This work presents a speed sensorless permanent magnet synchronous motor (PMSM) drive for single-stage solar photovoltaic (PV) powered water pumping. The elimination of speed sensor reduces the system cost and improves the system robustness. The estimation of rotor speed and position is achieved through estimation of stator flux from voltage and current in stationary reference frame. Conventional maximum power point technique uses two sensors for PV array voltage and current sensing. In the presented work, an effort is made to eliminate the PV array current sensor without compromising the system performance. The proposed system is modelled and its performance is simulated in MATLAB/Simulink. The experimental performance is validated on a developed laboratory prototype using a digital signal processor (DS-1202). A comprehensive comparison is made to validate the significance of the proposed work.

With higher penetration of converter-connected renewable energy sources (RES) into power systems, the successful operation of the system is challenged by significant reductions in system inertia. Presently, given the dominant share of the conventional synchronous power plant, RES power plants are not demanded to provide ancillary services. However, as RES connections increase, RES power plants will play a major role in power system operation, contributing to frequency control. This study demonstrates that photovoltaic power plants (PVPPs) can provide effectively different types of frequency support based on a power reserve and an offline maximum power point tracking (MPPT) technique. An innovative method to de-load the PVPP without significantly increasing the MPPT complexity is proposed. Results from different PVPP frequency support methods, under varying levels of photovoltaic penetration, are presented which demonstrate their capability to provide inertia support comparable to that of synchronous generators. A new variable droop control method, which releases maximum power during the inertial response and returns to fixed droop gain value after a specified time is also presented. The results from using the variable droop show that the frequency nadir and the rate-of-change-of-frequency can be significantly reduced and some power reserve still maintained after a frequency event.

High penetration of renewable energy sources will cause crucial challenges for future energy systems. This study presents a three-level model for adaptive robust expansion co-planning of electricity and natural gas infrastructures in multi-energy-hub networks, which is robust against uncertainties of maximum production of wind generation and gas-fired power plants as well as estimated load levels. The proposed min–max–min model is formulated as a mixed integer linear programming problem. The first level minimises the investment cost of electricity and natural gas infrastructures, the worst possible case is determined through the second level, and the third level minimises the overall operation cost under that condition. To solve this model, the final minimisation problem is replaced by its Karush–Kuhn–Tucker conditions and a two-level problem is determined. Finally, by using the column and constraint generation algorithm the original problem is decomposed to master and sub-problems and the optimal solution is derived iteratively. The proposed robust expansion co-planning model is tested on modified Garver's 6-hub, modified IEEE RTS 24-hub, and modified IEEE 118-hub test systems and numerical results show its effectiveness to cope with uncertainties with regard to control conservativeness of the plan.

With the rapid increase in photovoltaic (PV) power generation in microgrids, PV power fluctuations can initiate negative impacts on microgrid operations. This study presents a simulation analysis of PV power smoothing method based on hull enhanced linear exponential smoothing (HELES) technique using an energy storage system (ESS). The proposed method is employed to mitigate PV power fluctuations in microgrid systems. The ESS is allowed to charge and discharge for smoothing the PV output power based on a smoothing power reference provided by the HELES technique. The proposed method is investigated to acquire the smoothing performance considering smoothness and smoothing accuracy. In simulation analysis, the proposed method is analysed on the microgrid under both grid-connected and islanding modes to obtain its dynamic performance. The simulation results demonstrate that the proposed method evidently offers superior smoothing performance compared with the existing methods. Accordingly, the smoothing accuracy is successfully improved, and the ESS capacity is significantly reduced by improving smoothing accuracy. Moreover, the smoothness is effective to mitigate PV power fluctuations by using the proposed method. Eventually, the dynamic performance can be satisfactorily improved, and state of charge variation is reduced and also conserved to be available for unexpected PV power fluctuations.

Here, performance of 11 kW solar-powered lithium bromide water absorption chillers in cogeneration mode is investigated. A 40 m² solar parabolic dish of 19 kW_th capacity is used for both processes heating and cooling. Extensive thermodynamic design and analysis are carried out, and the results obtained are validated. Parabolic dish and cavity receiver are sized for Chennai (13°N, 80.18°E), India. In the present analysis, a new performance parameter COP_WE is introduced by replacing the thermal input component in the calculation of COP, by an equivalent amount of high-grade energy. Both physical and chemical exergy at all state points of the chiller are estimated and found that total irreversibility is about 2.37 kW in desorber followed by absorber which is 0.41 kW. The developed model estimates solution concentration at the exit of solution expansion valve (SEV) that is important since it affects absorption of refrigerant in the absorber.

