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As theincrease of wind power penetration, the fluctuations of wind power results in serious power system frequency turbulences. This article proposes a low-pass virtual filter (VF) for wind energy conversion systems (WECSs) to smoothen output power. First, a linearized model is established for a WECS. Then, a low-pass VF is derived for the active power control loop in WECS to modulate the kinetic energy stored in rotating mass for output smoothing. The principle is to modify the traditional wind power controller to emulate a physical energy storage system controlled as a low-pass filter to smooth the wind power output. The proposed low-pass VF does not need the physical deployment of energy storage system but still can filter the high-frequency fluctuations in the output wind power. Furthermore, in order to ensure operation stability of the wind turbine (WT), a stability-constrained coefficient is determined according to the proposed stability criteria to ensure the stability of WTs. Simulation and experiment results verify the effectiveness of the proposed VF in WECS for output wind power fluctuation reduction and the stability-constrained coefficient for stability ensuring. [ABSTRACT FROM AUTHOR]

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]

This article analyzes the power transfer limit (Pmax) of wind power plants (WPPs) under the weak grid condition. It is pointed out that the impact of different grid parameters and grid configurations on Pmax cannot be fully reflected by the short-circuit ratio (SCR), but can be readily captured by voltage sensitivity (∂Q/∂V). Hence, ∂Q/∂V turns out to be a more appropriate metric for the assessment of Pmax compared with the SCR. Based on this insight, the voltage control of the WPP is suggested to be implemented at the bus with the highest ∂Q/∂V to maximize the power transfer capability. Moreover, a dynamic voltage control is further added at the turbine level to improve the disturbance rejection capability of the WPP as well as its dynamic robustness against grid strength variations. Finally, simulation and field test results are given to demonstrate the theoretical analysis and the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

The wind–thermal-bundled transmission system is a feasible way to transmit wind power generation; however, the stability of the system should be paid more attention under high wind power penetration. In this article, the impact of wind energy penetration on torsional vibration and electrical characteristics is investigated for wind–thermal-bundled transmitted by high-voltage direct current system. The torsional vibration responses of generator shaft with different wind–thermal-bundled ratios are analyzed by time and frequency methods. The electrical characteristics of wind–thermal-bundled transmission system are disclosed under the influence of the wind farm penetration. The analysis illustrates that the penetration of doubly fed induction generation makes the torsional vibration of turbo generator and wind turbine shaft present different mode characteristics, and the risks of different modes are different. The current and voltage of wind–thermal-bundled transmission system show regular evolution with the change of wind–thermal-bundled proportion. Analytical results provide the value for the design and control of the wind–thermal-bundled transmitted system, which contributes to the improvement of power system stability. [ABSTRACT FROM AUTHOR]

This paper presents a dynamic event data-based stability risk assessment method for power grids with high penetrations of inverter-based resources (IBRs). This method relies on obtaining the IBRs’ DQ admittance through dynamic event data and computing the system’s eigenvalues based on the admittance models. Two critical technologies are employed in this research, including time-domain and frequency-domain data fitting and $dq$ -frame voltage and current signal derivation. The first technology is key to obtaining the $s$ -domain expressions from the transient response data, and the $s$ -domain DQ admittance model from the frequency-domain measurements. The second technology is key to obtaining the $dq$ -frame voltage and current signals from either the three-phase instantaneous measurements or the phasor measurement unit (PMU) data. The method is illustrated using data generated from a Type-4 wind power plant modeled in PSCAD. This paper demonstrates the technical feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

