Design of Charging Unit for Electric Vehicles Using Solar Power

Transcription

1 Design of Charging Unit for Electric Vehicles Using Solar Power R.Arulbel Benela Department of Electrical and Electronics Engineering GKM College of Engineering and Technology Anna University, Chennai, India Dr. K. Jamuna Department of Electrical and Electronics Engineering GKM College of Engineering and Technology Anna University, Chennai, India Abstract This paper presents a charging process undergone for electric vehicles in parking lot areas. It allows us to evaluate a wide range of Plug-in Hybrid Electric Vehicles (PHEVs) and Plug-in Electric Vehicles (PEVs) charging scenarios and the corresponding control strategies. In addition, this allows us to explore a variety of communication technologies for a PHEV/PEV charging facility. The charging scheme used here is monitored by Arduino board. Some vehicles are parked during the day at workplace parking garages and can be charged from the solar energy using Photo-Voltaic (PV) cell based charging facilities. The charging with solar energy helps to reduce the emissions from the power grid but increases the cost of charging. Moreover, it offers more flexibility to prepare for the emergence of new technologies (e.g., Vehicle-to-Grid, Vehicle-to-Building, and Smart Charging), which will become a reality in the near future. The simulation results provide a general overview of the impact of the proposed charging scenarios in terms of voltage profiles, peak demand, and charging cost. Keywords Digital charging test bed, Electric vehicle, Plug-in Electric Vehicle, Photo voltaic cell. I. INTRODUCTION Gasoline- and diesel-powered Internal Combustion Engine (ICE) vehicles ended up dominating transportation in the 20th century. However, concerns about the environmental impacts of ICE vehicles sparked a PEV renaissance at the end of the 20th century. First, advances in electric-drive technologies enabled commercialization of hybrid electric vehicles (HEVs), which integrate an ICE or other type of propulsion source with batteries, regenerative braking, and an electric motor to boost fuel economy. Continued technological advances have spawned PHEVs, which integrate small ICEs (or other types of propulsion sources) and large, grid-chargeable batteries that enable 10- to 40-mile all electric driving ranges. Advanced technologies have also created a new breed of EVs that don t use an ICE at all. Only a few models of newgeneration PEVs are available today. The market penetration and availability are growing quickly due to its benefits. PEVs are better than conventional vehicles in most performance categories. They are safe and convenient, and they can save money while slashing emissions and increasing the nation s energy security. PHEVs and PEVs have received increased attention because of their low pollution emissions and high fuel economy [1]. Imported oil in US comes from unstable SA Engineering College, Chennai INDIA regions, which is a potential threat to US national security. Ultimately, PHEVs/PEVs will transfer energy demands from crude oil to electricity for the personal transportation sector. This shift would reduce pollution and alleviate security issues related to oil extraction, importation, and combustion. Along with the use of grid power, PHEVs/PEVs also have the potential to transfer power to the grid, which alleviates peak power demand and provides ancillary services to the grid. Many automotive OEMs have made their plans to introduce PHEVs and EVs worldwide during the next few years with General Motors introducing the first PHEV - Volt - in production and Nissan with its electric vehicle LEAF in 2011 in the US market [2]. The US government has put a lot of effort in accelerating the introduction and penetration of advanced electric drive vehicles into the market. The US Department of Energy projects that about 1 million PHEVs/PEVs will be on the road by 2015 and 425,000 PHEVs/PEVs will be sold in 2015 alone. At this rate, PHEVs/PEVs would account for 2.5% of all new vehicle sales in The Electric Power Research Institute (EPRI) projects that 62% of the entire US vehicle fleet will consist of PHEVs/PEVs by 2050 using a moderate penetration scenario [4]. However, there is a need to address the potential problems caused by the emergence of PHEVs/PEVs charging. If properly managed, plug-in vehicles could be charged during low demand periods of the grid which minimizes the strain on the grid and obviating major generation and transmission infrastructure additions. Charging PEV requires electric vehicle supply equipment (EVSE). EVs must be charged regularly, and charging PHEVs regularly