To enhance the frequency regulation capability of direct-drive permanent magnet synchronous generator (PMSG)-based wind-power generation system, the frequency regulation control strategy for wind-power system with flywheel energy storage unit (FESU) based on fuzzy proportional plus differential (PD) controller is proposed in this study. According to the mathematical model of PMSG-based wind-power generation system with FESU, the small-signal model of the whole system is deduced in detail. In addition, the eigenvalue loci of the system are investigated to obtain the appropriate ranges of FESU's PD controller parameters for ensuring the system stable operation. Meanwhile, the impact of system equivalent inertia and damping on system frequency stability is analysed. Furthermore, a fuzzy PD controller of FESU is designed to dynamically regulate the system equivalent inertia and damping, leading to improved grid frequency characteristics. Finally, simulation studies on a 2 MW PMSG-based wind-power generation system with 400 kW FESU verify the validity of the proposed control strategy, contributing to enhance the frequency stability of power grid.

To ensure security operation of power systems with high wind penetration, wind turbines (WTs) are required to participate system frequency control. The amount of WT kinetic energy used for system frequency control is discussed and minimum rotor speeds according to different WT operation states are defined to avoid large drop of mechanical power during WT frequency control. The effect of different power shapes of releasing the kinetic energy on system frequency support is investigated and two methods are proposed. The first one is aimed at reducing the rate of change of frequency (ROCOF), whereas the second one aimed to reduce both the ROCOF and frequency nadir. The proposed strategies not only make full use of the available kinetic energy but also lead to a smooth transition when the rotor re-accelerates. The performance of the proposed strategies is validated by simulations using MATLAB/Simulink. The results indicate significant improvement on system frequency control.

This study presents the impact on power system frequency control in small power systems based on different generator topologies with a large penetration (50%) of variable speed wind turbines. The impact of a proposed controller is investigated versus various wind speeds. In particular, wind speeds with an average wind speed just below rated wind speed proves to cause the worst frequency fluctuations regardless of the type of backup generation topology investigated during 50% wind-penetration ratio. For this wind-speed session and a hydro-based system, the proposed control system improves the frequency duration outside of the specified range [49.9, 50.1]Hz from 81 to 53% while reducing its delivered energy by only 6%. Furthermore, the proposed control reduces the absolute value of requested reserve by 49% from the hydro unit responsible for primary frequency control.

The inertia response control (IRC) of doubly-fed induction generators is capable of providing the power system with controlled inertia by releasing mechanical power to or absorbing electrical power from the system when the system frequency experiences sudden changes. However, it will result in deviation of the rotor speed from the optimal working point and unexpectedly reduce the captured wind power. To restore the rotor speed as quickly after an IRC action as possible, in this study, the authors derive a novel rotor speed recovery strategy based on the extended state observer (ESO) technique. They first develop two ESOs to accurately estimate the captured wind power by the wind turbine and the system unbalance power, respectively. They then synthesise the rotor speed recovery strategy based on such estimates, including the optimal recovery timing and the control modes as well as the associated switching logics. Detailed simulations carried on PSCAD/EMTDC show that the authors’ controller outperforms the traditional proportional–integral controller in the aspects of dynamical performance, the robustness to varying working conditions and the capability to prevent the system frequency from a second drop.

Multivariable disturbance accommodated observer based control (DOBC) scheme is presented to mitigate loads generated due to wind shear and tower shadow using individual blade pitch for above-rated wind speed condition of wind turbine. Wind shear and tower shadow add flickers as 1p, 3p, 6p and so on, (p is the rotor rotational frequency) for three-bladed wind turbine. Novel DOBC with individual pitch control (IPC) to mitigate the flickers is presented and linear state-space model of wind turbine with tower dynamics is developed. The proposed controller is tuned using optimal control theory to reduce fatigue of drive-train, tower and to regulate output power. The authors have tested the controller on NREL's 5 MW wind turbine, FAST (fatigue, aerodynamics, structures and turbulence) code is used for load modelling and MATLAB/Simulink is used for the simulation. A comparison of power spectral density of generator speed, drive-train torsion and tower fore-aft moment shows better mitigation to the flickers by proposed controller as compared with proportional–integral (PI) and disturbance accommodation control (DAC) with collective pitch control. Furthermore, it shows less degradation in the performance as moving away from the operating point for above-rated wind speed condition of wind turbine. It is concluded that proposed multivariable controller shows better mitigation to turbulent and cyclic aerodynamic loads, provide better regulation to output power using IPC of wind turbine and increased the lifetime of drive-train torsion and tower as compared with PI and DAC.

