Mitigate Wind Power Fluctuations Research Articles

Enhanced low voltage ride-through control of multilevel flying capacitor inverter based wind generation

This paper introduces a cost-effective control method to enhance the low voltage ride-through (LVRT) capability and smooth the output power of a three-phase multilevel flying capacitor inverter (FCI) in wind turbine-based permanent magnet synchronous generator (PMSG). The proposed approach utilizes the energy storage capability of flying capacitors to mitigate wind power fluctuations and address short-duration outages and deep voltage sags. Additionally, a nonlinear controller based Lyapunov theory is developed to regulate capacitor voltages, improve power factors, and balance DC-link voltage. Numerical simulations are conducted in MATLAB/SimPower systems environment to validate the effectiveness of this comprehensive control strategy across different grid operation scenarios.

Low carbon scheduling method of electric power system considering energy-intensive load regulation of electrofused magnesium and wind powerfluctuation stabilization

The significant expansion of wind power has presented challenging obstacles to power system operation. The inherent stochasticity and variability of wind power have emerged as critical issues that impede the advancement of wind energy, affecting its integration and volatility control. Moreover, with the momentum of carbon peaking and carbon neutrality objectives, reducing CO2 emissions has become urgent. This study proposes a low-carbon dispatching methodology for power systems to address these challenges. It considers regulating energy-intensive loads of electrically fused magnesium and mitigating wind power fluctuations. The approach involves integrating electrically Fused magnesium loads with tight regulation characteristics on the demand side alongside thermal power plants to optimize the power grid and dispatch collectively. And battery energy storage devices are introduced into various wind power stations on the supply side to smooth out wind power fluctuations. The objective function aims to minimize the sum of the average variance of power fluctuations at all wind power busbars while adhering to constraints of maximum wind power consumption and minimum carbon emissions from thermal power plants. The problem is solved using genetic algorithms. Ultimately, we show how effective our proposed low-carbon dispatching method for power systems is, which deals with regulating energy-intensive loads of electrically fused magnesium and reducing wind power fluctuations. We demonstrate this through a case study of wind curtailment, CO2 emissions, wind power fluctuations, and other related parameters under different conditions. The approach can enhance renewable energy consumption, reduce carbon emissions, and mitigate the power fluctuations of renewable energy.

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.

Multi-Time-Scale Optimal Scheduling of Integrated Energy System Considering Transmission Delay and Heat Storage of Heating Network

In the integrated energy system, significant potential exists for the regulation of the heat storage capacity within the heating network. In relation to this attribute, the establishment of the quasi-dynamic model for the heating network is accomplished through the utilization of the fictitious node method. Additionally, a method is introduced to quantify the heat storage within the heating network. Moreover, a multi-time-scale scheduling approach is proposed for the integrated energy system, with consideration given to the heat storage of the heating network. During the day-ahead scheduling phase, the active regulation of the heat storage within the heating network is carried out to enhance the economy of system operation. Transitioning to the intra-day upper scheduling phase, the heat storage capacity of the heating network is utilized to eliminate the transmission delay effect, thereby achieving the coordinated scheduling of both electricity and heat. Shifting to the intra-day lower scheduling phase, the heat storage capacity of the heating network is utilized to enhance the operational flexibility of the power system. Simulation experiments demonstrate that the coordinated scheduling of electricity and heat in the integrated energy system can be effectively achieved through the utilization of the fictitious node method. Furthermore, the proposed multi-time-scale scheduling method, making full use of the heat storage characteristics of the heating network, can effectively suppress fluctuations in the new energy output and load demand while taking the economy into account. In this paper, it results in a 5.9% improvement in system operating economics and possesses the capacity to mitigate wind power fluctuations with an error rate of approximately 20%. This capability significantly enhances the integration of wind power as a sustainable energy source.

An Optimal Configuration Model for Supercapacitor Capacity to Suppress Wind Power Fluctuations

This paper presents an optimization configuration scheme for energy storage capacity by taking into account the operational characteristics of supercapacitors. The scheme utilizes Empirical Mode Decomposition (EMD) to address power fluctuations during the integration of wind power into the grid. To begin with, the wind power data undergoes EMD to decompose it into different-order intrinsic mode functions. These functions are then reconstructed as low-frequency components and high-frequency components. The low-frequency components are directly connected to the grid, while the high-frequency components are employed for power smoothing through energy storage. Subsequently, the impact of various wind power grid limits on the directly connected power is compared to identify the optimal value. A model is established to configure the capacity of supercapacitors, aiming to mitigate wind power fluctuations. The model considers an objective function that minimizes the sum of energy storage investment and operational maintenance costs, along with the compensation cost associated with wind power fluctuation opportunities. Finally, the proposed model’s effectiveness and economic feasibility are validated through case studies. This ensures that the model’s efficacy in reducing power fluctuations and its viability from a financial standpoint are thoroughly examined.