will minimize the amount of gasoline they consume. The aggregate load in a public charging facility (e.g., public parking lot) needs to be managed carefully in order to avoid interruptions when several thousand PHEVs/PEVs are introduced into the system over a short period of time (e.g., during the early morning hours when people arrive at work). A large number of PHEVs/PEVs connected to the grid simultaneously may pose a huge threat to the quality and stability of the overall power system. The effective communication technologies are critical to the successful rollout of EVs. Thus, a reliable communication network in a public charging facility is highly needed to enable the successful integration of a large number of 1

2 PHEVs/PEVs. Low-cost and effective communications with sufficient bandwidth is needed to pass needed information between PHEVs/PEVs and the controllers to perform effectively the charging and discharging. Therefore, the authors have developed a digital test bed for a large-scale PHEV/PEV enabled parking lot that integrates both an energy management module and a communications module. Fig. 1 illustrates the block diagram of the proposed charging scheme used in the parking lot. Fig. 1 Block diagram of the charging scheme in the parking lot The charging unit consists of two types of energy used for charging of vehicles coming into the parking lot. It used the conventional means of energy as well as solar energy. In the day the charging station charges its vehicle entering using solar power and during night hours it uses conventional energy. The voltage divider circuit gives a reference voltage or produces a low voltage signal proportional to the voltage to be measured ie.5v required for Arduino board. The entrance of the parking area contains the controller unit for driving the vehicles after checking their battery level, entry of parking time. According to the details the car is assigned a slot to charge. After the 100% charging level is reached, the owner of the car is intimated to park his/her vehicle in a separate parking lot, allowing other vehicles to charge. The remainder of this paper is organized as follows: Section II introduces the types of PEV charges for electric vehicles in parking space. It provides the basic platform that will simulate the future charging system in a Smart Grid System; The proposed transportation is designed and discussed in section III. Section IV and Section V describes the energy management module and communications module. In Section VI, the authors summarize the paper and briefly introduce their future work. II. TYPES OF PEV CHARGERS There are various types of EVSE, which differ based on charging period of a vehicle, and EVSE can be accessed at home or in public. EVSE for PEVs is classified into several categories by the maximum amount of power provided to the battery. Level 1 provides Alternating Current (AC) electricity to the vehicle. The vehicle s onboard equipment converts AC into Direct Current (DC) that charges the batteries. The level 2 is named as DC fast charging which provides DC electricity directly to the vehicle. Charging times varies from less than 30 minutes to 20 hours or more based on the type of EVSE, the type of battery and its energy capacity. EVs have more battery capacity than PHEVs, so charging a fully depleted EV takes longer than charging a fully depleted PHEV [5]. Level 1: Level 1 EVSE provides charging through a 120-volt (V) AC plug and requires a dedicated branch circuit. Most, if not all, PEVs will come with a portable Level 1 EVSE cord set that does not require installation of additional charging equipment. Typically, on one end of the cord is a standard, three-prong household plug. On the other end is a connector, which plugs into the vehicle. Level 1 works well for charging at home, work, or when there is only a 120-V outlet available. Based on the battery type and vehicle, Level 1 charging adds about 2 to 5 miles of range to a PEV per hour of charging time. Level 2: Level 2 EVSE offers charging through a 240-V, AC plug and requires installation of charging equipment and a dedicated electrical circuit (Figure 2). Because most houses have 240-V service available and Level 2 EVSE can easily charge a typical EV battery overnight, this will be a common installation for single-family houses. Level 2 equipment uses the same connector on the vehicle as Level 1 equipment. Based on the battery type, charger configuration, and circuit capacity, Level 2 charging adds about 10 to 20 miles of range to a PEV per hour of charging time. Fig.2 Level 2 Charging Scheme DC Fast Charging: DC fast-charging EVSE (480-V AC input to the