To exploit the full and flexible capability of offshore voltage-sourced converter high-voltage DC (VSC-HVDC) lines, interaction studies in the offshore AC grid are required but are not well understood or reported. This study examines the interaction dynamics of an offshore AC grid for interconnecting large wind power plants (WPPs). The conventional eigenvalue analysis method has limitations which make the interaction analysis of such systems difficult. Hence, in this study, an impedance-based analytical approach is employed to investigate the interaction phenomena. The impedance model of a VSC-HVDC converter for both direct and vector control with outer and droop controls are derived along with the impedance model of the full-converter wind generator. The interaction dynamics of the offshore grid is predicted through the well-established Nyquist criteria and is validated using time-domain simulations. The analysis shows that the system stability is decidedly influenced by the control configurations and tuning of the VSC-HVDC lines.

The utilisation of renewable sources brings many benefits to electric power systems, but also some challenges such as the impact that renewable power plants employing power electronics have on the grid, which is gaining importance as the penetration of this type of generating stations increases, driven by the construction of large wind or solar photovoltaic (PV) power plants. This study analyses the impact of large-scale PV power plants on a transmission grid for different penetration levels. The analysis considers power plants formed by a number of power converters employing synchronous power controllers (SPCs), that allow them to have a harmonious interaction with the grid, and compares their performance with that of conventional power converter controllers, assuming in both cases that the power plants participate in frequency and voltage regulation. The study addresses both the small-signal stability of the system and its response to large disturbances that alter the active power balance and frequency stability. The results of the analysis show that PV power plants using SPCs are able to limit frequency deviations, improve the oscillation damping, and reduce the stress of other generating units, thus having a beneficial impact on the power system.

A distributed generator (DG) based on renewable energy is a promising technology for the future of the electrical sector. DGs may benefit utility companies and customers in a variety of perspectives. However, DGs suffer from intermittent behaviour. Storage systems appear as an attractive solution to support the continuous operation of DGs. The technology within the storage also plays an important role, since DGs and storage are connected in medium-voltage grids. The use of batteries and the DC/AC converter in its conventional structure presents drawbacks in such grids. In this context, this study presents a three-phase transformerless battery storage system (BSS) based on a cascaded H-bridge inverter applied to a medium-voltage grid. The BSS is composed of eight equal series connected H-bridge converters, without bulk transformers, for connection to a distribution grid. Each converter contains 75, 12 V/600 Ah lead-acid batteries. The converters are controlled through pulse-width modulation at 600 Hz. The BSS is able to keep working even with a failure of one of its converters. Reactive energy compensation not compensated by an existent passive filter is also performed. A case study with simulated and experimental results obtained through a hardware-in-the-loop system is presented showing the efficacy of the proposed BSS.

Reactive power analysis of an autonomous hybrid energy system consisting of dish–Stirling solar thermal system (DSTS), diesel engine generator and static VAR compensator (SVC) has been conducted. Diesel engine coupled to a synchronous generator equipped with automatic voltage regulator (AVR) and DSTS is connected to an induction generator. The parameters of the proportional–integral controllers, employed with SVC and AVR are optimised simultaneously using genetic algorithm (GA), particle swarm optimisation (PSO) and flower pollination algorithm (FPA) techniques. The comparative performance of GA, PSO and FPA optimised controllers on the hybrid system model has been presented considering step change and random variations of solar thermal power as well as reactive power load. Simulation results revealed that FPA optimised controllers for AVR and SVC can provide the improved dynamic performance of the hybrid energy system as compared with GA and PSO optimised controllers.

This study presents a novel application of the gravitational search algorithm (GSA) to optimally control a wave energy conversion (WEC) system under different operating conditions. In the WEC system, the generator side converter controls the d-axis and q-axis current of the generator for minimising the generator power losses and extracting the maximum real power from the WEC system, respectively. The DC–DC converter is implemented to maintain the terminal voltage of the DC microgrid. The control of both converters relies on the proportional–integral controllers, which are optimally designed by the GSA through a simulation-based optimisation approach. In that manner, the integral of squared error criteria is used as an objective function. The validity of the WEC system model is verified by comparing its simulation results with the experimental results that extracted from a field test. The effectiveness of the proposed controller is tested when the system is subjected to different operating conditions such as a DC microgrid load disturbance, a temporary DC fault condition, and an irregular wave condition. Moreover, the effectiveness of the proposed controller is compared with that by using the genetic algorithm. The simulation results of the system are extensively carried out using PSCAD/EMTDC program.

