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Occupant-driven end use load models for demand response and flexibility service participation of residential grid-interactive buildings

As demand response becomes increasingly used as a tool to support improved grid flexibility, it is important to consider that there are many potential types of energy end uses that may be used to support such flexibility. Residential appliances, often accounting for 30 % or more of residential energy use, are a currently untapped source of demand flexibility, particularly when aggregated together across homes. To date there has been very limited analysis of residential appliances for use as grid-interactive loads. As such, this research uses disaggregated energy end use data for 564 households, to model the electricity demand flexibility potential of the use of residential dishwashers, clothes washers, clothes dryers, ovens, and ranges (oven + stovetop) on both weekdays and weekends. This includes both at the building level, as well as aggregated to the grid level, specifically the Midcontinent Independent System Operator (MISO) region. This study was divided into two parts. Part 1 focuses on determining appliance-level loads, and Part 2, which involves aggregation to the grid. Findings suggest that among the studied appliances, clothes dryers provide the greatest demand reduction potential for most times of the day, followed by dishwashers and clothes washers. The maximum potential reduction for clothes dryers is found to be approximately at 11:00 a.m. and this potential sustains throughout most of the daytime period. When considering the willingness of households to participate, based on a survey of households in the Midwest region, clothes dryers still have the most potential for demand reduction. The availability of appliances for load modulation on weekdays and weekends indicates similar load reduction potential for all appliances. Overall, the results of this study suggest that there is an opportunity for shifting appliance usage to optimize grid efficiency and enhance demand response strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Characterize Clustering of Non-Residential Alternating Current Level 2 Electric Vehicle Supply Equipment

The EVSE deployed by The EV Project included both residential and non-residential units. Approximately 4,000 non-residential AC Level 2 (ACL2) EVSE were installed in workplace environments, fleet applications and those publicly accessible located near retail centers, parking lots, and similar locations. The Blink ACL2 is capable of charging at up to 7.2 kW power, although most vehicles in The EV Project charged at about 3.7 kW. The charge rate and energy consumed to recharge the battery are determined by the plug-in electric vehicle’s (PEV’s) on-board battery management system. The impact on the local electrical grid becomes greater when several EVSE are charging PEVs on a site at the same time, or when several commercial EVSE sites are geographically close and charging simultaneously. This may place stresses on the local power transformer providing energy to these sites. What insight can The EV Project data provide in characterizing the effect of several geographically close non-residential EVSE?

33 ADVANCED PROPULSION SYSTEMS↗

Residential Building Energy Efficiency Field Studies: Low-Rise Multifamily

In recent years, the U.S. Department of Energy (DOE) has conducted a series of research studies to validate energy efficient building technologies in the field. Much of the work has focused on single-family construction, and some has also addressed commercial energy codes. The work detailed in this DOE-funded study (EE0007616) focuses on low-rise multifamily buildings (three stories or fewer above grade) in various regions of the United States, and reports on how state-level building codes are being implemented, both in terms of observed characteristics and also in terms of estimated energy impacts. Nearly 100 buildings across four states—Illinois, Minnesota, Oregon, and Washington—were sampled, which represent a range of climate types from mild temperature to very cold continental. Both common entry and outdoor entry buildings were included, and a parallel research project evaluated envelope air tightness and current still-evolving air tightness testing methods. Finally, a set of structured interviews of building designers and other relevant professionals was carried to out to gain more insight into this market. To the greatest extent possible, the methodology developed under the project for low-rise multifamily buildings mirrored the approach established by Pacific Northwest National Laboratory (PNNL) for single-family residential buildings (https://www.energy.gov/eere/buildings/downloads/residential-building-energy-code-field-study). This included the general approach to sampling, recruitment, and data collection, as well as data analysis and presentation. The range of permitting dates for the sites encompassed two energy code cycles in most regions. All states in the study had adopted a variation of the International Energy Conservation Code (IECC) for the structure of their state code. The low-rise multifamily occupancy presents a hybrid building type: most of the building’s conditioned floor area was covered by the residential chapter of the code while portions of the building (such as corridors and common spaces) fell under the commercial code chapter. The key items assessed in this work were: Building Shell—exterior wall insulation, ceiling insulation, foundation insulation, windows. Common Areas—HVAC and lighting. Living Units—lighting, ventilation. A few items were not assessed in detail, given their relative paucity in this occupancy type; these included duct leakage, pipe insulation, and hot water circulation controls. Building characteristics were collected via a combination of architectural, mechanical, electrical, and plumbing plan reviews and field inspections, and entered into a spreadsheet-based tool that was later queried to build a database. Data went through quality control both upon arrival and via a later semi-automated review and assurance process. Most of the data are presented graphically so that the reader can quickly assess compliance with the applicable energy codes (both by state and by code year). As a final step, EnergyPlus™ simulations were created for all buildings in the study to estimate both the as-found energy use intensity (EUI) and the energy and CO 2 that could be saved if features that were found to not meet code minimums were brought up to code. The savings estimates were tabulated for each of the four states in the study. The research team found that the single-family approach was largely applicable to low-rise multifamily buildings. This applies to both the data collection and the prototype EUI analysis. Most of the occupied space is living units and falls under residential energy codes, and many characteristics use similar envelope construction and relatively straightforward mechanical systems and lighting. One of the most challenging aspects of this work was to build an effective spreadsheet-based data collection instrument that could allow efficient collection of both building plan and field data. The research team is of the view that other methods could be equally effective if the work is done carefully with diligent quality control. The primary findings for the work center around the thermal envelope and mechanical systems and lighting at the sites: For thermal envelope components, the majority of buildings met or were better than the prescriptive code.This suggests that building designers and builders are aware of code requirements. In some cases, surveyed buildings were designed to qualify for energy efficiency certification programs. These buildings made up at least 20% of sampled buildings in each state. Almost all buildings met mechanical system efficiency requirements (for both living units and common areas). In some cases, sites employed systems that were considerably more efficient than required by the applicable energy code. Dwelling units had a majority of high-efficacy lighting, often in excess of the state’s residential code requirements. While high-efficacy fixtures were also typical in common areas (corridors and stairwells), lighting power densities (LPDs) in these areas were sometimes higher than levels dictated by the applicable part of the state commercial energy code. The simulation models run on a series of low-rise multifamily prototypes, informed by a composite of the field data collected, calculated annual EUIs of between 20 and 50 kBtu/ft2-yr, with the range representing the effects of both building characteristics and building location (climate zone). A detailed process (based on simulations of prototype buildings) was used to estimate the amount of avoided energy use that would occur if 100% adherence to energy codes were attained. The results indicated modest savings are attainable for items such as window thermal performance and common area lighting. The result is overall only a modest potential for additional energy savings, averaging about 10% of EUI.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Barriers to Broader Utilization of Fault Detection Technologies for Improving Residential HVAC Equipment Efficiency

