Power Smoothing Control Research Articles

Active power smoothing control strategy of offshore wind power system based on reduced matrix converter

On account of the fluctuation and randomness of wind speed, the output power of wind turbines fluctuates greatly, which may cause the frequency change of the power grid and increase the difficulty of power system dispatching. To solve this problem, an active power smoothing control (APSC) strategy based on RMC for offshore wind power systems is proposed in this paper. Compared with existing wind power converter systems, RMC adopted in this paper has the advantages of compact structure, small volume and high conversion efficiency. Based on the analysis of the exponential moving average (EMA) algorithm, a method for determining active power based on the fuzzy EMA algorithm is proposed. The method adjusts the cycle number N in real-time according to the wind speed, taking into account both the wind energy utilization rate and the smoothing performance of active power. The control principle of offshore wind power generation system (WPGS) based on RMC is analyzed in detail and the coordinated control strategy of RMC and inverter is proposed. Simulation results demonstrate the validity of the proposed method and control strategy.

On sizing of battery energy storage systems for PV plants power smoothing

The high variability of solar irradiance causes fluctuations in the generation of photovoltaic (PV) power plants. This characteristic affects power system operation, thus, strategies are necessary to mitigate the intermittent characteristics of PV power plants. Several countries adopt grid codes incorporating ramp rate (RR) limitations for PV power injection into the grid, also known as power smoothing control. In this sense, battery energy storage systems (BESS) with coordinated RR control algorithms are commonly applied to mitigate current fluctuations from the PV system to the grid. Therefore, studies on the effect of local solar irradiance on BESS requirements for PV power smoothing applications are very important. It is also worth highlighting that in the literature there is a gap in the evaluation of aspects of battery lifetime, BESS volume, price and BESS oversizing for selecting an ideal battery model, among a catalog of batteries, constituting an industrial concern. Therefore, this work presents a detailed BESS sizing methodology, evaluating aspects of the energy requirements, power, and discharging rate (C-rate), based on the mission profile (featuring a customized solution for each project). In addition, the effect of the battery temperature control on the BESS sizing is evaluated. The case study is based on a 1 MW PV system, assessed using a one-year mission profile of solar irradiance and ambient temperature from Goiânia-Brazil. The PV plant is connected to a 440 V grid associated with a BESS that mitigates oscillations of 10%/min. The BESS sizing is evaluated in terms of BESS volume, lifetime, and oversizing factor for power and energy. The proposed methodology reduces the BESS volume by 57.14% in relation to the traditional BESS design of literature.

Intermittent power smoothing control for grid connected hybrid wind/PV system using battery-EDLC storage devices

Wind and solar radiation are intermittent with stochastic fluctuations, which can influence the stability of operation of the hybrid system in the grid integrated mode of operation. In this research work, a smoothing control method for mitigating output power variations for a grid integrated wind/PV hybrid system using a battery and electric double layer capacitor (EDLC) is investigated. The power fluctuations of the hybrid system are absorbed by a battery and EDLC during wide variations in power generated from the solar and wind system, subsequently, the power supplied to the grid is smoothened. This makes higher penetration and incorporation of renewable energy resources to the utility system possible. The control strategy of the inverter is realized to inject the power to the utility system with the unity power factor and a constant DC bus voltage. Both photovoltaic (PV) and wind systems are controlled for extracting maximum output power. In order to observe the performance of the hybrid system under practical situations in smoothing the output power fluctuations, one-day practical site wind velocity and irradiation data are considered. The dynamic modeling and effectiveness of this control method are verified in the MATLAB/Simulink environment. The simulation results show that the output power variations of the hybrid wind/PV system can be significantly mitigated using the combination of battery and EDLC based storage systems. The power smoothing controller proposed for the hybrid storage devices is advantageous as compared to the control technique which uses either battery or ultracapacitor used for smoothing the fluctuating power

Coordinated Power Smoothing Control Strategy of Multi-Wind Turbines and Energy Storage Systems in Wind Farm Based on MADRL

The randomness and volatility of wind power greatly affect the safety and economy of the power systems, and the wake effect of the wind farm aggravates the wind energy loss and the wind power fluctuation. Taking into consideration the wake effect of the wind farm, a new coordinated wind power smoothing control strategy for multi-wind turbines (M-WT) and energy storage systems (ESS) is proposed. The proposed method is based on a multi-agent deep reinforcement learning (MADRL), in which the relationship between output power and wake effect is firstly analyzed, and a power smoothing control model of the M-WT and ESS is established. MADRL is then introduced to optimize the power control of M-WT and ESS. In order to further increase the learning and training efficiency, an improved MADRL algorithm based on the partitioned experience buffer and prioritized experience replay is proposed, where the experience buffer is divided into positive, negative, and neutral experiences, and the experiences are sampled according to experience priority. The effectiveness of the proposed strategy is verified on the SimWindFarm platform. The results show that the proposed control strategy can maximize the economic benefits while further smoothing wind power fluctuations and increasing power generation.

