Hydrokinetic energy conversion systems capture the power available in the water flowing in waterways. An electrical interface for the power take-off of a hydrokinetic energy conversion system was designed and a control strategy for the maximum power extraction was investigated. A laboratory prototype was used for the experimental characterisation of the system. High efficiencies were observed because of the restricted flow conditions. The power curves obtained from the experimental results were used for the simulation of the system in MATLAB/Simulink. A ‘perturb and observe’ method was used for the maximum power point tracking (MPPT). A control scheme based on a heuristic algorithm suitable for restricted and turbulent water flows was developed. A practical advantage of this scheme is that it does not require the use of mechanical sensors. The MPPT of the laboratory prototype was simulated and experimental validation undertaken, with simulation and experimental results agreeing well. The MPPT of a full-scale hydrokinetic energy conversion system was simulated to assess its performance towards practical deployment.

This study highlights the operation under the bilateral scenario of the deregulated environment, considering a three unequal area thermal system, wherein several renewable sources namely geothermal plant (GTP), solar thermal and wind had been integrated to analyse their effect both through dynamic responses as well as analytically from the aspect of GENCO participation, related to the price based environment. Later a flexible alternating current transmission (FACT) device, interline power flow controller (IPFC) is being connected to the above-considered system at different positions. Various observations are made for checking if there is an optimal location for the placement of IPFC and it reflects that IPFC placed between the tie lines of area 1 and area 3 shall economically be the most feasible option. The considered thermal systems are provided with suitable generation rate constraints. In this study, an initiative has been taken to use a new combination of fractional order (FO) cascade controller, FO integral-FO proportional-derivative as secondary controller and its capability is being checked with the traditional controllers revealing it to outperform the others. The gains and other required parameters of all the secondary controllers are optimised by means of the stochastic sine cosine algorithm.

This study presents the uncertainty analysis of a distribution network (DNR) caused by unit power output control (UPC) distributed generations (DGs) (solar, wind) and load demand by point estimate method (PEM) based on mixed-discrete-based particle swarm optimisation (MDPSO) technique. The uncertainties are taken care by the feeder flow control (FFC) DGs which make the DNR power independent of the main grid, which means the DNR does not exchange any power with the main grid at any load level. To analyse the situation, the load flow technique is modified with introducing and zero bus in the system. and the higher-order PEM methods are applied in this study for uncertainty analysis. The FFC and the UPC DGs are placed and sized by the MDPSO algorithm. The uncertainty analysis of the system is done based on different objective functions and test cases which are the combinations of active power loss, voltage deviation, and the DG operation cost. The proposed method is applied to the 69-bus DNR, and the results are compared with teaching learning-based meta-heuristic optimisation method. The cumulative distribution function and probability density function of the output random variable are approximate with Gram–Charlier expansion method.

Microgrid systems, such as solar photovoltaic (PV) and wind turbine (WT), integrated with diesel generator can provide adequate energy to supply increased demands and are economically feasible for current and future use considering depletion of conventional sources. It is, thus, important to determine the appropriate sizes of PV, WT, diesel generator, and associated energy storage system (ESS) for efficient, economic, and reliable operation of electric power system in microgrid. Stochastic nature of intermittent renewable energy (RE) resources complicate their planning, integration, and operation of electric power system. Therefore, it is critical to generate typical scenarios of wind speed, irradiation, and load time series to reflect their stochastic characteristic for microgrid system planning and operation. In this study, a wind-irradiation-load typical scenarios generation method is proposed for optimal sizing RE resources of microgrid. The teaching-learning-based optimisation (TLBO) method is used to find the best configuration of the microgrid system. Simulation results show that scenarios generated by the proposed model have ability to approximate the original scenarios and reduce planning data effectively.

This article presents a generalised asymmetrical cascaded multilevel inverter (MLI) for a single-phase grid-connected photovoltaic (PV) system and their control strategy. The control strategy, including maximum power tracking along with a suitable interface, is implemented for maximum power transfer from the PV source to the single-phase low-power grid. The balancing of DC-link voltages for an asymmetrical MLI under variable solar parameters as well as grid parameter variation is implemented using the proposed control strategy. The voltage controllers maintain the constant DC-link voltage ratio, whereas the current controller injects the sinusoidal current into the grid at unity power factor and track the grid voltage under variation of grid voltage using grid tracker. Stability analysis of the proposed grid-connected asymmetrical inverter system is also incorporated. The whole grid-tied PV system is simulated in the MATLAB/SIMULINK environment and the exhaustive simulation results of the system under different transient conditions are presented. In addition, a laboratory prototype for a low-power grid-tied PV system has been developed and implemented using DS1103. The performance of the system is also tested at varying irradiance conditions and the corresponding experimental results are also presented.

