Development of Probalistic Techniques for Network Assessment with Significant Wind Generation

Due to increasing awareness of global warming and high energy costs, more electrical power is being generated by using renewable sources. However some of these sources are not as predictable as conventional generation and they also lack the ability to be dispatched in the same way. The increase in the amount of wind power connected to transmission networks has been significant in some countries. But due to the stochastic nature of wind power, it is difficult to predict exactly how much power can be generated at any given time. This variable nature of wind power can cause line overloading and high voltage problems. To overcome these problems transmission networks can be upgraded but the cost of upgrade can make it uneconomical to accommodate wind power. Although wind turbines have very high availability rates, their ability to generate wind power depends on the wind speed. Most wind farms have capacity factors in the range of 30%-40%. The probability of wind farms operating at their rated output is quite low. As most techniques used to analyse new connections to transmission grids are based on conventional generation, these techniques can not be used for wind generation as they do not consider the variable nature of wind power. Probabilistic techniques have been used particularly in deregulated power systems where more than one company is involved in transmission system operation. Ireland has very high potential for wind generation due to its geographical location. But its transmission network is weak in some of the areas suitable for wind generation and the network has a low level of interconnection with other networks. Having a high level of wind generation can create significant reliability problems. To accommodate more wind generation, different analysis techniques have to be used to consider the variable nature of wind speed. The purpose of this research is to study and develop these probabilistic techniques and to investigate how these techniques can be used in Ireland to identify possible line overloading problems due to wind generation. Different cases with wind generation where probabilistic methods can be used or have been used are studied. A small part of the Irish transmission network with a significant level of wind generation connected is chosen for probabilistic analysis. Deterministic approaches are generally used to investigate the performance of the network. In this study, it is shown how probabilistic techniques can be used to give a clear picture of wind generation effects on transmission line overloading. The Line Flow Sensitivity Factor (LFSF) method is used to speed up the probabilistic analysis. By using probabilistic techniques for different periods of the year, analysis based on line overloading and reverse power flow are carried out. The amount of Expected Energy Not Produced (EENP) is calculated for different periods of the year. Based on the EENP, it can be decided whether it is economical to upgrade the transmission network or to curtail wind power during high wind production periods

Development and Verification of a Distributed Electro-Thermal Li-Ion Cell Model

Запропонована структура інформаційної системи (ІС) прогнозування розвитку інфраструктури в туристичній галузі, визначено її обов\u27язкові компоненти. Побудовано структурну схему потоків ІС, що дає уявлення про верхній рівень її функціонування та детально описано складові частини І

Universal Li-Ion Cell Electro-Thermal Model

This paper describes and verifies a Li-ion cell electro-thermal model and the associated data analysis process. It is designed to be adaptable and give accurate results across all variations of operating conditions and cell design based only on time domain voltage, current and temperature measurements. The creation of this model required an analysis process ensuring consistency in expressing the underlying cell behavior. This informed a flexible modelling structure adaptable both to cell performance variations and the limitations of the available test data. The model has been created with a combined thermal and electrical approach enabling 1D nodal distribution adaptable to both cylindrical and prismatic cells. These features combine with an intelligent parameter identification process identifying model structure and parameterization across the usage range, adaptable to any Nickel-Manganese-Cobalt Li-Ion cell. It is designed to retain physical meaning and representation to each circuit element across the temperature operating range. The model is verified in several different operating conditions through representative automotive cycling on an 18650 cell and a BEV2 format prismatic cell, representing the extremes of automotive cell design. The consistency of the model parameters with real phenomena is also analyzed and validated against Electrochemical Impedance Spectroscopy data

Holistic Approach To Understanding Battery Degradation

Li-ion cell degradation has a strong impact on electric vehicle performance both directly, through performance reduction, and indirectly through deviating behavior away from initial control system calibration. This necessitates a process for evaluating degradation causes and quantifying corresponding behavioral changes. This paper shows a holistic approach for achieving this, giving both an insight into the causes of cell degradation and emulation of the resultant performance changes through a virtual tools platform which can be used for degradation algorithm development. Additionally, the paper is an overview of the novel methodology developed within the process including testing, data evaluation, modelling and electrical and chemical validation. The process makes use of electrical cycling and electrochemical impedance spectroscopy (EIS) data to evaluate cell stoichiometry and individual impedance features to achieve a much more comprehensive ageing behavioral adaptation than is typically present in Li-ion cell equivalent circuit models. This is achieved while maintaining the versatility and computational efficiency of compact model approaches. The outlined process also gives a resolution of performance changes that allow for conclusions to be drawn on the root causes of ageing only through evaluation of electrical data, which is itself significant. Chemical analysis results are shown to verify the validity of the ageing cause conclusions shown by the process

Optimization of non-orthogonal multiple access based visible light communication systems

In visible light communication (VLC), the data is transmitted by modulating the light emitting diode (LED). The data-rate is throttled by the narrow modulation bandwidth of LEDs, which becomes a barrier for attaining high transmission rates. Non-orthogonal multiple access (NOMA) is a new scheme envisioned to improve the system capacity. In addition to multiple access schemes, optimization techniques are applied to further improve the data rate. In this letter, convex optimization is applied to NOMA-based VLC system for downlink. The proposed optimization system is analyzed in terms of the bit error rate (BER) and the sum-rate

Experimental evaluation of adaptive maximum power point tracking for a standalone photovoltaic system

The adaptability of maximum power point tracking (MPPT) of a solar PV system is important for integration to a microgrid. Depending on what fixed step-size the MPPT controller implements, there is an impact on settling time to reach the maximum power point (MPP) and the steady state operation for conventional tracking techniques. This paper presents experimental results of an adaptive tracking technique based on Perturb and Observe (P&O) and Incremental Conductance (IC) for standalone Photovoltaic (PV) systems under uniform irradiance and partial shading conditions. Analysis and verification of measured and MATLAB/Simulink simulation results have been carried out. The adaptive tracking technique splits the operational region of the solar PV’s power–voltage characteristic curve into four and six operational sectors to understand the MPP response and stability of the technique. By implementing more step-sizes at sector locations based on the distance of the sector from the MPP, the challenges associated with fixed step-size is improved on.The measured and simulation results clearly indicate that the proposed system tracks MPP faster and displays better steady state operation than conventional system. The proposed system’s tracking efficiency is over 10% greater than the conventional system for all techniques. The proposed system has been under partial shading condition has been and it outperforms other techniques with the GMPP achieved in 0.9 s which is better than conventional techniques

Photovoltaic module efficiency evaluation:The case of Iraq

This study aims to evaluate the performance of a photovoltaic module under some extreme climate conditions, and with a case study for Iraq. CFD model is developed for the analysis of the photovoltaic module using the commercial CFD software of COMSOL Multiphysics v5.3a for the transient conditions. The results are verified with the analytical solution to the one-dimensional non-linear energy balance equation using Matlab. The results are also compared with measurements reported in the literature for validation. The results reveal that the free convection currents in inclined and horizontal positions of the module were weaker relative to the vertical position. Also, the increase in the length of inclined photovoltaic module, up to 1.3 m, enhances the heat transfer rate. However, beyond this length, the temperature of the module becomes higher, and the convective heat transfer coefficients are reduced regardless of the inclination. In the horizontal position, the convective heat transfer rate is lower, particularly on the bottom surface of PV system