One of the short-coming challenges of power systems operation and planning is the difficulty to quantify the variability of power systems Kinetic Energy (KE) to unveil online additional information for the system operators’ decisions support. KE monitoring requires innovative methods to analyse the continuous fluctuations in the KE power’s systems. In this paper, we propose the use of information theory, specifically the concept of Information Length (IL), as a way to provide useful insights into the power system KE variability and to demonstrate its utility as a starting point in decision making for power systems management. The proposed IL metric is applied to monthly collected data from the Nordic Power System during three consecutive years in order to investigate the KE evolution. Our results reveal that the proposed method provides an effective description of the seasonal statistical variability enabling the identification of the particular month and day that have the least and the most KE variability. Additionally, by applying a Long Short-Term Memory (LSTM) neural network model to estimate the value of the IL on-line, we also show the possibility of using the metric as data-driven support. [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 loss of small signal stability under parameter variation (e.g., fluctuation of loads and wind powers) can be ascribed to local bifurcations, i.e., saddle-node, Hopf, singularity-induced, and limit-induced bifurcations. Classic bifurcation calculation methods like the direct method and continuation method can only provide a bifurcation point or two-parameter bifurcation curve. Based on Galerkin method and the implicit function theorem, this paper proposes accurate polynomial approximations of bifurcation hypersurfaces in the multi-dimensional parameter space of interest. The proposed method can ensure high accuracy in this parameter space, and thus is preferable to the existing Taylor expansion-based local approximation method, given the intrinsic large-variation characteristic of wind powers. Acquired bifurcation hypersurfaces are immediately used to construct the small signal stability region of the continuous system, and then compute the stability margin for the operating point subjected to uncertainty of wind generation. Besides, the validity scope of the proposed method is analyzed, and the handling of limit-triggered equation switching as well as its computational difficulty is discussed. Computational results on the two-parameter 11-bus two-area and six-parameter IEEE 145-bus test systems validate the high accuracy and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a novel stochastic robust real-time power dispatch model considering wind uncertainty. In this dispatch model that incorporates automatic power generation control, system constraints are constructed with affinely adjustable robust optimization to enhance the system security, while the objective concerning the expected value of generation cost is optimized to improve the cost efficiency. The optimized objective is consistent with stochastic optimization, while the formulation for the objective is different. A Nataf conversion-based three-point estimate (NC-TPE) is adopted, which uses an approximating function to formulate the expected generation cost with deterministic estimate points. Compared to traditional stochastic sampling methods, the deterministic assessment method NC-TPE achieves an accurate formulation with more stable and efficient computation performance. The dispatch model is derived as a problem with nonconvex objective and bilinear constraints using the dual theory. To address the highly nonconvex problem, the objective and bilinear constraints are first converted to difference-of-convexity functions, and then a tailored difference-of-convexity optimization is employed to convexify the nonconvex functions, such that the original problem can be solved with an iterative quadratically constrained program. Numerical simulations demonstrate the economic superiority and robustness of the proposed model, as well as the effectiveness of the convexified solution. [ABSTRACT FROM AUTHOR]

As the wind energy is progressively pursued to supplement conventional power generation, the stochastic wind behavior considerably deteriorates power quality (PQ) and stability of the connected grid. This article is attributed to the comprehensive control design of the grid-integrated doubly fed induction generator (DFIG) wind energy system that aims to address encountered wind variability and PQ intricacies. Battery energy storage with bidirectional dc–dc converter control is assimilated at the dc-link of the DFIG that regulates the dc-link voltage to mitigate the wind power fluctuations in specified grid power modes. A higher order adaptive control for grid-interfaced converter accurately computes desired weights of various components to exercise accurate power balance and PQ control. Moreover, a novel Jaya particle swarm optimization algorithm is adopted for the optimal tuning of wind maximum power point tracking and the dc-link voltage PI controller parameters that significantly improves steady-state and dynamic responses of both the controllers. The rotor speed converges faster with precise reference tracking that leads to almost zero steady-state error using optimized PI controller gains. Along with the attenuated initial overshoot and fast settling time during sudden large step wind speed change, the dc-link voltage also characterizes superior response with optimal tuning during load unbalance and abnormal grid voltage conditions. The presented control strategy analyzes the capability of DFIG system under variable wind-speed changes, specified grid power modes, load changes, and other grid disturbances. The satisfactory system response is endorsed through experimental results conducted on a laboratory prototype. [ABSTRACT FROM AUTHOR]

Probabilistic power flow (PPF) is pivotal to quantifying the state uncertainties of distribution power systems. However, it is very challenging due to underlying complex correlations among renewable outputs. To address this problem, a graph attention enabled convolutional network (GAECN) is proposed to approximate PPF in this article. Specifically, the graph convolutional layer of GAECN is used to aggregate the correlations among the nodal power injections during the training process. Within this layer, a full self-adaptive graph convolutional operation is proposed to automatically capture and learn the implicit correlation for achieving significantly enhanced accuracy of PPF. This layer is then followed by the convolutional neural network to capture the uncertain generation of renewable energy to achieve the robust computation of system state variable distributions. The simulation results demonstrate the accuracy and efficiency of the proposed method in IEEE 33, PG&E 69-node, 118-node, and practical 76-node distribution systems. [ABSTRACT FROM AUTHOR]

In this article, a sliding mode control (SMC) is applied to regulate the delivered power of a symmetrical six-phase induction generator. For this, the SMC strategy associated to the field-oriented control strategy is used in order to adjust the inner current loops of a squirrel cage six-phase induction generator (SC6PIG). In this way, the control algorithm switches between positive and negative feedback according to the position of the operating point in the phase plane. This technique guarantees the robustness of the SC6PIG in case of the loss of one to three stator phases or machine converter legs. The switching line slope and the initial operating point have been set so that the system starts with a negative feedback, then it continuously switches back and forth to positive feedback in order to maintain the desired trajectory of the system. The simulation and experimental results demonstrate the effectiveness and the robustness of this technique since the delivered power of the SC6PIG presents the same dynamics in healthy or faulty modes with one to two phase losses. [ABSTRACT FROM AUTHOR]

