Wyniki wyszukiwania - BazTech

1

Investigating the possibility of using a supervised neural network to predict the amount of electricity generated by wind farms

Kamiński Mateusz, Kolasa Marta

Przegląd Elektrotechniczny

|

2023

|

R. 99, nr 4

111--117

EN

The article presents the state-of-the-art and the results of the authors’ own research obtained with the use of an artificial neural network to predict the amount of energy generated by wind turbines. A supervised neural network was used to convert algorithmically inputted meteorological data into output forecast data representing the amount of energy that could be generated by the offshore wind turbines. The amount of energy produced by renewable energy sources is directly linked to unpredictable weather conditions. The stochastic nature of meteorological conditions makes it difficult to extrapolate generation curves, which are necessary for the balancing energy market. Implementing neural networks in national energy systems can make them more resilient and sustainable, by enabling the efficient synergy of RES and conventional energy sources.

PL

W artykule przedstawiono przegląd literatury oraz wyniki badań autorów związane z wykorzystaniem sieci neuronowych do predykcji generowanej energii elektrycznej przez farmy wiatrowe. W pracy wykorzystano nadzorowaną sieć neuronową do konwersji wartości wejściowych, w postaci meteorologicznych danych pogodowych, na dane wyjściowe, w postaci prognozowanej dostępnej generacji energii elektrycznej przez morską farmę wiatrową. Ilość wytwarzanej energii poprzez odnawialne źródła energii jest skorelowana z nieprzewidywalnymi warunkami środowiskowymi. Stochastyczna natura warunków atmosferycznych utrudnia wyprowadzenie ekstrapolowanych krzywych generacji, niezbędnych do zarządzania rynkiem bilansującym energii elektrycznej. Zastosowanie sieci neuronowych w krajowych systemach energetycznych może zagwarantować bezpieczną zrównoważoną synergię OZE z konwencjonalnymi źródłami wytwórczymi.

2

Robust estimation based nonlinear higher order sliding mode control strategies for PMSG-WECS

Nazir Awais, Khan Safdar Abbas, Khan Malak Adnan, Alam Zaheer, Khan Imran, Irfan Muhammad, Rehman Saifur, Nowakowski Grzegorz

Bulletin of the Polish Academy of Sciences. Technical Sciences

|

2023

|

Vol. 71, nr 5

art. no. e147063

EN

The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.

3

Decoupling vector control and optimisation of PMSG-based wind energy system using adaptive type-1 and type-2 fuzzy logic control

Mekki Mustapha, Tayeb Allaoui, Belabbas Belkacem, Mouloud Denai

Przegląd Elektrotechniczny

|

2020

|

R. 96, nr 8

112--116

EN

Variable-speed wind energy conversion systems based on permanent magnet synchronous generators (PMSG) are becoming increasingly popular over the recent years and PMSGs are being adopted by many wind turbine manufacturers especially due to several advantages such as high energy density, low maintenance, self-excitation and direct-drive operation. Vector control is currently the most widely used control strategyin PMSGs to achieve decoupling between the magnetic flux and torguqe via the direct and quadrature components of the current respectively.The major disadvantage of this method is the use of current sensors to ensure accurate decoupling. In this work, a decoupling vector control strategy based on Type-1 and Type-2 fuzzy logic is proposed eliminating the use of current sensors. In addition, a maximum power point tracking (MPPT) technique is proposed to optimise the power extracted from the wind turbine system. Two speed control methodes based on adaptive Type-1 and Type-2 fuzzy logic fractional proportional and integral (PI) controllers. Several simulations are presented to demonstrated the effectiveness of the proposed control schemes for the PMSG-based wind energy conversion system.

PL

Generator synchroniczny z magnesem trwałym PMSG odgrywa kluczową rolę w konwersji energii wiatru (WECS). Sterowanie wektorowe było najczęściej stosowane jako strategia sterowania dla tego generatora w celu zapewnienia oddzielenia prądu stałego od kwadratury. Wadą tej metody jest to, że potrzebuje czujników prądu, aby zapewnić oddzielenie. Artykuł koncentruje się na sterowaniu wektorem oddzielającym opartym na logice rozmytej typu 1 (DFLC1_VC) i logice rozmytej typu 2 (DFLC2_VC). Możemy zapewnić kontrolę systemu, a oddzielenie bez użycia czujników prądu zapewnia kontrolę i odsprzęgnięcie w tym samym czasie. Wyniki symulacji wykazały skuteczność proponowanych strategii kontroli WECS w oparciu o PMSG.