Renewable energies need high investment and they have lower efficiency rather than fossil fuels. So methods have to be devised to increase efficiency and to decrease investing cost. Here the combination of geothermal with solar has been proposed. The geothermal heat extraction from an abandoned oil well in Ahwaz oil field (DQ) was simulated and also a binary cycle power plant has been designed. Using this well, the cost of drilling and casing is eliminated. The system is assisted by combining of two solar power production systems. The first system is photovoltaic (PV) which works parallel to geothermal binary cycle. The second system that is concentrated solar thermal (CST) system is using parabolic trough collector to generate heat for super heating geothermal binary cycle. Although CST has more problems than photovoltaic (PV) in terms of setups, maintenance and the ease of transfer, due to the possibility of storing thermal energy when there is no sunlight, it has compatibility and ability to increase more efficiency in collaboration with geothermal binary cycle. The collaboration of CST with geothermal results in 23.5% increase in power generation in a year, while this figure equals to 15.7% for PV with geothermal.

A new differential current-based fast fault detection and accurate fault distance calculation is proposed for photovoltaic (PV)-based DC microgrid. A multiterminal direct current (MTDC) distribution network is studied as an adequate solution for present low-voltage utility grid scenario, where local distributed generators (DGs) are incorporated primarily by power electronics based DC–DC converters, DC–AC voltage-source converters (VSCs). PV and diesel generator (as auxiliary source) are considered for cascaded common DC bus, and AC utility bus integration is achieved by VSC unit for the proposed MTDC network. DC microgrid protection is quite significant research focus due to the absence of well-defined standards. Pole-to-pole, pole-to-ground, PV-side DC series and ground arc faults are basically considered as DC distribution network hazards. A discrete model differential current solution is considered to detect, classify and locate the faults by modified cumulative sum average approach. A comprehensive case study is presented with different DC loadings, to deliberate effectiveness of the proposed protection scheme in terms of percentage error and trip time (Ts). The result verification is conducted in MATLAB environment as well as TMS320C6713 digital signal processor-based test bench with the proposed multiple DGs based DC microgrid.

High wind velocities are required for wind projects to be economically efficient. To increase the wind speed, the concept of ducted wind turbines has been introduced in recent decades. Among them is the Invelox, which can capture the wind from all directions and funnel the collected air to the ground level. Primary results have shown that this design can increase the overall efficiency of a wind project. In this study, the effects of the main geometrical parameters affecting the aerodynamic performance of the Invelox are numerically studied. The effects of the inlet area, the diameter of the Venturi section and the height of the funnel on the wind speed increment inside the Venturi section have been determined. Results show that the inlet area and the Venturi cross section area have the most significant effects on the speed ratio (SR) of the Invelox, while the funnel height and air velocity have minor effects. In the case of appropriate selection of the geometry parameters, velocity increments up to 1.9 are achievable. Finally, the effects of adding a horizontal axis wind turbine inside the Venturi on its power coefficient are studied. Results show that Invelox greatly enhances the turbine maximum power coefficient. However, it decreases the tip speed ratio corresponding to the maximum power coefficient.

It is often assumed that the input voltage source of a switch-mode power supply is constant or shows negligible small variations. However, the last assumption is no longer valid when a fuel-cell stack is used as input source. A fuel-cell stack is characterised by low and unregulated DC output voltage, in addition, this voltage decreases in a non-linear fashion when the demanded current increases; henceforth, a suitable controller is required to cope the aforementioned issues. In this study, an average current-mode controller is designed using a combined model for a fuel-cell stack and a boost converter; moreover, a selection procedure for the controller gains ensuring system stability and output voltage regulation is developed. The proposed energy system uses a fuel-cell power module (polymer electrolyte membrane fuel cells) and a boost converter delivering a power of 900 W. Experimental results confirm the proposed controller performance for output voltage regulation via closed-loop gain measurements and step load changes. In addition, a comparison between open- and closed-loop measurements is made, where the controller robustness is tested for large load variations and fuel-cell stack output voltage changes as well.