With the large-scale wind power integration into the power system, the inertia and damping characteristics of the system have been weakened, which is not conducive to fulfill the grid-friendly operation of wind power. Aiming at this, an adaptive control scheme combining virtual inertia control (VIC) and supplementary damping controller (SDC) is proposed in this paper. Firstly, the mathematical model of wind grid-connected power system with VIC is established. Secondly, the polytopic linear parameter varying (LPV) system is built to describe the uncertainty of system operating points, and the gap metric-based nonlinear evaluation method is used for polytope vertex configuration. Next, Youla-Kucera parametrization are extended to polytopic LPV system to design an adaptive damping control, in which VIC and SDC are coordinated to provide damping and virtual inertia simultaneously. Finally, the proposed adaptive control scheme is compared with several existing control techniques to validate its effectiveness and advantages in suppressing system oscillation in the modified IEEE 39-bus system integrated with 2 wind turbines. [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]

Globally,wind power plants (WPPs) installations are dramatically increasing, leading to a large-scale integration into the power grids. Huge endeavors are devoted to achieving an efficient operation of WPPs. This paper offers a novel chaotic-billiards optimizer (C-BO) algorithm to properly design the fuzzy logic control (FLC) strategy for stability enhancement of grid-integrated WPPs. The C-BO algorithm has distinct features such as simple construction, low numbers of parameters required to design, high convergence speed, and low computational burden. The permanent-magnet synchronous generator (PMSG)-based WPP is interlinked into the electric power grid through power converters. A cascaded FLC approach, which is optimally fine-tuned by the C-BO, is offered as the control methodology for these converters. The C-BO algorithm fine-tunes the gain factors of multiple FLCs at a rapid convergence speed. A simulation-based optimization approach is applied, in which the integrated square error criterion is chosen as an objective function. For the sake of preciseness, the PMSG-based WPP is connected to the IEEE 39-bus New England test system. The effectiveness of the optimal FLC using the C-BO algorithm is compared with that achieved using the water cycle algorithm-based optimal FLC, the genetic algorithm-based optimal FLC, and the marine predator algorithm-based optimal proportional-integral controller, taking into account severe grid disturbances. Moreover, real wind speed measured data captured from Zaafarana Station in Egypt are extensively performed in the system studies. The validity of the offered control approach is widely verified by the simulation analyses using the MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

This paper presents a wind turbine (WT) control strategy to deliver frequency response (FR) that is similar to conventional synchronous generators, i.e., to deliver accurate and efficient FR. This is achieved by the coordination of WT’s rotor speed control (RSC) and pitch angle control (PAC), wherein the RSC is the summation of the proposed deloading power point tracking curves and FR signal; the PAC is kept as adjusting its control law according to the WT rotor speed. Through the above coordination, the strategy pre-reserves a portion of wind power and releasing it during underfrequency events. Compared with existing methods, the strategy has two significant advantages: 1) it does not need the switching of WT controls according to the real-time wind speed (WS), nor the identification of the boundaries among high, medium and low WSs according to the required reserved power, ultimately reducing the complexity of applying the strategy to practice; 2) its active power response during FR period is independent of the deviated rotor speed and is equal to the FR signal, ultimately enabling the WT to provide accurate and efficient FR. The simulations focusing on the grid frequency side demonstrated the advantages of the strategy over existing methods. [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]

Nowadays, with the rapid development of hydrogen powered vehicles, the demand for hydrogen refueling stations (HRSs) in the transportation field is growing. The renewable energy, e.g., wind energy, is used to produce and store hydrogen on site for HRSs, which may be a relatively cheap and clean solution. Considering the wind farm (WF) and HRSs belong to different entities, a new cooperative operation model of the WF-HRSs combined system is proposed. Specifically, the robust optimization methods are implemented to characterize the uncertainties of wind power and market electricity price, respectively, to alleviate risk. To ensure the fairness of profit allocation, the bargaining power is measured by various contribution levels of each stakeholder based on the Nash–Harsanyi bargaining game theory. Furthermore, the model is transformed into two sequential subproblems: energy trading problem (SP1) and the payment bargaining problem (SP2). Accordingly, a solving technique adopting column and constraint generation algorithm is provided to solve the SP1. In addition, for the sake of privacy protection, a distributed approach based on data-centric mode is developed to solve SP2. Finally, the numerical results can validate the effectiveness and scalability for the proposed scheme and algorithms. [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]

This article presents an investigation and evaluation of an integrated flux-modulated machine for wind power generation. The integrated flux-modulated machine has two rotors which function as two contrarotating rotors connected to two sets of turbine blades. Hence, compared to conventional wind generators, more wind energy could be captured by this wind power generation system. Moreover, the integrated machine consists of two sets of stator windings. By regulating the currents in these windings, dual maximum power point tracking control strategy could be achieved. As a result, the wind power conversion efficiency is further improved. Moreover, this wind power generation system exhibits the advantage of high torque/power density due to the enhanced magnetic-gearing effect involved in the integrated flux-modulated machine. Hence, this machine is more suitable for direct-drive wind power generation, where the reliability is improved without the maintenance issues related to mechanical gearboxes. The topology and operating principle of the investigated machine are demonstrated in detail. Decoupled design of the two sets of windings is investigated, and a general rule to achieve decoupled windings by appropriate slot-pole combination selection is illustrated. The advantages of the investigated machine are confirmed in comparison to a benchmark machine. Finally, the investigated flux-modulated machine is prototyped. The validity of the operating principle and the simulation results are verified by experimental results. [ABSTRACT FROM AUTHOR]

