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The actively commutated current source converter (CSC) does not need large energy storage capacitors and can realize the black start of wind farms, which provides a practicable scheme for the lightweight offshore wind power DC transmission system. However, resulted from utilizing pulse width modulation, the existing CSC has the disadvantages of high DC harmonics and high switching loss. To solve this problem, an offshore wind power transmission system based on the current source converter with fundamental frequency modulation employed (FFM-CSC) is investigated. Firstly, the topology and mathematical model are analyzed. Then, a steady-state control strategy coordinated by the offshore CSC and the onshore CSC is put forward, and the power operating range is researched. A black start control strategy for wind farms is also proposed. Finally, the offshore wind power transmission system is tested by simulation in PSCAD/EMTDC. The results demonstrate that the FFM-CSC-based offshore wind power transmission system can smoothly realize the black start, stably control the frequency and amplitude of AC voltage, adapt to output changes of wind turbines, and realize the fault ride-through. [ABSTRACT FROM AUTHOR]

In a wind farm, the interactions between turbines caused by wakes can significantly reduce the power output of the wind farm. Cooperative control among the turbines has the potential to improve the power output. However, existing centralized power optimization methods are computationally expensive and does not scale well for large wind farms, limiting their practical use in real-time control for time-varying wind conditions and turbine configuration (with adding or maintaining of turbines). To address this problem, this paper proposes a fully distributed power optimization method for wind farms using alternating direction method of multipliers (ADMM). The proposed method allows the wind farm power output to be optimized in fully distributed manner with turbine-to-turbine message passing over a mesh network, guarantees the implemented control actions satisfy the control constraints of all turbines, and provably converges to a stationary point of the wind farm power optimization problem. Simulation results demonstrate that the proposed method can significantly reduce the computation time with hardly sacrificing the power gain compared with centralized method and thus is computationally efficient for real-time power optimization of large wind farms. [ABSTRACT FROM AUTHOR]

The integration of large-scale renewables into the multienergy system has brought a series of problems and challenges to the optimal dispatch of system, especially how to effectively realize the dispatch and accommodation of wind power. In this article, a dynamic economic dispatch (DED) model of wind/combined heat and power (CHP) hybrid energy system considering uncertainty of multiple wind farms and different dispatch time scales is proposed, which aims to minimize expected total energy generation cost based on the typical scenarios of upper bound of wind farm output. The spatial dependence of hourly output of multiwind farm is modeled by copula-based model and improved scenario reduction technique, and the different adjustment time scales of heating system and power system are modeled as well to achieve more reasonable and accurate system dispatching. In addition, an improved adaptive cuckoo search algorithm (ACSA) is proposed for the solution of the DED model of wind/CHP hybrid energy system with highly nonlinear constraints, and a shared parallel computing platform is employed to realize the acceleration of the ACSA. Finally, the corresponding numerical simulation and comparative analysis are performed on two test systems to verify the validity of the proposed model and method. [ABSTRACT FROM AUTHOR]

One of the major challenges in evacuating power from the offshore renewable energy source is reducing the number of equipment involved in the energy conversion process. In the strategy presented in this article, the output of a permanent magnet synchronous generator coupled with a wind turbine is converted to a low voltage DC by an AC–DC converter and then directly connected to a Medium Voltage Direct Current (MVDC) corridor using a new fault tolerant soft switched high gain DC–DC converter. During the fault in the MVDC corridor, the DC–DC converter is blocked forcing the fault current to zero, the faulty MVDC corridor is bypassed using the simple DC disconnectors, and then the DC–DC converter is connected to the healthy MVDC corridor. In this article, the efficacy of the proposed scheme is discussed in detail and substantiated through extensive simulation studies done in PSCAD/EMTDC. The theoretical and simulation analysis is also verified by experimental results. [ABSTRACT FROM AUTHOR]

In this paper, an approximate aggregated impedance model (AAIM) of a grid-connected wind farm with multiple wind turbine generators (WTGs) for the small-signal stability study is derived. The derivation is conducted under the condition that the WTGs inside the wind farm are of the same type and from the same manufacturer. The AAIM derived can be seen as the impedance model (IM) of a grid-connected aggregated WTG. The IM of the aggregated WTG is the weighted average of the IMs of the individual WTGs in the wind farm and hence is simple to be built. The reactance of the line connecting the aggregated WTG to the external AC grid is the maximum eigenvalue of the network reactance matrix of the grid-connected wind farm. In addition, the derivation justifies the representation of a wind farm by an aggregated WTG in the IM-based small-signal stability analysis. Finally, two example grid-connected wind farms are used to evaluate and demonstrate the effectiveness of the AAIM proposed in the small-signal stability analysis. It is also shown that the computational burden of the stability analysis of a large-scale wind farm could be effectively reduced when the AAIM is used. [ABSTRACT FROM AUTHOR]

This article proposes a comprehensive coordinated suppression strategy for DC overvoltage to achieve the receiving-end fault ride-through of DC grid connected large-scale wind power. For the monopolar DC overvoltage, by reasonably switching the control mode of bipolar modular multilevel converter (MMC), the power transfer capability of the healthy pole MMC can be improved while maintaining DC voltage stability, and the precise load-shedding control of wind farm and its coordination scheme with dissipative resistors are designed, which can effectively reduce the input capacity of dissipative resistors and the risk of wind turbines being cut off. For the bipolar DC overvoltage, the load-shedding control strategy and its parameter selection principles are proposed, which can make wind farm and capacitors in each MMC absorb excess power together, to reduce the change rate and amplitude of DC voltage. Then its cooperation scheme with the dissipative resistors is designed to achieve fault ride-through in the full power range of wind farm. Finally, based on the simulation model of four- terminal DC grid, the effectiveness of the proposed coordinated control methods is verified. [ABSTRACT FROM AUTHOR]

