DC/DC power converters are critical parts of railway applications because they are required in on-board, off-board, and communication systems. Traditionally sliding-mode control is only insensitive to the matched disturbances, and the system performance is reduced when mismatched disturbances appear. This study develops a non-linear disturbance observer (NDO)-based adaptive non-singular fast terminal sliding-mode control strategy for DC/DC buck converter with mismatched disturbances. The proposed strategy exhibits the following three attractive features. Firstly, the observer can estimate the matched and mismatched disturbances in finite time. Next, by taking the estimations of the disturbances into account, a sliding-mode variable is designed, the system reach the sliding-mode surface in finite time, and the output voltage tracking error converges to zero in finite time. Then, the convergence rates of the sliding-mode variable and output voltage tracking error are faster compared with those of the NDO-based non-singular terminal sliding-mode (NTSM) controller. Finally, with the adaptive law, the control gain is adjusted to an appropriate value with respect to disturbances, and the chattering of the control signal is reduced. Experimental results show that comparing with the NDO-based NTSM controller, the proposed method exhibits better steady-state performance and dynamic performance including robustness and disturbance rejection ability.

Electrically powered rail vehicles are considered one of the most energy-efficient means of transport. Transport activity is responsible for a considerable part of global energy consumption. The transport industry is therefore obliged to develop strategies for more efficient energy use. Railway electrification systems transmit the electrical power supplied by substations to moving trains. However, part of the power supplied is consumed by the electrification systems and does not reach the trains. In this study, transmission losses in the 2 × 25 kV electrification system are evaluated. The 2 × 25 kV system is widely used in high-speed and high-capacity railway lines. Assessment of the performance of the 2 × 25 kV system is carried out by computer simulation of the power flows between the elements involved in train movement by means of simplified physical models. The results show that the reduction of transmission losses is a feasible way to achieve energy savings and to improve the energy efficiency in electrified rail transport. For this, it is essential to add the topology of the electrification system to the data considered in the design of the train trajectories.

Discontinuously electrified sections, such as neutral sections (NSs) widely exist in modern electrified railways. As a special arrangement of insulator, NSs with no electricity supplies are set up to ensure the two sections are kept electrically separate. This paper proposes a distance-based mixed-integer linear programming (MILP) model to incorporate both NS location planning and energy-efficient train control (EETC) problem and concurrently optimise the NS location and train speed trajectory. The main contribution of this study is that based on the proposed integrated model, a number of case studies are conducted to investigate on the impact mechanism of NS locations on the total energy consumption of train operations. The optimisation results show that the energy saving rate in comparison with the worst cases is ranging from 1.9% to 6.1%% in various scenarios and significant saving rate can be achieved via planning the NS to be located in coasting areas as determined by EETC. In conclusion, the energy-saving effect of the optimal NS location planning on the total energy consumption largely depends on how the NS-triggered forced coasting is located in the journey and NS locations near stations and switching areas of speed limit lead to significant energy increase for bi-directional journeys.

It is an effective way to regard the electric vehicles as the demand response for reducing the negative impact of large-scale introduction on the power system. Aiming at the microgrid with demand response, the adaptive uncertainty sets-based two-stage robust optimisation method is established in this study. The coordination of micro-gas turbine, energy storage, and demand response etc. are considered in the economic dispatch model. To effectively consider the uncertain variable contained in the microgrid, the concept of adaptive uncertainty sets is proposed in this study. The uncertainty sets are achieved by the long short-term memory network and modified fuzzy information granulation. To handle the adaptive uncertainty sets-based robust optimisation model, the column and constraint generation algorithm and strong duality theory are introduced to decompose the model into a master problem and a subproblem with mixed-integer linear structure. To verify the performance of the proposed adaptive uncertainty sets-based two-stage robust optimisation method, measured data from a plateau city of China are introduced in the simulation test. The simulation results demonstrate the effectiveness of the model and solution strategy.