DC collection and transmission is one of the main developing directions of the large-scale offshore wind power system. This article proposes a multifunctional dc collector (MDC) to construct a low-cost, high reliability, and high flexibility all-dc offshore wind power system. By introducing the MDC to achieve energy collection and cascade boost, not only the system cost, size, and intermediate links of power conversion are reduced but also the coupling among wind turbines (WTs) is greatly weakened. Accordingly, the maximum power point tracking operation can be achieved independently for each WT unit. Furthermore, a constant voltage ratio control with first harmonic elimination iterative algorithm is proposed for dc collector to link the HVdc bus voltage and discretized dc voltage for triggering the energy consumption operation and suppressing the inductor current ripple, and the detailed control parameter design is provided. Meanwhile, the various operating modes are considered for MDC, including practical engineering configuration, fault isolation, dynamic cut-in/out, and energy consumption operation, which provides a practical solution for the construction of a long-distance and large-capacity offshore system. Finally, the comprehensive experimental results are given to illustrate the effectiveness of MDC. [ABSTRACT FROM AUTHOR]

A power decoupling control for wind power converter based on series-connected modular multilevel converter (SCMMC) and open-winding permanent magnetic synchronous generator (OW-PMSG) is proposed in this article. The power converter based on SCMMC and OW-PMSG achieves medium voltage direct conversion and transmission and has higher dc-bus voltage compared with conventional MMC, which makes it a promising solution for copper consumption reduction of cable, low power transmission loss, and the elimination of the step-up converter. The proposed power decoupling control realizes independent power control of each phase in the wind power converter by decoupling the negative-sequence and zero-sequence current and guarantees the phase dc-link voltages balance of the SCMMC and the robustness to restrain the imbalance power disturbance. Instantaneous three phase dc-link voltages balance of the SCMMC is achieved especially when the imbalance of phase dc-link voltages occurs. The feasibility of the wind power converter based on SCMMC and OW-PMSG and the proposed power decoupling control is verified through simulations and a scaled-down laboratory prototype. [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 an efficient tool for uncertainty quantification of renewable energy forecasting, prediction intervals (PIs) provide essential prognosis to power system operator. Merely improving the statistical quality of PIs with respect to calibration and sharpness cannot always contribute to the operational value for specific decision-making issue. In this paper, the cost-oriented prediction intervals are firstly proposed to achieve the joint improvement of forecasting quality and decision performance. In order to bridge the gap between forecasting and decision, a novel cost-oriented machine learning (COML) framework is established, which unifies nonparametric renewable power PI construction and decision-making. Formulated as a bilevel programming model, the COML minimizes the operational costs of decision-making process by adaptively adjusting the quantile proportion pair of PIs resulting from extreme learning machine based quantile regression. The hierarchical optimization model of the COML is equivalently simplified as a single level nonlinear programming problem. Then an enhanced branch-and-contract algorithm with innovative bounds contraction strategy is devised to efficiently capture the optimum of the single level problem with bilinear nonconvexity. Numerical experiments based on actual wind farm data simulate the online forecasting and decision process for wind power offering. Comprehensive comparisons verify the substantial superiority of the proposed COML methodology in terms of forecasting quality, operational value, as well as computational efficiency for practical application. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy, accurate and efficient probabilistic optimal power flow (POPF) calculation becomes more and more important to provide decision support for secure and economic operation of power systems. This paper develops a novel nonparametric probabilistic optimal power flow (N-POPF) model describing the probabilistic information by quantiles, which avoids any parametric probability distribution assumptions of random variables. A novel critical region integral method (CRIM) which combines the multiparametric programming theory and discrete integral is proposed to efficiently solve the N-POPF problem. In the CRIM, the critical region partitioning algorithm is firstly introduced into the POPF model to directly establish the mapping relationship from wind power to optimal solutions of the POPF problem. Besides, a discrete integral method is developed in the CRIM to achieve the probability convolution calculation based on quantiles. Comprehensive numerical experiments verify the superior performance of the proposed CRIM in estimation accuracy and computational efficiency, and demonstrate that N-POPF model significantly improves the accuracy of uncertainty analysis. In general, the proposed N-POPF model and CRIM form a new framework of POPF problem for power system analysis and operation. [ABSTRACT FROM AUTHOR]

