Review of the Analysis and Suppression for High-frequency Oscillations of the Grid-connected Wind Power Generation System

High-frequency oscillation(HFO)of gridconnected wind power generation systems(WPGS)is one of the most critical issues in recent years that threaten the safe access of WPGS to the grid.Ensuring the WPGS can damp HFO is becoming more and more vital for the development of wind power.The HFO phenomenon of wind turbines under different scenarios usually has different mechanisms.Hence,engineers need to acquire the working mechanisms of the different HFO damping technologies and select the appropriate one to ensure the effective implementation of oscillation damping in practical engineering.This paper introduces the general assumptions of WPGS when analyzing HFO,systematically summarizes the reasons for the occurrence of HFO in different scenarios,deeply analyses the key points and difficulties of HFO damping under different scenarios,and then compares the technical performances of various types of HFO suppression methods to provide adequate references for engineers in the application of technology.Finally,this paper discusses possible future research difficulties in the problem of HFO,as well as the possible future trends in the demand for HFO damping.

Investigating Load Regulation Characteristics of a Wind-PV-Coal Storage Multi-Power Generation System

There is a growing need to explore the potential of coal-fired power plants(CFPPs)to enhance the utilization rate of wind power(wind)and photovoltaic power(PV)in the green energy field.This study developed a load regulation model for a multi-power generation system comprising wind,PV,and coal energy storage using realworld data.The power supply process was divided into eight fundamental load regulation scenarios,elucidating the influence of each scenario on load regulation.Within the framework of the multi-power generation system with the wind(50 MW)and PV(50 MW)alongside a CFPP(330 MW),a lithium-iron phosphate energy storage system(LIPBESS)was integrated to improve the system’s load regulation flexibility.The energy storage operation strategy was formulated based on the charging and discharging priority of the LIPBESS for each basic scenario and the charging and discharging load calculation method of LIPBESS auxiliary regulation.Through optimization using the particle swarm algorithm,the optimal capacity of LIPBESS was determined to be within the 5.24-4.88 MWh range.From an economic perspective,the LIPBESS operating with CFPP as the regulating power source was 49.1% lower in capacity compared to the renewable energy-based storage mode.

Dynamic and Power Generation Features of A Wind-Wave Hybrid System Consisting of A Spar-Type Wind Turbine and An Annular Wave Energy Converter in Irregular Waves

Combining wave energy converters(WECs)with floating offshore wind turbines proves a potential strategy to achieve better use of marine renewable energy.The full coupling investigation on the dynamic and power generation features of the hybrid systems under operational sea states is necessary but limited by numerical simulation tools.Here an aero-hydro-servo-elastic coupling numerical tool is developed and applied to investigate the motion,mooring tension,and energy conversion performance of a hybrid system consisting of a spar-type floating wind turbine and an annular wave energy converter.Results show that the addition of the WEC has no significant negative effect on the dynamic performance of the platform and even enhances the rotational stability of the platform.For surge and pitch motion,the peak of the spectra is originated from the dominating wave component,whereas for the heave motion,the peak of the spectrum is the superposed effect of the dominating wave component and the resonance of the system.The addition of the annular WEC can slightly improve the wind power by making the rotor to be in a better position to face the incoming wind and provide considerable wave energy production,which can compensate for the downtime of the offshore wind.

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system(DGs)that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner(UPQC).In addition to supplying active power to the utility grid,the system of hybrid wind photovoltaic functions as a UPQC,compensating reactive power and suppressing the harmonic load currents.Additionally,the load is supplied with harmonic-free,balanced and regulated output voltages.Since PVWind-UPQC is established on a dual compensation scheme,the series inverter works like a sinusoidal current source,while the parallel inverter works like a sinusoidal voltage source.Consequently,a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients.Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load,the converters should be sized cautiously.A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters.Thus,curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed.Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC.This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

Research on Equivalent Modeling Method of AC-DC Power Networks Integrating with Renewable Energy Generation

Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.