This letter proposes a novel transient stability criterion for power systems with multi-wind farms, which is deduced from power flow and inertia distribution. The variations of acceleration and deceleration power with and without wind integration, instead of the acceleration and deceleration areas themselves, are calculated, in which the power angle swing direction, the transient stability control of wind turbines, the position of wind farms access, and the unbalanced output of synchronous clusters are also considered. The simulation results show the effectiveness of the proposed criterion to distinguish transient stability. [ABSTRACT FROM AUTHOR]

As the wind power penetration increases, wind farms are required by the grid codes to provide frequency regulation services. This article develops a fully data-driven model predictive control (DMPC) scheme for the wind farm to provide temporal frequency support. The main technical challenge is the complexity and the nonlinearity of wind turbine dynamics that make the DMPC intractable. Based on Koopman operator (KO) theory, a specialized dynamic mode decomposition (SDMD) algorithm is proposed, which fits a global linear dynamic model of the wind turbines. The performance of learning dynamics is powered through integrating the physical knowledge of the wind turbine into the specialized observables of KO. To stabilize the rotor speeds in frequency regulation, the active power contribution is optimally dispatched in a moving horizon fashion. Simulation results show that the DMPC can efficiently learn and predict the wind turbine dynamics. During the frequency response process, the proposed method can effectively track the frequency support order specified by the utility grid operator while significantly stabilizing the rotor speeds. [ABSTRACT FROM AUTHOR]

To integrate large-scale islanded onshore wind power with different sizes, this paper proposes an integration system based on the cascaded hybrid HVDC transmission system, which consists of LCC and several MMCs in series connection at the DC side of the rectifier. A large-scale wind farm is connected with one LCC and one MMC while several small-scale wind farms are connected with MMCs directly. Owing to the hierarchical integration arrangement, the operating flexibility can be improved with reduced capacity and the number of step-up interfacing transformers. A resilient DC voltage control is proposed for the integration system to adaptively redistribute power among the converters during wind power fluctuations. Firstly, the topology and operating characteristics of the wind power integration system are introduced. Then, a resilient DC voltage control is proposed to ensure stable operation during wind power curtailments. Finally, a simulation model of the hybrid cascaded HVDC transmission system is built in PSCAD/EMTDC to verify the effectiveness. The research results show that the system provides a new option for long-distance transmission of large-scale islanded wind power. [ABSTRACT FROM AUTHOR]

Chance constrained economic dispatch (CCED) is widely used to handle uncertainties in power systems with high-proportion renewable energy sources (RESs). However, in such system, the upper and lower limits of reserve or transmission line constraints may be violated simultaneously, which makes single-side CCED (SS-CCED) inapplicable. This letter develops a two-side CCED (TS-CCED) model, in which the Gaussian mixture model (GMM) is used to characterize the correlated non-Gaussian distribution of RESs. We propose a hyperbolic tangent function based approximation method to approach GMM and make the TS-CCED tractable. Numerical studies show the proposed method is more applicable than SS-CCED with high efficiency. [ABSTRACT FROM AUTHOR]

Offshore wind farms (OWF) are being rapidly integrated to the power systems, which can be primarily attributed to saturation of the mainland onshore area, and high wind speed in offshore sites. However, to maintain stable grid operation, OWFs are required to comply with Low Voltage Ride Through (LVRT) capability. OWF during LVRT period should not only stay grid connected, but also support the grid during the disturbance. In this paper, a new communication-independent LVRT control scheme for HVDC connected OWF has been proposed. Under the proposed strategy, OWFs not only successfully ride through a fault induced voltage dip, but also comply with active power recovery ramp rate during the fault recovery period. Besides complying with LVRT requirement and ramp rate limit, the proposed strategy improves voltage dip induced frequency (VDIF) issue by increasing active power injection from the OWF during LVRT period. The proposed LVRT strategy also exploits the stored energy in HVDC link capacitors in order to reduce the impact of VDIF issue. The proposed and the conventional LVRT strategies for HVDC connected OWF have been implemented and evaluated on IEEE 39 bus benchmark system. [ABSTRACT FROM AUTHOR]

In a deregulated environment, the renewable energy producers will face the challenge of how to increase their revenues under uncertainties of power generation and time-varying electricity price. In traditional power network scheduling, prediction and optimization are two independent processes, which easily leads to information loss and modeling error. To deal with the uncertainty and realize an end-to-end controller, this article proposes an energy storage system control model (ESSCM) in the scene of the combined wind-solar storage system. The proposed ESSCM using deep reinforcement learning (DRL) algorithm is trained by interacting with the massive environment of a power grid without requiring the assumption on the uncertainties. It learns from scratch to realize the coordination operation of with wind power and photovoltaic power in a combined system, further maximize the benefits of the combined system in the electricity market. One state-of-the-art DRL algorithm, namely double deep Q-network, is used to formulate the proposed ESSCM. Numerical results illustrate that the proposed approach can effectively accommodate the uncertainty and bring high revenues to the combined system. [ABSTRACT FROM AUTHOR]

In this article, power flow transfer entropy (PFTE) is proposed as a criterion to evaluate the power flow transfer characteristics of the multiterminal HVdc (MTdc) wind power integration grid. This proposed criterion can detect and locate the ac three-phase to ground (TPG) faults in the MTdc grid by its sensitivity to power flow change to avoid communication. The transient energy dissipation control strategy is then designed according to the variety of PFTE, which reflects the power flow reversal characteristic of the MTdc grid during ac faults. Experimental results show that the system based on the proposed communication-free method can ride through ac TPG faults without blocking any converter. [ABSTRACT FROM AUTHOR]