This article presents an accurate computational technique for estimating the photovoltaic (PV) cell parameters from experimental measurements of the current-voltage (I–V) characteristics. The technique is based on using various evolutionary algorithms (EAs) and the double-diode eight-parameter cell model to precisely estimate unknown parameters. The proposed technique is implemented to extract the PV cell parameters of different manufacturer's modules by minimising the summation of absolute square errors between theoretical and measured I–V output characteristics obtained under different irradiation levels. The effectiveness and robustness of the proposed technique are demonstrated via a comparative assessment of the measured output I–V characteristics and those obtained by computer simulation, using Matlab SIMSCAPE library components. The good agreement obtained between theoretical and experimental results endorses the proposed approach to determine precisely the PV parameters required for power system studies. The proposed technique is useful power system studies with penetration of photovoltaic sources.

Home energy management systems (HEMSs) are important platforms to allow consumers the use of flexibility in their consumption to optimise the total energy cost. The optimisation procedure embedded in these systems takes advantage of the nature of the existing loads and the generation equipment while complying with user preferences such as air temperature comfort configurations. The complexity in finding the best schedule for the appliances within an acceptable execution time for practical applications is leading not only to the development of different formulations for this optimisation problem, but also to the exploitation of non-deterministic optimisation methods as an alternative to traditional deterministic solvers. This study proposes the use of genetic algorithms (GAs) and the cross-entropy method (CEM) in low-power HEMS to solve a conventional mixed-integer linear programming formulation to optimise the total energy cost. Different scenarios for different countries are considered as well as different types of devices to assess the HEMS operation performance, namely, in terms of outputting fast and feasible schedules for the existing devices and systems. Simulation results in low-power HEMS show that GAs and the CEM can produce comparable solutions with the traditional deterministic solver requiring considerably less execution time.

The back-to-back topology of dual active bridges DC/DC converter cascaded with DC/AC inverter has been widely used in solar power integration system. The output impedance of DAB converter will interact with the input impedance of inverter, and without proper design, stability degradation will be engaged. Against the impedance interaction caused stability degradation problems, typical solution is to modify converter's impedance feature through control strategies, named as active solution, but conventional active solutions solely pay attention to single individual converter. Here, a coordinative impedance active damping control method is proposed, which simultaneously modifies the front DAB and rear inverter impedances, promoting a more stable manner. This article compares the proposed control with conventional individual impedance damping control methods. The impedance-based stability evaluations show that the proposed control can prompt DC-link connected converters to perform resistive impedance in the low-frequency band, thus the impedance interaction will be more damped, which contributes to an enhanced stability and dynamics. The effectiveness of the proposed control has been tested by both simulation and experiment results.

This article investigates the operation of offshore wind farm connected by parallel diode-rectifier-based HVDC (DR-HVDC) and HVAC links. A secondary voltage control is proposed to control the offshore AC voltage amplitude by regulating the DC voltage of the DR-HVDC link. A secondary frequency control and a phase angle control are proposed to adjust the reactive power reference in the primary control, which synchronise the offshore point of common coupling (PCC) frequency and phase angle to those of the HVAC link. Such secondary voltage control, frequency control, and phase angle control enable seamless transition from DR-HVDC mode to parallel mode. A tertiary power control scheme is further proposed to control the active power flow distribution between DR-HVDC and HVAC links through the regulation of PCC phase angle. To ensure smooth transition from HVAC mode to parallel mode, a virtual DC power control is proposed to control the virtual DC power at zero prior to the connection of the DR-HVDC link. A small-signal model of the parallel system is developed, and the stability analysis is carried out for the proposed control scheme. Simulation results in PSCAD/EMTDC verify the proposed control under normal and fault conditions.

To continuously assess the performance of a wind turbine (WT), accurate power curve modelling is essential. Various statistical methods have been used to fit power curves to performance measurements; these are broadly classified into parametric and non-parametric methods. In this study, three advanced non-parametric approaches, namely: Gaussian Process (GP); Random Forest (RF); and Support Vector Machine (SVM) are assessed for WT power curve modelling. The modelled power curves are constructed using historical WT supervisory control and data acquisition, data obtained from operational three bladed pitch regulated WTs. The modelled power curve fitting performance is then compared using suitable performance, error metrics to identify the most accurate approach. It is found that a power curve based on a GP has the highest fitting accuracy, whereas the SVM approach gives poorer but acceptable results, over a restricted wind speed range. Power curves based on a GP or SVM provide smooth and continuous curves, whereas power curves based on the RF technique are neither smooth nor continuous. This study highlights the strengths and weaknesses of the proposed non-parametric techniques to construct a robust fault detection algorithm for WTs based on power curves.

