Research on Reactive Power Optimization of Offshore Wind Farms Based on Improved Particle Swarm Optimization

The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind farms.To improve the voltage stability and reactive power economy of wind farms,the improved particle swarmoptimization is used to optimize the reactive power planning in wind farms.First,the power flow of offshore wind farms is modeled,analyzed and calculated.To improve the global search ability and local optimization ability of particle swarm optimization,the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning factor.Taking the minimum active power loss of the offshore wind farms as the objective function,the installation location of the reactive power compensation device is compared according to the node voltage amplitude and the actual engineering needs.Finally,a reactive power optimizationmodel based on Static Var Compensator is established inMATLAB to consider the optimal compensation capacity,network loss,convergence speed and voltage amplitude enhancement effect of SVC.Comparing the compensation methods in several different locations,the compensation scheme with the best reactive power optimization effect is determined.Meanwhile,the optimization results of the standard particle swarm optimization and the improved particle swarm optimization are compared to verify the superiority of the proposed improved algorithm.

Performance of the CMA-GD Model in Predicting Wind Speed at Wind Farms in Hubei, China

This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).

Two-stage ADMM-based distributed optimal reactive power control method for wind farms considering wake effects

Since the connection of small-scale wind farms to distribution networks,power grid voltage stability has been reduced with increasing wind penetration in recent years,owing to the variable reactive power consumption of wind generators.In this study,a two-stage reactive power optimization method based on the alternating direction method of multipliers(ADMM)algorithm is proposed for achieving optimal reactive power dispatch in wind farm-integrated distribution systems.Unlike existing optimal reactive power control methods,the proposed method enables distributed reactive power flow optimization with a two-stage optimization structure.Furthermore,under the partition concept,the consensus protocol is not needed to solve the optimization problems.In this method,the influence of the wake effect of each wind turbine is also considered in the control design.Simulation results for a mid-voltage distribution system based on MATLAB verified the effectiveness of the proposed method.

Special report on relationship between wind farms and power grids

The installed capacity of a large scale wind power plant will be up to a number of hundreds MW, and the wind power is transmitted to load centers through long distance transmission lines with 220 kV, 500 kV, or 750 kV. Therefore, it is necessary not only considering the power transmission line between a wind power plant and the first connection node of the power network, but also the power network among the group of those wind power plants in a wind power base, the integration network from the base to the existed grids, as well as the distribution and consumption of the wind power generation by loads. Meanwhile, the impact of wind power stochastic fluctuation on power systems must be studied. In recent years, wind power prediction technology has been studied by the utilities and wind power plants. As a matter of fact, some European countries have used this prediction technology as a tool in national power dispatch centers and wind power companies.

Grid Integration of Wind Generation Considering Remote Wind Farms:Hybrid Markovian and Interval Unit Commitment

Grid integration of wind power is essential to reduce fossil fuel usage but challenging in view of the intermittent nature of wind.Recently,we developed a hybrid Markovian and interval approach for the unit commitment and economic dispatch problem where power generation of conventional units is linked to local wind states to dampen the effects of wind uncertainties.Also,to reduce complexity,extreme and expected states are considered as interval modeling.Although this approach is effective,the fact that major wind farms are often located in remote locations and not accompanied by conventional units leads to conservative results.Furthermore,weights of extreme and expected states in the objective function are difficult to tune,resulting in significant differences between optimization and simulation costs.In this paper,each remote wind farm is paired with a conventional unit to dampen the effects of wind uncertainties without using expensive utility-scaled battery storage,and extra constraints are innovatively established to model pairing.Additionally,proper weights are derived through a novel quadratic fit of cost functions.The problem is solved by using a creative integration of our recent surrogate Lagrangian relaxation and branch-and-cut.Results demonstrate modeling accuracy,computational efficiency,and significant reduction of conservativeness of the previous approach.