An integrated controller of wind turbines with both inertial response and primary frequency regulation (PFR) to provide complete dynamic frequency support for the grid with high wind power penetration is investigated. The wind turbine control governor contains two cross-coupled controllers: pitch controller and maximum power point tracking (MPPT) controller. First, as a precondition for the PFR, a de-loading pitch control scheme is proposed to reserve capacity required for frequency regulation. Then, by optimizing the MPPT scheme, the rapid virtual inertia response is achieved even under de-loading operation condition. Based on the analysis of the steady-state characteristics of wind turbines with frequency droop control, the primary frequency control strategy, which enables the adjustment of frequency droop coefficient, is further proposed through pitch angle changes. Thus, the PFR and inertial response can be both achieved by the proposed de-loading pitch controller and optimized MPPT controller. A three-machine prototype system containing two synchronous generators and a Doubly Fed Induction Generator (DFIG)-based wind turbine with 30% of wind penetration is implemented to validate the proposed integrated control strategies on providing inertial response and subsequent load sharing in the event of frequency change.

To reduce the impact of high penetration of renewable energy on the utility grid and suppress the influence of micro-grid power fluctuation on power quality, a power tracking control strategy for DC micro-grid has been studied. Furthermore, a central energy management method (CEMM) based on this control strategy has been designed. The DC micro-grid, which contains renewable energy and hybrid energy storage unit, is used to build a complete control system model according to the distributed power supply and its control system model. The power tracking control strategy has been analysed and designed based on frequency domain method. With the designed control strategy, the system can realise coordinated operation of the hybrid energy storage unit by absorbing the load power fluctuation within different frequency range. Furthermore, based on the CEMM, the system is controlled to absorb/deliver predefined amount of power from/to the utility grid under grid-connected mode. In this way, smooth switching between different modes and the stable operation of the micro-grid are realised. Finally, the function of the system is verified with an emulated DC micro-grid system.

This paper presents an effective concept for hybrid fuel cell-photovoltaic-wind-battery active power filter (FC-PV-Wind-Battery) energy scheme based on the variable structure sliding mode fuzzy logic controller (SMFLC) using the multi-objective particle swarm optimisation (MOPSO). The parameters of the fuzzy logic control membership functions and the weighting factors of the SMFLC can be tuned by MOPSO in such an approach to optimise the dynamic performance of the shunt active power filter (SAPF) and minimise the total harmonic distortion (THD) of the source current waveform and voltage waveform of the hybrid (FC-PV-Wind-Battery). A group of objective functions was chosen to validate the dynamic performance of the SAPF and the effectiveness of the MOPSO-SMFLC. These selected fitness functions are: (i) minimising the error of the inverter capacitor DC voltage, (ii) minimising the THD of the output current and voltage of DC and AC sides and (iii) minimising the controller reaching time. A computer simulation study using Simulink/Matlab and experimental laboratory prototype were carried on to asses and compare the dynamic performance of the proposed MOPSO-SMFLC controller with the conventional proportional–integral–derivative, variable structure SMFLC, the feed-forward multilayer neural network controller and the variable structure SMFLC based on the single-objective particle swarm optimisation.

This study presents an approach of the voltage regulation of DC bus for the photovoltaic energy storage by using a combination of batteries and supercapacitors (SCs). The batteries are used to meet the energy requirements for a relatively long duration, whereas the SCs are used to meet the instantaneous power demand. The energy management strategy is developed to manage the power flows between the storage devices by choosing the optimal operating mode, thereby to ensuring the continuous supply of the load by maintaining the state-of-charge (SoC) of SCs (SoC_sc) and the SoC of the batteries (SoC_bat) at acceptable levels. This energy management strategy is performed by using the fuzzy logic supervisor. The validation results prove the effectiveness of the proposed strategy.

