Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory

In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G) technique, electric vehicles (EVs) can act as mobile energy storage units, which could be a solution for load frequency control (LFC) in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC) theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG) are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances

Innovative Controller Design for a 5MW Wind Turbine Blade

The development and evaluation of a nonlinear pitch controller for wind turbine blades and the design and modeling of an associated actuator and controller was examined. The pitch actuator and controller were modeled and analyzed using Pneumatically Actuated Muscles (PAMs) for actively pitching the wind turbine blade. PAMs are very light and have a high specific work and a good contraction ratio. Proportional Integral and Derivative (PID) controllers were envisaged for the wind turbine pitching system at the blade tip due to its routine usage in the wind turbine industry. Deployment of controllers enables effective pitch angle tracking for power abatement at various configurations. The controller was subjected to four pitch angle trajectory signals. PID controllers were tuned to achieve satisfactory performance when subjected to the test signal. Low pitch angle errors resulted in satisfactory blade pitch angle tracking. Deployment of these controllers enhances wind turbine performance and reliability. The data suggest that the pitch system and actuator that was modeled using PAMs and PID controllers is effective providing robust pitch angle trajectory tracking. The results suggest that the proposed design can be successfully integrated into the family of wind turbine blade pitch angle controller technologies

SISTEM KONTROL SUDUT PITCH BILAH TURBIN ANGIN MENGGUNAKAN LOGIKA FUZZY UNTUK VARIABLE SPEED VERTICAL AXIS WIND TURBINE (VAWT)

VAWT (Vertical Axis Wind Turbine) is a turbine that has an upright mechanical structure with its blades rotating toward a perpendicular z-axis. Based on the experimental results, it is found that there is a relationship between the rotational speed of turbine that rotates generator with the output voltage and power. Thus, it is necessary to control the wind turbine speed so it can rotate according to the set point to be achieved. The contribution of this research is the development of a Fuzzy logic-based control system to control the speed of VAWT turbine where the speed of turbine is used as feedback. To design a Fuzzy rule base, the characteristics of the wind turbine’s response to wind speed are investigated first. Then Fuzzy logic-based controller is created and implemented. To test the effectiveness of the Fuzzy controller made, the implementation is carried out on a VAWT turbine while the simulation is applied to PMSG model using wind turbine through Simulink/Matlab. Based on simulation and experiment results, the performance of the control system using Integral Absolute Error (IAE) for each turbine speed set point value (35, 45, 85, and 100 RPM), it is found that for a small set point value, the IAE value will be larger than higher setpoints. The percentage of the average IAE value for the simulation is 10.25% higher than the experiment. It further shows that the control turbine speed at low speeds is relatively more difficult than at higher speeds.Turbin angin sumbu vertikal atau VAWT (Vertical Axis Wind Turbine) merupakan turbin angin yang memiliki struktur mekanik tegak ke atas dengan bilah-bilah turbin yang berputar terhadap sumbu-z tegak lurus. Berdasark an hasil eksperimen diperoleh bahwa terdapat hubungan antara kecepatan putaran turbin yang memutar generator dengan keluaran tegangan dan daya yang dihasilkan, sehingga diperlukan upaya mengendalikan kecepatan turbin angin agar dapat berputar sesuai setpoin yang ingin dicapai. Kontribusi dari penelitian ini berupa pengembangan sistem kontrol berbasis logika Fuzzy untuk mengendalikan kecepatan turbin VAWT dengan hanya menggunakan umpan balik berupa kecepatan turbin angin. Hal ini berbeda dengan penelitian sebelumnya dimana kecepatan angin dan keluaran daya dijadikan sebagai umpan balik. Untuk mengetahui karakteristik dari kecepatan turbin dan keluaran tegangan, serta hubungan antara kecepatan turbin dan kecepatan angin dengan variasi sudut pitch bilah, maka pengujian dilakukan dalam skala laboratorium dengan menggunakan blower. Untuk merancang rule base (aturan) Fuzzy, maka karakteristik dari respon turbin angin terhadap kecepatan angin diteliti terlebih dahulu. Kemudian kontroller berbasis logika Fuzzy dibuat dan diimplementasikan. Untuk menguji efektivitas kontroller Fuzzy yang dibuat, maka implementasi dilakukan pada turbin VAWT sedangkan simulasi diterapkan pada model PMSG turbin angin melalui Simulink/Matlab. Berdasarkan hasil pengujian melalui simulasi dan eksperimen dengan mengukur kinerja respon sistem kontrol menggunakan Integral Absolut Error (IAE) untuk masing-masing nilai setpoin kecepatan turbin (35, 45, 85, dan 100 RPM) diperoleh bahwa untuk nilai setpoin kecil maka nilai IAE akan semakin besar dibandingkan setpoin yang lebih tinggi. Persentase nilai rata-rata IAE untuk simulasi adalah 10,25% lebih tinggi dibandingkan dengan eksperimen. Hal ini kemudian menunjukkan bahwa pengendalian kecepatan turbin pada kecepatan rendah relatif lebih sulit dibandingkan dengan kecepatan turbin lebih tinggi

Gain scheduled torque compensation of PMSG-based wind turbine for frequency regulation in an isolated grid