Back-to-back converter based railway traction power supply system (TPSS) can eliminate neutral sections in the traction side and improve power quality in the grid side, but it still has some drawbacks such as low reliability, difficulty in accepting large-capacity renewable energy, and power mismatches. In this study, a double-layer DC/AC TPSS with renewable integration is proposed to address these challenges and to improve system performance. The proposed topology breaks the limit of back-to-back structure and enables more flexible free energy flow. A top-down system design method is proposed in this study. Firstly, the characteristics of the proposed TPSS for integration with renewable power are described and compared with the traditional back-to-back topology. Secondly, a DC droop controller and a AC droop controller are designed for DC layer grid and AC layer grid, respectively, to control the power flow in each layer. The traditional AC droop control is based on the inductive transmission impedance, but the resistance of traction transmission line cannot be ignored. Thus, a modified droop control strategy with the consideration of line resistance is also proposed in this study. Subsequently, the voltage control strategy for the single modular multilevel converter is designed to track the reference signal from the upper droop controller. Finally, a general double-layer DC/AC TPSS is designed from bottom to top, and the simulation results confirm that the proposed TPSS with renewable integration is capable of delivering desirable performance.

China has been the main source of global energy consumption growth for 18 years in a row. Railways account for a large proportion of China's energy consumption, and the greening of railway energy supply systems will be an irreversible trend over time. Using a SWOT analysis approach, the authors investigate the internal strengths and weaknesses and the external opportunities and threats for orchestrated development of a solar railway system in China. After discussing countermeasures and suggestions for integrated development of a solar railway system in China, the conclusion is drawn that the railway power system will be green, resilient, self-contained and sustainable by utilising the existing space in the railway system for photovoltaic power generation, using hybrid energy storage facilities and energy internet technologies to balance power supply and railway energy demands, and grasping the strategic opportunity for domestic and foreign construction projects.

Large-scale fast charging of electric vehicles inextricably entwines the operation of power and transportation systems. This study examines the integrated pricing of electricity and roads to maximise the social welfare associated with the coupled systems, i.e. minimising the total travel time and energy generation costs. While electric demand and transportation network conditions vary significantly over the day, most of the work, however, considers only static network flows for a single time period. This study proposes a multi-period integrated pricing model that can describe the variations of electricity and travel demands. Specifically, the distribution of traffic flows is characterised by a semi-dynamic traffic assignment model to consider flow propagation between adjacent time periods. To determine the optimal prices of electricity and road tolls, a marginal-cost pricing scheme based on the first-best tolls and locational marginal prices is developed. Mathematically, the multi-period pricing model is formulated as a convex optimisation problem. Moreover, a decentralised collaborative pricing framework is developed for independent power and transportation system operators to attain the optimal pricing strategies. Numerical experiments are conducted to demonstrate the effectiveness of the pricing method.

The access of distributed generations (DGs) in the traction power supply system (TPSS) can not only make use of the renewable energy near the railway route, but also improve the condition of weak external power supply. In order to quantify the effect when DGs access TPSS, this study proposes a method for evaluating the power supply capability and quality of TPSS which considers the access of DGs. First, the method fully considers the randomness and uncertainty of the power provided by DGs and that consumed by electrical locomotives. A comprehensive model of TPSS with the access of DGs is built by means of the stochastic model, and then the index system for evaluating the power supply capability and quality of TPSS is formulated. Finally, the Monte Carlo simulation is applied to calculate the probabilistic load flow to obtain the evaluation indices. The proposed method is verified by simulating a typical TPSS in a remote mountain area. The results show that the method can quantify the power supply capability and quality of the system after the access of DGs. It can provide an intuitive conception of the power supply condition for design and operation personnel.

This paper proposes an Electric Vehicle (EV) aggregator bidding strategy in the reserve market. The EV aggregator determines the charging/discharging operations of EVs in providing reserve service for profits maximization. In the Day-Ahead Market (DAM), the EV aggregator submits a bidding plan to the Independent Systems Operator (ISO) including base-load and reserve up/down capacities plans. In the Real-Time Market (RTM), the EV aggregator should deploy reserve based on the ISO's requirements, and the EV aggregator could receive income by deploying reserve or penalty for reserve shortage. The stochastic programming method is applied to address the uncertain reserve deployment requirements in RTM. In addition, Energy Storage Systems (ESS) are utilized by the EV aggregator to enhance the ability in providing reserve service. The aggregator–owner contract is designed to guarantee EV owners' economic benefits. Case studies show the expected profits of the EV aggregator are maximized and the risk of the reserve shortage is well managed, i.e., penalty is minimized. With the utilization of ESS, the performance of the EV aggregator in making response to the ISO's requirements is improved. That is, the required reserve percentage increases from 5.68% to 7.85%, and the deployed reserve percentage increases from 69.71% to 88.47%.

