Recent advances in renewable energy technologies and changes in the electric utility infrastructures have increased the interest of the power utilities in utilisation of distributed generation (DG) resources to generate electricity. The recent trends in the development and utilisation of DG resources for power generation application are subject to the deregulation of the electric power sector and technical constraints to extend distribution and transmission networks to some areas. The electric power system planners, regulators and the policy makers have derived many benefits from integration of DG units into the distribution networks. These benefits depend on the characteristics of DG units such as photovoltaic (PV), wind system and reciprocating engines, characteristics of the loads, local renewable resources and network configuration. This study comprehensively reviews various research works on the technical, environmental and economic benefits of renewable DG integration such as line-loss reduction, reliability improvement, economic benefits and environmental pollution optimisation. These benefits can be optimised if all the renewable DG units are optimally sized, located and configured. This study also reviews the current status of renewable DG technologies based on different characteristics and the operational issues of integration of renewable DG into the electric power systems.

Power generation from renewable energy resources is on the increase in most countries, and this trend is expected to continue in the foreseeable future. In an effort to enhance the integration of renewable power generation from solar and wind into the traditional power network, there is need to address the vulnerabilities posed to the grid as a result of the intermittent nature of these resources. Variability and ramp events in power output are the key challenges to the system operators due to their impact on system balancing, reserves management, scheduling and commitment of generating units. This has drawn the interest of utilities and researchers towards developing state of the art forecasting techniques for forecasting wind speeds and solar irradiance over a wide range of temporal and spatial horizons. The main forecasting approaches employ physical, statistical, artificial intelligence and hybrid methodologies. This study provides the rationale for forecasting in power systems, a succinct review of forecasting techniques as well as an assessment of their performance as applied in the literature. Also, techniques for improving the accuracy of forecasts have been presented together with key forecasting issues and developing trends.

In this study, the control objectives such as maximum power point tracking (MPPT), synchronisation with grid and current control are realised for single-stage utility-scale photovoltaic (PV) system which is also capable of injecting the reactive power into the grid. For utility-scale PV system, the single-stage scheme is used for high efficiency and simple power converter topology. The proposed MPPT approach utilising a modified particle swarm optimisation method is interrelated with other control schemes. The MPP changes with variation in solar irradiation and temperature. Also, the PV power characteristic of large system is characterised by multiple peaks under partial shaded condition. The conventional methods such as hill climbing and incremental conductance methods do not work properly in these conditions. The proposed method is suitable to all conditions with reduced steady-state fluctuations. The overall system is simulated in PSCAD and the effectiveness of the proposed method is tested on various conditions.

The load and hydrogen pressure changes in a proton exchange membrane fuel cell (PEMFC) result in instability and reduce the efficiency of the output power. This study proposes an extension sliding mode controller (ESMC) for maximum power point tracking (MPPT) of the fuel cells to enhance system efficiency and to reach the steady state of the output power. The experimental platform is set at a 200-watt PEMFC in this study. Results show that the tracking speed of the ESMC is 0.95 s, and the booster conversion efficiency is 94.5%; both are superior to other conventional MPPT methods. This study demonstrates a number of key technologies for renewable energy systems.

Differential-mode inverter topologies are promising for renewable energy generation since they offer advantages such as passive elements sizes reduction, having decreased power losses and reduced total cost. Single phase buck–boost differential-mode current-source inverters (DMCSIs) can deliver wider range of output voltage above or below the input dc voltage, which is necessary for high-efficiency modern renewable energy applications. Since these inverters have continuous input currents, they are suitable for maximum power point tracking (MPPT) operation of photovoltaic systems. Yet, the investigation, operation and implementation of these types of inverters have not been extensively discussed. As a drawback, the total dc side input current of a single-phase inverter consists of a dc component and an undesirable ac component. This ac component frequency is double the output voltage frequency and thus it affects MPPT resulting in reduced total efficiency. In this study, five promising DMCSIs are proposed and compared in terms of their total efficiencies, high-frequency ripple current in the dc side, total harmonic distortion, devices sizes and ratings. Moreover, the sliding mode controller's design and possible methods of eliminating the input second harmonic current are discussed. 2.5 kW bidirectional inverters are implemented to confirm the design flexibility of the proposed DMCSIs.

This study presents a control algorithm of a grid tied solar photovoltaic (PV) system using a dual reference phase shifted pulse width modulation technique for a single-phase cascaded N-level inverter. The grid tied inverter consists of several five-level hybrid inverter modules which are connected to the solar PV panels having equal DC voltage magnitudes. The proposed control technique for the multilevel inverter generate the near-sinusoidal current with near-unity power factor to the grid and balance the capacitor voltages across the DC links. The voltage and frequency of the multilevel inverter can be adjusted using closed loop control, such that, the maximum power flow to the grid can be achieved even under varying grid voltage. The performance of the complete system has been verified under different transient states. Experimental results verify the effectiveness of the proposed technique.

