The rapid development of photovoltaic (PV) systems in electrical grids brings new challenges in the control and operation of power systems. A considerable share of already installed PV units is small-scale units, usually connected to low-voltage (LV) distribution systems that were not designed to handle a high share of PV power. This study provides an in-depth review of methods and strategies proposed to prevent overvoltage in LV grids with PV and discusses the effectiveness, advantages, and disadvantages of them in detail. On the basis of the mathematical framework presented in this study, the overvoltage caused by high PV penetration is described, solutions to facilitate higher PV penetration are classified, and their effectiveness, advantages, and disadvantages are illustrated. The investigated solutions include the grid reinforcement, electrical energy storage application, reactive power absorption by PV inverters, application of active medium-voltage to LV transformers, active power curtailment, and demand response. Coordination between voltage control units by localised, distributed, and centralised voltage control methods is compared using the voltage sensitivity analysis. On the basis of the analysis, a combination of overvoltage prevention methods and coordination between voltage control units can provide an efficient solution to increase the PV hosting capacity of LV grids.

This study presents the analysed result of wind–diesel system with the consideration of real power-frequency control, reactive power-voltage control as well as cross-coupling between reactive power-frequency and real power-voltage control. The system under study uses synchronous generator (SG) for diesel generator and induction generator (IG) for wind generation systems. The mathematical model of the system with both direct and cross-coupling effect is derived to simulate the behaviour of the wind–diesel system. The classical control technique and eigenvalue, participation factor matrix is used to study the strength of the direct and cross-coupling effect, in the studied system. The simulated responses of the system under various types of disturbances are presented to show the cross-coupling effect in the wind–diesel system. System performances under interconnected mode of operation is also studied.

Microgrids (MGs) and their enabling technologies (e.g. small-scale renewable energy generation, energy storage systems, demand response, and information and communication systems) have attracted increasing attention in the past few years as they are expected to play an important role in future sustainable energy systems. There is a significant research gap in how to plan and manage energy systems with growing numbers of MGs. In this study, an energy system expansion planning (EP) model is used to investigate the quantitative impacts of MGs on energy system sustainability. The EP design problem is formulated as a multi-objective optimisation problem with a range of technical constraints such as AC power flow, reliability, and power quality constraints, as well as including variable and fixed costs. Several case studies are undertaken on electricity networks in New South Wales, Australia. The results confirm that MGs can significantly improve a system's efficiency. However, this efficiency improvement is influenced by factors such as the ratio of the MG participation, the network topology, and other specific power system constraints.

The study evaluated the capability of current thermal generation to back-up variation generation from solar energy penetration into the Nigerian power grid from a system operation perspective using security constraint unit commitment model. This provides an empirical evidence of the impacts that can tip the balance towards a sustainable future low carbon electricity mix. Through 10 and 20% solar energy penetration scenarios, greenhouse reduction of 1975.70 and 3590.03 lb/day, respectively, can be achieved. However, daily peak-valley net demand difference to be supplied by the thermal plants will increase from 702.5 to 857.5 and 1607.5 MW, numbers of daily start-up will increase from 23 to 30 and 25, daily system spinning reserve will increase from 723 to 757 and 815 MW and daily idle hours of the thermal plants will increase from 52 to 71 and 72 h, in a 10 and 20% solar energy integrated system, respectively. The daily operational revenue of the thermal plants will also reduce by 5.5 and 7.9% in a 10 and 20% solar energy integrated system, respectively. These are useful data in developing policy framework for the future electricity market as the country diversify her energy source and mitigate greenhouse effect.

Photovoltaic (PV) systems are prone to irradiance fluctuations caused by overpassing cloud shadows which can be very large and steep. Cloud shadows have an average diameter of almost 1 km meaning that even the largest PV power plants are widely affected by them. Fast irradiance transitions can lead to failures in maximum power point tracking and to mismatch power losses due to partial shading of the PV generator. In this study, the effects of irradiance transition characteristics: shading strength, duration and apparent speed and direction of movement on the mismatch losses of PV generators were studied by simulations using a mathematical model of irradiance transitions and an experimentally verified MATLAB Simulink model of a PV module. The studied electrical PV array configurations were series–parallel, total-cross-tied and multi-string. Furthermore, three different physical shapes of the configurations were studied. On the basis of the results, module strings of PV arrays should be placed perpendicularly to the dominant apparent direction of movement of shadow edges and the diameter of the strings should be minimised to decrease the mismatch losses. Another finding of practical importance was that there were only minor differences between the mismatch losses of different electrical PV array configurations.