It is more convenient and safer to employ wireless power transfer (WPT) systems to charge the battery pack of electric scooters (ESs) than conventional plug-in systems. A charging equaliser suitable for ESs is proposed to achieve constant current (CC) output without communication link between the transmitter side and the receiver side. The full-bridge rectifier and select switches utilised at the receiver side are employed to be operated once to change from the balancing mode to charging modes. The characteristics of the load-independent current output in the CC mode are achieved by properly selecting the parameters of the circuit so that no sophisticated control strategies are required to regulate the output as per the charging profile. The experimental results show that when the voltage of battery pack is charged at 32 or 4.2 V, the current is 1.02 or 1.12 A, respectively. Therefore, the proposed system can be considered as a CC system.

In railway traction power supply, co-phase system with hybrid power quality conditioner (HPQC) is capable of tackling the power quality issues caused by single-phase traction loads. To further reduce the overall carbon emissions in railway systems, this paper considers to integrate the renewable energy with railway power supply, which however leads to a more complicated system to model, design and control. This paper first investigates its modelling aspect. To reduce the operating capacity of HPQC while addressing the power unbalance, optimal design of the compensation scheme for co-phase system is formulated as a multi-objective optimization problem which is then solved by the nondominated sorting genetic algorithm-II (NSGA-II). To eliminate the impact of errors arising from imperfect predictions of the loads and renewable power, a hybrid optimal compensation control is proposed, yielding full and optimal compensations. Comprehensive simulation studies, considering three operation modes covering variable traction loads, renewable and regenerative braking power, are conducted. The simulation results confirm the validity of the proposed optimal compensation scheme, achieving an average of more than 20% reduction in HPQC capacity compared to the full compensation scheme. Meanwhile, the power quality requirement is satisfied, even in the presence of real-time prediction errors.

The full controllable electronic device based railway feeder station offers better power quality and more flexible configurations than conventional transformer based stations. This study investigates a modular multilevel converter (MMC)-based static frequency converter station with renewable energy access. Wind power generation is coupled into the station via DC link of the back to back converter. The dynamic single-phase traction load and intermittent renewable generation bring double frequency oscillation and large deviation problems to the DC link voltage. Special design considerations and control schemes are proposed for the MMC to stabilise DC link voltage by controlling the total number of total inserted modules. The proposed control scheme resolves the voltage oscillation issue caused by single-phase load and reduces the DC link voltage deviation under 10 MW step change. A series of device-based simulations validate the control scheme which realises a reliable coupling interface for connecting the renewable generation to the DC bus.

To coordinate the increasing application of electric vehicles (EVs), the deployment of charging stations becomes vital for supporting the charging and navigation for EVs, which also affects the reliability of the corresponding electricity network. To achieve the balanced reliability in both the electricity network and EV trip, an optimal planning method for charging stations in the electricity-transportation coupled networks is proposed. Firstly, an integrated management strategy of EVs is demonstrated to model the reliability enhancement of the two networks. Thereafter, a coupled network reliability assessment method based on the quasi-sequential Monte Carlo simulation is presented. This study proposes a novel reliability-oriented multi-objective optimal planning model for charging stations planning problem, which is resolved by implementing the optimal planning scheme from the candidate nodes. Additionally, correlation analysis is performed to ensure that the proposed model can be solved quickly for large-scale electricity network with complex transportation flow input data. A test case is presented and simulated to validate the feasibility and effectiveness of the proposed method.

This study presents a comprehensive study of microgrid systems using a single-phase self-excited induction generator (SEIG) using renewable energy sources (RESs) and their integration with other energy sources. It investigates on the use of a single-phase two-winding SEIG for off-grid single-phase power generation from different RESs. Various solid-state controllers are implemented for each configuration. This is the first time, such an attempt is made to use a specially designed SEIG for sustainable energy application to feed single-phase loads vastly prevalent in isolated and distant locations in accessible to the grid. This work has great importance due to the non-availability of the power in remote regions in developing countries. Moreover, there is a need to use local RESs such as bio, hydro, wind in combination with the solar energy. The present global need to generate pollution free electricity makes this work quite important. Thus, this study presents a comprehensive review of different modes of SEIG using RESs for single-phase power generation realising the microgrid feeding a combination of practical loads with viable and successful controllers to ensure desired quality power across loads.