Power electronic devices interfaced doubly fed induction generators (DFIGs) cause a reduction in the power system inertia and further the power system becomes vulnerable to severe disturbances. DFIGs provide fast frequency response (FFR) strategies to the power system by increasing the output power. Nevertheless, these strategies produce a large frequency second drop or a slow rotor speed restoration. This article suggests a FFR strategy of a DFIG based on variable power point tracking control to boost the frequency support capability with grid-friendly rotor speed recovery. Furthermore, the benefit of the proposed strategy when participating in FFR is calculated. The test results illustrate that the proposed FFR strategy enhances the performance of the frequency nadir, size of SFD, and benefits of auxiliary FFR service. Hence, the proposed strategy provides a promising solution of ancillary service for FFR from a wind turbine generator to power systems. [ABSTRACT FROM AUTHOR]

In this article it is proposed that permanent magnet Vernier generators be used for its new and unknown application in a small-scale uncontrolled passive wind generator system. Various aspects, such as the machine selection, conventional versus split-tooth topology, power matching, torque quality, and the overall feasibility of the proposal are investigated by evaluating optimized generator designs. It is found that the conventional permanent magnet Vernier generator with a magnetic gearing ratio of eight is the superior generator choice for this application. The performance of the optimum permanent magnet Vernier generator is validated through test results of a manufactured prototype. Other designs in the article are confirmed by comparing 2-D and 3-D finite element results. [ABSTRACT FROM AUTHOR]

This article presents a model predictive control (MPC) based multitime scale co-optimized dispatch for integrated electricity and natural gas system (IEGS) considering the bidirectional interactions and renewable uncertainties. In the proposed model, optimal dispatch is extended into three substages optimization problems of day-ahead, intraday, and real-time to coordinate the economy and accuracy of operations. The different optimization strategy is designed in each dispatching stage according to the operating characteristics of multienergy coupled units and high-penetration intermittent wind power. In the day-ahead stage, the unit commitment is tackled to arrange the start-stop plan of slow-response units, maintained in intraday and real-time stages to ensure full-term optimal economic operation. In the intraday stage, MPC-based rolling optimization is implemented to obtain the unit output scheme with the lowest operating cost target. Furthermore, the output scheme is rolling adjusted in the real-time stage based on the ultrashort-term forecast value, and a closed-loop feedback mechanism is introduced to achieve accurate power balance. In each stage, stochastic decision-making is executed based on the stochastic scenario method, efficiently capturing the uncertainty in IEGS. Besides, the proposed nonlinear model is transformed into a mixed-integer second-order cone programming problem using McCormick relaxation, which can be efficiently solved by commercial solvers. Simulation results on IEEE39-Gas20 and IEEE118-GAS40 test systems demonstrate the superiority of the proposed method in operational economy and wind power utilization, and also verify the effectiveness of the method to accurately track random fluctuations without obvious computational burden. [ABSTRACT FROM AUTHOR]

This article presents a robust adaptive position observer (RAPO) for implementing encoder-less speed control for permanent magnet synchronous generator (PMSG). The PMSG is driven by a wind turbine. The basic structure of sliding mode observer (SMO) includes a discontinuous signum function and low pass filter, which introduces not only chattering but also delay in the estimated position. To deal with the issue of classical SMO, RAPO consisting of sigmoid function based continuous super twisting SMO (CSTSMO) followed by a multilayered fourth order generalized integrator (MFGI) is used for this purpose. The CSTSMO is robust and with continuous switching function, it provides results with less chattering. The MFGI filters out the lower order dominating harmonics and ensues the fundamental signals, which helps in calculating accurate position and speed of PMSG. This technique is implemented on a wind battery energy storage based microgrid, which is operable in off-grid as well as in grid interfaced mode. This microgrid is suitable for rural areas, which suffers from the grid unavailability. Seamless transition between the operating modes is included for avoiding transients in the system during de-synchronization or resynchronization of utility grid. Furthermore, the system is proficient to mitigate some of the power quality issues. The system model is built in MATLAB/Simulink software and simulated results are validated through hardware results. [ABSTRACT FROM AUTHOR]

Wind energy systems are expected to supply the majority of future generation from renewables due to the maturity of technology and the availability of energy resources. In this paper, in order to improve the ability of tracking a desired power reference at high wind speed region, a pitch control strategy based on error-based active disturbance rejection control (ADRC) approach is proposed for variable speed wind turbine system, providing a novel practically appealing control structure. The stability analysis of the proposed pitch controller based on singular perturbation theory is provided. Next, an improved coyote optimization algorithm (COA) fused with L $\rm {\acute{e}}$ vy flight and Sinusoidal map is proposed to address the controller parameters tuning issue. Then, the effectiveness of the proposed solution is verified on a 1.5 MW FAST simulator taking into account both multi-step and IEC turbulence wind conditions. Finally, an analysis in frequency domain of the pitch control system with the proposed control strategy is presented. [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]

