As the integration of wind power into the power grid increases rapidly, the total output of the regional wind farms has become the concern of the power system operators and market traders. This study proposes a short-term probabilistic forecast model for this regional application. The uncertainty information provided by the proposed model can help the users make better decisions in the power system. A new distance-weighted kernel density estimation (DWKDE) method is proposed to forecast the full distribution function of the wind power. Its distance kernel is able to assign different weights to the samples similar to the target point. The beta kernels are introduced to adapt to the double-bounded characteristic of the wind power density. To further improve the performance of the DWKDE model, a regime-switching strategy is applied based on the regional wind direction clustering, while a feature selection method of minimal-redundancy-maximal-relevance is provided to determine the proper feature set. A case study of 28 wind farms in the East China is provided to evaluate the performance with the quality measures of reliability, sharpness, and the pinball score. The proposed method is easy to use and performs well according to the results of the evaluation.

Due to decoupling between mechanical part and electrical part of doubly fed induction generator (DFIG), the DFIG has no natural frequency response capability, which results in decreasing of total rotary inertia of power grid, and the frequency stability of power grid will face larger challenges. This study proposes an assessment method of equivalent inertia time constant, further gives the assessment value of equivalent inertia time constant of DFIG. Then, a virtual inertia optimisation control of DFIG using rotor current direct control based on status assessment value is proposed, which includes conventional function, status assessment and additional virtual inertia control. The assessment values of equivalent inertia time constant of wind farms, synchronous generator and power grid connected with multi-type generators are calculated, which are related to penetration of wind power and control strategies. The simulation results verify the efficacious of the proposed virtual inertia optimisation control and the accuracy of assessment method of equivalent inertia time constant, and the frequency stability of power grid is improved in the condition of different active power of wind farms and penetration of wind power.

In this study, the inertial response characteristics of the permanent magnetic synchronous generator (PMSG)-based wind energy conversion system (WECS) with different virtual synchronous generator (VSG) schemes are analysed and compared in detail. It is found that the dynamic coupling between the VSG active power control loop and the other control function, e.g. maximum power point tracking control and direct current bus voltage control, in VSG-controlled WECS (WECS-VSG) is inevitable. The coupling would result in the variations of the equivalent inertia constant and damping coefficient. The frequency support capability of the WECS-VSG is thus weakened and the WECS-VSG is even harmful to grid frequency support under some conditions. Besides, the requirement of the smooth energy recovery stage is usually put forward by the power system operator for the characteristics of the energy sources for inertial response (ESIRs) in WECS. To regain the expected synchronous generator alike inertial response characteristics and follow the ESIR property, a generalised optimal WECS-VSG control strategy which can be embedded into different WECS-VSG schemes is proposed and two examples for different ESIRs are designed. Finally, the effectiveness of the analysis and the proposed strategy are verified by simulation results.

Under partially shaded conditions (PSC), a photovoltaic (PV) array takes on more complex characteristics. It is very difficult and utterly necessary for PV system designers to understand and predict them. Other than the prevailing methodology of solving a set of non-linear equations, the proposed methodology focuses on three key points of short circuit, MPP and open circuit. Besides, its V–I curve is split into three regions and replaced by three asymptote lines. From this viewpoint, this paper presents a novel Psim-based piece-wise linear macro-model whose circuit parameter values are determined based on the foregoing three key points. The novel model, compared with the other published models, is characterised by short running time, relative high accuracy, and reliable unique solution. This model avoids the computational complexity and convergence issue. Furthermore, based on the novel model, an optimising configuration-simulation model is presented for PV system designers to optimise PV array configurations under several given shaded patterns. Two new concepts of power and voltage reducing rate shall be introduced to estimate the PSC effect. The novel model and formulas, therefore, shall provide a good solution for studying the behavior of a large-scale PV array in a complex scenario.