The integration of wind power into the power system causes difficulties in system operations due to its associated uncertainties. Spatial correlation is one aspect of uncertainties and derives from geographically dispersed distribution. However, spatial correlation is ignored by most studies, which decreases the modeling accuracy. In this paper, a high-dimensional t-copula model is first proposed to preserve spatial correlation characteristics. Through this model, adequate simulated data are sampled, which forms scenario generation. K-means clustering method is further used to reduce the number of scenarios generated. A case of 4 wind farms selected from AEMO dataset has been implemented to illustrate the establishment of the spatial correlation model. Then, a modified IEEE 24-bus test system is utilized to conduct optimal power flow (OPF) with and without the consideration of spatial dependence. The comparison results show that with spatial correlation accessing, the generation cost would have a certain increase. This implies, if the spatial correlation is ignored, the overall cost of OPF is underestimated. Furthermore, with the penetration level of wind power increasing, a lager cost gap is obtained, thus proving there exist benefits with the inclusion of spatial correlation during system modeling. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy, such as wind power, has brought great challenges to the power system operation due to its uncertainty. Flexibility, which measures the ability of power system to deal with the uncertainties, is critical for power system to adapt to the new era of renewable energy. The rising electrical demand of the water distribution system (WDS) creates opportunities for power system to leverage the flexibility provided by WDS. This paper investigates the water-energy relationship between these two systems and makes full use of the water pumps and tanks in the WDS to enhance the power system flexibility. Current WDS designs did not consider well the role WDS plays in the power system. This hinders the WDS from being fully used by power system to provide flexibility. An optimization model is proposed to determine the optimal tank size of WDS, which may provide the maximum available flexibility of power system. The effect of tank size on water quality is also investigated to ensure that the supplied water quality is not compromised. Moreover, a Benders-based heuristic algorithm is proposed to find the optimization solution more efficiently and to protect the data of each energy system. Results of case study highlight the merit of the proposed optimization design and the advantage of using WDS to provide flexibility for power system. [ABSTRACT FROM AUTHOR]

Case-by-case study in the literature has found from the results of numerical computation and simulation that a grid-connected virtual synchronous generator (VSG) can maintain the stability under the condition of extremely weak grid connection. This paper presents the theoretical proof to the finding and thus, generally concludes that the grid-connected VSG is immune to the instability risk under the condition of weak grid connection. In addition, the paper extends the theoretical proof to the case of a grid-connected PMSG wind farm with multiple VSGs. An example grid-connected PMSG wind farm with twenty VSGs is presented to demonstrate and evaluate the theoretical analysis and conclusion made in the paper. [ABSTRACT FROM AUTHOR]

The rotational inertia and primary frequency response capabilities of power systems are declining as synchronous generators (SGs) are replaced by inverter-based variable renewable energy (VRE) resources. Therefore, when a high VRE proportion is present, it becomes essential to include frequency security constraints in power system planning. Under this circumstance, the decline in SGs would deteriorate the system frequency response performance; thus, inverter-based resources are supposed to provide frequency response support. This paper presents a frequency-constrained stochastic planning method for high VRE share systems. Frequency response support from wind farms is considered in the planning process for the first time, and the unique characteristics of wind power support are addressed. Specifically, the uncertainty of and variations in wind power support capabilities are modeled from the field-measured data, and the optimal combination of various support schemes can be determined by introducing binary variables with novel linear constraints into the planning process. Moreover, the nonlinear frequency constraints are transformed and embedded in the planning model by the proposed computationally efficient adaptive piecewise linearization method. The planning is formulated as a stochastic optimization model to consider the VRE power uncertainty. Finally, case studies on the IEEE 30-bus system validate the proposed method, with results indicating time savings of 22%. Further, compared with the case that only SGs provide frequency support, the results based on the East China system demonstrate that considering wind power support can improve the VRE share from 49.5% to 79.7%. [ABSTRACT FROM AUTHOR]

Sub/Super-synchronous oscillations have occurred in wind farms consisting of doubly-fed induction generators (DFIGs) or permanent magnet synchronous generators (PMSGs). This paper investigates the impact of synchronous condenser (SC) on sub/super-synchronous oscillations in wind farms with different types of generator and compares it with STATCOM. Impedance model is adopted in this paper to explain the mechanism of oscillations in wind farms and its mitigation using SC. Compared to STATCOM, SC is more effective in oscillation mitigations of the two types of wind farms. Eigenvalue analysis and time domain simulations in PSCAD/EMTDC are used to check the influence on sub/super-synchronous oscillations from different parameters of SC, such as its capacity, leakage reactance and inertia constant. The results indicate that SC would improve the system stability while a larger capacity will induce a greater improvement. A smaller leakage reactance of SC also benefits the mitigation of oscillations while its inertia constant can hardly influence system stability. [ABSTRACT FROM AUTHOR]

Previous robust transmission expansion planning (RTEP) studies have rarely considered the important question of how large the uncertainty set should be, and hence, how the uncertainty budget can be determined objectively. This study addresses this issue by proposing a novel adaptive optimization method that optimizes the value of the uncertainty budget to minimize the size of the uncertainty set while considering the underlying risk for wind power generation (WPG) fluctuations residing outside of the proposed uncertainty set. As such, the proposed method ensures a good tradeoff between the robustness and costs of RTEP solutions. In addition, the proposed method optimizes investment strategies under forecasted WPG scenarios, while providing a security guarantee under extreme WPG scenarios. The variable-limit integral terms introduced by the proposed method are addressed in the solution process by applying the piecewise linearization approximation method combined with the quadratic Newton-Gregory interpolating polynomial technique, which allows the solution process to be cast as a mixed integer linear programming problem. The good performance and effectiveness of the proposed adaptive uncertainty set optimization method are verified by numerical results. [ABSTRACT FROM AUTHOR]