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.

A Storage and Transmission Joint Planning Method for Centralized Wind Power Transmission

Centralized delivery has become the main operation mode under the scaled development of wind power. Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base. The configuration of transmission capacity, which has the features of low utilization and poor economy, is hardly matching correctly due to the volatility and low energy density of wind. The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity, but facing the issue of energy storage cost recovery. Therefore, it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission. This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage, reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission. Then, analyze the multi-functional cost-sharing mode of energy storage, improve the efficiency of energy storage cost recovery. Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage, and realizes the transmission capacity optimization coordination and optimization with energy storage. The proposed method is verified by a wind base located in Northeast China.

The Effect of a Renewable Energy Certificate Incentive on Mitigating Wind Power Fluctuations: A Case Study of Jeju Island

As renewable energy penetration in power systems grows, adequate energy policies are needed to support the system’s operations with flexible resources and to adopt more sustainable energies. A peak-biased incentive for energy storage systems (ESS) using the Korean renewable portfolio standard could make power system operations more difficult. For the first time in the research, this study evaluates the effect of imposing a renewable energy certificate incentive in off-peak periods on mitigating wind power fluctuations. We design a coordinated model of a wind farm with an ESS to model the behavior of wind farm operators. Optimization problems are formulated as mixed integer linear programming problems to test the implementation of revenue models under Korean policy. These models are designed to consider additional incentives for discharging the ESS during off-peak periods. The effects of imposing the incentives on wind power fluctuations are evaluated using the magnitude of the renewable energy certificate (REC) multiplier.

Frequency dependent strategy for mitigating wind power fluctuations of a doubly-fed induction generator wind turbine based on virtual inertia control and blade pitch angle regulation

Abstract This paper presents a new approach to address the issue of the frequency deviations induced by the fluctuating power injected into the grid by doubly-fed induction generator based wind turbines in a weak or isolated power system that is based in a frequency dependent smoothing of the wind power. An algorithm that allows an improved maximum power point tracking curve shifting as a function of the blade pitch angle variation has been proposed, taking advantage of the combined effect of two frequency control strategies: one based on the use of the stored kinetic energy by means of the concept of virtual inertia, and the other, by limiting the captured wind power through blade pitch angle regulation. This algorithm has been devised to reduce the turbine deload requirements, and at the same time, to increase the available kinetic energy in the turbine. This results in a more effective fast-frequency response with a lower amount of non-dispatched wind energy. The effectiveness of the proposed method is assessed by considering a real wind profile in time-domain simulations.

A hybrid energy storage system with optimized operating strategy for mitigating wind power fluctuations

Abstract A novel method based on hybrid energy storage system (HESS), composed of adiabatic compressed air energy storage (A-CAES) and flywheel energy storage system (FESS), to mitigate wind power fluctuations and augment wind power penetration is proposed in this paper. Wind power fluctuates in different frequencies, mainly divided into low and high frequency, which can be coped with by A-CAES and FESS respectively. To fit with low frequency fluctuation exhibiting large magnitude, A-CAES with multi-operating strategies is first proposed to widen operational ranges. Mathematical model of key components' off-design performance is established. For a 49.5 MW wind farm in China, design and optimization of HESS are comprehensively investigated. More specifically, the selection of A-CAES system's key components, such as compressor and expander, and parameters of them are specified as well as the parameters of FESS. The key operating parameters of the HESS, when integrated with wind plant, are analyzed and the characteristics are revealed. The results indicate that by HESS, wind power with fluctuation within 0–49.5 MW (average 25.55 MW) can be stabilized to a steady electrical power output of 24.18 MW. The loss of wind power is 6.6%, far less than the wind power rejection rate 17.1% in China.

Research on Economics of Mixed Energy Storage for Smoothing Wind Power Fluctuation with Consideration of Confidence Level

This paper proposes a research method for mitigating wind power fluctuations in a hybrid energy storage system considering the confidence level of wind power volatility. First, the typical daily wind power output is subjected to Fourier spectrum analysis to determine the frequency range of wind power output, and combined with low-pass filtering to find the optimal cutoff frequency, for obtaining energy storage reference power; Then determining the optimal energy storage reference power by comparing the energy storage reference powers solved at different confidence levels. Finally, empirical mode decomposition (EMD) is used to decompose the stored energy into a series of intrinsic mode functions(IMFs), demarcation of the energy storage reference power with minimum aliasing in the instantaneous frequency-time curve, the high frequency part is configured by power type energy storage, and the low frequency part is configured by energy type energy storage. The simulation of the wind farms in a certain area of Hunan Province is carried out. The result shows that proper reduction of confidence level can reduce energy storage power and capacity.