Coordination between Fault-Ride-Through Capability and Over-current Protection of DFIG Generators for Wind Farms

Fault Ride-Through （FRT） capabilities set up according to the grid codes may affect the performance of related protective elements during fault periods. Therefore, in this paper the coordination between the FRT capability and over-current protection of DFIG Wind Generators in MV networks is investigated. Simulation test cases using MATLAB-Simulink are implemented on a 365-MW wind farm in AL-Zaafarana, Egypt. The simulation results show the influence of the FRT capability on the protective relaying coordination in wind farms, showing that the FRT may work in situations where is were expected not to work, and then disabling the over-current protection, which should have worked in this situation.

General Economic Analysis about the Wind Farms Repowering in Spain

Environmental pollution and emissions from greenhouse gases caused by fossil fuel use are a threat to sustainable development. With renewable energy sources, no polluting emissions are released into the atmosphere. Therefore, using these sources on a large-scale is a key to reducing emissions and meeting the commitments established by Kyoto Protocol. Moreover, EU wants that the 20% of energy consumption is renewable in 2020. This study describes economic aspects, such as net present value and internal profitability rate, of the repowering process for the wind farms. Repowering can generate considerably more power with fewer facilities. This process was the result of a growing demand for renewable energies, facilitated by the great potential of wind energy in the north of Spain. The wind farms studied in this work were set up before 1998 and they had obsolete machinery with low power. There are strong indications that repowering is a profitable endeavour.

Sub-synchronous frequency domain-equivalent modeling for wind farms based on rotor equivalent resistance characteristics

The equivalent simplification of large wind farms is essential for evaluating the safety of power systems.However,sub-synchronous oscillations can significantly affect the stability of power systems.Although detailed mathematical models of wind farms can help accurately analyze the oscillation mechanism,the solution process is complicated and may lead to problems such as the“dimensional disaster.”Therefore,this paper proposes a sub-synchronous frequency domain-equivalent modeling method for wind farms based on the nature of the equivalent resistance of the rotor,in order to analyze sub-synchronous oscillations accurately.To this end,Matlab/Simulink is used to simulate a detailed model,a single-unit model,and an equivalent model,considering a wind farm as an example.A simulation analysis is then performed under the sub-synchronous frequency to prove that the model is effective and that the wind farm equivalence model method is valid.

Characteristics of Lightning Damage to Coastal Wind Farms and Its Protective Measures

Firstly, characteristics of coastal wind farms were analyzed, and then lightning damage to coastal wind farms was discussed, finally main lightning protection measures were put forward from aspects of turbine blades, engine rooms and overvoltage protection. Besides conventional light- ning protection technology, local lightning protection, pre-discharge and lightning motoring and early warning techniques should be used to protect coastal wind farms against lightning.

Simulated Influence of Mountainous Wind Farms Operations on Local Climate

Renewable energy sources,especially wind power,were believed to be able to slow down global warming;however,evidence in recent years shows that wind farms may also induce climate change.With the rapid development of wind power industry,the number of wind farms installed in mountains has gradually increased.Therefore,it is necessary to study the impact of wind farms in mountainous areas on local climate.The Suizhou and Dawu wind farms in northern Hubei Province were chosen for the present study on the impact of wind farm operations on the local climate in mountainous areas.The mesoscale meteorological numerical model Weather Research and Forecasting Model(WRF)and the Fitch model,together with turbulence correction factor,were used to simulate wind farm operations and study their effects on local climate.The results showed the characteristics of wind speed attenuation in mountainous wind farms:the amplitude and range of wind speed attenuation were stronger in the nighttime than in the daytime,and stronger in summer than in winter.The surface temperature increased and became more significant in summer.However,a cooling variation was observed above the surface warming center.The height of this center was higher in the daytime than it was in the nighttime.The latent heat flux in the wind farms decreased at night,accompanied by an increase in sensible heat flux.However,these changes were not significant.Some differences were observed between the impact of wind farms on the climate in the plains and the mountains.Such differences are more likely to be related to complex terrain conditions,climate conditions,and the density of wind turbines.The present study may provide support for the development and construction of wind farms in mountainous areas.