In this letter, the voltage sensitivity-based coherent reactive power control is proposed to perform the online voltage security enhancement for insecure buses in the multi-area wind power generation systems. The proposed approach is realized in the two-level optimization problem, containing a master problem and two subproblems. The master problem is responsible for the equal reactive power adjustments in multiple regional clustering wind farms regarding to the voltage security enhancement while the subproblems proceed the further improvement of the voltage security based on the analysed result of the master problem. Case studies on IEEE 57-bus test system are presented to validate the cost-effectiveness of the proposed method. Also, the time-domain simulation is conducted to illustrate the validity of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical analysis of how wind generation impacts the slow coherency property of power systems. Slow coherency arises from time-scale separation in the dynamics of synchronous generators, where generator states inside a coherent area synchronize over a fast time-scale due to stronger coupling, while the areas themselves synchronize over a slower time-scale due to weaker coupling. This time-scale separation is reflected in the form of a spectral separation in the weighted Laplacian matrix describing the swing dynamics of the generators. However, when wind farms with doubly-fed induction generators (DFIG) are integrated into the system then this Laplacian matrix changes based on both the level of wind penetration and the location of the wind farms. The modified Laplacian changes the effective slow eigenspace of the generators. Depending on the penetration level, this change may result in changing the identities of the coherent areas. We develop a theoretical framework to quantify this modification, and propose an equivalent Laplacian matrix to compute the modified coherent areas. Results are validated using the IEEE 68-bus test system with one and multiple wind farms. The model-based slow coherency results are compared with measurement-based principal component analysis to substantiate our derivations. [ABSTRACT FROM AUTHOR]

Different from power prediction for a single wind farm, the regional wind power prediction is to predict the total power of multiple wind farms located in the specific region. The regional wind power prediction involves more data that implicate abundant information on spatiotemporal correlations and nonlinearity. So that addressing the massive data and extracting the representative features became the crucial issues to construct an effective regional wind power prediction model. This article proposes a spatiotemporal quantile regression (QR) algorithm to perform the short-term nonparametric probabilistic prediction of regional wind power, incorporating the advantages of the hybrid neural network (HNN) and QR. In the approach, the high-dimensional input data are reorganized into a feature graph that is ready for feature extraction by the HNN. Therefore, the advantages of HNN can be utilized to extract the representative features and construct nonlinear regression models. Meanwhile, by following the QR rules, the model obtains quantiles and perform probabilistic prediction. By properly addressing the explanatory variable selection issue, the approach provides a specific solution for regional wind power probabilistic prediction with the massive input data. The test results in a region with ten wind farms demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

A novel concurrent control scheme of optimal re/active power regulation in a wind farm is proposed in this letter, of which the objective is to minimize the detrimental shortfall of active power during low-voltage-fault events. Distinguished from the existing works, the proposed control scheme incorporates an efficient optimization module into the wind turbine controllers. Specifically, it features the merit that the practical feasibility of tracking the resultant references can be ensured via considering multiple constraints in presence of complex wake interactions. Case studies on a permanent-magnet-synchronous-generator based wind farm built in a joint DIgSILENT-MATLAB platform are carried out to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Chance-constrained program (CCP) is a popular stochastic optimization method in power system planning, and operation problems. Conditional Value-at-Risk (CVaR) provides a convex approximation for chance constraints which are nonconvex. Although CCP assumes an exact empirical distribution, and the optimum of a stochastic programming model is thought to be sensitive in the designated probability distribution, this letter discloses that CVaR reformulation of a chance constraint is intrinsically robust. A pair of indices are proposed to quantify the maximum tolerable perturbation of the probability distribution, and can be computed from a computationally-cheap dichotomy search. An example on the coordinated capacity optimization of energy storage, and transmission line for a remote wind farm validates the main claims. The above results demonstrate that stochastic optimization methods are not necessarily vulnerable to distributional uncertainty, and justify the positive effect of the conservatism brought by the CVaR reformulation. [ABSTRACT FROM AUTHOR]

Regional wind power prediction (WPP) is conducive to achieving scientific dispatch of the power system as well as improving its reliability. Data mining based on a large number of samples is an effective way to improve the accuracy of WPP. A new regional power forecasting method in the context of data mining is proposed in the article. First, a previously described regional WPP method, single feature similarity matching (SFSM) method, is analyzed and a new multifeature similarity matching (MFSM) method is proposed. Second, the optimization and analysis processes of four key parameters in the MFSM method are proposed and the impact of each key parameter on prediction error and the applicability of the method under different regional scales is analyzed. Finally, the new method and the optimization and analysis processes are verified by wind farm clusters, composed of 52 wind farms in northeast China, and the new method is compared with the conventional method, such as additive method, statistical up-scaling method, and the SFSM method. The results show that the improved MFSM method is superior to the conventional prediction method, whereby the root mean square error (RMSE) of 0 to 2 h is reduced by 3.65% and the RMSE of 0 to 4 h is reduced by 1.56%. The new method has been proved to be an effective WPP method for wind farm clusters and has potential industrial application prospects. [ABSTRACT FROM AUTHOR]