The operation of variable speed wind turbine (VSWT) greatly affects the efficiency and quality of wind power generation. The conventional controllers are not able to improve VSWT performance in the presence of higher degree of non-linearity, uncertain changes in wind speed, and coupling effects in the dynamical modelling. This study presents a controller design based on dynamic surface control (DSC) for a three-bladed, horizontal axis VSWT. The DSC design provides the robust performance while considering the problem of irregularity of wind speed, extraction of maximum available power from the wind, and vibration effect due to tower dynamics. The boundedness and the convergence of the proposed control have been ensured through a formal proof, leading to minimum tracking error. A comparative evaluation of a VSWT performance from the proposed DSC scheme has been analysed with the performances using quantitative feedback theory control, standard wind turbine controller, and conventional proportional integral control. The simulation results confirm that the application of DSC control has effectively produced maximum power and least tracking error than the other three existing controllers, performing robustly in presence of parametric variations upto ±15% and external disturbances.

This study presents the new interconnection scheme for solar photovoltaic (PV) modules to mitigate the power mismatch and wiring line losses employing improvised magic technique (IMT). The proposed interconnection scheme provides improved power enhancement compared to conventional total cross tied (TCT) technique. This technique can be implemented on PV array of any order with ‘x’ rows (x > 2) and ‘y’ columns (y > 2). However, in the higher order PV modules, power mismatch loss and wiring loss reduced significantly using segmented improvised magic technique (SIMT). The sequence of reconfiguring the PV modules has been explained using a flowchart and an algorithm both for IMT and SIMT. The effectiveness of these techniques is tested using MATLAB simulations and validated the analysis by comparing the performances with the existing TCT for lower order (3 × 3) with experimentation and higher order (9 × 9) PV modules. Thus, the proposed IMT and SIMT techniques provide the maximum power enhancement, less power mismatch and line loss, and maximum improved efficiency in real-time PV array installations.

Due to the integration of the renewable generation and the distributed load that inherently uncertain and unpredictable, developing an efficient distributed management structure of such a complex system remains a challenging issue. Most of the existing works on the demand-side management concentrate on the centralised methods or need a proper initialisation process. This study proposed a demand-side management strategy that can solve the optimisation problem in a distributed manner without initialisation. The objective of the designed demand management system is to maximise the social welfare of a smart grid by controlling the active power economically. The proposed optimisation strategy that generates the optimal power references uses the neighbouring information while considering the local feasible constraints by using a projection operation. Furthermore, the optimisation algorithm is initialisation free, which avoids any initialisation process when plugging-in new customers or plugging-out power units, such as demand loads, battery energy storage systems and distributed generators. The proposed strategy only uses the neighbouring information, so that the proposed approach is scalable and potentially applicable to large-scale smart grids. The effectiveness and scalability of the proposed algorithm are established and verified through case studies.

This study presents a bi-level model for expansion planning of generation systems. The proposed model endogenously determines the incentive to invest (guaranteed purchase contract) for wind and storage units. In the upper level of the proposed model, wind turbines and compressed air storage systems focus on maximising their profits by presenting a strategic offering, while at the lower level, there is an independent system operator with the purpose of increasing social welfare run the market clearing equations. In solving the bi-level model, the Karush–Kuhn–Tucker conditions are used to develop the mathematical program with equilibrium constraints. The problem was first linearised and then solved by GAMS software. The outputs of this problem are the installation time and capacity of the wind and storage units and the price of the purchase contract. The obtained results were compared with other existing studies for verification purposes.

A wind turbine is the most typical machine used to capture energy from the wind. The system design goal of a wind turbine is to obtain as much energy as possible from the wind while transmitting as much of that energy to the grid as possible, all under the highest possible level of stability. Currently, many inherent weaknesses result in a high failure rate in common commercial wind turbines with gear drive systems. To improve the performance, in this study, a typical 1.5 MW gear transmission was redesigned into a novel hydromechanical transmission system (HMTS). Parameters related to the HMTS efficiency were analysed to ensure that the efficiency was relatively high. The variable speed ratio (VSR) and torque triple absorption (TTA) principle were thoroughly deduced. Moreover, a MATLAB/Simulink- AMESim cosimulation model was proposed, and a 30 kW proportional prototype was established. Both simulation and experimental results show that the structural design and proposed control strategies meet the design goals, including a relatively high transmission efficiency around the rated wind speed, speed control below the rated wind speed, and torque control above the rated wind speed. These achievements should guarantee the future application of the novel transmission system in wind turbines.