Robust Proactive Power Smoothing Control of PV Systems Based on Deep Reinforcement Learning

Efficient integration of photovoltaic (PV) energy into the power grid calls for a robust regulation of its intermittency. At present, the solar forecasting-assisted proactive power smoothing control (PPSC) has shown superiority in handling such PV intermittency due to its battery-less operations. However, the implementation of PPSC is largely dependent on the quality of solar forecasts, i.e, high accuracy over a long horizon, which has seriously limited its extensive application in practice. In this context, this paper proposes a novel PPSC method based on deep reinforcement learning (RL). In addition to the actor-critic structures, a new module, namely, compensator is developed to tackle the problems of sparse reward and state transition stochasticity that are typically associated with the PPSC control task. On top of it, a novel scenario recognized experience replay (SRER) is devised to deal with the data distribution mismatching issue in PPSC. The effectiveness of the proposed method is verified using real-world data from a solar measurement grid. Empirical studies show that compared with the conventional PPSC method, the proposed method can achieve more robust smoothing performance under various forecasting scenarios, rendering it more applicable to practical PV system operations.

Research on a power smoothing control strategy for energy storage hydraulic wind turbines

AbstractTo solve the problem of large output power fluctuations in wind turbines and improve grid adaptability, a hydraulic energy storage system is introduced in traditional hydraulic wind turbines. Based on the working principle of energy storage hydraulic wind turbines, an energy storage hydraulic wind turbine state space model is established, and the feedback linearization method is introduced to solve the multiplication nonlinear problem in the modeling process. The output power is taken as the control output, and the torque compensation controller is established with the feedback linearization method. The displacement of the variable displacement pump motor is controlled to realize hydraulic energy storage system energy charging and discharging, and the wind turbine output power smoothing control is realized with the fluctuating wind speed. The power smoothing control strategy is verified with the 24 kW energy storage hydraulic wind turbines semi‐physical simulation experimental platform. The proposed control strategy lays the groundwork for the wide application of the energy storage hydraulic wind turbines.

CVR-Based Real-Time Power Fluctuation Smoothing Control for Distribution Systems With High Penetration of PV and Experimental Demonstration

This paper proposes a real-time power smoothing control strategy for distribution systems with high penetration of photovoltaic (PV) based on conservation voltage reduction (CVR) technology, which employs CVR effects of feeder loads to smooth net-load power fluctuations caused by PV intermittency. CVR technology is implemented in real-time based on feedback signals provided by phasor measurement unit, and feeder voltage is under closed-loop control within statutory limits to make load demand change with PV power. Meanwhile, an online CVR model identification application based on generalized recursive least squares and a power smoothing application based on PI-Smith controller are separately designed. CVR model identification application uses well-designed M-sequence voltage disturbance to online induce CVR effects, which can accurately identify dynamic and steady-state CVR effects without being affected by color-noises. Power smoothing application combines PI controller with Smith predictor to limit the fluctuation rate of net-load without being affected by practical time-delay. The parameters of controller are automatically tuned through the identified CVR model with small computational burden, which is beneficial to engineering applications. The proposed method has been demonstrated in real 10kV distribution system in China. Simulation and field results demonstrate that proposed method has significant potential for real-time power smoothing.

An improved fuzzy logic based DC-link voltage control strategy for smoothing output power of the PMSG-WECS

Direct power smoothing control methods relying on the wind turbine itself have been widely studied to improve wind turbines’ output power quality, and the DC-link voltage control based on the capacitor of the wind power converter is one of them. In this paper, the principle of DC-link capacitor voltage control is studied at first, then an improved time interval DC-link voltage control strategy on the basis of a low-pass filter (LPF) is proposed and compared with existing DC-link voltage power smoothing controls. To further improve the power smoothing effect, the fuzzy logic control is used to adjust the time constant of LPF, and the maximum time constant in the fuzzy logic control is determined through convolution calculation. For the sake of ensuring the system stability, the transfer function of proposed DC-link voltage control is derived to determine proper parameters of voltage loop. The proposed fuzzy logic-based DC-link power smoothing strategy is verified through effective simulation results of the permanent magnet synchronous generator wind energy conversion system (PMSG-WECS).

