This study presents the design and experimental validation of feedback control along with a high-gain observer to regulate the DC-link voltage in dual-stage grid-tied photovoltaic (PV) system. In particular, the composite controller is designed to ensure accurate and fast control of the DC-link voltage in response to abrupt changes in either the delivered active power or grid voltages. The high-gain observer is employed to estimate the unknown disturbance, which is then cancelled by the feedback controller to ensure asymptotic regulation. Fast disturbance estimation is required to retain the nominal transient response specified under the feedback controller, which mandates using high-observer gain. However, high-observer gain magnifies the effect of the measurement noise, which results in poor steady-state performances. This problem is addressed here by using a non-linear gain to allow for on-line adjustment of the observer gain. Specifically, a large observer gain is used during transients to ensure fast disturbance estimation, while a reduced observer gain is employed in the steady-state regime to mitigate the effect of the measurement noise. Experimental results demonstrated the ability of the proposed controller to achieve accurate control, good transient response, fast disturbance rejection, and negligible sensitivity to the measurement noise.

In the most common hierarchical control structure for microgrids, the secondary control layer relies on communication technologies for receiving feedback data and sending control commands. The imperfections of communication such as the delays can cause oscillations during the voltage and frequency restoration which degrade the power quality. This work aims at studying this effect in the case of a typical AC microgrid in the islanded mode. For this purpose, stochastic delay models for industrial communication protocols are combined with a simulation model of the microgrid together with its control system up to the secondary level. The results illustrate how the choice of communication technology can affect the transient response. Additionally, compensation of the control performance for the effects of communication is considered. A simple method is used to improve the control performance only by retuning the controller coefficients, without altering the standard control structure. It is shown that appropriate retuning of the secondary controller can prevent from oscillations caused by the delays and improve the power quality to some extent. The presented framework can be used for designing and verifying the combination of communication and control subsystems in microgrids.

This study proposes a control scheme for high power grid-connected wind power converters, which is oriented to enhance their performance when connected to weak grids with low short circuit ratio. The proposed controller consists of an outer current reference generation loop and an inner current loop, working in stationary reference frame. In the outer loop, the current reference is calculated to comply simultaneously with the grid code requirements, the control of the DC link, and the operational safety margins of the converter during faulty conditions. On the other hand, the proposed inner current loop consists of a proportional resonant controller, a capacitor voltage feedforward and a phase shifter. Moreover, simulation results considering different weak grid conditions, as well as experimental results of a full-scale 4 MW converter test-bench are presented to validate the good performance of the proposed method.

In this study, a distributed cooperative control protocol for inverter-based islanded microgrids (MGs) is presented. The MG consists of distributed generation units and battery energy storage systems (BESSs). Despite most of the reported works which assumed the ideal conditions and did not considered any delay in information exchange between local controllers, the authors design a controller for the restoration of voltage and frequency fluctuations, achieving accurate active power-sharing and state of charge (SoC) balancing of BESS in the presence of fixed communication time-delay and changing topology of the network. The stability analysis is performed based on the Lyapunov–Krasovskii method, and sufficient conditions are presented based on linear matrix inequalities (LMIs) to guarantee the system stability and to reach consensus under arbitrary switching topologies. The upper bound of communication delay that the system can tolerate is given, too. Finally, to evaluate the performance of the control laws, offline digital time-domain simulation studies are performed on a test MG system in MATLAB/Simulink, and simulation results reveal the effectiveness, efficiency, authenticity and accuracy of the proposed method in regulating MG voltage and frequency and providing accurate proportional active power-sharing and SoC balancing.

Inter-turn short-circuit fault of the stator winding is one of the most common faults of asynchronous generators and often found in doubly-fed wind turbines. The improper treatment methods will lead to unnecessary power loss or further damage to the insulation layer. To solve this problem, an optimal power dispatch strategy (OPDS) is proposed which combines the control at the turbine level and the optimisation at the farm level. At the turbine level, the faulty turbine is down-regulated based on the principle that the fault current does not exceed the rated current. At the farm level, particle swarm optimisation is used to optimise the power references considering wake effects to compensate for the power loss caused by the downregulated turbine. The effectiveness of OPDS is illustrated by comparing with two usually used strategies, one takes proportional dispatch strategy (PDS) and directly shuts down the faulty turbine, the other takes PDS but ignores the fault. The results show that OPDS can minimise power loss under the premise of protecting the faulty turbine. The study contributes to reduce the maintenance costs of wind farms and improve the operational capability of the wind turbine under fault conditions.