4

Modelling and Co-simulation of small wind turbine with permanent magnet synchronous generato

Quintal-Palomo Roberto Eduardo, Dybkowski Mateusz

Przegląd Elektrotechniczny

|

2019

|

R. 95, nr 10

208--213

EN

This paper presents the Co-Simulation of a Small Wind Turbine (SWT) with Permanent Magnet Synchronous Generator (PMSG). It combines Simulink, Maxwell and Simplorer software’s to show the electrical machine behaviour connected with the power electronics’ circuit. To the control of the system the Maximum Power Point Tracking (MPPT) algorithm is used. The finite element analysis (FEA) was used to design the novel electrical machine with permanent magnets. Application of FEA method for PMSG modelling guarantee exhibit a more accurate behaviour over simplified Simulink models, also during motor and power electronics faults.

PL

W artykule przedstawiono zagadnienie symulacji małej turbiny wiatrowej z generatorem synchronicznym z magnesami trwałymi (PMSG) przy wykorzystaniu trzech niezależnych środowisk programistycznych (tzw. współsymulacja). Podczas analizy wykorzystano wspólne obliczenia z programów Simulink, Maxwell i Simplorer. Model generatora wykonany został w środowisku Maxwell (z wykorzystaniem metody elementów skończonych (FEM)), co pozwala na jego dokładną analizę zarówno w stanach statycznych jak i dynamicznych. Układ energoelektroniki zamodelowano w programie Simplorer a układy sterowania (przy wykorzystaniu metody MPPT) w środowisku Simulink. Taka analiza pozwala na uzyskanie dokładnych rezyltatów w różnych warunkach pracy – w tym podczas uszkodzenia maszyny lub elementów energoelektroniki.

5

Comparison of three estimators used in a sensorless MPPT strategy for a wind energy conversion chain based on a PMSG

Echchaachouai A., El Hani S., Hammouch A.

Przegląd Elektrotechniczny

|

2018

|

R. 94, nr 3

18--22

EN

In this paper a WECS (Wind Energy Conversion System) based on a PMSG (Permanent Magnet Synchronous Generator) and implementing a sensorless MPPT (Maximum Power Point Tracking ) strategy is presented using three types of generator rotor speed and angle estimators; the Angle Tracking Observer, the Extended Kalman Filter and the Synchronous Reference Frame Phase Locked Loop. The main purpose is to compare these estimators. Simulation results in Matlab-Simulink allowing this comparison can be found at the end of this work.

PL

W artykule opisano generator z magnesami stałymi PMSG wykorzystujący strategię MPPT (śledzenie maksimum mocy). Porównano trzy typy estymatorów prędkości i kąta obrotu wirnika: czujnik kąta obrotu (angle tracking observer), filtr Kalmana i synchroniczną pętlę fazową (synchronous frame phase locked loop).

6

High performances of grid-connected DFIG based on direct power control with fixed switching frequency via MPPT strategy using MRAC and neuro-fuzzy control

Amrane F., Chaiba A., Mekhilef S.

Journal of Power Technologies

|

2016

|

Vol. 96, nr 1

27--39

EN

This paper presents high performance improved direct power control (DPC) based on model reference adaptive control (MRAC) and neuro-fuzzy control (NFC) for grid connected doubly fed induction generator (DFIG), to overcome the drawbacks of conventional DPC which was based only on PID controllers, namely the speed/efficiency trade-off and divergence from peak power under fast variation of wind speed. A mathematical model of DFIG implemented in the d-q reference frame is achieved. Then, a direct power control algorithm for controlling rotor currents of DFIG is incorporated using PID controllers, and space-vector modulation (SVM) is used to determine a fixed switching frequency. The condition of the stator side power factor is controlled at unity level via MPPT strategy. The MRAC which is based on DPC is investigated instead of PID regulators. Also, the performances of NFC based on DPC are tested and compared to those achieved using MRAC controller. The results obtained in the Matlab/Simulink environment using robustness tests show that the NFC is efficient, has superior dynamic performance and is more robust during parameter variations.

7

Evaluation of wind energy potential for four sites in Ireland using the Weibull distribution model

Jamdade P. G., Jamdade S. G.

Journal of Power Technologies

|

2015

|

Vol. 95, nr 1

48--53

EN

Wind speed is receiving greater attention in the design and study of wind energy conversion systems (WECS). Using meteorological data, this paper studies the availability of wind energy potential at four sites in Ireland: Malin Head, Dublin Airport, Belmullet and Mullingar. An analysis is made of mean wind speed data collected at a height of 50 m above ground level at each site over a period of seven years. A two parameter Weibull distribution model is used to analyze wind speed pattern variations. Weibull parameters are calculated by the Least Squares Method (LSM). The results relating to wind energy potential are given in terms of the density function. Analysis shows that coastal sites of Ireland such as Malin Head, Dublin Airport and Belmullet have good wind power potential.