Difficulties in identification of the fault property, for a fault on a single outgoing line of windfarm, arise due to rapid decrease in the electromagnetic energy of the transmission line after the tripping of three-phase breaker. An active solution to such problem is proposed based on low current injection from parallel connected static synchronous compensator (STATCOM). In the reclose sequence after wind turbines’ cut off, the circuit breaker near wind farm and grid-connected circuit breaker of STATCOM are reclosed first. Therefore, based on selected switching operation of power electronic devices of STATCOM converter, a short duration discharge of dc capacitance to the faulty ac line is suggested. Correlation coefficient of resulting current waveform is utilized as an identification criterion for fault presence. Finally, a three-phase adaptive auto-reclosing scheme is proposed for the single outgoing line of 110 kV wind farm. The effectiveness and robustness of the proposed scheme are verified by PSCAD/EMTDC simulation. [ABSTRACT FROM AUTHOR]

Unsteady motion of the atmosphere incurs nonlinear and spatiotemporally coupled uncertainties in the wind power prediction (WPP) of multiple wind farms. This brings both opportunities and challenges to wind power probabilistic forecasting (WPPF) of a wind farm cluster or region, particularly when wind power is highly penetrated within the power system. This paper proposes an Improved Deep Mixture Density Network (IDMDN) for short-term WPPF of multiple wind farms and the entire region. In this respect, a deep multi-to-multi (m2m) mapping Neural Network model, which adopts the beta kernel as the mixture component to avoid the density leakage problem, is established to produce probabilistic forecasts in an end-to-end manner. A novel modified activation function and several general training procedures are then introduced to overcome the unstable behavior and NaN (Not a Number) loss issues of the beta kernel function. Verification of IDMDN is based on an open-source dataset collected from seven wind farms, and comparison results show that the proposed model improves the WPPF performance at both wind farm and regional levels. Furthermore, a laconic and accurate probabilistic expression of predicted power at each time step is produced by the proposed model. [ABSTRACT FROM AUTHOR]

The construction of the uncertainty set is a key aspect of robust unit commitment (RUC) for the power systems with wind power integrated. The existing uncertainty sets based on the convex hull of historical data are limited to the specific shape of the historical data set or with high computational burden. In this letter, we propose the partition-combine method to build the minimal uncertainty set with the irregularly-distributed historical data. The partition of the box set is used to reduce the size of the uncertainty so that the set can properly adapt the data provided and is no longer limited to a specific shape. The combination of non-empty subsets is used to formulate the model of uncertainty set instead of the extreme points. The scale of uncertainty variables is reduced with quick identification of inner subsets which contain no extreme points. The simulation results validated the enhanced performances of the proposed method from both the conservativeness and computational burden perspectives. [ABSTRACT FROM AUTHOR]

To capture the stochastic characteristics of renewable energy generation output, chance-constrained unit commitment (CCUC) model is widely used. Conventionally, analytical reformulation for CCUC is usually based on simplified probability assumption or neglecting some operational constraints, otherwise scenario-based methods are used to approximate probability with heavy computational burden. In this paper, Gaussian mixture model (GMM) is employed to characterize the correlation between wind farms and probability distribution of their forecast errors. In our model, chance constraints including reserve sufficiency and branch power flow bounds are ensured to be satisfied with predetermined probability. To solve this CCUC problem, we propose a Newton method based procedure to acquire the quantiles and transform chance constraints into deterministic constraints. Therefore, the CCUC model is efficiently solved as a mixed-integer quadratic programming problem. Numerical tests are performed on several systems to illustrate efficiency and scalability of the proposed method. [ABSTRACT FROM AUTHOR]

The offshore ac side impedance model of the modular multilevel converter (MMC) based high voltage direct current (HVdc) system is essential for analyzing the interaction stability between MMC-HVdc and the offshore wind power plants. This paper develops the offshore ac side impedance model of an MMC-HVdc system for wind power integration taking the effects of offshore station, dc cable and onshore station into consideration. The dc impedance model of the onshore station is first derived which includes the effects of dual closed loop dc bus voltage control and circulating current control. Then, the dc impedance of the onshore station and dc cable impedance are used to derive the ac side impedance of the offshore station under open loop control. In addition, the influence of the dual closed loop based ac bus voltage and frequency (VF) control on the offshore ac impedance is analytically derived. As a result, the proposed model can be used to reveal the coupling between offshore offshore ac system and dc system as well as to investigate the influence of the dc system and VF controller in the offshore ac impedance of the MMC-HVdc system. Furthermore, the proposed model overcomes the deficiencies in harmonic resonance analysis of MMC-HVdc based offshore wind power integration system. The results of the simulation in PSCAD/EMTDC validate the proposed models and analyses. [ABSTRACT FROM AUTHOR]

This paper presents a derivation of the small-signal stability limit of a grid-connected wind farm with M permanent magnet synchronous generators (PMSGs) as determined by the dynamics of phased locked loops (PLLs). The stability limit reveals the mechanism whereby the PLLs can destabilize the wind farm in the case of a weak grid connection. Computation of the derived stability limit is simple and obviates the need to establish a parametric model of the wind farm. The stability limit can approximately indicate the potential instability risk collectively posed by the PLLs in the wind farm. Case studies are presented to evaluate the analytical conclusions obtained and the derived small-signal stability limit. Application of the stability limit during the planning and operating stages of a grid-connected wind farm is also demonstrated. Various factors that can affect the stability of the wind farm, and that must be considered during planning and operation, are examined and useful conclusions are obtained. These factors include the length of the transmission line connecting the wind farm to the AC grid, the topology of the wind farm, the wind speed, and its distribution over the wind farm, as well as the parameters of the PLLs. [ABSTRACT FROM AUTHOR]