The high level of penetration of photovoltaic (PV) systems into electric power grids increases rapidly due to many merits of such promising technology. In the simulation investigation of PV systems, an accurate PV model is vital, where it plays an important role through the dynamic analysis of these systems. The mathematical model of the PV module is a nonlinear I–V characteristic including many unknown parameters as data provided by the PV manufacturers' are inadequate. This paper introduces a novel application of the whale optimisation algorithm (WOA) for estimating the parameters of the single, double, and three diode PV models of a PV module. The WOA-based PV models are validated by the simulation results, which are carried out under various environmental conditions using MATLAB program. The effectiveness of the WOA-based PV models is checked by comparing their results with that obtained using other optimisation methods. To obtain a realistic study, these simulation outcomes are compared with the experimental outcomes of a Kyocera KC200GT PV module. The WOA-based PV model is efficiently evaluated by comparing the absolute current error of this model with that obtained using other PV models. Using this meta-heuristic algorithm application, an accurate PV model can be obtained.

Multi-terminal alternating current (AC)/direct current (DC) hybrid transmission technology is a promising alternative for the integration and transmission of large-scale wind power. Optimal power allocation (OPA), to distribute the active power between AC and DC transmission lines in order to minimise transmission power loss, is a significant problem to be solved. A new simplified OPA algorithm for multi-terminal AC/DC hybrid grids is proposed in this work. The power flow models of the AC grid and DC grid are separately established and linearised, and both AC and DC power losses are formulated in a simplified way. By doing so, the mathematical formula of the total power loss is expressed as a multivariate quadratic function, of which the minimum value can be directly obtained with the derivative method. Simulations based on a four-terminal AC/DC hybrid grid with wind power integration are carried out by using MATLAB, and the effectiveness of the proposed algorithm is validated by case studies.

Connecting large offshore wind farms using high-voltage direct current (HVDC) transmission systems based on the modular multilevel converter (MMC), the offshore alternating current (AC) voltage and frequency are regulated by the offshore MMC station and are important for the stable wind power generation and transmission. This study proposes an enhanced AC voltage and frequency control strategy of the offshore MMC for wind farm integration, where an additional frequency loop is used to improve its AC voltage and frequency controllability. A fault current injection control is also proposed, where the offshore MMC station actively provides fault currents during an offshore AC fault to enable overcurrent protection for the network. To ride-through onshore AC faults, a direct current (DC) voltage-dependent AC voltage controller is introduced to actively reduce the offshore AC voltage during an onshore AC fault to alleviate the DC overvoltage of the HVDC system. Simulation results in normal operation and during offshore and onshore faults confirm the feasibility of the proposed control scheme.

Power grid resilience has been a major concern as extreme weather events become more frequent recently. Particularly, wind power generation has constituted a significant body of generation portfolio worldwide. Under stormy weather conditions, wind power generation would be curtailed due to the over-speed protection of wind turbines. Subsequently, the sharply reduced generation resources would significantly endanger the reliability of power supply. In this study, the authors propose to apply the risk-limiting methodology to improve the efficient utilisation of wind power prior to reluctant wind curtailment on the advent of wind stormy events. The proposed method integrates three programs, namely, day-ahead unit commitment (UC), hourly-ahead UC, and real-time load shedding into one single model along with risk-limiting constraints. The first program provides the baseline of hourly dispatch; whereas, the latter two programs serve as recourse means while wind stormy event unfolds. The proposed model is cast into a multi-stage mixed-integer linear programming model and solved by commercial solvers. Illustrative examples demonstrate that the proposed method can reduce the total dispatch cost over the time-horizon including the wind stormy event, by postponing the timing of proactively starting quick-start generating units and shedding loads, in contrast to conventional two-stage stochastic dispatch methods.

Fault-ride-through (FRT) is an imperative capability in wind turbines (WTs) to ensure grid security and transient stability. However, doubly fed induction generator-based WTs (DFIG-WTs) are susceptible to disturbances in grid voltage, and therefore require supplementary protection to ensure nominal operation. The recent amendments in grid code requirements to ensure FRT capability has compelled this study of various FRT solutions. Therefore, for improving FRT capability in pre-installed WTs, re-configuration using external retrofit-based solutions is more suitable and generally adapted. The most relevant external solutions based on retrofitting available are classified as (a) protection circuit and storage-based methods and (b) flexible alternating current transmission system-based reactive power injection methods. However, for new DFIG-WT installations, internal control modification of rotor-side converter (RSC) and grid-side converter (GSC) controls are generally preferred. The solutions based on modifications in RSC and GSC control of DFIG-WT are classified as (a) traditional control techniques and (b) advanced control techniques. This study ensures to curate and compare the FRT solutions available based on external retrofitting-based solutions and internal control modifications. Also, the future trends in FRT augmentation of DFIG-WTs are discussed in this study.