Energy storage systems (ESSs) are being utilized to improve wind farms’ (WF) frequency support capability due to their high reliability, fast response and the dual role of energy users and suppliers. Nevertheless, the problem of how much capacity should each ESS possesses in order to better serve the WFs has never been investigated. With this perspective, this paper proposes an optimal ESS allocation (OEA) scheme for doubly fed induction generator (DFIG) based WFs to mitigate the impact of wake effect in frequency support. Firstly, the synchronous stability of wind turbines under frequency dips is analyzed with the concept of frequency support margin (FSM), and the detrimental impact of the wake effect is also investigated. Subsequently, the role of ESSs to improve wind turbines’ synchronous stability is demonstrated. To make the OEA scheme practical, the wind turbines in a WF are segmented into different clusters based on the received wind speed. Afterwards, the OEA problem is formulated, where the objective is to optimize the coherency of the wind turbine clusters’ FSM level. The simulation results show that ESS can provide secondary frequency support under major grid frequency drops, and the proposed OEA scheme can reduce the risk of loss of synchronous stability. [ABSTRACT FROM AUTHOR]

The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States, proposing, assessing, justifying, and illustrating a major infrastructure change involving two of the world's largest power grids. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.5, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions. [ABSTRACT FROM AUTHOR]

This paper proposes a new deep learning (DL) based model-free robust method for bulk system on-line load restoration with high penetration of wind power. Inspired by the iterative calculation of the two-stage robust load restoration model, the deep neural network (DNN) and deep convolutional neural network (CNN) are respectively designed to find the worst-case system condition of a load pickup decision and evaluate the corresponding security. In order to find the optimal result within a limited number of checks, a load pickup checklist generation (LPCG) algorithm is developed to ensure the optimality. Then, the fast robust load restoration strategy acquisition is achieved based on the designed one-line strategy generation (OSG) algorithm. The proposed method finds the optimal result in a model-free way, holds the robustness to handle uncertainties, and provides real-time computation. It can completely replace conventional robust optimization and supports on-line robust load restoration which better satisfies the changeable restoration process. The effectiveness of the proposed method is validated using the IEEE 30-bus system and the IEEE 118-bus system, showing high computational efficiency and considerable accuracy. [ABSTRACT FROM AUTHOR]

Power system planning is essential for ensuring development of a safe and stable power system. Articles on power system planning have been published in recent decades. In this paper, bibliometric analysis is applied to power system planning to identify its basic characteristics, and to summarize the research hotspots and trends. A total of 4562 publications were obtained from the Web of Science during 1971–2020. The 4562 publications cover 8136 keywords, 1526 journals, 107 countries/territories, and 2519 institutions. IEEE Transactions on Power Systems is the key journal in power system planning; USA, China, and England are the countries that dominate publication production. Research hotspots and trends were analyzed using author-keyword co-occurrence analysis and keyword burst detection. Four clusters were identified and topics from Cluster I (central nodes as power system stability and transient stability) and Cluster IV (central nodes as power system simulation and economics) are important for power system planning research. However, their relative popularities have declined over the past two decades. This indicates that Cluster II (central nodes as renewable energy, wind power, and energy storage) and Cluster III (central nodes as distributed generation and smart grids) will be the focus of future research. [ABSTRACT FROM AUTHOR]

With Denmark dedicated to maintaining its leading position in the integration of massive shares of wind energy, the construction of new offshore energy islands has been recently approved by the Danish government. These new islands will be zero-inertia systems, meaning that no synchronous generation will be installed in the island and that power imbalances will be shared only among converters. To this end, this paper proposes a methodology to calculate and update the frequency droops gains of the offshore converters in compliance with the N-1 security criterion in case of converter outage. The frequency droop gains are calculated solving an optimization problem which takes into consideration the power limitations of the converters as well as the stability of the system. As a consequence, the proposed controller ensures safe operation of off-shore systems in the event of any power imbalance and allows for greater loadability at pre-fault state, as confirmed by the simulation results. [ABSTRACT FROM AUTHOR]

An inevitable consequence of the power system transition towards nearly 100% inverter-based resources is the loss of synchronous generators with their associated inertia, frequency, and voltage control mechanisms. Battery energy storage with different converter technologies, due to their fast-ramping capabilities, are expected to address these challenges and replicate functionalities that so far have been provided by conventional generators. This article presents an in-depth dynamic analysis for the impact of grid forming and grid following battery energy storage locations on the frequency metrics. Performance comparisons that account for the interactions between storage technologies and the decrease of regional inertia are also investigated via dynamic simulations for the projected 90% inverter-based generations in Ireland in 2030. The analysis is conducted using a high-fidelity model of the 39 bus system, which was modified in DIgSILENT, to best replicate a real frequency event that occurred in the Irish power system. Finally, the empirical findings provide a new understanding of the optimal placement of grid-scale fast storage technologies to maintain power system security at high renewables. [ABSTRACT FROM AUTHOR]