Series-connected-based offshore wind farms can eliminate bulky central offshore converters, transformers, and platforms. In a series-connected-based offshore wind farm, the dc voltage of the converters should be changed within a large range to control the dc-link voltage (grid side) and maximize wind power acquisition (generator side). In this paper, the full-bridge-based modular multilevel converter (FB-MMC) is proposed as grid- and generator-side converters. The dc voltage of the FB-MMC can vary in a large range because the full-bridge submodule (FBSM) is used. The control method of the FB-MMC in a series-connected-based offshore wind farm is different from those of traditional ones. The dc current control and capacitor voltage balance control are proposed in this paper, with which the FB-MMC can operate normally in the series-connected offshore wind farm. Moreover, the capacitor ripple voltage in the generator-side FB-MMC is studied. The result shows that the capacitor in the FBSM can be designed in rated power and frequency, and it will be feasible when the power and frequency decrease. Simulation and experiment results verify the feasibility of the proposed configuration and the corresponding control algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for the forward estimation of thermal risk in offshore wind farm cables under scenarios where the farm is overplanted for economic purposes. A dynamic thermal rating assessment of the cable is proposed to estimate the thermal effects of probable load current scenarios considering actual temperatures. Calculated future temperatures are used to estimate the probability of the cable being overheated. Due to the ability of the method to estimate forward thermal risk, unnecessary power curtailment can be reduced while avoiding thermal damage to the cable. Simulated results of online thermal risk estimation and curtailment show additional power delivery of 7.26%, 9.16%, and 9.67% per year for a 6%, 9.9%, and 13.7% wind farm overplanting, respectively. The additional power is calculated compared to the annual power delivered (Wh/year) with the use of the traditional continuous rating limits for the case studied. [ABSTRACT FROM AUTHOR]

In recent years, the integration of wind power generation facilities, and especially offshore wind power generation facilities, into power grids has increased rapidly. Therefore, the grid codes concerning wind power integration have become a major factor in ensuring power system reliability. This work compares grid codes about wind power integration around the world. The grid codes of Denmark, Ireland, the U.K., Germany, Spain, China, the U.S., Canada, and other countries are considered. The most important of these grid codes concern reactive power, frequency regulation, fault ride through, and power quality. Several grid codes also address communication, ramp rate, and offshore wind power plants. This work provides information on the future of grid code requirements for offshore wind power integration, which helps the system operators ensure the safe operation of a power system with a high penetration of wind power generation. [ABSTRACT FROM AUTHOR]

Large-scale wind power cluster with distributed wind farms has generated the active power dispatch and control problems in the power system. In this paper, a novel hierarchical model predictive control (HMPC) strategy based on dynamic active power dispatch is proposed to improve wind power schedule and increase wind power accommodation. The strategy consists of four layers with refined time scales, including intra-day dispatch, real-time dispatch, cluster optimization, and wind farm modulation layer. A dynamic grouping strategy is specifically developed to allocate the schedule for wind farms in cluster optimization layer. In order to maximize wind power output, downward spinning reserve and transmission pathway utilization are developed in wind farm modulation layer. Meanwhile, a stratification analysis approach for ultra-short-term wind power forecasting error is presented as feedback correction to increase forecasting accuracy. The proposed strategy is evaluated by a case study in the IEEE Network with wind power cluster integration. Results show that wind power accommodation has been enhanced by use of the proposed HMPC strategy, compared with the conventional dispatch and allocation methods. [ABSTRACT FROM AUTHOR]

With regard to wind farms connected to the main system via dedicated overhead transmission lines, the available wind power absorbed by the system relies on not only the power generation capacity but also the power transmission threshold. Thus, this study centers on the close relationship between environmental conditions and power transfer limits that involve the thermal limit and steady-state stability limit. Simultaneous equations representing both overhead conductors’ heat balance and power transmission operation are established. In addition, formulations of the maximum transmission power for the steady-state stability limit are derived and then expressed as functions of environmental factors and the line length. The presented approach allows one to analyze the threshold considering not only the thermal limit but also the steady-state stability limit, which could be remarkably different under certain environmental and transmission distance conditions. Then, a scheme to identify the primary limitation and obtain the corresponding threshold value is proposed. Moreover, a simple treatment of wind speed correlation is deployed because of the close distance between a wind farm and its tie-line. Case studies demonstrate that, for a certain wind speed level, the process of transmission rather than generation could become the key factor determining the threshold value. [ABSTRACT FROM AUTHOR]

The injection of a significant amount of wind power tends to increase the rate of change of the grid frequency. Therefore, it is a trend for wind farm to participate in the grid frequency regulation. However, during the frequency control process, individual wind generators in a wind farm may prone to instability due to possible over-deceleration. To address this issue, this paper presents a new nonlinear model predictive control (NMPC) scheme for the wind farm frequency response. By incorporating the nonlinear dynamics of each individual wind generator into the NMPC design, it achieves both objectives of dynamically optimal frequency response and wind generator stability. This scheme has a three-layer structure. Based on the linear model predictive control and moving horizon estimation, a top-layer controller computes the overall wind farm power reference to support the frequency control. This overall power reference is fed to the middle-layer NMPC, and is further distributed among multiple wind generators. The dispatched power references are then sent to the bottom-layer wind generators local controllers for execution. Simulation results verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates an offshore wind farm based on modular dual-active-bridge (DAB) isolated DC-DC converter. The DAB converter is adopted due to its compact design and the galvanic isolation between its input and output terminals. The synchronous generator in each wind turbine is operated individually with the generator-side rectifier to maximize the power production. The output terminals of multiple DAB converters are connected in series so that the high voltage for DC transmission is achieved and the expensive offshore step-up substation is eliminated. The DC transmission voltage is excluded from the primary side of the DAB transformer by its galvanic isolation. To balance the power sharing among the DAB converters, their input terminals are connected in parallel. In addition, the droop voltage balancing control is presented for the series offshore wind farm. As a result, the input and output voltages of each DAB converter are governed by the same droop characteristic, and the DAB converters’ output voltages are kept balanced. The time-domain simulation results show that the DC voltages of each DAB converter and the high voltage direct current (HVDC) transmission system remain stable during the temporal and spatial variations in the wind power generation. [ABSTRACT FROM AUTHOR]