Faults in residential heating, ventilating, and air conditioning (HVAC) equipment may occur due to poor installation practices or develop over time, and these faults can negatively impact system efficiency, thermal comfort, and equipment lifespan. Automated fault detection and diagnostic (AFDD) technologies identify energy wasting HVAC faults, such as low indoor airflow and improper refrigerant charge, and guide technicians in improving system efficiency. For residential HVAC, AFDD consists of a range of fault detecting and diagnostic capabilities, sensor configurations, and target applications. AFDD technology can either be permanently installed by the original equipment manufacturer (OEM) using embedded sensors or as an add-on product either during or after installation. Additionally, several advanced installation tools and refrigerant gauge sets include AFDD features for temporary use during equipment installation and tune-ups. Some technologies can detect a fault but have limited diagnostic capabilities. For example, a single-point measurement from the home's thermostat or energy monitor can provide certain fault detection capability by analyzing the equipment runtime or energy consumption. These technologies, though limited at determining the cause of a given fault, may have significant energy savings potential due to their low cost and prevalence in the residential HVAC market. Despite the potential benefits, fault detection technologies face many technical and market barriers preventing broad adoption. Beyond the cost barriers due to the added sensor requirements and technology development, fault detection technologies face many implementation and adoption barriers such as installer training, customer awareness, standardized communication protocols, and methods of test for evaluating accuracy. The purpose of this whitepaper is to characterize market and technical barriers impeding broader utilization of fault detection technology for residential HVAC energy efficiency applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Improving Residential Building Simulations Through Large-Scale Empirical Validation

Residential building energy simulations are increasingly used for energy-efficient building design, codes and standards analysis, home certifications and ratings, utility programs, and technology assessments. Various software tools exist to perform residential building simulations, and these tools often use different models, inputs, and assumptions. This leads to inconsistencies that can undermine confidence in the predicted results. Validation of these tools can increase confidence by ensuring their accuracy and consistency. One way to validate simulation tools is through empirical testing, which compares predicted energy usage to measured utility billing data. This paper describes the process of data collection, data standardization, and empirical validation, and illustrates its use with our residential EnergyPlus (R)-based software. The data and process can be extended to other simulation tools and contribute to improving residential building simulations more broadly.

empirical validation↗

The Evolving Market Structure of the U.S. Residential Solar PV Installation Industry, 2000-2016

Market structure refers to the number of firms and the distribution of market shares among firms within an industry. In The Evolving Market Structure of the U.S. Residential Solar PV Installation Industry, 2000-2016, we examine market structure in the context of residential solar PV. We find that over 8,000 companies have installed at least one residential PV system, with about 2,900 companies active in 2016. The majority of residential PV installers are relatively small companies, with about half of installers installing fewer than five systems. At the same time, a subset of high-volume installers accumulated market share, especially beginning around 2010 with the emergence of alternative customer financing options.