The rise in electrical power demand and corresponding transmission or distribution loss is affecting the efficiency of power delivery. A new method for loss allocation in radial distribution system based on proportional sharing is proposed. Based on allocated loss, optimal location of distribution generation (DG) is selected. After selecting the location, optimal size of DG is obtained for that location. Loss allocation to DGs is based on formation of two matrices, power contribution matrix and power sharing matrix. Loss share of DGs and loads are decided based on both power injection by DGs and loss minimisation due to presence of DGs. Results of the proposed method are shown on 69 bus radial distribution system.

Environmental concerns and policy directives coupled with renewable energy penetration targets in Europe and United States are leading to a greater need for identifying technical and economic characteristics that facilitate the integration of electric vehicles (EVs) in the electricity network. An important step in mitigating instability associated with unregulated EV charging and renewable power feed-in is the integration of EVs as providers of load frequency control (LFC). This study presents an evaluation of six European and North American LFC systems on the basis of EV characteristics to identify suitability for EV integration. The evaluation shows that the Eastern Denmark network is most feasible for frequency containment and restoration reserve using EVs.

For the sake of studying the stability of the pumped storage power station, the authors focused on the mathematical modelling of the pump-turbine governing system (PTGS) at pump mode. First of all, six transfer coefficients were introduced into the model of the pump-turbine. Furthermore, utilising the internal characteristics formulas, they obtained six analytical expressions of the transfer coefficients at pump mode. Considering the elastic water-hammer model of the penstock with hydraulic friction and the second-order model of the generator, a non-linear model of the PTGS was proposed. On the basis of a real case, they obtained the curve of bifurcation points of the system by using the stability theorem, and verified the correctness of the theoretical analysis results from numerical experiments. Moreover, the stable domains of the proportional–integral–derivative parameters and were identified and the non-linear dynamic behaviours of the governing system were studied. Finally, these methods and analytic results could help them improve the safety operation and performance of the pumped storage power station.

Wind power is one of the promising renewable energy resources to achieve energy sustainability. Its growth poses increasing financial and technical challenges to power systems, mainly due to the wind intermittency. Existing transmission networks may require infrastructure investment, in order to maintain the economical, secure and reliable operations of power systems with increasing wind power penetration. This study proposes a stochastic transmission expansion planning (TEP) framework to assess the impacts of wind power penetration and demand response incorporation. A risk constraint on load curtailment is introduced and its effect on TEP solutions is investigated. Also, to reduce the complexity and size the formulated TEP problem, a decomposition-based approach is adopted. According to the numerical results on the Garver's six-bus and the modified IEEE 30-bus systems, the solutions of TEP are subject to the variation of wind power characteristics and cannot be determined straightforward. Hence risk-analysis should be carried out to guide transmission investment with increased flexibility. The incorporation of wind power uncertainty increases the total cost and expected energy not supplied, which can be mitigated by the proposed TEP approach.

Microgrids have the capability to enhance the resiliency of power systems by supplying local loads during emergency situations. However, the disturbance incident and clearance times cannot be predicted precisely. Therefore, this study is focused on enhancing the resiliency of hybrid microgrids considering feasible islanding and survivability of critical loads. The optimisation problem is decomposed into normal and emergency operation problems. In normal operation, unit commitment status of dispatchable generators and schedules of batteries are revised to ensure a feasible islanding following a disturbance event. In emergency operation, the decision between charging of batteries for future dispatch and feeding of lesser critical loads is considered. In addition, a strategy for minimisation of load curtailment during switching of scheduling windows is also considered. These two considerations can mitigate the curtailment of critical loads during the emergency period. Finally, a resiliency index is formulated to evaluate the performance of the proposed strategy during emergency operation. Numerical simulations have demonstrated the effectiveness of the proposed strategy for enhancing the resiliency of hybrid microgrids.