This study presents a method for regulation parameters of a distributed generation (DG) system by means of a hybrid optimisation algorithm. This aims in increasing the stability and reducing the losses and the cost of generation. The hybrid algorithm which includes probability based incremental learning and micro genetic algorithm are tested among other computational intelligence techniques to validate the efficiency of the method by maximising the total social welfare and minimising the network congestion. Simultaneous optimisation of DG parameters which includes DG size, location and type is explored using generation rescheduling and with load curtailment which is vindicated on a modified IEEE distribution system and in a real time Indian utility system. Results show us that the proposed method presents advantages of low computational complexity.

This study investigates the application of a robust method to solve the problem of security constrained unit commitment (SCUC) with flexible resources for managing the uncertainty of significant wind power generation (WPG) to sustain the load-generation balance. The flexible resources include up/down ramping capability of thermal units, hourly demand response, energy storage system and transmission switching action through an integrated scheme. The application of mixed-integer linear programming to deal with the SCUC problem with flexibility resources has been discussed in this study using information-gap decision theory (IGDT) to realise a robust strategy for power system decision maker. Besides, this study proposes an effective solution strategy based on Benders' decomposition to solve the proposed problem. Numerical simulation results on the modified six-bus system and IEEE 118-bus system clearly demonstrate the benefits of applying flexibility resources for managing the WPG uncertainty and validate the applicability of the proposed IGDT-based SCUC model.

With the rapid development of distributed generations (DGs) and interruptible loads (ILs), distribution network company can actively purchase electricity in market instead of playing as a traditional passive purchaser. This study proposes a stochastic bi-level model-based strategic trading model for an active distribution company (ADisCo) which operates the active distribution network (ADN) to maximise its profit in electricity market. Uncertainties pertaining to bidding and offering prices of other market rivals’, the imbalance prices in the balance market and the productions of DGs are considered via stochastic programming. Besides, a linear ADN operation model is proposed to ensure ADN operation security within the stochastic programming model. The proposed model is initially formulated as a stochastic bi-level model, where the upper-level problem represents the maximisation of the profit of ADN operator, whereas the lower-level model represents the maximisation of the social welfare in clearing of market from the perspective of independent system operator. On the basis of the complementarity theory, the proposed model can be transformed into a mixed integer linear programming model. Case studies demonstrate the efficiency and effectiveness of the proposed strategic trading model for an ADisCo with DGs and ILs.

The brush and slip ring system is an important part of excitation system in doubly-fed induction generators, but the excitation instability caused by the surface damage of slip ring often occurs, which brings a great security trouble to the stable operation in the generator. To solve this problem, the method that the vibration signal is used to carry out diagnosis of slip ring surface in different fault states was proposed. First, the principle based on vibration, the transmission route and failure mechanism of the slip ring were analysed. Then, the experiment platform of the brush and slip ring was set up; the real-time vibration signal was collected before and after fault; the wavelet energy spectrum was applied to the vibration signal processing. The abnormal vibration band was found by the contrast and proportion analysis of the wavelet energy spectrum distribution of vibration signals before and after fault, which can be the basis for fault diagnosis of the slip ring device.

Wind–diesel power systems (WDPS) are isolated microgrids which combine diesel generators (DGs) with wind turbine generators (WTGs). The WDPS modelled in this study consists of one 275 kW-WTG, one 300 kVA-DG, a 240 V/390.625 Ah Ni–MH battery energy storage system (BESS) and consumer load. The WDPS working modes considered are: Wind Diesel (WD) mode where both the DG and WTG supply power and wind-only (WO) mode where only the WTG produces active power. First, the dynamic models of the enumerated WDPS components are described. Then, WDPS control requirements in WD and WO modes are studied and a control system to govern the consumed/supplied BESS active power is presented. Finally, the WDPS is simulated and graphs of the system frequency and voltage, active power in each component and the battery current/voltage/state of charge are shown. The simulations cover: the WD mode, where it is shown that the BESS filters the load and WTG power variations and avoids a DG reverse power situation, the WD to WO mode transition where the BESS makes possible a bumpless transition and the WO mode where the BESS regulates the system frequency. Simulations demonstrate that the BESS increases the WDPS stability, reliability and security.

Several studies have been published considering fuel cell (FC) operation in normal conditions; but few of them addressed their operation under fault conditions. Among fault detection methods, a simple method based on the variable behaviour analysis is introduced. Basically, a fault supervisor is responsible for analysing unexpected changes in some variables, since each change in the variable behaviour can be attributed to a pre-classified fault cause, and then a fault diagnosis can be performed. The diagnosis considers several types of faults in polymer electrolyte membrane FC: faults in the reaction air feeding, rupture of the membrane-electrode assembly, low pressure in the hydrogen fuel line, and fault refrigeration system; those faults are detected based on the monitoring of a limited number of variables. Tests show that the methodology is reliable, flexible (once it permits the addition of other fault detection modules) and easy for implementation.

