Program: 3rd Session on Friday (13:20-15:00)

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F3-1Modeling & Computing Methods

13:20 Evaluation of Wind Turbine Characteristics Built-in Model in Matlab Simulink

Abobkr Abobkr (College of Engineering Technology Houn, Libya); Mohamed El-Hawary (Dalhousie University, Canada)

Due to growing concerns over climate change, more and more countries are looking to renewable energy sources to generate electricity. Therefore, wind turbines are increasing in popularity. The amount of mechanical power that can be extracted from the wind by a turbine rotor depends on the characteristics of wind turbine. Furthermore, the aim of the characteristics of any wind turbine is to provide an expectation of how to design the generator’s control system in order to track these characteristics and extract maximum power from the wind. The characteristics of wind turbines is the focus of this paper. A new wind turbine characteristics methodology is proposed and summarized in a new flowchart. A Matlab simulator was written to evaluate the performance coefficient of wind turbine. Unlike the conventional simulations which use the wind turbine block in the MATLAB /SIMULINK library, a block was modeled by supplementing the drive train subsystem with aerodynamic model

13:40 Neural Network Backpropagation Algorithm Control for PEM Fuel Cell in Residential Applications

Mohamed Chemsi (Universite du Quebec à Trois-Rivieres, Canada); Kodjo Agbossou (Universite du Quebec à Trois-Rivieres, Canada); Alben Cardenas (Universite du Quebec a Trois-Rivieres, Canada)

Integration of renewable energy in residential applications is one of the most promising options to reduce the impact of human activities on the environment. Residential loads are generally AC loads with high variations generating low-frequency ripples that can harm the sources especially the fuel cell. This paper investigates the use of a neural network algorithm to control a power converter for fuel cell (FC) system supplying a thermostatic residential load. The proposed algorithm allows a limitation of the FC current ripple under 2% without compromising the transient response of the system and permitting the correctly supply the AC load. The model of a two stages conditioning system, including a DC-DC boost converter and a full bridge IGBT, single-phase inverter with their control, has been implemented using MATLAB/Simulink and validated by simulation

14:00 An Approach to Precise Modeling of Photovoltaic Modules Under Changing Environmental Conditions

Seyedkazem Hosseini (Université du Québec, Canada); Shamsodin Taheri (Université du Québec en Outaouais, Canada); Masoud Farzaneh (UQAC/CIGELE, Canada); Hamed Taheri (École de Technologie Stupérieure, Canada)

Equivalent circuit models of photovoltaic (PV) modules are used to investigate the performance of PV systems for different operating conditions. The electrical characteristics of PV modules change as environmental conditions vary. Hence, for an accurate study of the PV modules when insolation and temperature are variable, it is necessary to verify the dependence of the parameters of the PV module model to insolation and temperature. This paper proposes a single-diode model of PV modules based on a novel approach for extracting the climate dependent parameters. The parameters of the model are updated for given environmental conditions so that the model is able to precisely yield the corresponding real characteristics of the PV module. Comparison between the simulated model and experimentally measured data demonstrates the effectiveness of the developed approach in determining the PV characteristics under variable weather conditions. The proposed model can be helpful to properly design and select PV systems.

14:20 On Optimization of SVMs Kernels and Parameters for Electricity Price Forecasting

Abdussalam Mohamed (Dalhousie University, Canada); Mohamed El-Hawary (Dalhousie University, Canada)

Forecasting electricity price is a popular task in a modern electricity market. Forecasting of future prices allows market trading participators to gain insight and make decisions. Selecting the best training parameters is often involved in forecasting in order to obtain optimal prediction. Support Vector Regression (SVR) provides a well-established and powerful regression method to fit data and find minimal-risk slack variables around the fit line. Finding the best fit strongly depend on input feature set and the tuning of hyper-parameters. SVR quadratic programming (QP) and parameters optimization are applied to improve the forecasting accuracy. In this paper, quadratic programming optimization solving techniques are applied to improve the performance of SVMs, and a research conducted to study the influence of optimized hyperparameters using several known SVM kernels for electricity price forecasting.


13:20 In-Situ Test Assessment of Thyristor Level in the Converter Valve of HVDC Power Transmission

Longchen Liu (State Grid Sichuan Electric Power Research Institute, P.R. China); Ke Yue (Xi’an Jiaotong University, P.R. China)

The thyristor level is the basic unit of HVDC converter valve, which is the core equipment in the HVDC power transmission system. Because the converter valve performance directly affect the reliability, stability and efficiency of the whole power system, each thyristor level in the converter valve needs to be test routinely during the maintenance period of the converter valve equipment. Currently there is no specific and detailed test scheme for the thyristor level with thyristor control unit (TCU). Therefore, it is particularly urgent to study the in-situ test technology for the thyristor level in the HVDC converter valve. In this paper, the in-situ test principle, content and methods for the thyristor level with TCU are presented based on the analysis of the thyristor level working principle and the IEC 60700-1-2008 standard in order to offer technical support for the operation and maintenance of the HVDC converter valve. In general, the reverse recovery period of thyristor level is the most vulnerable stage of thyristor operation process, so a transient high-voltage pulse is applied to the thyristor level during its reverse recovery period in order to test the characteristics of thyristor level. Then, the in-situ test method for the thyristor level is applied to the converter valve test of ±800kV HVDC power transmission project, and the practical test result verifies the reasonability and validity of the proposed in-situ test method.