Supercapacitors based energy storage system for mitigating solar photovoltaic output power fluctuations

PurposeNon-linear power–voltage characteristics of solar cell and frequently changing output due to variation in solar irradiance caused by movement of clouds are the major issues need to be considered in photovoltaic (PV) penetration to maintain the power quality of the grid. It is important for a PV module to always function at its maximum available power point to increase the efficiency and to maintain the grid stability. A possible solution to mitigate these generation fluctuations is the use of an electric double-layer capacitor or supercapacitor energy storage device, which is an efficient storage device for power smoothing applications. This study aims to propose a power smoothing control approach to smoothen out the output power variations of a solar PV system using a supercapacitor energy storage device.Design/methodology/approachTo extract the maximum possible power from a PV panel, there are several maximum power points tracking (MPPT) algorithms developed in literature. Fuzzy logic controller-MPPT method is used in this work as it is a very efficient and popular technique which responds quickly under varying ecological conditions, reduced computational complexity and does not depend on any system constraints. Fuzzy logic-based MPPT controller by Boost DC–DC converter is developed for operating the PV panels at available maximum power point. Fuzzy logic-proportional integral (PI) charge controller is implemented by Buck–Boost converter to provide the constant current and suitable voltage for supercapacitor and to achieve better power smoothing. PI charge controller is preferred in this work as it offers better outcomes and is very easy to implement.FindingsSimulation results conclude that the proposed power smoothing control approach can efficiently smooth out the power variations under variable irradiance and temperature situations. To confirm the accurateness of the proposed system, it is validated for poly-crystalline PV module and comparison of results is done by using different case study with and without the use of an energy storage system under change in irradiance condition. The proposed system is developed and examined on MATLAB/Simulink environment.Originality/valueThe performance comparison between PV power output with and without the use of a supercapacitor energy storage device under different Case Studies shows that the improved performance in smoothing of power output was achieved with the use of a supercapacitor energy storage device.

Transient power smoothing control strategy for battery of pure electric bus

Transient power smoothing control strategy for battery of pure electric bus

Transient power smoothing control strategy for battery of pure electric bus

Transient power smoothing control strategy for battery of pure electric bus

A Review on the Application of the MPC Technology in Wind Power Control of Wind Farms

Due to the uncertainty and volatility of wind speed, its natural output power also exhibits strong volatility. In order to avoid the negative effects of the excessive fluctuation of the output power of wind turbines in the wind farm and the power grid, it is very important to accurately predict and reasonably plan and control the output power of the wind farm. Model predictive control (MPC) is a type of advanced control method that can deal with a multi-input multi-output nonlinear system. Compared to the traditional proportional integral derivative control, MPC is more suitable for the complex wind farm model and exhibits good control performance, and has been gradually applied to control the wind power in wind farms. In this article, we have summarized the application of the MPC technology in the prediction and control of wind power in a wind farm, analyze the application of the MPC technology, including MPC, multi-objective MPC, nonlinear MPC, and distributed MPC, in the wind farm power control with different optimization objectives. In addition, the optimization of the active and reactive power of wind farms has also been discussed in detail. Furthermore, some hot topics in the current research, such as the multi-objective optimization problem of coordinating the maximum power and reducing the fatigue load and power smoothing control problem, have been summarized. Finally, the existing problems of MPC applied to wind power systems have been discussed.

Kinetic energy based output power smoothing control and parameters design for PMSG-WECSs

The fluctuating output power of wind turbines can lead to the instability of grid, and the effective and economic power smoothing control strategies are essential. Hence, this paper proposes a kinetic energy based power smoothing control strategy for the permanent magnet synchronous generator based wind energy conversion system (PMSG-WECS). The low-pass filter is adopted to replace the traditional average value calculation module. Moreover, the parameters of the proposed power smoothing strategy are designed through the stability analysis of the control transfer functions. The simulation model of a 2MW PMSG-WECS is developed in Matlab/Simulink to validate the feasibility and effectiveness of the proposed power smoothing method. Furthermore, experiments are carried out based on a low power 5.5 kW experimental platform in the lab. Both the simulation and experimental results show that the proposed strategy can provide a satisfactory performance of power smoothing.

Optimal power smoothing control for superconducting fault current limiter-magnetic energy storage system

Optimal energy management is a major challenge for most energy storage systems (ESSs), which is especially a big concern for the superconducting fault current limiter-magnetic ESS (SFCL-MES). To prevent malfunction, the superconducting coil (SC) current of the SFCL-MES needs to be controlled strictly within a well-defined operational range. To optimally utilize the energy capability of the ESS while keeping the state of charge (SOC) within a safe range, a novel multi-input multi-output fuzzy logic controller (FLC), which adjusts both the filter time constant and the SOC regulator gains, is proposed for optimal energy utilization. The parameters of the FLC were further optimized offline by particle swarm optimization with real collected operational data. The optimized FLC has been successfully implemented on a 1MVA/1MJ prototype installed in a wind farm. The operational results of the prototype demonstrate the good performance of the proposed approaches.