Here, an implementation of three-phase grid-tied single-stage solar photovoltaic (PV) system is done at adverse grid situations of voltage unbalances. The proposed convex combination of least mean square (CCLMS) control approach is adaptive in nature, which extracts the fundamental component of load current (FCI) with fast convergence and provides good performance than conventional controls. The CCLMS algorithm overcomes the compromise of LMS filters between precision and tracking capability due to fixed stepping by providing a combination of two filters for precision and fast tracking. The perturb and observe (P&O)-based maximum power point tracking (MPPT) is employed for peak power extraction from a PV array. The system is tested in the laboratory on a developed prototype at several adverse conditions like voltages unbalance, load currents unbalances, and irradiation changes. The system performance is acceptable and harmonics distortion is in the limits according to the IEEE-519 standard while supplying energy to the utility and to the loads.

This study proposes a modified decentralised droop controller for inverter-based autonomous photovoltaics (PV) microgrids to address the problem of instability and slower power sharing between PV inverters. The proposed controller modifies the conventional droop mechanism in transient as well as in steady state by adding an auxiliary control signal in the power control loop of the inverters. The proposed approach offers three key benefits, i.e. improves active power sharing, enhances system stability and performs the secondary control action by nullifying the frequency deviation by using only one auxiliary signal in the control loop. The accuracy of the proposed modified droop controller is verified with the help of time-domain simulations in MATLAB/SIMULINK. The results obtained show that the controller is able to improve the power sharing and stability of the microgrid as well as to restore frequency. The performance of the proposed control scheme is also validated by experimental results and small-signal analysis.

This study focuses on a fuzzy generalised predictive control (FGPC) method for a time-delay hydro-turbine governing system (HTGS). First, based on the time-delay Takagi–Sugeno fuzzy model, a time-delay HTGS and its fuzzy prediction model are given. Second, with the help of delay fuzzy linearisation and a fourth-order Runge–Kutta algorithm, a transformed controlled auto-regressive integrated moving average model is obtained. Then, a new FGPC scheme for the time-delay HTGS is proposed. Finally, numerical simulations are implemented to verify the validity and superiority of the proposed method. It also provides a reference for the stability control of relevant hydropower station systems.

The soft switching flyback inverters still cannot provide high efficiency and low output current total harmonic distortion (THD) in all load ranges. Therefore, a new flyback inverter with soft switching for photovoltaic AC module applications is presented in this study. The introduced inverter is simple and a small auxiliary circuit is added to the conventional topology of the flyback inverter. Since the primary current of the transformer is not affected by the auxiliary branch, the output current THD does not increase. In addition, all of the high-frequency switches of the proposed topology are switched under soft switching condition, which allows high-switching frequency. Hence, high efficiency, as well as compact design, can be achieved in the proposed inverter. Moreover, the voltage overshoot of the main switch during the turn-off process is limited. This effect decreases the conduction losses because the lower voltage rating switch can be used. Furthermore, a new control method is presented, which provides high efficiency in all load ranges. The operations of the introduced flyback inverter and component selection have been discussed in detail. The performance of the proposed inverter with the auxiliary circuit and corresponding controllers are validated with the help of experimental results.

An integrated dc–dc converter with maximum power point tracker (IDCCM) is an electronic device that can be utilised to increase the output power of a photovoltaic generation system. Despite its potential benefits, there is an absence of a comprehensive analytical work to characterise the IDCCM performance under different partial shading conditions. Thus, this work proposes an analytical method to evaluate the system with IDCCM for different shading pattern/intensity, irradiance, and temperature. To validate the analysis, the SPV 1020 boost-type IDCCM devices are incorporated into a 2 kWp experimental test-rig. The performance of the IDCCM is benchmarked against the conventional system that utilises bypass diodes (alone). The results indicate that the IDCCM improves the performance of the central inverter as it ensures the latter consistently tracks the global peak. Also, it was found that that the performance of the IDCCM depends on the shading intensity: at low intensity, the IDCCM is able to extract energy from the shaded modules; however, it is ineffective at high shading intensity. Furthermore, when the shading is absent, the energy gained by the IDCCM is offset by the continuous power losses due to its internal operations.