Price-elastic load (PEL) is a typical demand response resource. PEL provides an effective option to address the challenge of wind power output fluctuation. This study proposes a stochastic scheduling model, considering uncertainties of variable wind power and PEL response. A PEL stochastic security-constrained economic dispatch model using chance-constrained programming is presented for scheduling. The authors propose that the chance-constrained transmission interface flow constraints should be considered to control the probability of transmission interface flow limit violation via the parameter of security probability. An approach is suggested to transform the stochastic model into a deterministic quadratic programming problem via linearising the branch flow constraints and transmission interface flow constraints with sensitivity analysis method. Then, the probabilistic transmission interface flow constraints are equivalently transformed into conventional constraints. Case simulations on a provincial power system with 151 buses demonstrate the effectiveness and feasibility of the proposed mechanism, models, and methods.

This study proposes a probabilistic multi-objective optimisation method for the operation of three-phase distribution networks incorporating active network management (ANM) schemes including coordinated voltage control and adaptive power factor control. The proposed probabilistic method incorporates detailed modelling of three-phase distribution network components and considers different operational objectives. The method simultaneously minimises the total energy losses of the lines from the point of view of distribution network operators and maximises the energy generated by photovoltaic (PV) cells considering ANM schemes and network constraints. Uncertainties related to intermittent generation of PVs and load demands are modelled by probability density functions (PDFs). Monte Carlo simulation method is employed to use the generated PDFs. The problem is solved using ɛ-constraint approach and fuzzy satisfying method is used to select the best solution from the Pareto optimal set. The effectiveness of the proposed probabilistic method is demonstrated with IEEE 13- and 34-bus test feeders.

All the sources are required to supply the scheduled power to the system as directed by the system operator, within a time frame of operation. The fluctuating nature of wind makes supplying the scheduled power a challenging task. To address this, gas turbines are proposed to augment the wind generator to work as buffer owing to their high ramping capability. However, the cost of gas turbine increases with increased ramp rates, whereas, operating efficiency and the life time decreases. Hence, to relieve the buffering gas turbines from higher ramp rate requirements, emulation of inertia of the wind generator is proposed in this paper. The controller is designed to operate in inertia emulation mode whenever there is a retardation of rotor of the wind turbine and the proposed ramp controller will be in action only for first few seconds after the fall in wind speed. While emulating the inertia, the performance of the proposed control philosophy with different ramp rates is investigated in this paper. Guide lines for the selection of the ramp duration and ramp rate for seamless transition from inertia emulation mode to maximum power extraction mode are also suggested in this paper.

This study presents a wind–solar photovoltaic based standalone hybrid energy system (HES) for an un-electrified village for central region of India – Madhya Pradesh. The inputs for the designing of HES are wind speed, solar radiation, temperature and the load demand which are variable with respect to time. In this study, hourly values of meteorological data and hourly load demand are considered over a year. For sizing and performance analysis of this standalone HES, ant colony optimisation technique has been used. The performance analysis of the system is done for the various parameters such as total cost of the system, power generated by various sources, state of charge of battery, contribution of various sources, continuity of supply to the load demand and unmet load. The obtained optimal configuration of the proposed HES is found to provide minimal energy cost with excellent performance and reduced unmet load.

A control strategy is formulated for photovoltaic generators (PVG) operating in parallel in a Microgrid. A radial microgrid is considered and when it is isolated from the utility grid, the PVG's must operate in the voltage-frequency control mode in the absence of a storage or a diesel generator unit. It is observed that the conventional P-f and Q-v droop control method fails to deliver correct power references for inverters operating in parallel when network impedance is unequal, and therefore an active power-reactive power-frequency-derivative (PQFD) droop control is proposed to achieve an error free power sharing. Seamless operation from the grid connected mode to isolated mode and vice-versa is achieved with the help of the aforementioned control, which in addition assists in the alleviation of sluggish response in the presence of Induction motor (IM) loads by providing appropriate damping. For a transient free transfer from isolated mode to grid connected mode, a synchronisation control is formulated which helps in the proper reconnection. The controller designed is tested in both Microgrid and the grid connected mode and during transition. The controller gains used in the paper have been obtained with the help of a small signal analysis of the system considered.

An improved differential evolution (IDE) algorithm-based Elman neural network (ENN) controller is proposed to control a squirrel-cage induction generator (SCIG) system for grid-connected wind power applications. First, the control characteristics of a wind turbine emulator are introduced. Then, an AC/DC converter and a DC/AC inverter are developed to convert the electric power generated by a three-phase SCIG to the grid. Moreover, the dynamic model of the SCIG system is derived for the control of the square of DC-link voltage according to the principle of power balance. Furthermore, in order to improve the transient and steady-state responses of the square of DC-link voltage of the SCIG system, an IDE-based ENN controller is proposed for the control of the SCIG system. In addition, the network structure and the online learning algorithm of the ENN are described in detail. Additionally, according to the different wind speed variations, a lookup table built offline by the dynamic model of the SCIG system using the IDE is provided for the optimisation of the learning rates of ENN. Finally, to verify the control performance, some experimental results are provided to verify the feasibility and the effectiveness of the proposed SCIG system for grid-connected wind power applications.