Solar energy applications and research are becoming increasingly popular, and photovoltaics (PVs) are among the most significant solar energy applications. To simulate and optimise PV system performance, the optimal parameters of the solar cell models should be estimated exactly. In this study, improved simplified swarm optimisation (iSSO), a recently introduced soft computing method based on simplified swarm optimisation, is proposed to minimise the least square error between the extracted and the measured data for the solar cell models parameter estimation of the single- and double-diode model problems. Based on the new all-variable difference update mechanism and survival of the fittest policy, the proposed algorithm is able to find an improved approximation for estimating the parameters of single- and double-diode solar cell models. As evidence of the utility of the proposed iSSO, the authors present extensive computational results for two benchmark problems. The comparison of the computational results supports the proposed iSSO algorithm outperforms the previously developed algorithms for all of the experiments in the literature.

This study proposes a multitasking three-phase four (3P4W) wire solar photovoltaic (SPV) system using a modified lattice wave digital filter (M-LWDF)-based control technique. For effective utilisation of SPV array, an incremental conductance-based maximum power point tracking approach is used to obtain the peak power. However, M-LWDF-based control technique is used to control the grid tied 4-leg voltage source converter. The proposed control technique with reduced computational burden is an analytical tool for extracting the harmonics free fundamental component of load current and the mitigation of load neutral current. The M-LWDF-based control technique is implemented under various working modes at non-linear loads.

Low-voltage ride-thorough capability is among the challenges in the operation of medium- and large-scale grid-connected photovoltaic power plants (PVPPs). In addition, reactive power injection during voltage sags is required by power system operators in order to enhance the voltage of the point of common coupling. The performance of medium- and large-scale grid-connected PVPPs during these events is studied. An algorithm for the calculation of current references, in the dq-frame, during voltage sags is introduced, which considers the inverter current limitation, grid code requirements and the amount of extracted power from photovoltaic strings. The proposed algorithm uses the full current capacity of the inverter in injecting active or reactive powers to the grid during voltage sags, which leads in a better grid voltage enhancement. The performance of proposed control strategies is investigated on a 150-kVA PVPP connected to the 12.47-kV medium-voltage test-case system simulation model during different fault conditions. An experimental setup of the 3.3-kVA grid-connected three-level neutral-point-clamped inverter with a dc/dc converter illustrates and validates the performance of the controller in injecting required active/reactive power and supporting the network voltage.

In this study, small-signal stability of the power system integrated with ancillary-controlled large-scale doubly fed induction generator (DFIG) based wind farm (WF) is studied. A model which considers grid code requirements and ancillary controllers is presented to indicate important DFIG dynamics for the study. The ancillary control of the WF which aims to improve power system voltage/frequency stability is evaluated from the small-signal stability perspective. It is shown that the ancillary controller deteriorates power system low-frequency oscillations and/or induces new lightly damped oscillation modes especially in a weak grid. The potential risks may restrict the WF to fulfil gird code requirements and threaten small-signal stability of the power system. Meanwhile, this study reveals that wind power penetration level and WF connection impedance are two main factors which affect dynamic interactions between the WF and the power system and thus affect system small-signal stability. The principle of the influence on the small-signal stability with different grid weakness and ancillary control schemes is evaluated in this study by eigenvalue analysis and verified with time-domain simulations.

This study addresses the frequency regulation for a microgrid under islanded mode with variable renewables. Due to the structure and parameters of microgrids, the frequency of the system and the voltages on the buses are coupled. Furthermore, to smooth out the fast fluctuations of renewables, the controllability of components are quantified accurately. In this study, some critical and realistic considerations are identified and modelled, and the guidelines for battery energy storage system (BESS) sizing are thus obtained. First, the frequency and voltage regulation loops are coordinated by a non-linear model predictive control (MPC) controller, and the controllable resources are sequentially dispatched. Second, the dynamic model for evaluating the state of charge (SOC) of BESS under a fast response is introduced. Finally, general guidelines of the required energy capacity of BESS and the length of MPC control horizons are quantified by deriving the process of the responding disturbances. Ramping rates and response time delays of controllable resources are involved in the mathematical analysis. The simulation results show that the effectiveness of the proposed MPC controller and design guidelines can be generalised for microgrids in islanded mode with two kinds of controllable operating resources, which are represented by diesel generators and BESS.