Microgrids (MG) provide advantages such as providing energy supply to areas far from the distribution grid, efficient use of resources by supporting demand management and having a more dynamic grid. However, if an advanced control system is not implemented in the islanded MG, problems of power quality may arise. One of these problems is the voltage unbalance. Increasing the number of single-phase roof-mounted PV plants and the number of electric vehicle charging stations in recent times may negatively affect voltage unbalance. One of the methods used to mitigate this problem is the demand-side management (DSM). Here, a solution method based on DSM is presented for the voltage unbalance problem that may occur in an islanded MG. Thermostatically controlled loads, which are often used for DSM, are preferred as controllable loads. A new and novel control algorithm based on voltage sensitivity have been developed. Effects of TCLs on different buses and phases are determined with voltage sensitivity matrix including neutral components. The proposed control algorithm reduces successfully both the voltage unbalance factor and the number of controlled TCLs. The algorithm was tested with the PSCAD/EMTDC analysis software.

The increase in the price of fossil fuel due to its rarity and emissions means more integration of renewable energy sources (RESs) is required to improve economic management of the grid. This study analyses a combination of the tie-line power between conventional power sources and the renewable energy system and its frequency deviations which are known as area control error. The minimisation of the tie-line by optimal control is affected in such a way that the frequency and tie-line power error can be minimised while maintaining the power balance between generation and load. The tie-line connected to the microgrid consists of two main parts, namely the conventional source and the renewable energy source, each made up of a synchronous generator. The control application of the active power and frequency to a network is referred to as load frequency control (LFC) with the storage system as an integral part of RES. The simulation results show the performance of the proposed optimal control model in microgrid during the changing loads' condition, where the energy storage system applied to optimal control has shown a quick response to frequency deviation, which is close to 80%.

This study investigates optimal wind power generator bidding strategies in the real-time electricity market. The goal is to maximise its operating profit by determining the optimal amount of wind power to bid in the real-time market. A bi-level stochastic optimisation model is proposed in which the upper-level problem is minimising the negative profit of wind power producers, while the low-level problem clears the real-time market. The uncertainties in the wind power production, thermal power, hydro power, demand, and energy storage are considered in the stochastic model. This study utilises a mathematical programming problem with equilibrium constraints (MPEC) and Karush–Kuhn–Tucker (KKT) conditions to transform the bi-level problem into an equivalent single-level mixed-integer linear problem (MILP). Case studies obtained with the IEEE RTS-24 Bus system demonstrate the effectiveness of the proposed model and the effect of scenarios on the wind power producer's profit.

As the development of the energy industry, the integration and complementary of various energy resources will be trends of future multiple energy systems. Energy hub (EH) plays an important role in allocating energy resources efficiently. This study proposes a robust coalitional game theoretic optimisation model to execute the cooperative operation of multiple EHs with correlated wind power. First, an EH model with wind power generation is established. It considers both uncertainties and correlations of wind power. Then, coalitional game theory is introduced to solve the cooperation problem of multiple EHs. Distributed coalition formation algorithm called merge–split rule is developed to form coalitions of EHs. Furthermore, the robust optimisation method is presented to cope with the uncertainties of wind power. Scenarios of correlated historical data are covered by minimum volume enclosing ellipsoid and solved by Khachiyan's first-order algorithm. Numerical results are given to verify the feasibility and efficiency of our proposed models and methods.

A robust fault-detection design based on residual Kullback–Leibler (K–L) divergence, which is applied to a 5 MW offshore wind turbine (WT) benchmark, is presented. The main challenges of the wind turbine fault detection lie in its complex operation conditions and disturbances as well as measurement noise. For overcoming these difficulties, the measured data are divided on the basis of the operation conditions of WT. The robust residual generator based on parity vector is adopted to calculate the residual under different operation conditions. The K–L divergence based on probability density function is employed to measure the residual. Then, the threshold for the fault detection is determined in line with both false alarm rate and missed detection rate. The simulation results show that the performance and effectiveness of the proposed robust fault detection are better than compared with other data-driven fault-detection approaches.