Extensive deployment of non-dispatchable renewable energy sources in microgrids (MGs) has led to frequent fault events, DG and line trips and is arduous to discriminate islanding events (IEs) from other transient conditions. For enhanced grid security, time synchronised data from phasor measurement units is utilised. However, data handling at the control centre is tedious as system variables monitored often exhibit non-linear characteristics that impose a problem to the operator in discriminating between islanding and non-IEs. To cope with this, a zero non-detection zone, reliable and precise islanding detection method for data-intensive grid-connected MG, is proposed. Voltage phasors, frequency and rate of change of frequency from various locations are processed through moving window principal component analysis (MWPCA) cascaded with extended mathematical morphological filter (EMMF). MWPCA reduces data dimensionality and Q statistics obtained are passed to EMMF, which acts as a non-linear filter. Further, the islanding detecting factor identified all IEs within the prescribed time limit with minimum false alarms. Accuracy, precision and reliability demonstrated by using a case study model using DIgSILENT are encouraging. It can be adopted by operators to run MG securely. Further, testing of the proposed method on a typical utility feeder shows promising results.

This study presents a robust Kalman filter-based multifunctional control strategy, to enable wide-scale utilisation of the grid-interfaced solar energy conversion system (SECS). The presented control technique offers multifunctional features such as unity power factor, harmonics mitigation, reactive power compensation along with ride through operation under balanced and unbalanced low-voltage faults in the distribution grid. Under fault in the grid side area, the DC–DC converter is controlled in a way that it reduces the active power injection and restricts the inverter currents within its maximum current limit. Based on the depth of grid voltage sag, reactive power supply to the grid is adaptively adjusted, as recommended by IEEE 1547-2018 standard. To minimise the inverter losses, adaptive DC link voltage is introduced, which adapts the DC link voltage in proportion to the grid voltages. Simulation results exhibit the efficacious of the presented robust control strategy in achieving multifunctional features such as harmonics mitigation, grid currents balancing feature and reactive power requirement, under unbalanced line to ground (L-G) and double line to ground faults. Test results demonstrate the satisfactory performance for diverse operating scenarios such as imbalanced currents in the load side network, SECS to DSTATCOM mode and vice-versa, and L-G fault.

Photovoltaic (PV) technology is rapidly developing for grid-tied applications around the globe. However, the high-level PV integration in the distribution networks is tailed with technical challenges. Some technical challenges concern the stability issues associated with intensive PV penetration into the power system are reviewed in this study. To mitigate the voltage disturbances in a system with massive PVs integration, some techniques are devoted such as frequency regulation techniques, active power curtailment, reactive power injection (RPI), and storage energy. Also, with a high penetration level of distributed generators, the potential of dynamic grid support is discussed. Islanding operation and microgrid, operating using different control techniques, which ensure a smooth transition between grid-connected and islanded operation modes as well as synchronisation between the two modes, are discussed.

A multilayer frequency adaptive fundamental signal extractor-based filter is used for the improvement of power quality of a single phase utility grid interfaced to a wind–photovoltaic (PV) system. This filter is used for the grid synchronisation, serving multiple objectives such as mitigating the lower-order harmonics, DC offset elimination, load reactive power compensation, and power flow management. As this filtering technique is based on frequency adaptation, it adapts the changes in the grid fundamental frequency. The effectiveness of this filter is studied with simulations using MATLAB Simulink under varying solar irradiance, wind speeds, and loads also validated on the test setup developed in the laboratory.

This study proposes a fault-tolerant control to suppress the second harmonic (2 h) torque ripple and DC bus voltage ripple simultaneously in dual three-phase permanent-magnet synchronous generator (PMSG) wind turbine drive system by negative-sequence current compensation when one channel of the rectifier is faulty. In the dual three-phase PMSG system with two channels of back-to-back rectifier/inverter, only the other healthy channel can keep working with up to half-rated power if one channel of rectifier fails. In some scenarios, the healthy channel might be asymmetric, which will result in 2 h torque, power and corresponding DC bus voltage ripples in the reduced rectifier/inverter operation. In the previous research, the 2 h torque and DC bus voltage ripples are suppressed simultaneously by compensation with some extra hardware in parallel with DC bus or in series with phase windings, which increases the system cost. In this work, by utilising the inverter and three-phase windings in the faulty channel which are still functional, the 2 h torque and DC bus voltage ripples can be suppressed effectively without any extra hardware, which is validated on a prototype dual three-phase PMSG wind turbine drive system.