The suitability assessment of system modelling is critical to a resource-limited computational environment, which aims to strike a balance between the modelling accuracy and efficiency. In this study, a novel approach to evaluate the damping torque contributions from different dynamic components of doubly fed induction generator (DFIG) to system oscillation stability is first proposed. Then, this approach is employed to investigate the change of DFIG parameters (i.e. parameters of induction generator and converter controllers, and connection status), with the aim of identifying impact mechanism of these parameters on the damping torque contribution of each dynamic component. On this basis, the dynamic model of DFIGs with least orders but acceptable accuracy for oscillation stability analysis can be determined under certain parameter conditions, which undoubtedly brings significant benefits to system planner and operator to mitigate computational burden and save planning time when dealing with large-scale power systems. In this study, the model validation of grid-connected DFIGs is demonstrated in the New York power system - New England test system (NYPS-NETS) example system with 16 machines and 68 buses. Time-domain simulation is used to verify the calculation results of the proposed approach.

The probabilistic power flow (PPF) of active distribution networks and microgrids based on the conventional power flow algorithms is almost impossible or at least cumbersome. Always, Mont Carlo simulation is a reliable solution. However, its computation time is relatively high that makes it unattractive to be a reliable solution for large interconnected power systems. This study presents a new method based on fuzzy unscented transform and radial basis function neural networks (RBFNN) for possibilistic-PPF in the microgrids including uncertain loads, correlated wind and solar distributed energy resources and plug-in hybrid electric vehicles. When sufficient historical data of the system variables is not available, a probability density function might not be defined, while they must be represented in another way namely possibilistically. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution methodology is needed. The proposed method exploits the ability of RBFNN and unscented transform in non-linear mapping with an acceptable level of accuracy, robustness and reliability. Simulation results for the proposed PPF algorithm and its comparison with the reported methods for different test power systems reveals its efficiency, accuracy, robustness and authenticity.

Solar photovoltaic (PV) is fast being deployed in electric power grids. For its more reliable integration into grids, the impact of its intermittent generation on grids should be further examined. However, high-resolution solar and meteorological measurement data in 1 s or 1 min intervals are often not available for many areas or they are expensive to obtain. Thus, the objective of this study is to present a first-order Markov chain Monte Carlo (MCMC) method that synthesises the short-term variation, or sudden energy shortages and overages, in the power generation of a PV system in high-resolution, from low-resolution solar and meteorological data. In addition, up and down ramp rates in PV output are significant for the application of battery storage systems or grid operation. Thus, the acceptance–rejection algorithm able to limit such ramp rates is proposed. The proposed MCMC and acceptance–rejection methods are verified by comparing the statistical characteristics of the synthesised data to those of the original data. From case studies, this study found that the proposed methods could present the sufficient short-term variation in generation output of a PV system.

In this study, an artificial neural network (ANN) and empirical mode decomposition (EMD) based condition monitoring approach of a wind turbine using Simulink, FAST (fatigue, aerodynamics, structures and turbulence) and TurbSim is presented. The complete dynamics of a permanent magnet synchronous generator (PMSG) based wind turbine [i.e. wind turbine generator (WTG)] model is simulated in an amalgamated domain of Simulink, FAST and TurbSim under six distinct conditions, i.e. aerodynamic asymmetry, rotor-furl imbalance, tail-furl imbalance, blade imbalance, nacelle-yaw imbalance and normal operating scenarios. The simulation results in time domain of the PMSG output stator current are decomposed into the intrinsic mode functions using EMD method then RapidMiner-based principal component analysis method is used to select most relevant input variables. An ANN model is then proposed to differentiate the normal operating scenarios from five fault conditions. The analysed results proclaim the effectiveness of the proposed approach to identify the different imbalance faults in WTG. The presented work renders initial results that are helpful for online condition monitoring and health assessment of WTG.