Combined low voltage ride through and power smoothing control for DFIG/PMSG hybrid wind energy conversion system employing a SMES-based AC-DC unified power quality conditioner

An Interline AC-DC unified power quality conditioner (UPQC) protection device is proposed and designed based on superconducting magnetic energy storage (SMES) in this paper to improve low voltage ride through (LVRT) capacity and smooth output power for doubly fed induction generator (DFIG)/ permanent magnet synchronous generator (PMSG) hybrid wind energy conversion system (WECS). The AC side of the proposed UPQC is connected in series with the terminal of DFIG as a dynamic voltage restorer (DVR), and the DC side of the UPQC is connected in parallel with the DC bus of PMSG for DC bus voltage maintenance and output power adjustment. For a case verification, a 4.76-H/1760-A superconducting coil (SC) is designed as an energy storage device utilized in UPQC to carry out the energy conversion. Finally, the performances of the proposed protection scheme under the conditions of wind speed variation, three-phase-to-ground fault and two-phase-to-ground fault have been presented and analyzed via simulation, to verify the effectiveness of the proposed AC-DC UPQC in DFIG/PMSG hybrid WECS.

Power Smoothing Control of Photovoltaic Power Generation System based on Hybrid Energy Storage

Among many renewable energy sources, solar energy is widely used, and photovoltaic power generation has become an effective way of solar energy utilization. In recent years, it has been widely studied and applied, and remarkable results have been achieved. However, due to the influence of sunlight intensity and temperature, the power of the photovoltaic power generation is relatively fluctuating, so there are still some problems in large-scale grid-connection technology. In this paper, to direct at the power fluctuation of photovoltaic power generation caused by the change of illumination intensity and temperature, an energy storage photovoltaic grid-connected power generation system was proposed. A simulation model of photovoltaic power generation system based on mixed energy storage system was built in MATLAB/Simulink, and relevant simulation analysis and researches were conducted.

A power smoothing control method for a photovoltaic generation system using a water electrolyzer and its filtering characteristics

AbstractThis paper proposes a novel power smoothing control method for a photovoltaic generation (PV) system using a water electrolyzer (ELY). This method realizes that the long‐period components of the PV power fluctuation are supplied to the power grid and the short‐period components of the PV power fluctuation are supplied to the ELY. The power supplied to the ELY is converted to hydrogen for fuel cell vehicles. The results of the power smoothing control method are evaluated in terms of the power in the load frequency control (LFC) band and the ability of generating hydrogen. Furthermore, filtering characteristics of the proposed method are clarified. As the result, the proposed method has reduced the power in LFC band by 83.7% compared to the PV power without the power smoothing control. The filter characteristics of the proposed method have shown that fluctuating components with periods less than 1000 seconds, in which the step voltage regulator does not perform, can be sufficiently eliminated from the PV power fluctuation components. When applying the proposed method for a PV system rated at 800 kW, the ability of generating hydrogen was about 2.30% of the hydrogen required for one hydrogen station.

A Power Smoothing Control Method for a Photovoltaic Generation System using a Water Electrolyzer and its Filtering Characteristics

A Power Smoothing Control Method for a Photovoltaic Generation System using a Water Electrolyzer and its Filtering Characteristics

Power Filtering Based Wind Farm Power Fluctuation Smoothing Control Strategy

The output active power of the wind-power generator fluctuates with the change of the wind speed, which affects the output power quality of the wind farm. In order to reduce output power fluctuation of wind farm, based on analyzing of Wind Power Fluctuation Spectrum, an active power smoothing control strategy had been proposed through the pitch angle control and speed control of the generator. The simulation results show that the proposed control strategy can effectively reduce the output active power fluctuations of wind farm.

Output Power Smoothing Control for a Wind Farm Based on the Allocation of Wind Turbines

This paper presents a new output power smoothing control strategy for a wind farm based on the allocation of wind turbines. The wind turbines in the wind farm are divided into control wind turbines (CWT) and power wind turbines (PWT), separately. The PWTs are expected to output as much power as possible and a maximum power point tracking (MPPT) control strategy combining the rotor inertia based power smoothing method is adopted. The CWTs are in charge of the output power smoothing for the whole wind farm by giving the calculated appropriate power. The battery energy storage system (BESS) with small capacity is installed to be the support and its charge and discharge times are greatly reduced comparing with the traditional ESSs based power smoothing strategies. The simulation model of the permanent magnet synchronous generators (PMSG) based wind farm by considering the wake effect is built in Matlab/Simulink to test the proposed power smoothing method. Three different working modes of the wind farm are given in the simulation and the simulation results verify the effectiveness of the proposed power smoothing control strategy.