Hybrid renewable energy systems (RESs) with storage are gaining significant attention for off-grid communities. Planning of reliability constrained social-economic analysis is a combinatory optimisation problem. This work focuses on the reliability constrained optimisation of the levelized cost of energy (LCOE) of RES with the storage considering the cost of emission. Hybrid energy systems consist of photovoltaic (PV), wind turbine (WT) and diesel generator (DG) with storage. In this work, a systematic approach for determination of reliability constrained optimal combination of generating and storage technologies based on techno-socio-economic criteria has been developed. To evaluate the reliability and the expected generation from the individual unit, probabilistic production costing simulation has been performed using an analytical technique. The optimal sizing of RES with storage has been evaluated using particle swarm optimisation technique and tested on ten different cases. The combination of generation/storage technologies that fetch minimum LCOE while satisfying the reliability standards is chosen as the optimal configuration. Results show that a combination of PV, WT and pumped storage hydro is the best option to meet the energy requirements, with the least LCOE of 0.268 $/kW while satisfying reliability criteria. Further, an optimum generation expansion plan has also been determined for the aforementioned optimal configuration.

Recent years have seen a steep increase in penetration of renewable energy sources (RES) based generators and storage devices; collectively referred as distributed energy resources (DERs). The traditional reliability indices used by utilities such as loss of load expectation, loss of energy expectation and loss of load probability are suitable for systems with conventional generators. However, they fail to acknowledge stochastic behaviour of RES based generators and energy limited capabilities of storage appropriately. In this study, new probabilistic reliability indices for investigating impact of penetration of DERs on system reliability have been proposed. In order to provide effective assessment, a reliability index referred as expectation of failure in grid connected mode (EFG) and three reliability indices viz. expectation of complete success in islanded mode, expectation of partial failure in islanded mode, expectation of complete failure in islanded mode have been proposed in grid connected mode and islanded mode, respectively. The mathematical formulation for proposed indices has been developed in probabilistic framework. The formulation has been implemented on a 33-bus distribution feeder. Different penetration levels have been investigated to provide adequate justification for proposed indices. Parametric analyses with storage integration have also been carried out. The proposed reliability metrics will assist system planners to choose optimum penetration level with greater efficacy.

This study aims at validating the simultaneous operation of grid following and grid forming wind power plants when connected to a common diode rectifier-based HVDC link. The controllers for both grid forming and grid following wind turbines include fault-ride-through capability with soft restoration of the off-shore AC-grid. Current and voltage controllers are developed in the stationary reference frame. The presented control and soft restoration strategies are based on local measurements only and do not require communication between wind turbine generators. The small-signal stability analysis of the mixed system in multiple d–q axis using detailed string models is carried out in order to show the sensitivity to grid following phase-locked-loop gains and to grid forming droop gains. Interoperability between grid forming and grid following wind turbines during transients is shown by means of detailed simulation during symmetric faults in different locations of the off-shore grid.

In this study, a coordinated control scheme is proposed for sharing harmonics compensation effort among voltage and current controlled mode (VCM and CCM) inverters in islanded microgrids. In this method, the voltage harmonics compensation of sensitive bus (SB) is achieved by using secondary control as well as virtual impedance and admittance loops in primary control of VCM and CCM units. The limited capacity of the inverter is taken into account for harmonics compensation. Photovoltaic (PV) systems are considered as CCM units. The harmonics compensation is mainly performed by VCM inverters. However, in order to prevent these units from overloading, the PV interfacing inverters (CCM units) are called to collaborate in harmonics compensation whenever needed. The results of simulation study in Matlab/Simulink show the effectiveness of this method in coordination of CCM and VCM units.

The study suggests a method aimed to improve the performance of practical grid-connected converters connected to distorted mains, utilising total uncertainty and disturbance estimator (TUDE) based control structures with time-delay filter. Such a TUDE filter enhances disturbance rejection performance by possessing near-unity magnitude and near-zero phase at integer multiples of the base frequency, imposing repetitive-control-alike behaviour. However, it is well-known that in repetitive control, disturbance rejection at mid-frequencies, were non-periodic disturbances and noise may exist, is deteriorated. This study presents an enhancement, allowing to retain good disturbance rejection at mid-frequencies within the low-frequency portion of control bandwidth (relevant in practical systems) while trading-off the performance in the high-frequency control bandwidth part. The proposed methodology is verified by application to output current control of LCL-filter based inverter feeding distorted AC mains. The validity and performance of the proposed methodology are well-supported by simulations and experiments.

