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This article presents an application of neural network-based Model Predictive Control (MPC) to improve the wind turbine control system's performance in providing frequency control ancillary services to the grid. A closed-loop Hammerstein structure is used to approximate the behavior of a 5MW floating offshore wind turbine with a Permanent Magnet Synchronous Generator (PMSG). The multilayer perceptron neural networks estimate the aerodynamic behavior of the nonlinear steady-state part, and the linear AutoRegressive with Exogenous input (ARX) is applied to identify the linear time-invariant dynamic part. Using the specific structure of the Cascade Hammerstein design simplifies the online linearization at each operating point. The proposed algorithm evades the necessity of nonlinear optimization and uses quadratic programming to obtain control actions. Eventually, the proposed control design provides a fast and stable response to the grid frequency variations with optimal pitch and torque cooperation. The performance of the MPC is compared with the gain-scheduled proportional-integral (PI) controller. Results demonstrate the effectiveness of the designed control system in providing Frequency Containment Reserve (FCR) and frequency regulation in the future of power systems.

This paper compares three modelling approaches to capture the motion dynamics of a linear track sliding platform. Non-linear disturbances affecting the platform’s motion were observed. Effective control requires that these disturbances are modelled and can be dealt with in the control strategy. Step responses are measured experimentally to study the relation between motor torque and the speed of the platform. The model parameters are identified using the experimental data. A co-simulation based model (Siemens NX - Simulink) in conjunction with an equation-based resisting torque is developed as a first candidate, and compared with a non-linear autoregressive model with exogenous input (NLARX) and a simple first-order transfer function. The models’ ability to capture the system dynamics are then evaluated. The NLARX model and co-simulation models are found to have significant value for control applications.

In a decarbonised economy, hydrogen could be a promising energy carrier, mainly for the transportation sector. Using hydrogen-filled vehicles can decrease air pollution and greenhouse gas emission. One of the requirements for the implementation of hydrogen as a fuel for the transportation sector is a focus on the optimal design of hydrogen refuelling stations. In this work, a model was developed to study and optimise the performance of a hydrogen refuelling station located in Belgium. To maximise the total annual profits, the capacity of each subcomponent for a hydrogen refuelling station, including the electrolyser, compressor and storage, was optimised. The effect of participation in the reserve market on the economic feasibility of the hydrogen refuelling station was studied as well. The simulation was established by realistic data from the Belgian electricity market. The analysis showed that the price of both hydrogen and electricity notably affect the economic viability. Besides, results confirmed that the economic feasibility could be enhanced through participation in the reserve market.

The global wind power capacity is on a constant rise. Many countries are moving towards renewable energy sources. Wind energy accounts for the biggest renewable energy resource in Europe. Despite all the benefits, wind energy tends to weaken the grid stability. One reason for this is the fact that most wind turbine generators are not directly coupled to the grid and do not provide ancillary services, such as primary frequency control, due to the lack of rotating inertia. This paper presents detailed models of a wind turbine with a permanent magnet synchronous generator (PMSG). This model is used to test the feasibility of providing ancillary services by performing the pre-qualification test for primary frequency control, as established by the Belgian Transmission System Operator (TSO). These tests are conducted under 4 different wind profiles, each having a different level of turbulence.

The objective of this paper is to investigate the performance pitch and active speed stall control, and their impact on the structural loads of small and medium wind turbines (SMWTs). Large wind turbines use blade pitching to limit the power at high wind speeds. For SMWTs, the cost and complexity of a blade pitching system are not justified, so that passive yaw, stall control, or a furling tail mechanism is used instead. However, the choice of a proper control concept is not straightforward for SMWTs. In this regard, it is important to take into account that the control strategy has a significant impact on the structural loads. Reducing the structural loads results in a longer lifespan and ensures the safe operation of the wind turbine in stormy wind gusts or fierce winds. In this study, a 10 kW wind turbine is operated with different control strategies to investigate the corresponding loads, both in uniform and turbulent winds. The simulation results show that controlling power around the rated value is feasible and stable for both control strategies. However, active speed stall control increases the bending moments at the blade root, while it lightens the tower base moments, in contrast to the pitch control.