In this article, two different strategies to enhance power system stability exploiting synthetic inertia are presented and compared to assess the possibility of increasing the penetration of converter-based generation in power systems, keeping a suitable stability margin. Synthetic inertia is the emulation, carried out by converted-based generation, of the inertial response provided by rotating generators during frequency events. Two approaches are hence described, focusing on wind power. In the first approach, the primary power source is connected to the grid by a grid-following converter, and it exploits the energy content of the direct current link, suitably sized (or, with the same concept, of a suitable energy buffer available). The second approach uses a grid-forming converter model, whose features resemble more a traditional synchronous machine. The article aims at assessing the contribution to frequency stability that can be provided by converter-based generation. The simulation results demonstrate that converter-based generation can efficiently guarantee frequency stability, thus proving that future power systems will be able to manage ever-increasing renewable energy source converter-based generation. [ABSTRACT FROM AUTHOR]

This article focuses on the implementation of peer-to-peer (P2P) energy trading and planning of a grid-connected multi-microgrid system based on an advanced optimization approach. The proposed architecture is comprised of three microgrids (MGs) with combinations of distributed energy resources (DERs), including wind turbines, photovoltaic panels, and storage batteries, to meet the load requirement. A game theory technique, Nash equilibrium, is used to structure the proposed model for multiobjective optimization, where the main objectives are used to determine the correct sizing of DERs and optimum payoff values. Due to the variability of DERs, to maintain lower energy costs, the reliability index (IR) and levelized cost of energy are the benchmarks considered for optimization. The proposed model is analyzed, and rigorous comparison is carried out for both peer-to-grid and P2P energy trading schemes, considering the Australian profiles for wind speed, solar irradiation, and residential load. The simulation model is built in MATLAB software, and the particle swarm optimization algorithm is exploited for the optimization. The results illustrate that P2P energy trading reduces the payoff value of the multiobjective function (MOF) to 36%. The robustness of MOF is validated and analyzed with different combinations of constant coefficients K1 and K2. In the end, the most economical and suitable models with DERs are proposed for each MG, and the results are verified with sensitivity analysis. [ABSTRACT FROM AUTHOR]

This study addresses the problem of the estimation of state when heterogeneous multiagent systems are affected by homologous unknown inputs (UIs). Homologous UIs refer to identical UIs affecting different agents. An improved semidistributed filter based on previous research is proposed. The improved filter uses neighbors’ information for UI estimation but not state estimation. A necessary and sufficient condition for the proposed filter to achieve minimum-variance unbiased estimation is presented and proven. Moreover, the asymptotic stability of the filter is analyzed. A sufficient condition of the asymptotic stability is presented and proven. The theoretical and numerical analyses indicate that the proposed filter has less communication pressure, fewer calculation requirements, and better estimation performance compared with the existing solutions. Note to Practitioners—In the industry, homologous unknown inputs (UIs) exist in many different systems. For example, the same ambient temperature affects the performance of every battery in a battery pack. Similarly, the same wind power can affect different aircrafts flying in the same region. Temperature and wind power can be considered the homologous UIs of a multiagent system. Estimation of homologous UIs is important because of the latter’s massive impact on the system. In this study, data transmission delay and packet loss are ignored. Hence, the study is limited to low-rate systems. Moreover, nonlinear filters must be studied further in future work. [ABSTRACT FROM AUTHOR]

Virtual power plant (VPP) provides a flexible solution to distributed energy resources integration by aggregating renewable generation units, conventional power plants, energy storages, and flexible demands. This paper proposes a novel stochastic adaptive robust optimization (SARO) model for determining the optimal self-scheduling plan for VPP’s participation in the day-ahead energy-reserve market. We consider exogenous uncertainties (or called decision-independent uncertainties, DIUs) associated with market clearing prices and available wind generation, as well as endogenous uncertainties (or called decision-dependent uncertainties, DDUs) pertaining to real-time reserve deployment requests. A tractable solution methodology based on modified Benders dual decomposition is developed to effectively solve the proposed SARO model with both DIUs and DDUs. Case studies are conducted to verify the efficiency and applicability of the proposed approach. Comparative results show that the proposed method can mitigate the conservatism of robust strategy by capturing a satisfactory trade-off between profitability and real-time operation feasibility. [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]

This manuscript presents a novel control architecture for the E-STATCOM (STATCOM integrated with Energy Storage System (ESS)) that is common for both the Stand-Alone (SA) as well as the Grid-Connected (GC) modes of operation of a microgrid operating under unbalanced conditions. The proposed control architecture fulfils the aim of regulating the E-STATCOM in such a manner so as to smoothen the power fluctuations of a nearby renewable energy source (solar, wind, etc) and also to maintain the voltage and frequency at the Point of Common Coupling (PCC) within the normal range of operation. Hence, the resultant real power injected by the renewable energy source along with the E-STATCOM is constant in magnitude, irrespective of whether the microgrid is in the GC or the SA mode of operation. Dynamically varying limits are introduced to provide inherent VSC over-current protection. In order to illustrate the performance of these control architectures, a model of the IEEE 34 node power distribution network that is being supplied by a solar Photo-Voltaic (PV) Distributed Generation (DG) unit, a wind DG unit and two identical E-STATCOMs (for compensating the power fluctuations from the PV and wind DG units) has been considered for study in PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