In this paper, we review the emerging challenges and research opportunities for voltage control in smart grids. For transmission grids, the voltage control for accommodating wind and solar power, fault-induced delayed voltage recovery, and measurement-based Thévenin equivalent for voltage stability analysis are reviewed. For distribution grids, the impact of high penetration of distributed energy resources is analyzed, typical control strategies are reviewed, and the challenges for local inverter Volt–Var control is discussed. In addition, the motivation, state-of-the-art, and future directions of the coordination of transmission system operators (TSO) and distribution system operators (DSO) are also thoroughly discussed. [ABSTRACT FROM AUTHOR]

Experimental results and performance analyses of wind farms providing secondary frequency regulation is lacking. This is despite the increasing share of variable generators in electrical energy production. As variable generators displace traditional generators that provide ancillary services, there is a growing need for alternate providers of these ancillary services. Wind generators are technologically capable of providing ancillary services, such as frequency regulation. This paper presents experimental results of a secondary frequency regulation test carried out on a 10 MW wind farm with Type-V wind turbines. This is a 5 h test of the wind farm's ability to follow an external, historical automatic generation control signal. 1 MW of power is offered on the regulation market with up-regulation provided via a fixed curtailment value. The performance of the farm is evaluated using the performance score method developed by the Pennsylvania–New Jersey–Maryland (PJM) system operator. Performance scores are used to perform an economic analysis using 2017 hourly PJM price data. This results in an estimated additional income of $\$$ 7200 from participating in the regulation market versus providing energy alone. A sensitivity analysis reveals that profitability is more influenced by the turbine's performance scores than regulation and energy prices. This paper also examines some practical aspects of providing secondary regulation, such as pitch activity, power error, and operating power ranges. [ABSTRACT FROM AUTHOR]

Modular multilevel cascade converters (MMCCs) are becoming attractive solutions as high-voltage Static Synchronous Compensators (STATCOMs) for power plants in renewable energy generation, in order to satisfy the strict grid codes under both normal and grid fault conditions. This paper investigates the performances of four potentially used configurations of the MMCC family for the STATCOM in large-scale offshore wind power plants, with special focus on asymmetrical low-voltage ride through capability under grid faults. The specifications and the sizing of components of each type of practical 80-MVar/33-kV-scaled MMCC-STATCOM are carefully designed and compared. The total cost and volume are compared based on the total power semiconductor chip area and the total energy stored in the passive components. Asymmetrical reactive power delivering operation of the MMCC family considering the dc-link capacitor voltage-balancing method is solved mathematically in order to quantitatively understand the performance limitations and behaviors. The electrothermal stress of the power modules used in each type of the MMCC for a practical 80-MVar/33-kV-scaled STATCOM is analyzed. The asymmetrical reactive power capability of the MMCC solutions is compared under different scenarios of grid faults, while considering the device temperature limits as well as voltage saturation. It is found that the MMCC configuration with double-star bridge cells becomes the most attractive circuit configuration for the STATCOM application based on the obtained results. [ABSTRACT FROM AUTHOR]

As the typical clean and renewable energy, wind energy has witnessed a continuous annual increase in the last few decades. Due to the random and intermittent characteristics, the wind producers in the electric market meet serious financial losses caused by the deviation between the actual power output and forecasting result. It is difficult to increase the accuracy of forecasting in a short time. How to improve the financial income has become a major task to wind producers and academia. Being the backbone network of the offshore wind farms (OWFs), voltage source converter-based multi-terminal HVdc system (VSC-MTdc) has been regarded as one of the effective solutions to transport wind power. In this paper, an optimal distribution method is proposed for VSC-MTdc system integrating OWFs to reduce the financial loss due to wind power output deviation. The proposed method could be divided into two optimizing functions. The first optimizing function of the proposed method is to analyze the onshore external system according to the historical system operation data and adjust the droop coefficient with the analytic hierarchy process. The second optimizing function of the proposed method is to do further adjusting with the regulating price. With the case study, the proposed optimal distribution method has proved that it can bring more benefit to wind producers. [ABSTRACT FROM AUTHOR]

This paper presents a day-ahead coordinated scheduling method of hydro and wind power generation systems (HWPGSs) with consideration of uncertainties. In this method, we first formulate the coordinated scheduling model with two-part price and power flow constraints, which manifests the fixed and variable economic benefits as well as the secure operation of HWPGS, respectively. Then, the interval analysis is used to study the effect of uncertain wind power, water inflow, and electricity load on the coordinated scheduling model. Finally, we use a real test system in a western area of China to conduct simulation studies, which verify the effectiveness of the interval analysis and the effect of price mechanism on the day-ahead coordinated scheduling of HWPGS. [ABSTRACT FROM AUTHOR]