This study investigates the performance of ‘Group Method of Data Handling’ type neural network algorithm in short-term time series prediction of the renewable energy and grid-balancing variables, such as the Net Regulation Volume (NRV) and System Imbalance (SI). The proposed method is compared with a Multi-layer Perceptron (MLP) neural network which is known as a universal approximator. Empirical validation results show that the GMDH performance is more accurate in compression with the most recent forecast which is provided by ELIA (Belgian transmission system operator). This study aims to practice the applicability of the polynomial GMDH-type neural network algorithm in time series prediction under a wide range of complexity and uncertainty related to the environment and electricity market.

The need for balancing services in the European electricity grid is increasing. The reason is twofold: renewable energy sources (RES) are still in up rise, meanwhile the classical power plants — commonly used to provide balancing — are economically pushed out of the market. This results in less available balancing resources but increasing balancing needs as RES are less predictable and controllable. The decline of the balancing volume provided by classical power plants can be counteracted by the concept of Demand Side Response (DSR). Balancing services are shifted towards the electricity consumers instead of traditionally being an electricity producer's responsibility. The concept of DSR is well documented as it was already introduced in 1973 at the time of the first energy (oil) crisis. Now, the DSR concept gains again momentum as electricity markets rapidly change to adopt RES. New insights and incentives are to be investigated as the electrical landscape has changed tremendously since the first introduction of DSR. This paper will focus on the concept of DSR in process industry.

Due to an increasing amount of wind turbines in the power system, which have a volatile power output, the need for flexibility increases. This flexibility can be obtained by ancillary services. Therefore, the provision of ancillary services with wind turbines is gaining interest. As they currently do not participate in the frequency control, this might compromise the proper functioning of the power system. The modern turbines are equipped with a power-electronic converter, so they can be used to provide a variety of ancillary services when the appropriate control strategies are used. In this paper, the provision of active power reserves for frequency control is considered. Three state-of-the-art power control strategies, i.e., constant power control, linear slope control and percentage control are compared to determine their ability to maintain reserves. It is concluded that all the strategies are able to provide reserves, but linear slope control and percentage control perform the best, especially when the wind turbines are aggregated in wind farms.

With increasing levels of distributed generation (DG) units in the power system, smart control systems have to be developed to obtain a reliable operation of the system. It is likely that this 'smart grid' will emerge from several small smart grids called microgrids. These microgrids are able to provide a coordinated integration of DG units in the electric power system. Integrating wind turbines as microsources in islanded microgrids could be a first step towards achieving this goal. In this paper, a small wind turbine and storage device are equipped with the voltage based droop control (VBD) strategy to investigate their ability to obtain a stable microgrid operation. It was shown in an experimental setup that the wind turbine has the ability to maintain the power balance and control the voltage in the microgrid. The addition of a storage device leads to better results as the energy yield losses can be lowered by storing the excess energy in the batteries or providing energy when needed.

A smart transformer enables to control the power exchange between a microgrid and the utility network by controlling the voltage at the microgrid side within certain limits. The distributed generation units in the microgrid are equipped with a voltage-based droop control strategy. This controller reacts on the voltage change, making the smart transformer an element that controls power exchange without the need for communication to other elements in the microgrid. To build a smart transformer, several concepts are possible. In a smart transformer with continuous turns ratio, hereafter referred to as continuous smart transformer, the transformer's microgrid-side voltage can be controlled without voltage steps and the accuracy of the voltage control can be very high. The voltage control of a smart transformer with discrete turns ratio, hereafter referred to as discrete smart transformer, is less accurate, as the output voltage is regulated between several discrete values. In this paper, the development of a continuous and discrete smart transformer will be elaborated. Their validity will be proven by implementing these smart transformers in an experimental test setup. Also, some concepts to improve the control accuracy will be proposed.

Grid-connected small and medium wind turbines are a promising technology to further increase the share of renewable energy sources. Although their impact on the environment is proven to be advantageous, the cost effectiveness still needs to increase. In this paper, the impact of the passive diode rectifier on the Joule losses in the generator is investigated. Passive diode rectifiers cause unwanted harmonics in the current waveform and a low power factor, increasing the losses. The capacitance value at the output of this rectifier has a large influence on these harmonics. The amount of harmonics could be reduced by including an inductance in series with the generator terminals. However, this results in a higher reactive power demand, which also affects the losses. In this paper, the impact of both the capacitor and inductance values on the losses are investigated.