This study aims to propose a methodology for a hybrid wind–solar power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar–wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of wind and solar with optimal ratio will lead to clear benefits for hybrid wind–solar power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into electricity grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. This research targets at battery storage technology and proposes a generic methodology for optimal capacity calculations for the proposed hybrid wind–solar power system.

With a radiant energy of 4.5 kWh/m² (International Power Plant in Iran), Iran has a good potential for using solar thermal energy to dehumidify products in the agricultural and pharmaceutical industry. In fact, drying provides the possibility of restoring surplus products due to its longer shelf life, for future use. Indirect drying results are better results (nutrition and taste) than direct drying. Indirect solar dryer today works in many countries in industrial and lower levels of humidity and is quite satisfactory. It should be noted that the electronic and control system is embedded in data creation and air flow when necessary. The solar dryer is a device that performs the drying of different products with the use of renewable energies, in other words, performs dehumidifying operations without even using 1 W of electricity from the city.

Islanding in power systems is a challenge that results in various uncertainties in the system parameters, degrades power quality, and may endanger the maintenance workers. This study presents a new passive islanding detection approach for grid-connected distributed generation (DG) units. The proposed method employs a Kalman filter (KF) to extract and filter the harmonic contents of the voltage signal measured at DG terminals. A three-phase voltage signal is measured at the point of common coupling and taken as a test signal for islanding detection. First, a residual signal is generated using the KF to detect different changes in the power system. In the second step, multiple harmonic contents are estimated by the KF to calculate a criterion named selected harmonic distortion (SHD). The variation of SHD classifies between islanding and normal conditions. The IEEE 13-bus test system simulated in Matlab/Simulink is used as a testbed to assess the performance of the proposed approach. The proposed method is extensively analysed under various islanding and non-islanding scenarios. The results demonstrate that the proposed method can successfully differentiate between islanding and non-islanding events. Moreover, it provides high reliability by eliminating the non-detection zone and stands robust against the false operation.

In this circumstance of global warming, energy market deregulation, and enormous load growth, distribution network entails a proficient strategy to maintain the reliability and efficiency of the power service. Incorporation of solar photovoltaic (PV) system and battery storage (BS) in coordination with distributed static compensator (DSTATCOM) is a competent and practical approach to alleviate the power quality and reliability concern. In this study, a comprehensive strategic model is presented to optimally deploy PV, BS, and DSTATCOM to maximise voltage profile improvement, reliability, economic, and ecological benefit of the network. An accurate and precise novel voltage profile improvement indicator namely network voltage profile improvement index is proposed. Benefit–cost ratio and environment benefit index are proposed to quantify economic and environmental benefits, respectively. Similarly, reliability indices such as expected energy not served are used to appraise the system reliability. A fuzzy based extended version of NSGA II is utilised for the optimal deployment of the devices considering security limits. The proposed method is tested on 33-bus and 69-bus distribution networks considering time variant practical load models and the obtained results validate the efficacy and efficiency of the proposed method when compared with other multi-objective algorithms.

In this study, a novel data-driven framework is proposed to offer predictive analytics of wind turbine (WT) unexpected shut-downs based on data collected by the supervisory control and data acquisition (SCADA) system. A new parameter, the remaining functional life (RFL), is introduced to describe the length of a period until the next WT shut-down and a binary target parameter is created based on the RFL for indicating impending unexpected WT shut-downs. A two-stage data-driven framework is proposed to develop the predictive analytics model of the unexpected WT shut-downs based on SCADA data. The first stage employs clustering methods to automatically cluster WT SCADA data through unsupervised learning. In the second stage, based on clusters of SCADA data, famous classification methods are applied to develop models for inferring the binary target parameter. To validate the proposed data-driven framework, case studies and intensive computational experiments are conducted. Computational results confirm that meaningful predictive analytics of unexpected WT shut-downs can be produced through the proposed data-driven framework.