Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California

This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits

Estimating the Benefits of Electric Vehicle Smart Charging at Non-Residential Locations: A Data-Driven Approach

In this paper, we use data collected from over 2000 non-residential electric vehicle supply equipments (EVSEs) located in Northern California for the year of 2013 to estimate the potential benefits of smart electric vehicle (EV) charging. We develop a smart charging framework to identify the benefits of non-residential EV charging to the load aggregators and the distribution grid. Using this extensive dataset, we aim to improve upon past studies focusing on the benefits of smart EV charging by relaxing the assumptions made in these studies regarding: (i) driving patterns, driver behavior and driver types; (ii) the scalability of a limited number of simulated vehicles to represent different load aggregation points in the power system with different customer characteristics; and (iii) the charging profile of EVs. First, we study the benefits of EV aggregations behind-the-meter, where a time-of-use pricing schema is used to understand the benefits to the owner when EV aggregations shift load from high cost periods to lower cost periods. For the year of 2013, we show a reduction of up to 24.8% in the monthly bill is possible. Then, following a similar aggregation strategy, we show that EV aggregations decrease their contribution to the system peak load by approximately 40% when charging is controlled within arrival and departure times. Our results also show that it could be expected to shift approximately 0.25kWh (~2.8%) of energy per non-residential EV charging session from peak periods (12PM-6PM) to off-peak periods (after 6PM) in Northern California for the year of 2013.Comment: Pre-print, under review at Applied Energ

Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates

The United Arab Emirates is moving towards the use of renewable energy for many reasons, including the country’s high energy consumption, unstable oil prices, and increasing carbon dioxide emissions. The usage of electric vehicles can improve public health and reduce emissions that contribute to climate change. Thus, the usage of renewable energy resources to meet the demands of electric vehicles is the major challenge influencing the development of an optimal smart system that can satisfy energy requirements, enhance sustainability and reduce negative environmental impacts. The objective of this study was to examine different configurations of hybrid renewable energy systems for electric vehicle charging in Abu Dhabi city, UAE. A comprehensive study was conducted to investigate previous electric vehicle charging approaches and formulate the problem accordingly. Subsequently, methods for acquiring data with respect to the energy input and load profiles were determined, and a techno-economic analysis was performed using Hybrid Optimization of Multiple Energy Resources (HOMER) software. The results demonstrated that the optimal electric vehicle charging model comprising solar photovoltaics, wind turbines, batteries and a distribution grid was superior to the other studied configurations from the technical, economic and environmental perspectives. An optimal model could produce excess electricity of 22,006 kWh/year with an energy cost of 0.06743 USD/kWh. Furthermore, the proposed battery–grid–solar photovoltaics–wind turbine system had the highest renewable penetration and thus reduced carbon dioxide emissions by 384 tons/year. The results also indicated that the carbon credits associated with this system could result in savings of 8786.8 USD/year. This study provides new guidelines and identifies the best indicators for electric vehicle charging systems that will positively influence the trend in carbon dioxide emissions and achieve sustainable electricity generation. This study also provides a valid financial assessment for investors looking to encourage the use of renewable energy

Electric Vehicle Charging Station Placement: Formulation, Complexity, and Solutions

To enhance environmental sustainability, many countries will electrify their transportation systems in their future smart city plans. So the number of electric vehicles (EVs) running in a city will grow significantly. There are many ways to re-charge EVs' batteries and charging stations will be considered as the main source of energy. The locations of charging stations are critical; they should not only be pervasive enough such that an EV anywhere can easily access a charging station within its driving range, but also widely spread so that EVs can cruise around the whole city upon being re-charged. Based on these new perspectives, we formulate the Electric Vehicle Charging Station Placement Problem (EVCSPP) in this paper. We prove that the problem is non-deterministic polynomial-time hard. We also propose four solution methods to tackle EVCSPP and evaluate their performance on various artificial and practical cases. As verified by the simulation results, the methods have their own characteristics and they are suitable for different situations depending on the requirements for solution quality, algorithmic efficiency, problem size, nature of the algorithm, and existence of system prerequisite.Comment: Submitted to IEEE Transactions on Smart Grid, revise

Smart grid interoperability use cases for extending electricity storage modeling within the IEC Common Information Model

Copyright @ 2012 IEEEThe IEC Common Information Model (CIM) is recognized as a core standard, supporting electricity transmission system interoperability. Packages of UML classes make up its domain ontology to enable a standardised abstraction of network topology and proprietary power system models. Since the early days of its design, the CIM has grown to reflect the widening scope and detail of utility information use cases as the desire to interoperate between a greater number of systems has increased. The cyber-physical nature of the smart grid places even greater demand upon the CIM to model future scenarios for power system operation and management that are starting to arise. Recent developments of modern electricity networks have begun to implement electricity storage (ES) technologies to provide ancillary balancing services, useful to grid integration of large-scale renewable energy systems. In response to this we investigate modeling of grid-scale electricity storage, by drawing on information use cases for future smart grid operational scenarios at National Grid, the GB Transmission System Operator. We find current structures within the CIM do not accommodate the informational requirements associated with novel ES systems and propose extensions to address this requirement.This study is supported by the UK National Grid and Brunel Universit

TECHNICAL CHALLENGES, IMPACTS AND PERSPECTIVES FOR ELECTRIC VEHICLES (EVS)

Preventing environmental issues and growing concerns about global energy crises are driving the need for new opportunities and technologies that can meet significantly greater demand for cleaner generation and products, zero-carbon, and sustainable energy systems. This requires developing more efficient transport and energy generation. Changing the transport model to electric is a promising approach for ecological systems and for reducing the problems of climate change. This article inspects the current status, latest deployment, and challenging issues when installing an electric vehicle charging and infrastructure (EVs) system in conjunction with various international standards and charging codes. The article further analyzes the impacts of (EVs) and perspectives on society. A complete assessment of charging systems for (EVs) with battery charging techniques. Besides, the beneficial and harmful impacts of (EVs) are categorized and carefully reviewed. Corrective measures for harmful impacts are presented and the benefits obtained from them are highlighted. Bidirectional charging offers the vehicle's key feature for smart grid technology. In this article, the current challenging issues due to the massive deployment of (EVs) and future research trends are also presented.Preventing environmental issues and growing concerns about global energy crises are driving the need for new opportunities and technologies that can meet significantly greater demand for cleaner generation and products, zero-carbon, and sustainable energy systems. This requires developing more efficient transport and energy generation. Changing the transport model to electric is a promising approach for ecological systems and for reducing the problems of climate change. This article inspects the current status, latest deployment, and challenging issues when installing an electric vehicle charging and infrastructure (EVs) system in conjunction with various international standards and charging codes. The article further analyzes the impacts of (EVs) and perspectives on society. A complete assessment of charging systems for (EVs) with battery charging techniques. Besides, the beneficial and harmful impacts of (EVs) are categorized and carefully reviewed. Corrective measures for harmful impacts are presented and the benefits obtained from them are highlighted. Bidirectional charging offers the vehicle's key feature for smart grid technology. In this article, the current challenging issues due to the massive deployment of (EVs) and future research trends are also presented