The penetration of photovoltaic systems (PVs) to existing power grids is increasing as they are considered attractive options for electricity generation in distribution networks. This paper focuses on estimating the total power generated by a group of neighbouring PVs, spread over a distribution network using a single pyranometer for measuring the solar irradiance. A new empirical-based model that employs the Gene Expression Programming (GEP) technique is proposed to correlate the distribution of the PVs and the irradiance measured by the pyranometer and estimate the total power generated by the PVs. The geographic variability reduction index has been considered in developing the proposed model that also employs a Wavelet Transform technique to enhance its accuracy. The effective performance of the proposed model is validated using real data collected by the Solar Project at the University of Queensland, Brisbane, Australia. Results reveal that the proposed technique yields more accurate results when compared with other existing approaches in the literature.

In this study, a fuzzy current-sensor less maximum power point tracking (MPPT) algorithm is presented. The algorithm proposed to improve the performance and reduce the cost of photovoltaic systems. The proposed algorithm creates the variable step-size/variable frequency specification in the drift-free single input voltage sensor (SIVS) method designing a reliable and widely used fuzzy control algorithm. The proposed algorithm will improve the SIVS methods employing the advantages of the fuzzy controllers in the MPPT algorithms based on the real and false error areas analysis concept developed by Tousi et al. (2016). The proposed method will detect exact drift conditions and move to the optimal setpoint at the maximum speed. The method selects the correct direction, appropriate step-size, and suitable control frequency to increase dynamic efficiency against the drift condition. Also, the steady-state efficiency of the algorithm will increase because of high-frequency and low-power oscillation performances. The proposed method will be simulated and compared in Matlab/Simulink environment and tested in laboratory conditions on the designed solar charge controller.

The increase of renewable energy generation penetration rate exerts a passive impact on the power system. A pumped-storage plant (PSP) is a proper technology to depress power fluctuation and regulate the frequency of the power system. Variable-speed PSP (VSPSP) is a relatively novel technology and has unique advantages when participating in power and frequency regulation. This study focuses on the generating phase modulation of VSPSP and fixed-speed PSP (FSPSP). The integrated hydraulic-mechanical-electrical models of FSPSP and VSPSP are built and vector control theory is introduced in the model of VSPSP. Based on these two models, this study analyses operational performance and power response under generating phase-modulation mode. The results reveal that the power regulation ability of VSPSP is more accurate and rapid. In addition, the operation of VSPSP is not restricted by a stability limit and the range of power regulation is expanded. Eventually, it could be observed that weak coupling between the mechanical and electrical system in VSPSP helps to increase efficiency and prolong life-span of pumped-turbine. The results and conclusions obtained from this study help to mitigate power fluctuation and improve strategies of power regulation of hybrid power systems with PSP.

In this study, a passive islanding detection technique based on the variation in the angles of superimposed sequence components of voltage and current is proposed. The pre- and post-islanding voltage and current superimposed components are derived using the corresponding voltage and current phasors. The angle between the positive and negative sequence voltage and current and the superimposed components of these quantities are derived to take further action. Furthermore, decisions obtained from the angles of different superimposed components are combined using a voting technique to take the final decision with more reliability and accuracy. The scheme does not require the establishment of any threshold and completely relies on the rule base obtained through a simulation study. A microgrid with multiple connection points is simulated using a real-time digital simulator (RTDS). A hardware-in-the-loop test bench is arranged using a dSPACE DS1104 and RTDS. Numerous test cases are simulated to assess the performance of the proposed technique.

As residential PV generation penetrates in the low-voltage distribution network (LVDN), the unbalance issue may be intensified due to the asymmetry of generations/loads in different phases. Phase-reconfiguration device (PRD), which can reconfigure connected phases of residential customers, provides an effective method to address this issue. Noting that although the benefit brought by PRDs can vary if they are placed at different locations in the network, little literature has been reported on this topic. To bridge the research gap, this paper presents a novel method to optimally place PRDs in an LVDN aiming at minimizing the power unbalance running through the distribution transformer. The problem considers both installation, operational constraints, and boils down to a challenging mixed-integer non-convex programming problem, which is then reformulated as an efficient solvable mixed-integer linear programming problem. Moreover, operational constraints are relaxed with slack variables penalized in the objective function, which makes sure a feasible solution is always available without or with minimal operational violations. Case studies based on a modified IEEE system and a practical system in Australia demonstrate that an efficient strategy can be provided to address the unbalance issue while improving the network's power supply qualities.