Frequency stability in an isolated grid can be easily impacted by sudden load or wind speed changes. Many frequency regulation techniques are utilized to solve this problem. However, there are only few studies designing torque compensation controllers based on power performances in different Speed Parts. It is a major challenge for a wind turbine generator (WTG) to achieve the satisfactory compensation performance in different Speed Parts. To tackle this challenge, this paper proposes a gain scheduled torque compensation strategy for permanent magnet synchronous generator (PMSG) based wind turbines. Our main idea is to improve the anti-disturbance ability for frequency regulation by compensating torque based on WTG speed Parts. To achieve higher power reserve in each Speed Part, an enhanced deloading method of WTG is proposed. We develop a new small-signal dynamic model through analyzing the steady-state performances of deloaded WTG in the whole range of wind speed. Subsequently, H∞ theory is leveraged in designing the gain scheduled torque compensation controller to effectively suppress frequency fluctuation. Moreover, since torque compensation brings about untimely power adjustment in over-rated wind speed condition, the conventional speed reference of pitch control system is improved. Our simulation and experimental results demonstrate that the proposed strategy can significantly improve frequency stability and smoothen power fluctuation resulting from wind speed variations. The minimum of frequency deviation with the proposed strategy is improved by up to 0.16 Hz at over-rated wind speed. Our technique can also improve anti-disturbance ability in frequency domain and achieve power balance

Coordination of heat pumps, electric vehicles and AGC for efficient LFC in a smart hybrid power system via SCA-based optimized FOPID controllers

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Due to the high price of fossil fuels, the increased carbon footprint in conventional generation units and the intermittent functionality of renewable units, alternative sources must contribute to the load frequency control (LFC) of the power system. To tackle the challenge, dealing with controllable loads, the ongoing study aims at efficient LFC in smart hybrid power systems. To achieve this goal, heat pumps (HPs) and electric vehicles (EVs) are selected as the most effective controllable loads to contribute to the LFC issue. In this regard, the EVs can be controlled in a bidirectional manner as known charging and discharging states under a smart structure. In addition, regarding the HPs, the power consumption is controllable. As the main task, this paper proposes a fractional order proportional integral differential (FOPID) controller for coordinated control of power consumption in HPs, the discharging state in EVs and automatic generation control (AGC). The parameters of the FOPID controllers are optimized simultaneously by the sine cosine algorithm (SCA), which is a new method for optimization problems. In the sequel, four scenarios, including step and random load changes, aggregated intermittent generated power from wind turbines, a random load change scenario and a sensitivity analysis scenario, are selected to demonstrate the efficiency of the proposed SCA-based FOPID controllers in a hybrid two-area power system

Adaptive model predictive control of renewable energy-based micro-grid.

Doctoral Degree. University of KwaZulu-Natal, Durban.Energy sector is facing a shift from a fossil-fuel energy system to a modern energy system focused on renewable energy and electric transport systems. New control algorithms are required to deal with the intermittent, stochastic, and distributed nature of the generation and with the new patterns of consumption. Firstly, this study proposes an adaptive model-based receding horizon control technique to address the issues associated with the energy management system (EMS) in micro-grid operations. The essential objective of the EMS is to balance power generation and demand through energy storage for optimal operation of the renewable energy-based micro-grid. At each sampling point, the proposed control system compares the expected power produced by the renewable generators with the expected load demand and determines the scheduling of the different energy storage devices and generators for the next few hours. The control technique solves the optimization problem in order to minimize or determines the minimum running cost of the overall micro-grid operations, while satisfying the demand and taking into account technical and physical constraints. Micro-grid, as any other systems are subject to disturbances during their normal operation. Hence, the power generated by the renewable energy sources (RESs) and the demanded power are the main disturbances acting on the micro-grid. As renewable sources are used for the generation, their time-varying nature, their difficulty in predicting, and their lack of ability to manipulate make them a problem for the control system to solve. In view of this, the study investigates the impacts of considering the prediction of disturbances on the performance of the energy management system (EMS) based on the adaptive model predictive control (AMPC) algorithm in order to improve the operating costs of the micro-grid with hybrid-energy storage systems. Furthermore, adequate management of loads and electric vehicle (EV) charging can help enhance the micro-grid operation. This study also introduced the concept of demand-side management (DSM), which allows the customers to make decisions regarding their energy consumption and also help to reduce the peak load demand and to reshape the load profile so as to improve the efficiency of the system, environmental impacts, and reduction in the overall operational costs. More so, the intermittent nature of renewable energy and consumer random behavior introduces a stochastic component to the problem of control. Therefore, in order to solve this problem, this study utilizes an AMPC control technique, which provides some robustness to the control of systems with uncertainties. Lastly, the performances of the micro-grids used as a case study are evaluated through simulation modeling, implemented in MATLAB/Simulink environment, and the simulation results show the accuracy and efficiency of the proposed control technique. More so, the results also show how the AMPC can adapt to various generation scenarios, providing an optimal solution to power-sharing among the distributed energy resources (DERs) and taking into consideration both the physical and operational constraints and similarly, the optimization of the imposed operational criteria