13:40 Self-synchronisation of Wind Farm in MMC-based HVDC System

Mohammad Amin (Norwegian University of Science and Technology, Norway); Marta Molinas (NTNU, Norway)

The stability of a offshore wind power network connected through a high voltage dc (HVDC) transmission line is a critical problem since there is no direct connection to a strong ac collection (ACC) bus. Field experience has shown that subsynchronous oscillation (SSO) and harmonic resonance can occur between the wind farms and the HVDC systems. The oscillations can appear in the presence of background harmonics and is arguably resulting from the controller interaction of the Wind Energy Conversion System (WECS) converter controller and the HVDC converter controller. The design of the synchronization unit (Phase-Locked-Loop) has shown to have a significant impact in achieving satisfactory performance. However, both slow and very fast synchronization units could directly affect the control performance and degrade system stability. This paper proposes a controller design without PLL for the WECS grid-side converter which does not have a dedicated synchronization unit (PLL) in the controller. This controller is implemented on the WECS converters of the ACC side to synchronise them to the Modular Multi-level Converter (MMC)-based HVDC system. A detailed analysis is presented and the results are compared with the widely used decouple d-q control structure. The impedance frequency responses for both the d-q frame control and the synchronverterbased control are presented to show a comparison of the system performance. The time domain simulation results are presented to show how the self-synchronisation impacts on the system performance compared to the classical control solution.

14:00 Planning and Design of a European HVDC Grid Divided Into Feasible Protection Zones

Sebastian Weck (Technische Universität Darmstadt, Germany); Simon Wenig (Karlsruhe Institute of Technology, Germany); Tim Bongers (RWTH Aachen University, Germany); Jutta Hanson (TU Darmstadt, Germany); Thomas Leibfried (Karlsruhe Institute of Technology, Germany); Albert Moser (IAEW, Germany)

While recent advances in voltage source converter technology boost the number of installed offshore DC links and interconnectors, the possibility to build HVDC-grids only arises, if existing technical barriers can be removed. In this work the planning of an HVDC overlay grid is introduced. Using a European transmission network model, a future scenario of 2020 is considered to identify HVDC terminals and connect them in an optimal way. Based on the determined HVDC network, strategies are applied to split the network into protection zones subsequent to contingencies. Transient simulations proof that DC faults can be handled and a global outage is avoided.

14:20 Droop Gains Selection Methodology for Offshore Multi-Terminal HVDC Networks

Mohamed Abdelwahed (University of Waterloo, Canada); Ehab El-Saadany (Waterloo University, Canada)

This paper presents a methodology for selecting the droop gains of the voltage source converters (VSCs) in multi-terminal high-voltage direct current (MT HVDC) transmission system. The droop gains are selected to improve the DC voltage transient and steady state dynamics performance. The proposed methodology relies on improving the small signal stability of the HVDC network, which is performed by selecting the droop gains values that increase minimize the real part of the system critical eigenvalues, while maintaining the steady state voltage deviation within limits. The proposed methodology has been tested on the CIGRE B4 DC grid test system. Furthermore, the simulation results confirm the effects of selecting the proper droop gains on the DC voltage dynamics.

14:40 Dynamic Performance Control of Modular Multilevel Converters in HVDC Transmission Systems

Seyedkazem Hosseini (Université du Québec, Canada); Shamsodin Taheri (Université du Québec en Outaouais, Canada); Edris Pouresmaeil (Polytechnic University of Catalonia, Spain); Joao Catalão (University of Beira Interior, Portugal)

This paper focuses on dynamic performance control of modular multilevel converters (MMC) in high-voltage direct current (HVDC) transmission systems. To achieve this objective, a new mathematical model including six state variables of ac-currents and dc-link voltage of MMC, and circulating currents of converter arms are proposed for MMC in d-q reference frame. In addition, a robust control technique with three sub-control loops is designed to provide the stable operation of MMC. In the overall structure of the proposed controller, three outer, central and inner loops have the duties of 1) making the state variables error zero with changeable convergence rate, 2) adding robustness characteristic to the proposed controller, and 3) generating the appropriate reference values for MMC’s currents, respectively. The effectiveness of the proposed control algorithm is investigated via MATLAB simulation. The simulation results highlight the capability of the proposed control algorithm in offering an accurate active and reactive power tracking through the control method of MMC, a stabilized dc-link voltage, capacitor voltage balancing of submodules, and minimization of circulating currents of converter arms during dynamic transitions and steady state operation.