With the growing penetration of distributed energy resources and energy hubs, the transactive energy market appears as a modern power market that facilitates coordinated operation and end-to-end energy trading. An energy hub can actively participate in the day-ahead and real-time markets for fulfilling various goals. This study proposes an interval–stochastic optimisation model based upon the transactive energy methodology for the scheduling of energy hubs in coupled electrical and thermal systems. Transactive energy technology is employed for the energy exchange management among the hub, consumers and the power grid. In the proposed model, the day-ahead stage's uncertainties are modelled by using interval optimisation to avoid stochastic programming challenges in problems with lots of uncertainties. Further, the stochastic optimisation is employed in the real-time stage as stochastic programming challenges will be conducted by updating the forecasts. By envisaging the uncertainties quiddity and the most of technical constraints of a hub, the real-life situation is created. In addition, most of linearised constraints are applied to achieve reliable outcomes in a shorter time. Numerical simulations confirm the effectiveness and applicability of the proposed model.

Recently large-scale integration of power-electronic-based devices has made system-level oscillations occur frequently, which posed a big challenge for modern power grids. Previous studies mainly treated sustained oscillations under the framework of (linear) small-signal stability and/or by incorporating the impact of current saturation, but seldom considered system non-linearity like phase-locked-loop. In this study, the authors established a sixth-order non-linear model for a three-phase voltage-source converter tied to AC grid, and studied its dynamics completely from non-linear system theory and signal analysis technique, with all parameters including current controllers, phase-locked-loop, line inductance, and grid voltage. They found that the operation point usually becomes unstable by Hopf bifurcation, and the sustained oscillations are possible only for super-critical Hopf bifurcation. Based on these observations, sustained periodic oscillation should be treated as a limit cycle even without saturation. With saturation, some other phenomena have also been found, such as saturation-induced instability and saturation-restricted oscillation. In addition, they discovered that for sustained oscillations, the usual purely sinusoidal three-phase currents exhibit the form of or , where () denotes basic (modal oscillation) frequency with c a constant. This work could provide an improved understanding of sustained oscillations and associated system dynamics in an overall perspective manner.

As the distributed energy resources penetration level increases, the distribution system operator faces a challenging task of unintentional islanding detection. Besides islanding detection schemes are affected due to the presence of different types of distributed generation systems and smart inverters. The presence of these devices hinders the capability of islanding detection schemes. To mitigate these issues, this study proposes a practical methodology of variational mode decomposition-based energy index for islanding detection. It decomposes the sampled voltage signal at the point of common coupling into four modes/intrinsic mode functions (IMFs). Among these modes/IMFs, the energy index of mode two has been utilised to detect the islanding. It is an entirely intrinsic, adaptive, and variational method. The five bus and practical distribution systems have been modelled using PSCAD/EMTDC software while considering various components' practical aspects. The technique has been tested for the mixed type of distributed generation and various transient events. The test results reveal that the proposed method is capable of discriminating the islanding event from other disturbances.

The proposal focuses on the role of data centres (DCs) and electric vehicle (EV) energy storage systems (ESSs) for frequency regulation and it provides a new opportunity for different resources to participate in the power sector. Frequency fluctuations are introduced with the emergence of inverter-dominated renewable energy sources (RESs) as it does not provide rotational inertia to the grid, such as synchronous generators. In this study, the virtual synchronous generator (VSG) controlled inverter compensates for the lack of inertia. Particularly, this research work analyses the involvement of DC and EV batteries as ESSs in designing an integrated technical virtual power plant (VPP) to support frequency variations using the VSG concept. Microgrid (MG) simulations are performed in MATLAB/ Simulink platform. Case studies are carried out to validate the grid export and grid import performance of the model by using variations in the load and the solar irradiance of the MG. It is verified that bidirectional power flow takes place between the proposed VPP components and the grid that enables the grid with high penetration of RESs. The work provides a conceptual framework for future contributions towards the smarter usage of assets such as ESS and a greener future.

