Smart Grids as Cyber Physical Systems, 2 Volume Set -

Smart Grids as Cyber Physical Systems, 2 Volume Set (eBook)

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2024 | 1. Auflage
784 Seiten
Wiley (Verlag)
978-1-394-26170-3 (ISBN)
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Smart Grids as Cyber Physical Systems, a new two-volume set from Wiley-Scrivener, provides a comprehensive overview of the fundamental security of supervisory control and data acquisition (SCADA) systems, offering clarity on specific operating and security issues that may arise that deteriorate the overall operation and efficiency of smart grid systems. It also provides techniques to monitor and protect systems, as well as aids for designing a threat-free system.  This title discusses how artificial intelligence (AI) may be extensively deployed in the prediction of energy generation, electric grid-related line loss prediction, load forecasting, and for predicting equipment failure prevention. It also discusses power generation systems, building service systems, and explores advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms. Additionally, we will explore research contribution of experts in CPS infrastructure systems, incorporating sustainability by embedding computing and communication in day-to-day smart grid applications. This book will be of immense use to practitioners in industries focusing on adaptive configuration and optimization in smart grid systems. Through case studies, it offers a rigorous introduction to the theoretical foundations, techniques, and practical solutions CPS offers. Building CPS with effective communication, control, intelligence, and security is discussed from societal and research perspectives and a forum for researchers and practitioners to exchange ideas and achieve progress in CPS is provided by highlighting applications, advances, and research challenges. This book offers a comprehensive look at ICS cyber threats, attacks, metrics, risk, situational awareness, intrusion detection, and security testing, providing a valuable reference set for current system owners who wish to configure and operate their ICSs securely.



O. V. Gnana Swathika, PhD received a PhD in electrical engineering from Vellore Institute of Technology University, Chennai, Tamilnadu, India, in 2017. She also completed her post-doctoral studies at the University of Moratuwa, Sri Lanka in 2019. Her current research interests include microgrid protection and energy management systems.

 

K. Karthikeyan is the chief engineering manager of electrical designs for Larsen and Toubro Construction, a multinational Indian contracting company.  He has two decades of experience in electrical design and has contributed to several projects including the Building airports, railway stations and depots, hospitals, and educational buildings in India and abroad. His primary role involves preparing and reviewing complete electrical system designs up to 110KV voltage levels, acting as a point of contact between clients and projects teams, peer review, and project management.

 

Sanjeevikumar Padmanaban, PhD is a faculty member in the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He has authored over three hundred scientific papers and an editor for several academic journals. He is a fellow of the Institution of Engineers, India, the Institution of Electronics and Telecommunication Engineers, India, and the Institution of Engineering and Technology, U.K.


Smart Grids as Cyber Physical Systems, a new two-volume set from Wiley-Scrivener, provides a comprehensive overview of the fundamental security of supervisory control and data acquisition (SCADA) systems, offering clarity on specific operating and security issues that may arise that deteriorate the overall operation and efficiency of smart grid systems. It also provides techniques to monitor and protect systems, as well as aids for designing a threat-free system. This title discusses how artificial intelligence (AI) may be extensively deployed in the prediction of energy generation, electric grid-related line loss prediction, load forecasting, and for predicting equipment failure prevention. It also discusses power generation systems, building service systems, and explores advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms. Additionally, we will explore research contribution of experts in CPS infrastructure systems, incorporating sustainability by embedding computing and communication in day-to-day smart grid applications. This book will be of immense use to practitioners in industries focusing on adaptive configuration and optimization in smart grid systems. Through case studies, it offers a rigorous introduction to the theoretical foundations, techniques, and practical solutions CPS offers. Building CPS with effective communication, control, intelligence, and security is discussed from societal and research perspectives and a forum for researchers and practitioners to exchange ideas and achieve progress in CPS is provided by highlighting applications, advances, and research challenges. This book offers a comprehensive look at ICS cyber threats, attacks, metrics, risk, situational awareness, intrusion detection, and security testing, providing a valuable reference set for current system owners who wish to configure and operate their ICSs securely.