Photovoltaics has gained popularity as a renewable energy source in recent decades. The main challenge for this energy source is the instability in the amount of generated energy owing to its strong dependency on the weather. Therefore, prediction of solar power generation is important for reliable and efficient operation. Popular data sources for predictors are largely divided into recent weather records and numerical weather predictions. This study proposes adequate deep neural networks that can utilise each data source or both. Focusing on a 24-hour-ahead prediction problem, the authors first design two deep neural networks for prediction: a deep feedforward network that uses the weather forecast data and a recurrent neural network that uses recent weather observations. Finally, a hybrid network, named PVHybNet, combines the both networks to enhance their prediction performance. In predicting the solar power generation by Yeongam power plant in South Korea, the final model yields an R-squared value of 92.7%. The results support the effectiveness of the combined network that utilises both weather forecasts and recent weather observations. The authors also demonstrate that the hybrid model outperforms several machine learning models.

The design of electrical power subsystem of a satellite is challenging since it involves many components and depends on multiple parameters including mission duration, satellite orbit, eclipse times and etc. In contrast to the existing mission specific designs, we propose a generalized and comprehensive method to design and size key EPS elements: PV array and battery, which are integral for mission success. For battery, the proposed design incorporates battery cell characteristics, round trip efficiency, degradation, eclipse load profile and operating modes. The proposed design of PV array takes into account orbit inclination and altitude. In addition, structure and geometry of PV array are also considered and used for irradiance forecasting. Reliability, power margins and power fraction for summer solstice are also factored in the design. For the planning and development of operational strategy, parameter limits are determined for depth of discharge, initial state-of-charge, final state-of-charge and end-of-charge voltage of the battery. The controller design is also presented for the EPS. The effectiveness of the proposed design methodology is verified by a case study of Mysat-1, an imaging nanosatellite developed and launched by Khalifa University.

This work presents a linear state-feedback controller using a backstepping design approach for output voltage regulation of voltage-sourced converters feeding to customers' loads in a stand-alone AC microgrid system. Irrespective of load type and its variations, parameter uncertainties, and other disturbances, the controller is robust enough to achieve a regulated voltage magnitude within the prescribed bounds and exact frequency tracking. The criterion for gain selection using Lyapunov analysis is given. With global exponential convergence feature and better coordination among inner current and outer voltage control loops, improved transient response is achieved. Controller features are examined by eigenvalue analysis and extensive simulation studies. Experimental results demonstrate the feasibility of the proposed controller implementation.

This study proposes a novel linear time-variant model predictive controller (LTV-MPC) for the centralised control of non-linear standalone micro-grids. At each sample, within the prediction horizon, LTV-MPC linearises the non-linear micro-grid model around the state and input reference trajectories resulting in a linear time-variant (LTV) model. The LTV model is used for predicting the forced response of the micro-grid. The natural response is predicted by solving the non-linear model along the state and input reference trajectories. An optimal control problem for the LTV-MPC is formulated using the complete predicted response, which is a quadratic programming problem instead of a non-convex non-linear programming problem. The quadratic programming problem is solved online at each sample to generate the optimal control trajectories within the control horizon. The study recommends the use of two-parameter orthonormal Kautz networks in the LTV-MPC design for the control trajectories approximation. The approximation drastically reduces the number of optimising variables in the optimal control problem without compromising LTV-MPC performance. A standalone eight bus micro-grid with one synchronous distributed generator (DG) and one photovoltaic-DG is considered for the analysis. The LTV-MPC performance is assessed for the different load disturbance and source intermittency scenarios. The results are compared with the existing MPC designs.

This study investigates the stability of multiple three-phase converters connected to weak grids. It has been derived a flexible modelling regarding the number of converter and type of collector system. The both eigenvalues and impedance based methods are applied to the stability analysis. The eigenvalues method is used to give guidelines on the choice of the phase-looked loop (PLL) gains. To improve the stability margins, the increase in the PLL damping ratio is proposed. Moreover, it is used to investigate the PLL interaction with converter current and DC bus voltage controllers. The impedance based method extends the stability analysis to multiple three-phase converters. In addition, it has been used to show the effects of converter current and DC bus voltage controllers parameters on the stability margins. Finally, in order to validate the theoretical analysis, time-domain results with hardware-in-the-loop are given, showing a strong correlation with the theoretical analysis in the frequency domain.