The installed capacity of non-synchronous devices (NSD), including renewable energy generation and other converter-interfaced equipment is expected to increase and contribute a large proportion of total generation capacity in future power systems. Concerns have been expressed relating to operability and stability of such systems, since NSD are typically decoupled from the grid via power electronic devices and consequently reduce the ‘natural’ inertia, short-circuit levels and damping which are inherently provided by synchronous machines. This study establishes the instantaneous penetration level (IPL) limits of NSD connected to a model power system in terms of steady-state stability beyond which the system condition becomes unstable. The NSD used in this example will be a conventional dq-axis current injection (DQCI) convertor model. The study introduces a set of system ‘viability’ criteria relating to locking signal in converter phase-locked loop, frequency, rate of change of frequency and voltage magnitude, which are used to determine the IPL limits. Among many factors which can affect the IPL limits, the impact of frequency and voltage droop slopes and filter time-constants of DQCI converter is quantified. Finally, a frequency domain visualisation method referred here as ‘network frequency perturbation’ is introduced to provide additional insight into contributions of individual generators.

Power flow calculation is a basic tool for power systems operation and control. Considering static frequency regulation characteristics of power systems, dynamic power flow (DPF) gives more precise results of system operation with frequency deviation than conventional power flow. The increasing penetration of wind energy into power grid makes it necessary to take wind power into consideration in DPF calculation. The operational traits and frequency regulation characteristics of major types of wind turbines are discussed, including fixed speed wind turbines and variable speed wind turbines with integrated control strategy combining over-speed control and droop control. With the primary frequency regulation characteristics of wind turbines, a simplified DPF algorithm is proposed in this study for power systems integrating wind power generation. The IEEE 30-bus system is modified to verify the proposed method considering different levels of wind power penetration.

A coordinated fast primary frequency control scheme from offshore wind power plants (OWPPs) integrated to a three terminal high voltage DC (HVDC) system is proposed in this study. The impact of wind speed variation on the OWPP active power output and thus on the AC grid frequency and DC grid voltage is analysed. The removal of active power support from OWPP after the frequency control action may result in second frequency (and DC voltage) dips. Three different methods to mitigate these secondary effects are proposed, such as, (i) Varying the droop gains of the HVDC converter (ii) Releasing the active power support from OWPP with a ramp rate limiter and (iii) An alternative method for the wind turbine overloading considering rotor speed. The effectiveness of the proposed control scheme is demonstrated on a wind power plant integrated into a three terminal HVDC system developed in DIgSILIENT PowerFactory. The results show that the proposed coordinated frequency control method performs effectively at different wind speeds and minimises the secondary effects on frequency and DC voltage.

This study presents a control structure, based on model predictive control, applied to energy management optimisation in a sugar cane processing plant including renewable sources. The proposed energy plant is set upon a sugar cane processing industry and has to produce and maintain an amount of electric power throughout the year, defined by contract. This plant is, also, bound to produce flows of steam in different pressures, to comply to the demands of the production process of ethanol and sugar, from the sugar cane. The renewable sources in the system include photovoltaic, wind power generation and the use of biomass, from the remains of the sugar cane. The proposed control algorithm has the task of performing the management of which energy system to use (combined heat and power generation systems, boilers or others), maximise the use of renewable energy sources, maximise the gains of the boilers (that vary according to the biomass mixture used), manage the use of energy storages and supply the defined amount of energy. Simulation results show the satisfactory operation of the proposed control structure.

This study discusses the connection of wind farms (WFs) to power system through unified inter-phase power controller (UIPC) for enhanced transient stability of the power system. The power circuit of the UIPC is based on the conventional inter-phase power controller (IPC), which its phase-shifting transforms are substituted by two series converters and one shunt converter. During fault condition, the WF connected through UIPC acts as STATCOM with capability of the active and reactive power control at UIPC connecting point. Based on the UIPC model and low-voltage ride-through requirements of the new grid codes, a control system for active and reactive powers control is proposed for enhancement transient stability of power system. The proposed approach is validated in a four-machine two-area test system. Power systems computer aided design (PSCAD)/EMTDC simulation results demonstrate that the UIPC provides an effective solution for enhancement of transient stability of power system including WFs.