A current source with a space-vector hysteresis band and a constant switching frequency has been designed to be used with surface-mounted permanent magnet synchronous generators. Its fast response makes it very suitable to carry out the precise control necessary in wave energy converters (WEC). These systems are characterised by large variations of speed, torque (or force) and frequency which means that the control has to cope with large variations of voltage and current and also with persistent periods where these variables present low values. The control system takes into account both rotation direction (or displacement direction, when a linear generator is considered) and electrical sequences, something necessary in WEC such as point absorbers. The algorithm was successfully tested in the laboratory using an ad hoc built emulator, that reproduces the behaviour of an oscillating water-column-based WEC. The emulator was built using a similar hardware to those used in equivalent real systems.

The enormous load growth in recent times has forced distribution companies to undertake comprehensive planning of the active distribution system (ADS) to maintain superior service to their consumers. Under different critical situations in the restructured power system, reconfiguration in combination with the incorporation of renewable energy sources (RESs) and distributed static compensator (DSTATCOM) must be utilised for accurate system planning. In addition, from a practical viewpoint, the time-variant load demand of different consumers and the intermittency of RES units must be considered. This study proposes a modified multi-objective particle swarm optimisation (m-MOPSO) technique for ADS planning considering reconfiguration, RES, and DSTATCOM to enhance voltage stability, reduce pollution, improve reliability, and maximise financial benefits. In the proposed m-MOPSO, a novel non-dominant sorting strategy is used to maintain diversity among the non-dominated solutions. The time-varying system load, yearly load growth, and intermittent power generation of RES are considered to construct a realistic planning model. The proposed technique is tested on the 33-bus ADS considering different planning schemes to provide the most suitable planning scheme to the ADS planners. Moreover, the accuracy of the proposed algorithm is confirmed by comparing it with other multi-objective algorithms.

This study proposes a linear magnetic gear (LMG). Unlike conventional LMGs, the proposed one purposely uses high-temperature superconducting (HTS) bulks replace permanent magnets (PMs). The high-speed mover of the magnetic gear is connected to the secondary of the linear permanent magnet generator (LPMG), which constitutes a direct-drive wave power system that converts wave energy into electrical energy. First, the LMG structure is presented according to the principle of magnetic field modulation, and the authors briefly analyzed the number of pole pairs of inner, outer, and ferromagnetic modulators. Second, they also established a finite element analysis model to analyze the performance of magnetic gear, including magnetic field distribution, radial air gap magnetic flux density, and force characteristic. An LMG with HTS bulks not only increased the radial air gap magnetic flux density but also improved the speed of LPMG. In conclusion, this experiment verifies the efficacy of direct-drive wave power take-off system and effectively converts wave energy into electrical energy.

This study presents an adaptive sliding mode type-2 neuro-fuzzy controller for power control of doubly fed induction generators (DFIGs). DFIG-based wind turbine system is variable-speed constant-frequency wind energy conversion system. In this proposed control scheme, in order to enhance its performance, sliding mode control (SMC) theory is used for online training the parameters of type-2 fuzzy system membership functions. To regulate the antecedent and consequent part parameters, the SMC adaptive technique is used according to the controller inputs. These inputs are active and reactive power errors and their time derivative, which applied to the structure of T2NF system. The proposed controller employs an interval type-2 fuzzy system because of the uncertainties of the wind speed and variation in parameters in the wind power conversion system. The simulations carried out for a DFIG-based 1.5 MW wind turbine. The results of simulation are compared with the classical proportional–integral controller to confirm the effectiveness of this control scheme. This comparison is carried out between the cut-in and rated region wind speeds. The results of simulation show that the proposed control scheme has better performance to track the peak power and is more robust to machine parameter variations.