The generation structure in the European power systems is continuously changing towards an increasing share of non-synchronous energy sources. This leads to significant challenges in maintaining frequency stability due to declining system inertia. In this study, a novel concept of demand response very fast active power control (DR VFAPC) capability using in a direct way the braking energy in electric trainsets being in motion is presented. In order to assess the potential to ensure DR VFAPC capability by freight railway carriers and examine the impact of such service on frequency dynamics, a simplified mathematical model of Polish power system representing the frequency regulation process has been developed. The impact of basic characteristics of the freight train transport, as well as the selected power system parameters on the DR VFAPC operation, has been studied. In conclusion, current technical constraints of implementing the presented idea and future works have been discussed.

The digitally controlled inverter is widely applied to the photovoltaic (PV) plant, however, the effects of inverter digital time delay on the harmonic characteristic of PV system which directly influences the power quality and even the stability of the system, have not been investigated yet. This study investigates the harmonic characteristic of a grid-connected large-scale PV system based on the equivalent Norton model of the system with considering the digital time delay of the inverter. According to the system equivalent model, the series harmonic resonance circuit and the parallel harmonic resonance circuit are divided to study the impacts of digital time delay in the cases of the inverter output harmonic exist and the grid voltage harmonic exit, respectively. Then, the harmonic resonance mechanism of a grid-connected large-scale PV system is studied and the effects of digital time delay on the harmonic characteristic of system output current is quantitatively analysed by defining the harmonic magnification coefficient. It turns out that frequency and magnitude of harmonic magnification points in the grid-side current of the system are increased as the digital time delay increases. Reference to the actual 20 MWp grid-connected PV system, a simulation model is built to verify the theoretical analysis results.

In this study, a novel methodology is proposed for sensitivity-based tuning and analysis of derivative-based fast active power injection (FAPI) controllers in type-4 wind turbine units integrated into a low-inertia power system. The FAPI controller is attached to a power electronic interfaced generation (PEIG) represented by a generic model of wind turbines type 4. It consists of a combination of droop and derivative controllers, which is dependent on the measurement of the frequency. The tuning methodology performs parametric sensitivity to search for the most suitable set of parameters of the attached FAPI that minimises the maximum frequency deviation in the containment period. The FAPI is adjusted to safeguard system stability when increasing the share of PEIG. Since the input signal of the FAPI is the measured frequency, the impact of different values and parameter settings of the phase-locked loop used for the FAPI controller is also investigated. Detailed validation with a full-scaled wind power converter is also provided with a real-time digital simulator testbed. Obtained simulation results using a three-area test system, identify the maximum achievable degree of increase in the share of wind power when a proper combination of wind park locations considering their suggested settings for inertia emulation.

Matching of the colossal energy demand with carbon-free resources originates a global challenge to produce and innovate advanced energy technologies that generate clean and friendly energy supplies without threatening our environment. Nevertheless, with the increase in the penetration from renewable energy resources like solar and wind farms many technical issues are presented typically; power stability, power quality, and frequency fluctuations. The aforementioned problems stem from the intermittent nature of renewable resources which makes the generated power unpredictable and requires controlling and smoothing before dispatching. Conventionally low pass filter (LPF) is used with a controlled energy storage system to smoothen the fluctuated power due to its simplicity, but a delay problem increases with higher values of the filtering the time constant. This study suggests a smoothing controller-based fuzzy logic that determines the value of the filtering time constant based on the present solar power ramp rate to avoid the battery overworking, which results in the predetermined configuration of the LPF. The presented simulation results prove the smoothing performance of the proposed controller and compare its performance to the LPF during clear, normal, and cloudy irradiance profiles.

The Reynolds-averaged Navier–Stokes (RANS) method coupling with the actuator disc model (ADM) is considered as a promising numerical simulation technology of wind turbine wake, and it is widely utilised in the aerodynamics of wind turbines and optimal layout of wind farms. The turbulence model is widely adopted, among the RANS-based turbulence models. However, the turbulence model easily overestimates the turbulence viscosity in the wake, which results in fast recovery of wake velocity and failure in wake forecasting. In addition, ADM with the oversimplified geometrical structure ignores the effects of nacelle and tower on the wind turbine wake, which further lowers the accuracy of wake simulation. Therefore, the numerical simulation of wind turbine wake based on the extended turbulence model of EI Kasmi coupling with ADM considering nacelle and tower is proposed. Comparing the results of Marchwood Engineering Laboratories (MEL) ABL wind tunnel measurements and TNO wind tunnel experiments, it has been found that the proposed model improves the simulation effect for the near wake and has a certain contribution to the wake prediction accuracy overall.