Impact of the Objective Function on the Construction of Internal Grids of Wind Farms Using Genetic Algorithm

The macro complex of the construction industry is energy intensive. Solutions that enable the supply of this demand while meeting the principles of sustainability are needed. The construction of wind farms has been a strategy employed by many countries to produce clean energy. An increase in the construction of wind farms has also been witnessed in Brazil. This calls for different activities, such as the design and construction of infrastructure. This article focuses on the design of internal medium voltage distribution grids for wind farms. The purpose is to find a radial configuration that connects a set of wind generators to the substation, in an optimum way, minimizing operational and construction costs, reducing loss and therefore contributing to sustainability. In large farms, the project design consists of a large combinatorial optimization problem, given the large number of possible configurations to be deployed. Finding the best solution for the internal grid depends on the criterion adopted for the objectives pursued. This article analyzes the different criteria that can be adopted in the design of the wind farm’s internal grid using a methodology based on genetic algorithm (GA). Its aim is to identify their influence on the solution of the problem and help decision-making by finding the most adequate criterion for the objectives pursued. The results show that the design of the internal grid is sensitive to the criteria adopted for the objective function. In addition, the degree of sensitivity is analyzed, showing that, in some cases, the solutions are not economically attractive and do not contribute to the reduction of losses.

Ecological impacts of the expansion of offshore wind farms on trophic level species of marine food chain

The global demand for renewable energy has resulted in a rapid expansion of offshore wind farms(OWFs)and increased attention to the ecological impacts of OWFs on the marine ecosystem.Previous reviews mainly focused on the OWFs’impacts on individual species like birds,bats,or mammals.This review collected numerous field-measured data and simulated results to summarize the ecological impacts on phytoplankton,zooplankton,zoobenthos,fishes,and mammals from each trophic level and also analyze their interactions in the marine food chain.Phytoplankton and zooplankton are positively or adversely affected by the‘wave effect’,‘shading effect’,oxygen depletion and predation pressure,leading to a ±10% fluctuation of primary production.Although zoobenthos are threatened transiently by habitat destruction with a reduction of around 60% in biomass in the construction stage,their abundance exhibited an over 90% increase,dominated by sessile species,due to the‘reef effect’in the operation stage.Marine fishes and mammals are to endure the interferences of noise and electromagnetic,but they are also aggregated around OWFs by the‘reef effect’and‘reserve effect’.Furthermore,the complexity of marine ecosystem would increase with a promotion of the total system biomass by 40% through trophic cascade effects strengthen and resource partitioning alternation triggered by the proliferation of filter-feeders.The suitable site selection,long-term monitoring,and life-cycle-assessment of ecological impacts of OWFs that are lacking in current literature have been described in this review,as well as the carbon emission and deposition.

Detection of Nonlinear Behavior Induced by Hard Limiting in Voltage Source Converters in Wind Farms Based on Higher-order Spectral Analysis

In recent years, sub-synchronous oscillation accidents caused by wind power integration have received extensive attention. The recorded constant-amplitude waveforms can be induced by either linear or nonlinear oscillation mechanisms. Hence, the nonlinear behavior needs to be distinguished prior to choosing the analysis method. Since the 1960s, the higher-order statistics(HOS) theory has become a powerful tool for the detection of nonlinear behavior(DNB) in production quality control wherein it has mainly been applied to mechanical condition monitoring and fault diagnosis. This study focuses on the hard limiters of the voltage source converter(VSC) control systems in the wind farms and attempts to detect the nonlinear behavior caused by bi-or uni-lateral saturation hard limiting using the HOS analysis. First, the conventional describing function is extended to obtain the detailed frequency domain information on the bi-and uni-lateral saturation hard limiting. Furthermore, the bi-and tri-spectra are introduced as the HOS, which are extended into bi-and tri-coherence spectra to eliminate the effects of the linear parts on the harmonic characteristics of hard limiting in the VSC control system, respectively. The effectiveness of the HOS in the DNB and the classification of the hard-limiting types is proven, and its detailed derivation and estimation procedure is presented. Finally, the quadratic and cubic phase coupling in the signals is illustrated, and the performance of the proposed method is evaluated and discussed.