Difference between grid connections of large-scale wind power and conventional synchronous generation

In China, regions with abundant wind energy resources are generally located at the end of power grids. The power grid architecture in these regions is typically not sufficiently strong, and the energy structure is relatively simple. Thus, connecting large-capacity wind power units complicates the peak load regulation and stable operation of the power grids in these regions. Most wind turbines use power electronic converter technology, which affects the safety and stability of the power grid differently compared with conventional synchronous generators. Furthermore, fluctuations in wind power cause fluctuations in the output of wind farms, making it difficult to create and implement suitable power generation plans for wind farms. The generation technology and grid connection scheme for wind power and conventional thermal power generation differ considerably. Moreover, the active and reactive power control abilities of wind turbines are weaker than those of thermal power units, necessitating additional equipment to control wind turbines. Hence, to address the aforementioned issues with large-scale wind power generation, this study analyzes the differences between the grid connection and collection strategies for wind power bases and thermal power plants. Based on this analysis, the differences in the power control modes of wind power and thermal power are further investigated. Finally, the stability of different control modes is analyzed through simulation. The findings can be beneficial for the planning and development of large-scale wind power generation farms.

Forecasting method of monthly wind power generation based on climate model and long short-term memory neural network

Predicting wind power gen eration over the medium and long term is helpful for dispatchi ng departme nts,as it aids in constructing generation plans and electricity market transactions.This study presents a monthly wind power gen eration forecast!ng method based on a climate model and long short-term memory(LSTM)n eural n etwork.A non linear mappi ng model is established between the meteorological elements and wind power monthly utilization hours.After considering the meteorological data(as predicted for the future)and new installed capacity planning,the monthly wind power gen eration forecast results are output.A case study shows the effectiveness of the prediction method.

An Optimal Dynamic Generation Scheduling for a Wind-Thermal Power System

In this paper, a dynamic generation scheduling model is formulated, aiming at minimizing the costs of power generation and taking into account the constraints of thermal power units and spinning reserve in wind power integrated systems. A dynamic solving method blended with particle swarm optimization algorithm is proposed. In this method, the solution space of the states of unit commitment is created and will be updated when the status of unit commitment changes in a period to meet the spinning reserve demand. The thermal unit operation constrains are inspected in adjacent time intervals to ensure all the states in the solution space effective. The particle swarm algorithm is applied in the procedure to optimize the load distribution of each unit commitment state. A case study in a simulation system is finally given to verify the feasibility and effectiveness of this dynamic optimization algorithm.

Important Issues and Results When Considering the Stochastic Representation of Wind Power Plants in a Generation Optimization Model: An Application to the Large Brazilian Interconnected Power System

Wind power has an increasing share of the Brazilian energy market and may represent 11.6% of total capacity by 2024. For large hydro-thermal systems having high-storage capacity, a complementarity between hydro and wind production could have important effects. The current optimization models are applied to dispatch power plants to meet the market demand and optimize the generation dispatches considering only hydroelectric and thermal power plants. The remaining sources, including wind power, small-hydroelectric plants and biomass plants, are excluded from the optimization model and are included deterministically. This work introduces a general methodology to represent the stochastic behavior of wind production aimed at the planning and operation of large interconnected power systems. In fact, considering the generation of the wind power source stochastically could show the complementarity between the hydro and wind power production, reducing the energy price in the spot market with the reduction of thermal power dispatches. In addition to that, with a reduction in wind power and a simultaneous dry-season occurrence, this model, is able to show the need of thermal power plants dispatches as well as the reduction of the risk of energy shortages.

Research on Power Control of Wind Power Generation Based on Neural Network Adaptive Control

For the characteristics of wind power generation system is multivariable, nonlinear and random, in this paper the neural network PID adaptive control is adopted. The size of pitch angle is adjusted in time to improve the perfomance of power control. The PID parameters are corrected by the gradient descent method, and Radial Basis Functiion （RBF） neural network is used as the system identifier in this method. Sinlation results show that by using neural network adaptive PID controller the generator power control can inhibit effectively the speed and affect the output prover of generator. The dynamic performnce and robustness of the controlled system is good, and the peformance of wind power system is improved.