EVSE) enables rapid charging at sites such as heavy traffic corridors and public fueling stations. A DC fast charger can add 60 to 80 miles of range to a PEV in 20 minutes. Inductive Charging: Inductive-charging EVSE, which uses an electromagnetic field to transfer electricity to a PEV, is still being used in some areas where it was installed for EVs in the 1990s. Currently available PEVs cannot use inductive charging, although SAE International is working on a standard that may apply to PEVs in the future. Typical Charging Characteristics: The rate at which charging adds range to a PEV depends on the vehicle, the battery type, and the type of EVSE. The following are typical rates: Level 1: 2 to 5 miles of range per hour of charging 2

3 Level 2: 10 to 20 miles of range per hour of charging DC fast charging: 60 to 80 miles of range in 20 minutes of charging Inlet Connector Utility 240-V AC Cord EV Coupler EVSE Control Device Battery Charger [3]. III. PROPOSED TRANSPORTATION SYSTEM This section describes the structure and functions of the new proposed transportation system which provides the basic platform to simulate the future transportation system in a Smart Grid environment which emulates the Intelligent Transportation Systems (ITS). ITS build as a network based, integrated navigation system with different modules that combine together to guide several PEVs from central location. Two observations are made regarding vehicle usage and solar energy availability: a) National Household Travel Survey is shown in Fig. 3. The vehicles are mainly used for travelling to work during weekdays and 60% of vehicles are parked at the workplace for more than 4 hours. Also typically the vehicles are parked at the workplace from about 7AM to 6PM. of electrical energy per day which is sufficient to drive for about 40 mile/day. A similar condition exists in India too, as the survey reports are reported by the UNO and is shown in Fig.5. In India at the managerial level, particularly in smaller Indian companies, a person generally works for 11 hours a day and 6 days a week. Most of Indian companies and MNC offices located in India and Government offices tend to follow a 5-day, 8-9 hour per day working schedule. These observations show that vehicles are typically parked for a sufficiently long time during the day such that it is possible to use solar energy directly to charge the PEVs at the workplace without using large energy storage. This concept of workplace charging using PV panels is studied in this paper. This PV based parking garage concept can be implemented in tropical country like India easily. Fig.3 Time spent at workplaces by US drivers Fig.5 India s Energy Potential The parking structure consists of multiple PEV charging stations, PV panels installed on the surface parking garage and a grid connection. The grid connection is used to draw additional power requirement for PEV charging and also to sell extra PV energy to the grid in smart grid environment. Fig.4 US Energy Potential b) Fig.4 shows that most of the United States receives, on average, more that 4kWh per day of solar energy. Considering that the surface area of one parking spot is covered with PV panels with 12% conversion efficiency, gives 5.7 to 7.6 kwh IV. ENERGY ECONOMIC MODEL An energy economic model of the PV based charging station is presented in this paper along with economic feasibility for the garage owner, PEV owner, and emission impact on the power grid. The simulation model and inputs considered in this analysis are shown in Fig. 6. The core of the simulator is a program that performs hourly calculations of energy available in PV panels and charging demand from vehicles and calculates electricity from the power grid, emissions from the power grid and cost of the energy. The simulation tool also calculates cash flow and payback time considering all the incentives, taxes and electricity rates. The inputs are divided into four bins: 1) Vehicle - arrival time, 3