The negative impacts imposed by wind power on power systems can be decomposed into different time scales. Demand response (DR) can relieve these impacts by providing different auxiliary services. However, based on the current integration requirement, wind farms cannot earn more even if they try to provide power with less negative impacts. In this regard, three indicators are proposed for three different time scales to evaluate these efforts of wind power resources. The system operator sets the purchasing price of wind power by using these indicators. It aims to encourage wind farms to improve their output curves by purchasing the DR supporting services products. In the next step, a bi-level optimisation model is developed to assist the wind farms in their bidding and DR purchasing strategies. The case studies show that the proposed model can reduce wind power curtailment and improve the power's features. Moreover, by using the indicators as the integration requirement, the revenue of wind farms and the economic benefit of system dispatch are improved.

Wind turbines are complicated systems with different aerodynamic and electromechanical aspects. An integrated platform which includes design, simulation, and experimental evaluation of wind energy conversion systems is very helpful to design, develop, and examine the performance of different wind turbine sub-systems. The previous studies exclude such a platform and this study tries to fill this gap. In this study, the blades of a 5.5 kW fixed-speed stall-regulated wind turbine are initially designed then employed in simulation and emulation. The same as the simulation setup, the utilised emulator uses AeroDyn and FAST software tools to model the aerodynamic and mechanical aspects of the turbine in a laboratory environment. The emulator is capable of reproducing the static and dynamic behaviour of the turbine in a laboratory similar to the real turbines. For simulation, the electrical parts are implemented in MATLAB/Simulink, whereas the real electrical parts are used for the emulator. The performance of the turbine with the designed blades is investigated in simulation and emulation considering a simple hub-height and turbulent wind profile, generated by TurbSim software tool based on the IEC standards. Moreover, the start-up process of the wind turbine is evaluated using the wind turbine emulator and the results are discussed.

Distribution system possesses high resistance to reactance ratio and unbalanced load profile. Introduction of power electronic devices such as solar photovoltaic (PV) inverter in the distribution system leads to power imbalance and unregulated voltage profile at the point of common coupling (PCC) because these devices having low-voltage ride through feature remain connected to grid during fault and inject balanced current to unbalanced fault. Also, high PV integration may increase the voltage at PCC beyond its desired limit. To overcome such unbalanced conditions and to maintain voltage at PCC, a positive, negative and zero sequence-based current controller with reactive power compensation is proposed in this work. The sequence controller controls the sequence currents to their reference command. DC-link voltage regulator, reactive power compensator and PCC voltage regulator decide the references for sequence currents. The proposed reactive power compensator uses both positive sequence voltage at PCC and reactive power supplied by the filter capacitor to generate the reactive power reference value. Feedforward and feedback actions are involved in the controller to produce switching pulses for inverter. The proposed method is tested in OPAL-RT for real-time validation using IEEE 13 bus distribution system model and found to be accurate.

A phase-locked loop (PLL) plays an integral part in synchronisation circuits and is immensely used in grid-connected systems, active filters, and uninterrupted power supplies. A number of these circuits based on synchronous reference frame and its modifications, second-order generalised integrator, enhanced PLL (EPLL) have recently been reported in literature. This article proposes an adaptive version of EPLL whose gain adjusts automatically with the variation of error. Adaptive EPLL (A-EPLL) is developed for positive sequence extraction of load current and its performance is tested for active filter operation. A PV system is also connected at the DC link of the shunt active power filter (SAPF) and the developed controller is tested under dynamic load changes. The complete control technique is tested for harmonics reduction, load balancing, and power balance between grid, load, and photovoltaic (PV) source. Detailed experimental results showing a new adaptive PLL for load compensation are illustrated here.

This article presents a harmonic compensation capability-based coordinated control strategy for a hybrid wind farm including doubly fed induction generator (DFIG)-based and direct-driven permanent-magnet synchronous generator (PMSG)-based wind turbines operation under distorted grid voltage conditions. First, the maximum harmonic current compensation capabilities of the DFIG and PMSG systems are analysed in detail when the grid voltage is harmonically distorted. Combining the maximum harmonic current compensation capabilities with the harmonic current requirements of different control targets, the controllable operating regions of each control target of the DFIG and PMSG systems during network voltage distortions are presented. Furthermore, the effects of the voltage total harmonic distortion (THD) and the system operating conditions on the controllable operating regions are analysed. Based on the analysis, the coordination strategy is proposed for a hybrid wind farm without communication equipment between the different wind power generators. The proposed strategy can improve the interoperability and the output power quality of the entire hybrid wind farm during grid-voltage harmonic distortions. Finally, the effectiveness of the proposed coordination strategy for the hybrid wind farm is validated by simulation and experimental results.