Dynamic Couplingand Cooperative Control for Multi-paralleled Doubly Fed Induction Generator Wind Farms during Symmetrical Low Voltage Ride-through in a Weak Grid

In multi-fed grid-connected systems,there are complex dynamic interactions between different pieces of equipment.Particularly in situations of weak-grid faults,the dynamic coupling between equipment becomes more pronounced.This may cause the system to experience small-signal instability during the fault steady-state.In this paper,multi-paralleled doubly fed induction generator(DFIG)-based wind farms(WFs)are taken as an example to study the dynamic coupling within a multi-fed system during fault steady-state of symmetrical low voltage ride-through(LVRT)in a weak grid.The analysis reveals that the dynamic coupling between WFs will introduce a damping shift to each WF.This inevitably affects the system’s dynamic stability and brings the risk of small-signal instability during fault steady-state in LVRT scenarios.Increasing the distance to fault location and fault severity will exacerbate the dynamic coupling between WFs.Because of the dynamic coupling,adjusting the control state of one WF will affect the stability of the remaining WFs in the system.Hence,a cooperative control strategy for multi-paralleled DFIG WFs is proposed to improve dynamic stability during LVRT.The analysis and the effectiveness of the proposed control strategy are verified by modal analysis and simu-lation.

Distributed and Risk-averse ADP Algorithm for Stochastic Economic Dispatch of Power System with Multiple Offshore Wind Farms

With more and more offshore wind power being increasingly connected to power grids,fluctuations in offshore wind speeds result in risks of high operation costs.To mitigate this problem,a risk-averse stochastic economic dispatch(ED)model of power system with multiple offshore wind farms(OWFs)is proposed in this paper.In this model,a novel GlueVaR method is used to measure the tail risk of the probability distribution of operation cost.The weighted sum of the expected operation cost and the GlueVaR is used to reflect the risk of operation cost,which can consider different risk requirements including risk aversion and risk neutrality flexibly by adjusting parameters.Then,a risk-averse approximate dynamic programming(ADP)algorithm is designed for solving the proposed model,in which multi-period ED problem is decoupled into a series of single-period ED problems.Besides,GlueVaR is introduced into the approximate value function training process for risk aversion.Finally,a distributed and risk-averse ADP algorithm is constructed based on the alternating direction method of multipliers,which can further decouple single-period ED between transmission system and multiple OWFs for ensuring information privacy.Case studies on the modified IEEE 39-bus system with an OWF and an actual provincial power system with four OWFs demonstrate correctness and efficiency of the proposed model and algorithm.

Shared mooring systems for offshore floating wind farms: A review

Offshore wind energy,as a form of renewable power,has seen rapid development in recent years.While fixedbottom wind turbines are typically used in water depths less than 50 m,the utilization of floating offshore wind turbines(FOWTs)becomes essential for deeper waters.Secure and effective mooring systems play a crucial role in making FOWTs commercially viable.The concept of a shared mooring system offers an innovative solution for deploying floating wind farms in clusters or arrays,which can reduce overall construction costs for large-scale floating wind farms.It is imperative to optimize the shared mooring arrangement for maximum cost-effectiveness and wind farm stability.However,implementing a shared mooring system introduces complexity to the dynamics of FOWTs,requiring the development of advanced simulation tools to meet modelling requirements.Under the shared mooring arrangement,mooring lines and anchors face more significant challenges,such as chain-seabed interactions,soil cyclic weakening,and anchor out-of-plane loading,which underscore the need for innovative,reliable,and efficient shared anchor designs.This article offers an overview of the current research status on shared mooring systems for floating wind farms,which might serve as a valuable reference for the construction of large-scale floating wind farms worldwide.

Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Wind power has been developing rapidly as a key measure to mitigate human-driven global warming.The under-standing of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited.In this study,we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats.We explored the impacts of wind farms on land surface temperature(LST)and vegetation net primary productivity(NPP)between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas.The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020.Spatially,wind farms are mainly clustered in three aggregation areas in the center.Further,wind farms increased nighttime LST,with a mean value of 0.23℃,but had minor impacts on the daytime LST.Moreover,wind farms caused a decline in NPP,especially over forest areas,with an average reduction of 12.37 GC/m^(2).Given the impact of wind farms on LST and NPP,we suggest that the development of wind farms should fully consider their direct and potential impacts.This study provides scientific guidance on the spatial pattern of future wind farms.

Fast Protection for Collector Lines in Large-Scale Wind Farms Based on Random Matrix Theory

The impact of large-scale wind farms on power system stability should be carefully investigated,in which mal-functions usually exist in the collector line's relay protection.In order to solve this challenging problem,a novel time-domain protection scheme for collector lines,based on random matrix theory(RMT),is proposed in this paper.First,the collected currents are preprocessed to form time series data.Then,a real-time sliding time window is used to form a consecutive time series data matrix.Based on RMT,mean spectral radius(MSR)is used to analyze time series data characteristics after real-time calculations are performed.Case studies demonstrate that RMT is independent from fault locations and fault types.In particular,faulty and non-faulty collector lines can be accurately and efficiently identified compared with traditional protection schemes.

Impact of Different AC Voltage Control Modes of Wind-farm-side MMC on Stability of MMC-HVDC with Offshore Wind Farms

Wind-farm-side modular multilevel converters(WFMMCs) used in modular multilevel converter based highvoltage direct current(MMC-HVDC) transmission systems must be able to control the AC grid voltage in offshore wind farms. Different AC voltage control strategies can significantly affect the dynamic characteristics of WFMMCs. However, existing studies have not provided a general methodology of controller parameter design, and few comparative studies have been conducted on control performance under varying operating conditions as well as the effects of different AC voltage control modes(AVCMs) on the stability of MMC-HVDCs with offshore wind farms. This paper provides a controller parameter design method for AVCMs, which is tested in various operating scenarios. Sequence impedance models of offshore wind farms and WFMMCs under different AVCMs are then developed. The effects of AVCMs on the small-signal stability of the interconnected system are then analyzed and compared using the impedance-based method. Finally, case studies are conducted on a practical MMC-HVDC system with offshore wind farms to verify the theoretical analysis.

Resilient Power Systems Operation with Offshore Wind Farms and Cloud Data Centers

To enhance the resilience of power systems with offshore wind farms(OWFs),a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers(CDCs)responding to uncertain spatial and temporal impacts induced by hurricanes.The total life simulation(TLS)is adopted to project the local weather conditions at transmission lines and OWFs,before,during,and after the hurricane.The static power curve of wind turbines(WTs)is used to capture the output of OWFs,and the fragility analysis of transmission-line components is used to formulate the time-varying failure rates of transmission lines.A novel distributionally robust ambiguity set is constructed with a discrete support set,where the impacts of hurricanes are depicted by these supports.To minimize load sheddings and dropping workloads,the spatial and temporal demand response capabilities of CDCs according to task migration and delay tolerance are incorporated into resilient management.The flexibilities of CDC’s power consumption are integrated into a two-stage distributionally robust optimization problem with conditional value at risk(CVaR).Based on Lagrange duality,this problem is reformulated into its deterministic counterpart and solved by a novel decomposition method with hybrid cuts,admitting fewer iterations and a faster convergence rate.The effectiveness of the proposed resilient management strategy is verified through case studies conducted on the modified IEEERTS 24 system,which includes 4 data centers and 5 offshore wind farms.