This study presents an inverse hyperbolic secant function based islanding detection technique for distribution network containing various types of distributed generations. The proposed scheme is based on rate of change of inverse hyperbolic secant function of negative sequence voltage signal. Different non-islanding events along with various islanding conditions have been simulated by modelling IEEE 34-bus system using PSCAD/EMTDC software package. The proposed scheme is able to detect islanding condition even with zero active and reactive power mismatches. Moreover, it eliminates non-detection zone completely and at the same time also remains stable during diversified non-islanding events including change in network topology. The simulation results indicate that the proposed scheme not only detects islanding condition rapidly, but also provides better stability in case of critical non-islanding events during which most of the existing schemes issue nuisance tripping. Furthermore, comparative evaluation of the proposed scheme with the recently proposed techniques in the literature clearly indicates superiority of the proposed scheme. At the end, issues related to practical implementation of the proposed scheme have also been discussed.

In recent years, multi-crystalline solar grade silicon (mc-SoG-Si), instead of expensive electronic-grade Si, is being considered in photovoltaic industry for production of solar modules. These materials usually contain a comparable amount of acceptors (e.g. boron) and donors (e.g. phosphorus) and are therefore called compensated mc-SoG-Si. The electrical parameters, e.g. majority carrier mobility (μ), majority carrier density (p) and resistivity (ρ), of compensated mc-SoG-Si which affect performance of the solar cells vary non-linearly with temperature due to several complex mechanisms. In this study, the authors propose artificial neural network (ANN)-based models to predict the three electrical parameters of mc-SoG-Si material. Using a limited amount of measurement data, the authors have shown that the ANN-based models can predict the three electrical parameters of a given sample over a wide temperature range of 70–400 K and a specific range of compensation ratio. The authors have shown with extensive simulated results that these models can predict the three parameters with a maximum error of ±10%.

Integrating cooling systems with photovoltaic (PV) modules represents a very important aspect of keeping modules within acceptable operating temperatures. The objective of this study is to analyse the performance of each series-connected PV cell in photovoltaic thermal (PVT) modules. The importance of this analysis is due to the consideration of the variable operating temperature values of the PV cells, resulting in a different performance of each PV cell. The PVT modules are cooled with water serving as both a heat sink and a solar heat collector. This enhances the electrical efficiency value of the PVT modules by preventing them from elevated temperature values, while the recovered thermal energy can be utilised to increase the overall PV effectiveness. The new consideration in this study over the existing ones is the temperature distribution of each PV cell is applied for the calculation of the current voltage characteristics of the PV modules, which makes the analysis more accurate. The variance in the temperature values is a result of the temperature gradient of the fluid flowing through the pipes where the heat exchange differs in the flow direction. The potential of this study becomes more important for countries of high ambient temperatures and high solar intensity.

This study analyses the voltage dip behaviour of the doubly-fed induction generator (DFIG) connected to a common dc link on both the stator and rotor sides, via a diode bridge and a voltage source inverter (VSI), respectively. After a voltage dip in the dc grid, the rotor VSI can transiently lose control so that rotor currents circulate through the VSI free-wheeling diodes. However, during the uncontrolled period, both stator and rotor voltages are clamped to the same dc-link voltage and no rotor overvoltage occurs. In order to analyse the behaviour of the system during the first periods of the uncontrolled current transients, this study presents a simplified average model which is validated through simulations. Voltage dips are classified into three types depending on their severity. A simple analytical expression is derived for the maximum amplitude of the current during the voltage dip, and an overcurrent chart in the plane ‘rotor speed – dip amplitude’ is deduced. These results provide deep insight into the DFIG-DC system behaviour and are useful for design purpose.

The three-phase quasi-Z-source AC–DC converter possesses many attractive attributes for applications with wide AC input variations, such as variable speed wind generator applications. This is due to its buck–boost capability, high input power factor, low output ripple and low rating of components. Detailed steady-state and small-signal models of the converter are derived using circuit averaging and the synchronous reference frame. From the steady-state model, it is shown that the three-phase quasi-Z-source rectifier (QZSR) has all the advantages of the three-phase Z-source rectifier (ZSR) as well as further advantages such as lower rated capacitors. The small-signal model reveals that the QZSR has non-minimum-phase zeroes in its control-to-output voltage and control-to-inductor L ₁ current transfer-function similar to the ZSR. Right-half-plane zeroes tend to limit the maximum control bandwidth and destabilise the wide-bandwidth feedback loop. The key elements in the design of a closed-loop controller, namely, the transfer functions and the block diagram models are derived. Simulations and experimental results are presented to validate the models developed.

Doubly fed induction generators (DFIGs) are widely used in wind power systems; hence their reliability model is an important consideration for production assessment and economic analysis of wind energy conversion systems. However, to date mutual influences of reliability analysis, production estimations and economic assessments of wind farms have not been fully investigated. This study proposes a reliability model for DFIG wind turbines considering their subcomponent failure rates and downtimes. The proposed production estimation algorithm leads to an economic assessment for wind farms. A comprehensive spare parts management procedure is then presented in the study. As a case study, practical data from a prominent wind farm is used and the procedure of the study is verified.