This study introduces a type of solid-state transformer (SST) for solar power station design and an energy management strategy (EMS) for the SST. The purpose of this study is to design a real efficient EMS for the photovoltaic-assisted charging station in smart grid ancillary services and apply the optimal decision method. Also, the energy bound calculation (EBC) model is proposed to find the upper and lower bounds of flexible sources. Also, taking into account the EBC results and the power order from the aggregator, a charge power allocation algorithm is designed to distribute the power of flexible electric vehicles (EVs). With the help of a case study and laboratory analysis, the proposed EMS strategy is effective in real-time energy management and is suitable for practical applications. The obtained results show the stable performance in the calculation of the energy range and real-time power allocation which improves the efficiency of the photovoltaic-based charging station. Also, the SST improves the operation of charge stations for supplying the sustaining power.

The requirement of high power (MW-size) power conditioning unit (PCU) has increased to minimise the plant balance of system cost due to a continuous increase in solar photovoltaic (PV) plant capacity. Traditionally used high-frequency pulse-width modulated two/three-level PCUs have high device switching losses and lower conversion efficiency and are not suitable for high power PCU application as high switching losses lead to high heat generation within the converter, which is very difficult to manage, and lower conversion efficiency leads to less revenue realisation. In the present work, fundamental switching selective harmonic elimination (SHE) modulated 11-level cascaded H-bridge voltage source converter is utilised for high power MW-size PCU application, as it has lower switching losses, higher conversion efficiency, and higher AC/DC voltage ratio. The PV plant configuration for a 40 MW (AC) capacity is developed in the MATLAB/Simulink environment and implemented in real-time simulator OPAL-RT to validate the design and control. Harmonics, steady-state, and dynamic performances are demonstrated at constant and changing solar irradiance levels. The converter conduction and switching losses and conversion efficiency at different loading conditions are presented. The converter control with the capacitor voltage balancing method for fundamental switched SHE is presented in detail.

This study presents the performance of a novel hybrid islanding detection method for multi-single-phase photovoltaic (PV) inverters based on the combination of four active methods and three passive methods. Although islanding detection in PV multi-inverter systems has been widely researched, most islanding studies are focused on three-phase inverters, rather than single-phase ones. In this study, different active and passive methods are used to detect the islanding of four paralleled single-phase PV inverters. By combining those methods synergistically, it reduces their weakness of each method, while combining their advantages. The novelty of the proposed system methodology consists of four paralleled single-phase inverters equipped with four different active methods, namely active frequency drift, Sandia frequency shift (SFS), sliding mode frequency shift, and Sandia voltage shift triggered by a block composed of three passive methods: voltage frequency protection, rate of change of frequency, and DC-link. This novel hybrid system is studied under different detailed scenarios, where it shows its performance and characteristics.

High-voltage direct current (HVDC) power modulation can effectively improve the system frequency stability after high power shortage fault disturbance. This study presents an emergency control method by coordinating the active powers of multiple HVDC lines for enhancing the frequency stability. Firstly, the system frequency response model with HVDC modulation is built, and then a simplified method for calculating the sensitivity of maximum frequency to HVDC modulation is proposed based on the first-order differential method. Next, based on a functional relationship of the AC bus voltage and the actual HVDC modulation capacity, the methodology for calculating the HVDC real-time modulation capacity is proposed. Finally, the coordinated multiple HVDC modulation emergency control model is established which aims to minimise the modulation cost considering the maximum frequency threshold. The proposed methodology has been tested in a real-power system. The simulation results of different scenarios have verified its effectiveness in suppressing the rise of maximum frequency and enhancing frequency stability.

In order to better schedule distributed energy resources (DERs) to improve the recovery ability of the distribution network, the optimal recovery strategy is proposed in this study. The strategy can be applied to speed up the recovery process and reduce the power shortage of shedding loads in the distribution network when a power outage occurs. The scheduling coefficient is defined to quantify the rationality of each scheduling resource. Based on this index, this study establishes an optimal scheduling model, which consists of three objectives. The non-dominated sorting genetic algorithm-II is applied to search this multi-objective optimal recovery solution in this study. Then, the modified IEEE 39-node system is used as the case study to verify the feasibility of the proposed model and the test results prove the effectiveness and efficiency of the proposed model.