This study proposes a new distributed networked control (DNC) scheme and its stability analysis framework for automatic generation control in networked interconnected power systems with participation of wind turbine. It is assumed that the remote control signals are measured at locations away from the control site and exchanged among a non-ideal communication network with both time-varying delays and random packet dropouts. First, a model is proposed for large-scale DNC system consisting of subsystems, in which the states of each subsystem have their own time-varying delay and there are also delay and packet dropouts in their interconnection links. Then, a linear matrix inequality (LMI)-based method is proposed to design the distributed controller for better system performance. For this, a new Lyapunov–Krasovskii function is developed to conclude some LMI-based delay-independent theorem for designing control law. To evaluate the proposed method, a multi-area power system with participation of wind turbine is considered. Simulation results show the capability of the proposed approach to enhance the performance of networked power system in the presence of load perturbation among a non-ideal communication network with both time-varying delays and random packet dropouts.

A new long-term wind power prediction approach based on time windows is proposed to improve the accuracy and efficiency of wind power ramp prediction. An optimisation model is built to select the optimal time window size which is the key point of the wind power forecasting. First, a swinging door algorithm is applied to identify historical ramp events, and historical data is divided into several sections by assumed time window size. Then, windows are classified into ramp windows and non-ramp windows, and the non-ramp data of ramp windows is required to be minimal. The variables, parameters, and constraints of the model are investigated in the study, and a kind of genetic algorithm is utilised to achieve the optimal solution. The model presented in this study is validated by the study case of actual wind farms, and evaluation and discussion demonstrate the validity of the proposed approach.

In this study a forecasting model for wind power ramps based on strongly convective weather classification is presented. First, the dynamics and thermodynamic behaviours of strongly convective weather are characterised by the predictors in the selected region. Then the support vector domain description for ramps scenario classification is introduced to establish an initialised extremum model, and the parameter templates method is used to identify the ramps weather in strongly convective weather library. Meanwhile, the original wind speed data is modified to obtain more accurate wind speed, and a new wind power ramps definition is proposed based on the ramp character itself and its impact on the power grid. Thus the catastrophe detection method (Bernaola Galvan algorithm) used for strongly convective weather forecasting. Finally, the wind power ramps forecasting method based on the discrimination of convective weather is developed. Comparing with the existing wind power ramps forecasting algorithms, the proposed prediction method here gets into meteorologic essence of triggering great fluctuation of wind speed.

In this paper, a new methodology is developed to assess the adequacy of frequency reserves to handle power imbalances caused by wind power forecast errors. The goal of this methodology is to estimate the adequate volume and speed of activation of frequency reserves required to handle power imbalances caused due to high penetration of wind power. An algorithm is proposed and developed to estimate the power imbalances due to wind power forecast error following activation of different operating reserves. Frequency containment reserve (FCR) requirements for mitigating these power imbalances are developed through this methodology. Furthermore, the probability of reducing this FCR requirement is investigated through this methodology with activation of different volumes and speed of frequency restoration reserve. Wind power generation for 2020 and 2030 scenarios for Continental Europe network are investigated based on which recommendations are made for requirements of frequency reserves in these scenarios. It has been observed through simulations that FCR requirements reduce exponentially with increase in volume of frequency restoration reserve and remains almost unaffected by increase activation speed of frequency restoration reserve.

To solve the problem of low inertia in DC microgrid and enable the distributed units to provide adaptive inertia support for the system under disturbance, this study proposes a novel adaptive inertia control strategy for DC microgrid combined with fast predictive converter control. In this strategy, adaptive coordinated inertia control of wind power system, AC power grid and energy storage system of the microgrid is designed according to the characteristics of corresponding micro-sources. Therefore, inertial response of the DC microgrid under disturbance is improved through the regulation of controllable inertia coefficient of each converter. In addition, to avoid control hysteresis and adjustment error, a fast converter local control method based on model predictive approach is proposed to cooperate with the rapid inertia adjustment strategy. To verify the effectiveness of the proposed adaptive inertia control method based on model predictive approach, contrastive simulations are conducted using the proposed control strategy and the traditional control strategy separately based on MATLAB/Simulink. The results show that the proposed control method can effectively improve the transient response to disturbance of the system and guarantee the stability of DC bus voltage as well as the output power quality on AC side of grid-connected converter.