4 park time, battery capacity and state of charge at garage entrance; 2) PV panels - installation cost, maintenance cost, conversion efficiency and hourly solar radiation considering weather impacts; 3) Charging infrastructure - installation cost, taxes, incentives and parking charges. Simulation steps are discussed below in detail. 1) Assumptions: The installation cost is calculated for the charging station and PV panels but that not include the cost of parking construction. Three types of vehicles (Chevy Volt (EPA data), Nissan Leaf (EPA data), and plug-in Prius (official estimate data)) are considered with their respective usable battery energy. 2) Vehicle parking statistics: Vehicles parked in the parking garage are modeled as a Markov chain by assuming probability distributions for the number of vehicles (total N) arriving during every hour and their parking time in hours. The probability distributions are derived empirically from the data available from The Ohio State University s parking garages. The numbers of vehicles arriving during each hour are modeled as Gaussian distributions such that the maximum numbers of vehicles arrive between 7 and 10 AM and with a small arrival peak between 12 and 2 PM to represent lunch time. The parking time (Tpark(n)) of the vehicles is modeled by two Gaussian distributions with mean 4 and 8. The variances are selected such that the maximum number of vehicles leaves between 4 to 6 PM and with empty parking garage after 9 PM. Another assumption is that only 20% of the vehicles come to the parking garage during weekends. The SOC (n, k) of a vehicle is calculated with entering time of the parking garage (k), the vehicles daily travel distance (dn), all electric range (AERn) and allowable SOC range (ΔSOCn) that is represented in eqn. (1). Fig.7 Number of vehicles in parking garage A Gaussian distribution is used for the vehicle driving distances. An EV mode control strategy is considered to calculate the battery SOC at the garage entrance. This is a reasonable assumption since the PEVs currently in the market use EV mode control for energy management. It is assumed that the vehicles do not charge at home. HOURLY SOLAR ENERGY Location, Weather PV rating Fig.8 Charging Power VEHICLE Type Arrival Time Park Time Battery capacity Initial SoC HOURLY SIMULATI ONS Power Emission OUTPUT Emission Rates Net Payback FINANCE Installation Incentive Taxes Parking Charges 2) Charging time and power demand: The generated data about parking time Tpark(n), battery SOC are used to calculate the charging time and the charging power by considering constant charging power of 6.6 kw (Level II charging) and data on battery capacity En. The charging time and power are given in eqns (2) and (3) respectively. (1) (2) Fig.6 Energy Economic Analysis of PV based Charging station 1) Battery State of Charge at garage entrance: The battery state of charge (SOC) when vehicles enter the parking garage is required to calculate the charging time and charging energy. (3) The power demand from the fifty vehicles is calculated as sum of charging power for individual vehicle as given in eqn. (4). (4) 4

5 3) Solar radiation: Satellite derived solar radiation data is available from NREL which includes effects of cloud shading, ground reflectivity and scattering. This data is used in this analysis to calculate hourly solar energy. Hourly power from PV panels (PPV (k)) is calculated using the System Advisor Model (SAM) tool by DOE/NREL/MRI. SAM makes performance predictions for grid-connected solar, small wind, and geothermal power systems and economic estimates for distributed energy and central generation projects. It is based on an hourly simulation engine that interacts with performance, cost, and finance models to calculate energy output, energy costs, and cash flows. 4) Financial data: The simulation model considers various incentives, tax rebates from local, state and federal government and utilities applicable for building and using renewable energy sources PEVs from one point. 5) Parking charges: Assigning the cost of charging or parking charges is a crucial assumption. Since no other entity than utilities are allowed to sell electric energy, a parking garage owner cannot charge for the electricity. A flat rate is assumed in this study and a parametric study is presented with different parking rates[2]. V. COMMUNICATION MODULE Low-cost and effective communications with sufficient bandwidth is necessary to pass information between PHEVs and the controllers in order to perform effective PHEV/PEV charging process. The existing communication module is mainly used to demonstrate the two-way communication among vehicles, charging stations, and intelligent energy management system through internet (TCP/IP) and ZigBee network. Various communication protocols achieve reliable, two-way communication networks such as ZigBee, Bluetooth, Z-Wave, and Home-Plug. Since PHEVs/PEVs can be recharged at various locations (e.g., home, office parking lot), it is critical to maintain the compatibility of communication technologies. Intimation to the owner: SMS is a very suitable technology for delivering alerts and notifications of important events. Connect a mobile phone or GSM/GPRS modem to a computer /PC. Then use the computer / PC and Attention (AT) commands to instruct the mobile phone or GSM/GPRS