1
Grid Independent Dynamic Charging of EV Batteries Using Solar Energy


P. Balamurugan1*, Tekumalla Lakshmi Sowjanya2, Manas Goyan2, J.L. Febin Daya1 and V. Ananthakrishnan3

1eVITRC, Vellore Institute of Technology - Chennai, Tamil Nadu, India

2VIT-Bhopal University, Madhya Pradesh, India

3School of Electrical Engineering, Vellore Institute of Technology - Chennai, Tamil Nadu, India

Abstract


This research aims to utilize energy emitted by the sun as a source to charge an electric car and to eliminate the need for installing more charging stations to save electricity. The proposed concept of dynamic charging from solar source minimizes carbon footprint. The concept can be applied in a wide range by installing flexible solar panels that are available commercially in the market. This concept enables embedding the flexible panels during the manufacturing stage and widespread utilization of available solar energy surplus. This will reduce the consumption of electricity generated from conventional energy sources to charge the electric vehicles. The dynamic charging will also extend the range provided by the battery per charge cycle improving the reliability of the electric vehicle.

Keywords: EV charging, dynamic charging, flexible PV panels, boost converter

1.1 Introduction


Climate changes due to emission of CO2 from remnant fuels is a major concern in recent years. This enabled electrical engineers and researchers to look out for alternate sources of energy like solar farms, wind farms, and other sources like biomass. Vehicles are the primary sources where the CO2 emission is present everywhere compared to large industries where it is localized and regulated. Hence, electric vehicles (EV) came into picture, resulting in rapid manufacturing and production of EVs. The use of additional battery storage in automotive systems for supplying the power train and internal utilities extending the range of operation influencing economic challenges is the next challenge. As a promising technology and preference, harvesting renewable energy resources is a boon for both EV industries and the transportation sector. Charging batteries and similar storage systems directly from renewable resources increases the reliability of the battery-operated vehicles. Utilizing energy from alternative energy resources as an alternative to conventional electric network to run the EV is perceived to expand the complete system efficacy and diminish carbon footprint.

Energy from photovoltaic (PV) panels are progressively competing with other forms of renewable sources of energy due to its splendid nature and is easily extractable. Hence, the adaptability of e-transportation is facilitated much by PV sources. In recent days, utilizing PV as a primary source of energy is adapted from small scale to large industries, airports, and residential applications. Since it exhibits lesser maneuver cost and maintenance, low greenhouse gas emanations, and self-governing capability, PV is adopted everywhere. Vast exploration of technology has been adopted lately to charge EV with energy from solar. Many countries have initiated design standards for PV systems.

Analyzing the current scenario and forthcoming challenges in the implementation of EV and charging systems, it is essential to adopt operation of EVs independent on conventional grid for charging. Several agencies analyzed the challenges and deployed several universal standards and codes for charging EVs. Considering wide-spread applications and situations, batteries are charged by PVs which are installed on the vehicles, causing the reduction in the installation of charging stations.

This work, “Solar Powered 4-Wheeler” is a dynamic system, wherein the energy from the sun is transformed into the electrical energy using the required number of solar panels of sufficient area mounted on the EV, to power up the lead–acid battery, which is used in the 4-wheeler [1].