Doubly fed induction generator (DFIG) based wind turbines are sensitive to grid faults due to utilising small-scale rotor side converter (RSC). The application of crowbar protection to improve the fault ride-through (FRT) capability of the DFIG converts it to a squirrel cage induction generator, which makes it difficult to comply with grid codes. This study proposes an innovative DC-link controllable fault current limiter (C-FCL) based FRT scheme for the RSC to improve the FRT capability of the DFIG. The proposed scheme replaces the AC crowbar protection and eliminates its disadvantages. The C-FCL does not affect the normal operation of the DFIG. By means of the proposed scheme, rotor over-currents are successfully limited during balanced and unbalanced grid faults, even at zero grid voltage. Also, the C-FCL prevents rotor acceleration and high torque oscillations. In this study, an analysis of the proposed approach is presented in detail. The performance of the proposed scheme is compared with the conventional crowbar protection scheme through simulation studies carried out in power system computer-aided design/electromagnetic transients, including dc software (PSCAD/EMTDC). Moreover, the main concept of the proposed approach is validated with an experimental setup and test results are presented.

A grid tied photovoltaic (PV) power conversion topology is presented in this study with a novel scheme of re-synchronisation to the grid. This scheme serves the purpose of supplying continuous power to the load along with feeding power to the grid. The control approach helps in mitigation of harmonics and improving the power quality while extracting the optimum power from the PV array. Depending on the availability of grid voltage, the proposed configuration is controlled using three approaches, defined as grid current control, Point of Common Coupling (PCC) voltage control and intentional islanding with re-synchronisation. A simple proportional integral controller manages the grid current, load voltage, battery current and DC Direct Current (DC) link voltage within these modes. Moreover, a control scheme for quick and smooth transitions among the modes is described. The robustness of the system under erratic behaviour of solar insolation, load power and disturbances in grid supply makes it a suitable choice for a residential application. The control, design and simulation results are presented to demonstrate the satisfactory operation of the proposed system.

Contribution to the damping of inter-area and torsional oscillation modes, in doubly fed induction generators (DFIG) based wind farms, by power oscillation damping controllers (PODCs) based on two conventional structures and a fuzzy control strategy is investigated in this study. In this regard, a PODC with no lead/lag compensation is designed first and then a PODC with one lead/lag block is developed using eigenvalue techniques and the application of an iterative process based on the bat optimisation algorithm (BOA). Moreover, a fuzzy PODC, based on a simple fuzzy controller and tuned with the BOA according to the system transient response under a critical perturbation, is also designed. Comparative performance of the three PODCs is evaluated on a multi-machine power system. It is observed that all three PODCs can contribute to improving the damping of inter-area oscillations. However, eigenvalue analysis and non-linear time domain simulations reveal that each of them may also impact to a lesser or greater extent the shaft torsional oscillation mode damping. Their relative impact in this regard is also investigated.

This study investigates the performance of solar powered organic Rankine cycle (ORC) system. Parabolic trough collector PTC is utilised in this study. The selected site is located in the northern part of Jordan. Simulation models are built to assess the performance of system. The simulation models are built by means of mass and energy balances applied to every component of the system. The model simulates the hourly thermal behaviour of all system components. Different working fluids are compared. The effect of key operating variables on the system performance is examined. Simulation results show that there is an optimum values for mass flow rate, and inlet turbine pressure for each months. For the working fluid studied, the average daily overall efficiency ranges between 9 to 22% during summer time. The comparison between working fluids showed that the most efficient fluid is Butane. The optimal daily average overall efficiency reaches 18%. It is found that using PTC of area of 617 m² with ORC is reliable system producing above 80 kW during summer time. Mass flow rates have major effect on the cost of energy production. Furthermore, this study presents design optimisation so that solar thermal power plant can achieve higher reliable continuous operation with system components.

This study presents a fuzzy logic approach for reactive power coordination in grid connected wind farms with different types of wind generator units to improve steady state voltage stability of power systems. The load bus voltage deviation is minimised by changing the reactive power controllers according to their sensitivity using fuzzy set theory. The proposed approach uses only few controllers of high sensitivity to achieve the desired objectives. The 297-bus and 417-bus equivalent grid connected wind systems are considered to present the simulation results. To prove the effectiveness of the proposed approach, a comparative analysis is carried out with the conventional linear programming based reactive power optimisation technique. Results demonstrated that the proposed approach is more effective in improving the system performance as compared with the conventional existing technique.

In this study, adaptive control is used to damp network subsynchronous oscillations via doubly fed induction generator (DFIG)-based wind turbines. With an increase in wind power penetration in power systems and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. One of the important issues in regards to the stability of power systems are the subsynchronous oscillations. Damping subsynchronous oscillations using wind turbines has been studied in various research effort, mainly by adding a supplementary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this study, adaptive control is used for this purpose. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in network subsynchronous oscillations damping at different wind speeds and system operating points, as shown in this study. It is also shown that this controller has an insignificant effect on the dynamic performance of the wind turbine, itself.