modem to send SMS messages. AT Commands: AT commands are instructions that used for controlling a modem. AT is the abbreviation of Attention. Every command line starts with "AT" or "at". That's why modem commands are called AT commands. There are two types of AT commands: Basic commands are AT commands that do not start with a "+". For example, D (Dial), A (Answer), H (Hook control), and O (Return to online data state) are the basic commands. Extended commands: AT commands are extended commands that starts with +. For example, +CMGS (Send SMS message), +CMGL (List SMS messages), and +CMGR (Read SMS messages) are extended commands. The test bed allows us to explore a variety of possible communication protocols (e.g., ZigBee, Bluetooth, HomePlug, Z-Wave, and Cellular Network) and certain bandwidth, reliability, security, and power consumption requirements for public PHEV/PEV charging/v2g facilities. VI. SIMULTION RESULTS Fig. 9 Simulation model in VBB Virtual Breadboard is a software platform designing Breadboard form-factor electronic circuits and developing the microcontroller firmware that drives them. Use of Virtual Breadboard to: Develop and debug microcontroller based applications Program microcontrollers directly Develop Control Panels for Embedded Applications Act as a guide for assembling solderless Breadboard circuits VBB is a.net application and has the following dependency Microsoft.NET 2.0 Microsoft JSharp. The simulations are carried out in Virtual BB and the model is shown in Fig. 9. Here in the charging unit, three battery chargers C1, C2, C3 are taken and the battery level is determined. At the entrance of the parking space, the battery levels of the cars are checked and priority is given to car with least battery to go to the first slot. The Arduino simulator performs efficient monitoring of charging level and sends SMS to the owner of the vehicle after fully charged. VII. CONCLUSION AND FUTURE WORK The developed digital test-bed for a PHEV/PEV enabled parking lot in order to prepare for the commercial deployment of the PHEV/PEV charging facilities in the near future. This work can provide us with potential solutions to facilitate the interaction between plug-in vehicles and grids. Vehicle-to- Grid (V2G) technology is a most promising opportunity in EV adoption. It will become a reality much sooner than 5

6 anticipated. The developed digital test-bed has the potential capabilities to evaluate a wide range of PHEV/PEV discharging scenarios and their corresponding control strategies. Also, the proposed technologies in this test-bed can be extended to other large-scale PHEV/PEV charging/v2g scenarios as well as large-scale power system applications. REFERENCES [1] Wencong Su, Wente Zeng and Mo-Yuen Chow, Computational intelligence-based energy management for a large-scale PHEV/PEV enabled municipal parking deck, Applied Energy, vol. 96, Aug. 2012, pp [2] Tulpule Pinak, Energy economic analysis of PV based charging station at workplace parking garage, in IEEE conference proceedings of Energytech, 2011, pp.1-5. [3] Shane Hutchinson, Mesut Baran and Srdjan Lukic, Power Supply for an Electric Vehicle Charging System for a Large Parking Deck, IEEE Annual Meeting report of Industry Applications Society, IAS [4] Wencong Su and Mo-Yuen Chow, Investigating a Large-scale PHEV/PEV Parking Deck in a Smart Grid Environment, in conference proceedings of North American Power Symposium (NAPS), 2011 [5] Murat Yilmaz, Review of Battery Charger Topologies, Charging Power Levels and Infrastructure for Plug-in Electric and Hybrid Vehicles, IEEE Transactions on Power Electronics, vol., no. 99, pp [6] Habiballah Rahimi-Eichi, Wente Zeng, A Survey on the Electrification of Transportation in a Smart Grid Environment, IEEE Transactions on Industrial Informatics, vol. 8, no. 1, Feb Biographies R. Arulbel Benela received her Bachelor's Degree in Electronics and Communication Engineering from St.Peters Engineering College, Chennai and currently pursuing ME in GKM College of Engineering and Technology in the area of Embedded system technogies. Her research interests are embedded control and communication systems. Dr. K. Jamuna is currently a Professor in the Department of Electrical and Electronics Engineering, GKM College of Engineering and Technology, Chennai, India. She received her Bachelor's Degree in Electrical and Electronics Engineering from Thiagarajar College of Engineering Madurai, Masters in Power Systems Engineering from College of Engineering Trivandrum and PhD in IIT Madras in the area of Power system. Her research interests are power system state estimation, wide area measurement systems and control. 6