Islanding detection in microgrid using harmonic filters connected at the distributed generation units (DGs) end has been described. Traditional islanding techniques related to impedance estimation suffer from poor detection accuracy due to false detection during load switching. In the proposed method, tuned filters connected at DG terminals are utilised for islanding detection in the microgrid. These filters can be connected at the DG end to reduce harmonic injection to the source end, besides helping the islanding detection through the proposed technique. The measured grid-side harmonic impedances at tuned frequency after the filter are used for islanding detection instead of the direct input harmonic impedance calculated in traditional techniques. The proposed method can overcome the difficulties of the existing impedance-based islanding detection techniques like larger non-detection zone (NDZ), false detection during load switching etc. The effectiveness of the proposed method is tested in a six bus microgrid system and comparison with other existing islanding detection techniques reveals the fact that the proposed method has much better performance in terms of improved detection accuracy, detection speed, and it also significantly reduces the NDZ.

This study deals with a fault-tolerant control of a smart PV-grid plant. The small scale system is dedicated to a stationary alternative current load and it consists of a photovoltaic module, supported by a single-phase grid. To ensure a smart permutation between the two proposed operation modes, a fuzzy logic-based power management algorithm is designed and implemented. In case of a sub-system failure, a fault-tolerant control technique is adopted to maintain the service continuity. In this study, two scenarios are proposed. The first concerns a load current sensor failure, where a material redundancy is adopted through the use of two observers, selected via a voting algorithm. The second deals to sense the system ability to maintain the service continuity in the worst case, where a grid black-out (grid-off) is planned. In this scenario, an additional functioning mode is added to reconfigure the control strategy. To prove the effectiveness of the proposed algorithms, the obtained experimental results with a given load profile are presented and commented.

Under the low-voltage ride-through (LVRT) of the doubly fed induction generator, extra efforts are required for the model predictive control (MPC)-based direct stator/rotor current controls (DSCC/DRCC) against the stator flux oscillation. Constant stator/rotor currents are maintained at the cost of rotor/stator current oscillations, respectively, due to stator flux oscillation. Necessity to incorporate the stator flux transient in the MPC-based DSCC/DRCC under the LVRT is analysed based on tracking effects of the current references. To quantify LVRT effect with the MPC-based DSCC/DRCC, analytical expressions of the stator current, rotor current and rotor voltage are proposed, whose accuracy is validated based on comparison with the time-domain simulations. On the basis of analytical study, advantages and disadvantages of the DSCC/DRCC are analysed considering impacts of the current oscillations on the security of the rotor-side converter. With the DRCC, rotor voltage increase is suppressed with damping to the stator flux oscillation and rotor current constraint is satisfied without decreasing stator output power; thus, the LVRT effect is desirable compared with the DSCC. The MPC-based DSCC/DRCC is extended to LVRT under the asymmetrical fault to realise effective control to both the positive and negative sequence stator/rotor currents.

As the ocean environment is more complex than the land environment, the offshore wind turbines especially the floating types generally suffer significant structural loads. In this study, in order to carry out the accurate simulation and analysis for the dynamic characteristics of a barge-type floating wind turbine, a detailed turbine model including the complete drivetrain is constructed. Additionally, the structural responses of the wind turbine are mitigated by using a single-degree of freedom tuned mass damper (TMD) system installed in the platform. In order to achieve the ideal response mitigation effect, a parametric study on the TMD configuration is carried out. Based on a new co-simulation model combining multi-body model and external control codes, the turbine model coupled with the TMD is then simulated under the combined wind and wave. The results demonstrate the effectiveness of the designed TMD on mitigating the structural responses of the barge-type floating wind turbine.

Increased installed capacity of distributed photovoltaic (PV) systems has necessitated accurate measurement and tracking of PV performance under locality-specific conditions of irradiance, temperature, and derate factors. Existing PV generation estimation methods are strictly model based and not responsive to changes in weather and system losses. Metrics computed using these methods, therefore, do not capture the real PV behaviour well. This study proposes a hybrid data-model method (HDMM) that uses historical PV data in addition to model information to improve the accuracy of generation estimation. The generation estimated by HDMM is used to compute performance metrics – performance ratio, yield, capacity factor, energy performance index, and power performance index – for two real-world PV systems at Miami (, 1.4 MW) and Daytona (, 1.28 MW) for 2017. The significance of these metrics is then evaluated, and a preliminary analysis of inverter efficiencies is provided. Results from this study show that when compared with the existing estimation method, HDMM performs better on an average by 75% for and 10% for . Further, at a given point in time, system is likely to perform better than . The study gives system installers and other stakeholders better PV system visibility, enabling aggregation and transactive energy.