Security-constrained economic dispatch is executed based on consecutive dispatch intervals in real time. The short-term variations of wind power can cause the system to enter an unsecured operating region inside a dispatch interval, which is referred to as the intra-interval security (IIS) problem in this paper. IIS may not be addressed by existing dispatch methods as the traditional dispatch is to ensure the security at the interval end. This can lead to IIS risks in an interval when a high-wind-penetrated system encounters large intra-interval variations (IIVs) of wind power. To address this issue, an IIS preventive dispatch approach is proposed in this study. This approach models the wind power IIVs and develops a preventive dispatch to ensure the IIS over the interval in terms of line overloads while taking into account the tradeoff between security and economics. The proposed approach is implemented in a linear-programming model whose global optimum can be efficiently obtained by adding Benders-like cuts. Case study on the IEEE 118-bus system proves that a high level of nonlinear IIVs can cause the IIS issue (inside of an interval) even with accurate wind forecasts at both interval ends. The simulations show that some lines can have severe overloads inside the dispatch interval in spite of having flows below their capacity limits at both interval ends, and demonstrate that the proposed approach can mitigate such intra-interval overloads even under the worst case IIV scenario. [ABSTRACT FROM AUTHOR]

The large scale integration of wind energy generation adds a new burden to frequency regulation because of the volatility of wind power. Incorporating wind turbines (WTs) into automatic generation control (AGC) is a new approach for maintaining a satisfactory frequency regulation performance, which requires the active power control (APC) of WTs. Conventionally, the APC of WTs is achieved by pitch angle control (PAC) or rotor speed control (RSC), which respectively show a slow response and a narrow regulating range. To improve the regulation performance of variable speed WTs, a coordinated APC strategy that includes the simultaneous activation of PAC and RSC and takes full advantage of rotor kinetic energy to absorb or release extra mechanical energy is proposed in this paper. The simulations focusing on both the WT and power system levels have shown the effectiveness of proposed control strategy. [ABSTRACT FROM AUTHOR]

With the wind power energy largely interconnected with power grid, it is necessary to develop a robust dynamic equivalent model of the wind farm for the system stability analysis and control. In this paper, a detailed wind farm model with doubly fed induction generators is established according to Western Electricity Coordinating Council benchmark test system. Then, the parameters identification process based on aggregation technique consisting of a hybrid algorithm combined improved-particle swarm optimization with improved-genetic algorithm is proposed for dynamic equivalent model development by using the measurement data from phasor measurement unit at the point of interconnection. Additionally, the robustness of the developed equivalent model is analyzed. The simulation results of the benchmark test system and IEEE-9 bus system demonstrate the effectiveness and robustness of the proposed equivalent modeling and identification methodology. [ABSTRACT FROM AUTHOR]

This paper focuses on economic dispatch (ED) in power systems with intermittent wind power, which is a very critical issue in future power systems. A stochastic ED problem is formed based on the recently proposed versatile probability distribution of wind power. The problem is then analyzed and proved to be strictly convex. Although such convex optimization is tractable in many cases, it may take a long time to solve due to its large scale. This paper proposes a dual decomposition method to decompose the large problem. Then, two methods are employed to solve the decomposed problem, namely, the subgradient method and a faster method, limited-memory BFGS with box constraints (L-BFGS-B, a quasi-Newton method). Case studies were conducted to verify the efficiency of the dual decomposition and L-BFGS-B method for solving the stochastic ED problem. [ABSTRACT FROM AUTHOR]

Using off-site predictors to capture spatio-temporal correlations among geographically distributed wind farms is seen as one solution to improve the forecast accuracy of wind power generation. However, in practice, wind farm operators are usually unwilling to share their private data with each other because of competitive reasons and security considerations. To address this issue, this paper presents how wind power probabilistic forecasting using off-site information could be achieved in a privacy-preserving and distributed fashion. Wind power probabilistic forecasts are created by means of multiple quantile regression. The original large-scale forecasting problem is first decomposed into a large number of small-scale subproblems. The subproblem can be computed locally on each farm. Then, the closed-form solution to the subproblem is derived exactly for achieving high computational efficiency. The proposed approach offers a flexible framework for using off-site information, but without having to exchange commercially sensitive data among all participants. It relies on the alternating direction method of multipliers algorithm to achieve the cooperation among all participants and finally converges to the optimal solution. Case studies with real-world data validate improvements in the forecast accuracy when considering spatio-temporal correlations. Distributed approaches also show higher computational efficiency than traditional centralized approaches. [ABSTRACT FROM AUTHOR]

In this study, a novel approach for look-ahead dispatch (LAD) considering large-scale wind power integration is proposed. An index designated the conditional value-at-risk of wind power (CVaR-WP) is introduced to evaluate the risk of wind power accommodation. A flexible LAD model is developed to balance the operational costs and the CVaR-WP based on robust optimization (RO). According to the proposed model, the base points, participation factors, and flexible capacity of automatic generation control units are co-optimized. In addition, a reasonable admissible region of wind power on each node can be obtained correspondingly. An efficient algorithm based on the big-M method and the decomposition method is presented to solve the resulting bilinear programing model. The proposed approach combines the advantages of RO and stochastic programing, which can avoid the overconservativeness of RO while maintaining its high computing efficiency. Test results illustrate the effectiveness and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

This two-paper series introduces a new multistage robust approach for solving the transmission expansion planning (TEP) problem under the uncertainty of loads and wind power productions. The proposed multistage robust TEP model is formulated using mixed binary and linear decision rules, which aims at finding a solution withstanding any realization of the uncertain parameters belonging to a set-based uncertainty model. The robustness of the optimal expansion plan can be adjusted by the budget of uncertainty. The first part of this two-paper series presents the extended and compact formulations for a deterministic TEP problem. Then, the compact formulation of the TEP problem under the uncertainty of loads and wind power productions is introduced as a multistage robust optimization problem, which is reformulated using mixed binary and linear decision rules. The extended formulation of these decision rules, as functions of uncertain parameters, is presented in this part as well. [ABSTRACT FROM AUTHOR]