New energy power generation-wind power generation

This paper introduced the status quo of wind power and wind power generation technology. Focusing on the introduction of wind power generating system ibrational self-consistent field（VSCF）, program implementation included Alternating Current （AC）-Direct Current （DC）-AC conversion system, magnetic field modulation generator system, doubly-fed generator system etc. Among these, doubly-fed generator system is the trend. Where to build the wind farm is very important, so a perfect site is needed. Wind power generation will have a bright future. As long as the wind power can be linked to the grid in large scale.

The Hidden-Layers Topology Analysis of Deep Learning Models in Survey for Forecasting and Generation of the Wind Power and Photovoltaic Energy

As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.

Rolling Generation Dispatch Based on Ultra-short-term Wind Power Forecast

The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.

An Improved Method of the Energy Loss Calculation Considering the Volatility of Wind Power Generation

The energy loss of the power grid is one of the key factors affecting the economic operation of power systems. How to calculate the electric energy consumption accurately will have a great influence on the planning, operation and management of the power grid. Currently there is a mountain of theoretical methods to calculate the line loss of the power system. However, these methods have some limitation, such as less considering the volatility of wind power resources. This paper presents an improved method to calculate the energy loss of wind power generation, considering the fluctuations of wind power generation. First, data are collected to obtain the curve of the typical daily expected output of wind farms for one month. Second, the curve of the typical daily expected output are corrected by the average electricity and the shape factor to obtain the curve of the typical daily equivalent output of wind farms for one month. Finally, the power flow is calculated by using typical daily equivalent output curve to describe the energy loss for one month. The results in the 110 kV main network show that the method is feasible.

Hydrodynamic Characteristics of New Floating Wind-Wave Energy Combined Power Generation Devices Under Typhoon-Wave-Current Coupling

The South China Sea is rich in wind and wave energy resources,and the wind-wave combined power generation device is currently in the concept research and development stage.In recent years,extreme sea conditions such as super typhoons have frequently occurred,which poses a serious challenge to the safety of offshore floating platforms.In view of the lack of safety analysis of wind-wave combined power generation devices in extreme sea conditions at present,this paper takes the OC4-WEC combined with semi-submersible wind turbine(Semi-OC4)and the oscillating buoy wave energy converter as the research object,and establishes a mesoscale WRF-SWANFVCOM(W-S-F)real-time coupling platform based on the model coupling Toolkit(MCT)to analyze the spatial and temporal evolution of wind-wave-current in offshore wind farms during the whole process of super typhoon“Rammasun”transit.Combined with the medium/small scale nested method,the flow field characteristics of OC4-WEC platform are analyzed.The results show that the simulation accuracy of the established W-S-F platform for typhoon track is 42.51%higher than that of the single WRF model.Under the action of typhoon-wave-current,the heave motion amplitude of OC4-WEC platform is reduced by 38.1%,the surge motion amplitude is reduced by 26.7%,and the pitch motion amplitude is reduced by 23.4%.

Inner Mongolia builds up world's class wind power generation farm

The first phase project of Huitengxile Wind Power Generation Farm in Inner Mongolia, with nine 600 kW wind power generators installed, was formally put into commercial operation on November 28,

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Electric-heat coupling characteristics of a cogeneration system and the operating mode of fixing electricity with heat are the main reasons for wind abandonment during the heating season in the Three North area.To improve the wind-power absorption capacity and operating economy of the system,the structure of the system is improved by adding a heat storage device and an electric boiler.First,aiming at the minimum operating cost of the system,the optimal scheduling model of the cogeneration system,including a heat storage device and electric boiler,is constructed.Second,according to the characteristics of the problem,a cultural gene algorithm program is compiled to simulate the calculation example.Finally,through the system improvement,the comparison between the conditions before and after and the simulation solutions of similar algorithms prove the effectiveness of the proposed scheme.The simulation results show that adding the heat storage device and electric boiler to the scheduling optimization process not only improves the wind power consumption capacity of the cogeneration system but also reduces the operating cost of the system by significantly reducing the coal consumption of the unit and improving the economy of the system operation.The cultural gene algorithm framework has both the global evolution process of the population and the local search for the characteristics of the problem,which has a better optimization effect on the solution.