In several countries, the wind power penetration increased tremendously in the last years. As the current wind turbines do not participate in frequency control nor reserve provision, this may compromise the proper functioning of the primary control and the provision of power reserves. If no actions are taken, increasing levels of wind penetration may result in serious problems concerning the stable operation of the power system. This paper focuses on the provision of power reserves by wind turbines. For this service, the constant power control strategy is chosen as control strategy, as it gives a constant power output and has the ability to provide power reserves. In this way, the wind turbine behaves more like a conventional power plant. The choice of the power reference value is crucial as it determines whether or not a stable operation of the wind turbine is possible and power reserves can be provided. In this paper, an algorithm is proposed to obtain the range of possible reference values. By means of simulations, the optimal reference value to provide power reserves with a single wind turbine is obtained. Also, reserve provision in a wind farm is investigated. It is shown that the provision of power reserves with wind turbines using the constant power strategy is possible, especially in wind farms.

Smart microgrids are becoming an important concept to cope with the increasing demand of electricity and to integrate the large amounts of intermittent power sources in the electrical network. Microgrids are able to operate in grid-connected and islanded mode and present themselves to the utility network as controllable entities. For the primary control of the inverter-interfaced DG units, voltage-based droop controllers have been developed. With this fully distributed controller, an optimized integration of renewable energy is obtained, by possibly increasing the penetration depth of renewable DG units and mitigating over-voltage conditions. The main reason is the usage of a constant-power band with a width dependent on the nature of the energy source. This paper investigates the usage of secondary control in a microgrid with primary voltage droops. The secondary control operates at a slower rate than the voltage-based primary control and is communication-based, opposed to the primary controller. The secondary controller regulates the voltage at pilot points in the microgrid, the voltage at the point of common coupling or the power exchange between microgrid and utility network. The set-points for secondary control can be determined based on an optimisation scheme such as for losses, power quality and economic revenue. Dependent on these set-points, the microgrid secondary controller changes the power set-points of the DG units.

An increasing amount of converter-connected distributed generators (DG) inject electrical energy in the power grid. On the other hand the increasing amount of non-linear and unbalanced loads put the power grid under increasing stress. Therefore, it is important not only to maximize the power output of the DG's through Maximum Power Point Tracking, but also to minimize the harmonic voltage and harmonic current distortion of the power system. In this article the interaction between the control system injecting the power in the grid and the control system maximizing the power output of the solar array is examined.

The main contribution of this work is a novel calibration method to determine the clock parameters of the UWB receivers as well as their 3D positions. It exclusively uses time-of-arrival measurements, thereby removing the need for the typically labor-intensive and time-consuming process of surveying the receiver positions. Experiments show that the method is capable of accurately calibrating a UWB setup within minutes.

This paper is concerned with the problem of estimating the relative translation and orientation between an inertial measurement unit and a camera which are rigidly connected. The key is to realise that this problem is in fact an instance of a standard problem within the area of system identification, referred to as a gray-box problem. We propose a new algorithm for estimating the relative translation and orientation, which does not require any additional hardware, except a piece of paper with a checkerboard pattern on it. Furthermore, covariance expressions are provided for all involved estimates. The experimental results shows that the method works well in practice.

This paper is concerned with the problem of estimating the relative translation and orientation of an inertial measurement unit and a spherical camera, which are rigidly connected. The key is to realize that this problem is in fact an instance of a standard problem within the area of system identification, referred to as a gray-box problem. We propose a new algorithm for estimating the relative translation and orientation, which does not require any additional hardware, except a piece of paper with a checkerboard pattern on it. The experimental results show that the method works well in practice.

In this paper a comparison is made between four frequently encountered resampling algorithms for particle filters. A theoretical framework is introduced to be able to understand and explain the differences between the resampling algorithms. This facilitates a comparison of the algorithms with respect to their resampling quality and computational complexity. Using extensive Monte Carlo simulations the theoretical results are verified. It is found that systematic resampling is favourable, both in terms of resampling quality and computational complexity.

In Augmented Reality (AR), the position and orientation of the camera have to be estimated with high accuracy and low latency. This nonlinear estimation problem is studied in the present paper. The proposed solution makes use of measurements from inertial sensors and computer vision. These measurements are fused using a Kalman filtering framework, incorporating a rather detailed model for the dynamics of the camera. Experiments show that the resulting filter provides good estimates of the camera motion, even during fast movements.