As this is a dynamic system, due to weather conditions, the charging is influenced by parameters like irradiance and temperature. The unregulated output of the PV panel is regulated using DC-DC charge controller that is capable of boosting or stepping down the PV output with simultaneous tracking of maximum power output from the panel. The maximum power point tracking (MPPT) controller is better for the high-power range applications rather than the pulse width modulation (PWM) controller to measure the maximum power point (MPP) and keep the battery in charging mode whenever the variable parameters get changed [2]. Solar cells are implemented on the surface of the scooter by calculating the parameters of the single cell and connect those cells in the series and parallel to get the output that is helpful to charge the battery [3]. The battery plays a major role in electric vehicles. Knowing the total energy left in a battery and the driving conditions, the control system notifies the user, and the range for which the battery will perform until the next recharge, which is a measure of the intermittent ability of the battery [4]. The state-of-charge (SOC) of the battery can be resolute from the discharging characteristics of the battery. An SOC of 100% is a measure of area under the discharge characteristics of a battery from 100% charge to 0% charge in the battery [5]. The battery charging is done using three stages of charging of the battery to maintain the standard and charging takes place with respect to the SOC of battery by constant-current and constant-voltage methods [6].

1.2 Proposed Methodology


In this proposed methodology, flexible solar panels will be mounted on car surfaces, where maximum light will fall. Since the PV panels are flexible, their size and power ratings are not regular. Hence, the power rating of the panel must be calculated using the number of cells present in the section and the data sheet of the PV panel. Based on the efficiency of solar panel, the size and power are finalized. From the data sheet, the power output of a single cell is computed and based on the area of the panel, the total power of the PV is calculated. To get the desired amount of power generation, many such cells will be connected in series and parallel. Once the PV panels are designed, then it requires a DC-DC converter to extract power from the PV panel. In this work, a boost converter is chosen to extract power from the PV. The boost converter provides necessary charging current at desired voltage to the battery present in EV. The power output of PV varies depending on cell temperature and irradiance falling on the panel. Hence, it is necessary to regulate and extract maximum power output from PV with suitable control technique using boost converter. Maximum power point tracking (MPPT) is one of the classical approaches that aims at tracking and extracting the maximum power output from the PV panel and feeds the connected loads. For tracking the maximum power, the perturb and observe (P&O) algorithm is applied. The energy output of the boost converter will be given to the battery for storage or an inverter to convert the DC to AC. The algorithm for the charge controller will adjust the current and voltage with respect to the SOC of the battery. Based on the current from the boost converter, the charging time of the battery can be computed. The functional illustration of the planned system is depicted in Figure 1.1.

Figure 1.1 Functional illustration of the proposed system.

The specifications of Renogy UK monocrystalline flexible solar panels are provided in Table 1.1. The image of Renogy UK monocrystalline flexible PV panel is shown in Figure 1.2 for reference along with its dimensions specified.

Single solar cell parameters from the selected manufacturer solar panel

  • Cell area = 6.5 * 3.3 in = 16.51 * 8.382 cm2 = 138.39 cm2 = 13,839 mm2
  • Open circuit voltage from the single cell = Voc of solar panel/ No. of cells in panel
  • No. of cells connected in series = PV module voltage / voltage at the operating condition
  • Here, PV module voltage is 52 because we need 52 V from the source to charge 48 V

Table 1.1 Renogy UK monocrystalline flexible PV panel specifications.

Parameter Values
Maximum power 100 W
Open circuit voltage (Voc) 23.5 V
Voltage at maximum power point 19.4 V
Temperature coefficient (Voc, Isc, Pmax) –0.29%, 0.05%, –0.38%
Short circuit current (ISC) 5.51 A
Current at maximum power point 5.2 A
Irradiance and nominal temperature 1000 W/m2 and 25°C
Panel dimensions in mm 1093 × 582
No. of cells 36

Figure 1.2 Renogy UK monocrystalline flexible PV panel.

  • Light generated current (IL) = 5.5453 A
  • Diode saturation current (I0) = 12.358 pA
  • Diode ideality factor = 0.94781
  • Shunt resistance = 185.7255 Ω
  • Series resistance = 0.26886 Ω
  • Series connected...

Erscheint lt. Verlag 29.4.2024
Sprache englisch
Themenwelt Technik Elektrotechnik / Energietechnik
ISBN-10 1-394-26170-5 / 1394261705
ISBN-13 978-1-394-26170-3 / 9781394261703
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