Transient stability of a power system can be significantly affected by wind power generators due to their stochastic power output and complex dynamic characteristics. This paper proposes a robust optimization approach for coordinating generation dispatch and emergency load shedding against transient instability under uncertain wind power output. The problem is modelled as a two-stage robust optimization (TSRO) model considering transient stability constraints, where the first-stage is to optimize the generation dispatch (preventive control) before a contingency and the second-stage decision is the emergency load shedding (emergency control) after the contingency occurrence under the worst case of wind power variation. To solve this TSRO problem, this paper also proposes a solution algorithm which integrates transient stability assessment and transient stability constraint construction in a column and constraint generation framework. The proposed method is validated on the New-England 39-bus system and the Nordic32 system, which shows high computational efficiency and stability robustness against uncertain wind power. [ABSTRACT FROM AUTHOR]

A joint raw moments-based analytical method (JRMAM) is first proposed herein to deal with probabilistic power flow (PPF) of hybrid AC/VSC-MTDC (Alternate Current/Voltage Source Control-Multiple Terminal Direct Current) power systems with integration of the offshore wind farms. JRMAM is able to overcome the challenges of some existing combined methods in estimating the high order moments of target outputs, and the dramatic time consumption of Monte Carlo simulation method (MCSM) in performing the PPF analysis particularly due to the complication of its deterministic power flow (DPF) model. The proposed JRMAM has a further superiority on efficiency, even compared to the joint cumulants-based analytical method (JCAM). As a preliminary step, discrete Fourier transformation matrix (DFTM) method is applied to calculate the joint raw moments of random inputs which are required by conducting JRMAM, and the probability density function (PDF) of outputs can be estimated by means of the Gram-Charlier expansions (GCE) based on the results obtained from JRMAM. Two modified IEEE test cases connected with DC subsystems through the VSC devices are adopted to verify the effectiveness and the scalability of JRMAM, where the result of MCSM is treated as a reference, and the properties of the hybrid AC/VSC-MTDC power system with these master-slave controlled VSCs are investigated for a further acceleration on PPF analysis. [ABSTRACT FROM AUTHOR]

The power and natural-gas industries have narrowed the time differences between daily power market clearing and natural-gas market clearing. This facilitates the gas-power coordination in day-ahead scheduling. However, using natural-gas-fired power units to balance the variability of renewable energy production may cause fluctuations in natural-gas demand, which result in risks to the natural-gas system in actual operation. As such, gas-power coordination at all time is highly desirable. We analyze the coordinated operation of power and natural-gas systems at the scheduling stage and in actual operation. We assume that the two systems are operated independently, but with information interchange. We use a Lagrangian decomposition approach to identify an operational equilibrium involving the two systems. Numerical results on two test systems verify the value of gas-power coordination in actual operation. [ABSTRACT FROM AUTHOR]

The accuracy of short-term wind power forecasting (WPF) can be improved by effective mining of numerical weather prediction data. In this article, a novel short-term WPF approach is proposed by combining wave division (WD), improved grey wolf optimizer based on fuzzy C-means clusters (IGFCM), and Seq2Seq model with attention mechanism based on long short-term memory model (LSTMS), named the WD-IGFCM-LSTMS model. Based on the fluctuation trend, the wind speed sequences of NWP are divided into a series of waves. Six fluctuation features that reflect the shape characteristics are extracted to quantify the partitioned waves. A new strategy is proposed to improve the global searching ability of the GWO to select the initial clustering center of FCM more effectively. The Seq2Seq deep learning model based on LSTM, named LSTMS, is applied for wave-oriented forecasting. The proposed approach outperforms the traditional point-to-point forecasting and realizes continuous sequence forecasting. The simulation results demonstrate that the WD-IGFCM-LSTMS model can perform better than other benchmark forecasting models. [ABSTRACT FROM AUTHOR]

A planning of integrated electricity–hydrogen–gas system to supply hydrogen for hydrogen vehicles (HVs) with the consideration of carbon emission flow (CEF) is proposed in this article. From the perspective of energy consumption, hydrogen production will inevitably produce carbon dioxide. This article innovatively presents the CEF model to quantify the distribution of carbon emission in each energy hub by tracing the energy flow in the coupled network. After solving the CEF model, a novel tri-level planning method is utilized to coordinate the plan of electricity–hydrogen–gas integrated network to highlight the role of hydrogen in reducing carbon emission of HVs. Moreover, two major hydrogen production methods, seawater electrolysis and steam methane reforming, are considered and analyzed simultaneously to provide hydrogen for HVs. Therefore, the proposed approach will satisfy the growing requirement of carbon reduction by installing new clean energy equipment in electricity–hydrogen–gas integrated network. A coupling system of 24-node power system, 9-node hydrogen energy network, and 7-node natural gas network is utilized in the case study. Simulation results show that the proposed model plays an effective role in reducing carbon emission of the coupled system with growing number of HVs. [ABSTRACT FROM AUTHOR]