Fuzzy Empirical Mode Decomposition for Smoothing Wind Power with Battery Energy Storage System

The intermittency and fluctuations of wind power cause problems in integration of wind energy systems into the grid. To smooth the fluctuations of wind power, a control scheme based on fuzzy empirical mode decomposition (EMD) is proposed with the use of battery energy storage system (BESS). With this idea, the wind power signal is decomposed via EMD and filtered into two parts: the low-frequency part is taken as the target smooth wind power for grid connection, and the high-frequency part is stored by BESS before connecting to the grid to compensate for the fluctuations in the original wind power signal. A fuzzy EMD filter is developed by considering constraints on both the power fluctuation rate and the state of charge (SOC) of the BESS. The performance of the proposed strategy has been examined through case study simulations, which demonstrates improvement in mitigating wind power fluctuations and also in reducing over charging/discharging operations of the integrated BESS.

Power Flow Features and Balancing in MTDC Integrated Offshore Wind Farms

This paper proposes a novel control strategy for converter stations of multi-terminal DC (MTDC) grid system. It optimizes the offshore wind farms power generation dispatched to the separate onshore AC systems while minimizing their impacts on AC grids. Based on the MTDC power flow analysis, the minimal control dimensions of MTDC converters are firstly proposed. The impact of DC resistances on power dispatching among MTDC grid is then fully discussed by analyzing the structure of inverse Jacobian matrix of MTDC grid power flow equation and the power dispatch law for each onshore AC grid is deduced subsequently. Finally, an optimization strategy that seeks to re-dispatch the power to each onshore converter according to the system inertia of connected AC grid is proposed. Case study using a typical five-terminal MTDC system shows that the proposed strategy can effectively mitigate wind power fluctuations by approximately equalizing the induced disturbances to the system frequency of each AC grid.

Distributed coordination regulation marginal cost control strategy for automatic generation control of interconnected power 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.

Finite-time convergence robust control of battery energy storage system to mitigate wind power fluctuations

Wind energy is envisioned to be one of the most promising clean and renewable energy to drive our future society. Due to its intermittency nature, wind power may change rapidly and frequently. Wind power fluctuations pose great challenges on power quality, reliability and raise many other issues like frequency and voltage regulation. This paper proposes a finite-time convergence robust control algorithm of battery energy storage system (BESS) to mitigate the wind power fluctuations. The major advantages of the proposed algorithm include, being insensitive to uncertainty and disturbance, enabling adjustable convergence time to accommodate different operating conditions and maintaining the state of charge (SOC) within a proper range for regulation capability reserve. Finite-time convergence of the proposed algorithm is derived through rigorous analysis. Simulation results demonstrate the effectiveness of the proposed algorithm.

A Flywheel Energy Storage System Based on a Doubly Fed Induction Machine and Battery for Microgrid Control

Microgrids are eco-friendly power systems because they use renewable sources such as solar and wind power as the main power source. However, the stochastic nature of wind and solar power is a considerable challenge for the efficient operation of microgrids. Microgrid operations have to satisfy quality requirements in terms of the frequency and voltage. To overcome these problems, energy storage systems for short- and long-term storage are used with microgrids. Recently, the use of short-term energy storage systems such as flywheels has attracted significant interest as a potential solution to this problem. Conventional flywheel energy storage systems exhibit only one control mode during operation: either smoothing wind power control or frequency control. In this paper, we propose a new flywheel energy storage system based on a doubly fed induction machine and a battery for use with microgrids. The new flywheel energy storage system can be used not only to mitigate wind power fluctuations, but also to control the frequency as well as the voltage of the microgrid during islanded operation. The performance of the proposed flywheel energy storage system is investigated through various simulations using MATLAB/Simulink software. In addition, a conventional flywheel energy storage system based on a doubly fed induction machine is simulated and its performance compared with that of the proposed one.

Two-Time-Scale Coordination Control for a Battery Energy Storage System to Mitigate Wind Power Fluctuations

In this paper, a two-time-scale coordination control method to mitigate wind power fluctuations using a battery energy storage system (BESS) is proposed. Two-time-scale maximal power fluctuation restrictions (MPFRs) are set for the combined output of the wind farm and the BESS: the maximal fluctuation of the combined power in any 1- and 30-min time window must be kept within γ1min% and γ30min%, respectively, of the rated power of the wind farm. A flexible first-order low-pass filter (FLF) with an optimization of time constant Tf is developed to limit the power fluctuation under restriction with smaller BESS capacity. Then, a coordination control method is developed on base of the FLF, which contains: 1) PSO-based time constant real-time optimizing algorithm; 2) remaining energy level feedback control; 3) two-time-scale coordination control strategy. Finally, an estimation of BESS capacity and power rating for a wind farm to achieve the MPFRs is presented, and the whole method is tested in a time-domain simulation system.