Unity power factor injection from single-phase photovoltaics (PVs) located towards the end of a residential feeder leads to voltage rise problems. Also, unbalanced current injection due to variable solar insolation results in voltage unbalancing and makes the situation worst. A decoupled controller for a single-phase PV inverter is proposed to improve the voltage profile of the distribution feeders. The proposed controller consists of the following components: voltage regulator (to control the amount of reactive power injection), outer voltage control loop (slow controller to set the reference for the inner current loop), inner current control loop (to control the PV inverters) and modified second-order generalised integrator (to generate fundamental frequency). A sample distribution systems consisting of several PVs located in all three phases and a three-phase induction motor load is considered. The real-time hardware-in-the-loop simulations are performed to test the efficacy of the proposed controller scheme. Results show the improvement in voltage regulation of different buses.

Wind energy integration into microgrids, has introduced new challenges to energy management systems because of its intermittent behaviour. Owing to continuous changes in generation and consumption, the energy price is volatile. This study proposes a new two-stage stochastic framework for day-ahead scheduling of microgrids. Uncertainties associated to wind power generation, real-time electricity price and load demand are considered. Different scenarios are generated using autoregressive moving-average method and then are reduced using fast-forward technique. On the first stage, the microgrid master controller determines the procured energy from the day-ahead market and commitment states of distributed energy resources (DERs). In the second stage, the purchased energy from the real-time market and schedules of committed DERs are obtained. The problem is modelled using mixed-integer linear programming approach and is solved via CPLEX^® optimizer. Both grid-connected and stand-alone modes of operation are investigated. Despite of high operation cost in island mode, coordination of energy storage systems, incentive-based and price-based demand response (DR) programmes affect economy of microgrids. The framework is examined on a test microgrid. Results show that both of the releasing the microgrid master controller authority and DR resources result in significant saving in operating; especially in emergency conditions such as islanded mode.

The power control of small-scale wind energy conversion system is usually limited by the sluggish mechanical dynamic. Aiming at highlighting this phenomenon, this article introduces a small-scale wind energy conversion system using the permanent magnet synchronous machine as generator to validate different combinations of control strategy resulting from four different maximum power point tracking (MPPT) methods with hysteresis control: one indirect MPPT method based on a look-up table and three direct methods based on perturb and observe relationship. Following two ideal wind speed profiles, a real rapid wind speed profile and using a test bench emulating a small-scale wind turbine, the MPPT methods are compared and analysed based on experimental results. The indirect method operates with the best MPPT performances for all three wind speed profiles while requiring accurate knowledge of the controlled system. The direct methods operate with low MPPT performance under rapid variation of wind speed and the superiority of variable step size is not significant since the dynamic process of the perturbation strongly weakens the effect of MPPT algorithm.

An intelligent wind power smoothing control using recurrent fuzzy neural network (RFNN) is proposed in this study. First, the modeling of wind power generator and the designed battery energy storage system (BESS) are introduced. The BESS is consisted of a bidirectional interleaved DC/DC converter and a 3-arm 3-level inverter. Then, the network structure of the RFNN and its online learning algorithms are described in detail. Moreover, actual wind data is adopted as the input to the designed wind power generator model. Furthermore, the three-phase output currents of the wind power generator are converted to dq-axis current components. The resulted q-axis current is the input of the RFNN power smoothing control and the output is a gentle wind power curve to achieve the effect of wind power smoothing. The difference of the actual wind power and smoothed power is supplied by the BESS. The minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the RFNN power smoothing control. A digital signal processor (DSP) based BESS is built using two TMS320F28335. From the experimental results of various wind variation sceneries, the effectiveness of the proposed intelligent wind power smoothing control is verified.

Power optimisation is quite important for the doubly-fed induction generator (DFIG)-based variable speed wind turbine (VSWT) in the modern renewable power generation system. However, the VSWTs are generally non-linear and uncertain systems. This study proposes a super-twisting second-order sliding mode (SOSM) control scheme to maximise the wind energy capture of a DFIG-based VSWT system, and regulate the stator reactive power to follow the grid requirements. By regulating the generator rotor voltage, the designed SOSM controller makes the wind turbine rotor speed track the optimal speed to maximise the power generation, and controls the rotor current to follow the external reference to regulate the stator reactive power. A quadratic form Lyapunov function is adopted to determine the range of controller parameters and guarantee the finite time stability. Simulation results on a 1.5 MW DFIG-based VSWT demonstrate the effectiveness of the proposed control strategy.