermostat regulation is used to manage the charging/discharging power of the VESS within the customer comfort level range and the virtual state of charge(VSOC)is used to describe the charging/discharging power of the VESS.On this basis,the model of the hybrid energy storage system is built with a VESS and a battery storage system(BSS).Then,an optimal coordination control strategy(OCCS)for a hybrid energy storage system is developed considering the state-space equation to describe the OCCS,the constraints of the OCCS,and the objective function to express the optimal coordination control performance.Finally,the influence of the outdoor temperature and the deadband of air conditioners on the results of the OCCS is analyzed.Results show that the OCCS can realize optimal allocation of the storage response amount to trace the reference target accurately and guarantee both the state of charge(SOC)of the batteries in a reasonable range to prolong the battery life and ensure the level of comfort experienced by users.

Space and Frequency Diversity Characterization of Mobile GNSS Receivers in Multipath Fading Channels

Diversity reception of multipath Global Navigation Satellte System(GNSS)signals offers a new insight into carrier phase-based high-precision positioning.The focus of this paper is to demonstrate the fading independence between space and frequency diversity GNSS signals.In harsh urban environments,multipath components arrive to the mobile receiver antenna with different phases and Doppler shifts,therefore giving rise to the discontinuity of code and Doppler observations and large tracking errors.In this paper,an empirical model of fading GNSS signals is constructed,including power fluctuations and spread metrics.Based on this model,real BeiDou Navigation Satellite System(BDS)signals from two GNSS dual-frequency antennas are characterized,at both information and signal level.The block processing algorithm is utilized for signal investigation.Results show that:(1)a high proportion of asynchronous loss-of-lock(around 16%)is experienced by observations of diversity signals;and(2)power fluctuations of fading signals are uncorrelated in frequency separated branches unconditionally,yet for space diversity signals the independency exists in dynamic fading channels only.The results above corroborate the significant potential gain of diversity reception,and could be further implemented in researches of diversity combined GNSS parameter estimation in dense fading conditions.