Nowadays power transmission losses in multi-terminal high-voltage DC (MT–HVDC) systems of large offshore wind farms are the main concerns to wind farm operators. Maintaining the DC voltages and currents within pre-specified limits and simultaneously optimising DC power flows of MT-HVDC systems using optimum droop control settings becomes a complex optimisation problem. This droop control scheme was less explored with power loss minimisation applications due to the difficulties in the optimisation of these droop gain settings. This study presents a new mathematical programming plus meta-heuristic-based optimisation approach to solve this optimisation problem. This hybrid optimisation methodology is also termed as ‘matheuristic approach’. The proposed matheuristic method optimises the droop control settings for different operating conditions of offshore wind farms and simultaneously minimises the DC power losses in the MT-HVDC system. The proposed optimisation method has been tested upon a six-terminal HVDC system connected with large offshore wind farms. The superiority of the proposed optimisation method is demonstrated using the steady state as well as dynamic simulation studies. The simulation results show that DC power losses could be reduced significantly by adopting the proposed method to facilitate optimal power flows in the MT-HVDC system of large offshore wind farms.

Aiming to achieve the flexible operation of distribution network (ADN), an energy management strategy of ADN with integrated distributed wind power and smart buildings is proposed in this study. First, based on the thermal storage characteristics of buildings, the resistor–capacitor model is used to develop an energy consumption prediction model of smart buildings. Second, the smart buildings are modelled as flexible resources of ADN. A multi-objective ADN model is further formulated based on analytic hierarchy process (AHP) by comprehensively considering constraints of power grid and smart buildings. Then, the unified model of ADN is transformed by second-order conic relaxation to guarantee the global optimal solution. Finally, the scheduling results for the unified model of ADN under different control methods for heating ventilation and air-conditioning (HVAC) systems are compared in the winter heating scenario. In addition, the impact of the demand response capability for smart buildings on the economic and secure operation of the ADN is further analysed. Numerical studies demonstrate that the proposed method can increase the penetration of local wind power, reduce peak-valley load difference and network loss of the grid while ensuring the comfort temperature of customers, and further achieve the flexible operation of ADN.

When a hybrid wind farm based on doubly fed induction generator (DFIG) and fixed speed induction generator (FSIG) is connected to an unbalanced network, most of the negative sequence current caused by the unbalanced grid will be centralised at the FSIG for its inherent small negative sequence output impedance (NSOI). The centralised negative sequence current can cause significant torque pulsation in the drive train of FSIG, which may go beyond the pressure endurance of the drive train and cause some damages. Meanwhile, losses and risks of overcurrent and grid code violation can also be increased. This study presents a control strategy for DFIG in hybrid wind farm during network unbalance, which can disperse the negative sequence current and the consequent pressure among the three parallel power sources without communication, i.e. among the DFIG stator, the grid side converter (GSC), and the FSIG, rather than centralising the pressure at any of them. In order to achieve this target, a novel hybrid virtual impedance method is proposed to flexibly control the NSOI of the DFIG stator and the GSC from zero to infinity. Theoretical analysis and simulation results are provided to verify the operation performance of the proposed strategy.

In this study, novel control schemes are developed for cooperative control of stand-alone and grid-connected photovoltaic (PV) based water pumping system. Brushless DC motor is used as pumping motor due to its superior characteristics. The cooperative control effectively utilises the available resources. In stand-alone system, control scheme is developed for power sharing among PV pumping units. Assuming some of the PV units have battery, the charging/discharging controller is incorporated. In grid-connected system, flexible control scheme is proposed so that consumer can draw lesser power from grid by running the motor at lower speed instead of rated speed. In case of high PV power penetration into weak grid, the modified perturb and observe algorithm is proposed for sharing of de-loaded power among the PV units. Due to de-loading of PV power, motor speed reduces, hence, speed compensation mechanism is developed to bring back the speed at desired value. As a futuristic concept, consumer can buy power from neighbour instead of taking from grid. To establish above-mentioned concept, control scheme is developed for sharing the power among PV pumping units. The simulation and hardware results are carried out to test performance of the proposed control schemes.

Changing mainstream electricity supply from a thermal to a renewable-supplied grid has important benefits to sustainable electricity generation. However, challenges, especially at high levels of renewable energy sources (RESs) penetration, need to be addressed. In particular, for economic and stability reasons, RESs are underdogs in competition with fossil-fuel generation unless proper incentives are provided and incorporated into electricity bills of consumers. Also, the intermittent output of RESs can compromise grid efficiency and increase the cost of electricity. These issues can be resolved, using demand response, if load flexibility was not limited. Volunteer load shedding could help with this problem if consumers are willing to voluntarily shed their non-essential loads (NLs). This study investigates the impact of NLs planned outage rates on the required incentive, in order to reach different levels of RES penetration. To illustrate the effectiveness of the contributions of consumer load shedding on the integration of RESs and utility grids, their collaborative impact is explored against a numerical system based on real historical data. The results demonstrate the positive impact of consumers' contribution by substantial reduction in the incentive. The margin of savings will then be used to evaluate the value of volunteer load shedding of consumers.