14 SOLAR ENERGY↗

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗

New Advances in Data and Analysis-Driven Residential Energy Efficiency Program Design

This paper presents new capabilities and applications of ResStock, a public-domain tool for residential energy efficiency analysis. The high level of granularity available in the ResStock platform makes it a unique tool to more accurately model the potential for energy efficiency and demand response across the diversity of the residential housing stock. We present state-level results including interactive fact sheets of energy efficiency potential for each state. Energy efficiency program designers can use these results to identify strategic improvements with the highest potential for cost-effective savings in a particular state or region, as well as help identify customer segments for targeted marketing and deployment. Beyond the state-level results, the paper presents three new advances in ResStock capabilities: 1) sub-state, county-level results and evaluation of energy efficiency potential in specific ranges of household income, 2) ability to analyze the cost-effectiveness and emissions impact of electrification measures and packages 3) ability to evaluate the time value of energy efficiency by predicting changes in load shapes. The paper includes discussion and real-world examples of how these new capabilities can be used to enhance the design and implementation of residential energy efficiency programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Techno-economic analysis of high-efficiency natural-gas generators for residential combined heat and power

Residential combined heat and power (CHP) systems produce electricity onsite while utilizing waste heat to supplement home heating requirements, which can lead to significant reductions in CO 2 emissions and primary energy consumption. However, the current deployment of such CHP systems in the U.S. residential sector is extremely low primarily due to their high cost, short system life, and low system efficiency. Based on an analysis of average energy consumption of representative single-family homes in 10 U.S. cities across 7 different climate zones, it is concluded that there is no one-size-fits-all residential CHP system, but that a range of products are more likely to reflect consumer preferences. It is further identified via a systematic techno-economic analysis (TEA) that high-efficiency (e.g., 30% - 40% fuel to electricity), long-life (e.g., 15 years), low-cost (preferably less than U.S. $2,500 installed price), and low emissions are key requirements to enable widespread deployment of CHP systems in the U.S. residential sector. This article analyzes how the payback period would change for each city by varying nearly a dozen parameters and concludes with an evaluation on maximum market penetration based on a given set of parameters, and the resulting energy and emissions savings that can be practically achieved in some scenarios.

03 NATURAL GAS↗

Framework to select robust energy retrofit measures for residential communities

Residential building energy retrofits are essential for enhancing environmental sustainability and reducing energy costs. The selection of retrofit measures is influenced by factors such as building systems, occupant behavior, government policy, weather variability, and climate change, all of which can significantly impact energy performance. Compared to retrofitting individual homes, evaluating and selecting optimal retrofit solutions for an entire community is challenging due to diverse residential compositions and variability present. Therefore, engineering robustness is crucial for ensuring consistent energy performance and resilience across different conditions. In this context, robustness refers to the ability of a retrofit measure to maintain its functionality and remain an optimal choice despite external disturbances or changes in inputs and conditions. This study presents a framework for evaluating the robustness of multiple retrofit measures across various building systems, occupant behaviors, and environmental scenarios at the community level. The framework comprises five key steps: scenario model development, integration of the National Residential Efficiency Measures database, energy performance simulation, cost-benefit aggregation, and retrofit solution selection. Each step enhances the framework’s robustness by incorporating the diversity of building characteristics, occupant behaviors, environmental conditions, retrofit options, and evaluation criteria. The framework’s effectiveness is demonstrated through a case study in southern Michigan in the United States, which includes 63 one-story single-family houses, 121 two-story single-family houses, and 8 townhouses. The study identifies furnace retrofits as the most robust solution for the entire community, consistently achieving source energy reductions of 4.7 %–8.0 % and payback period of 10–20 years across various scenarios. These findings are consistent with previous research, indicating the framework’s potential for broader applications in optimizing community-scale residential energy retrofits.

Shu, Lei↗

Forecasting residential solar photovoltaic deployment in California

Residential distributed photovoltaic (PV) deployment in the United States has experienced robust growth, and policy changes impacting the value of solar are likely to occur at the federal and state levels. To establish a credible baseline and evaluate impacts of potential new policies, this analysis employs multiple methods to forecast residential PV deployment in California, including a time-series forecasting model, a threshold heterogeneity diffusion model, a Bass diffusion model, and National Renewable Energy Laboratory's dSolar model. As a baseline, the residential PV market in California is modeled to peak in the early 2020s, with a peak annual installation of 1.5-2 GW across models. We then use the baseline results from the dSolar model and the threshold model to gauge the impact of the recent federal investment tax credit (ITC) extension, the newly approved California net energy metering (NEM) policy, and a hypothetical value-of-solar (VOS) compensation scheme. We find that the recent ITC extension may increase annual PV installations by 12%-18% (roughly 500 MW, MW) for the California residential sector in 2019-2020. The new NEM policy only has a negligible effect in California due to the relatively small new charges (< 100 MW in 2019-2020). Moreover, impacts of the VOS compensation scheme (0.12 cents per kilowatt-hour) are larger, reducing annual PV adoption by 32% (or 900-1300 MW) in 2019-2020.

14 SOLAR ENERGY↗

Energy efficiency to reduce residential electricity and natural gas use under climate change

also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy effficiency to offset increased demand. We calibrate residential energy use against metered data, accounting for differences in building materials and appliances. Under temperature increases, we find that without policy intervention, residential electricity demand could increase by as much as 41–87% between 2020 and 2060. However, aggressive policies aimed at upgrading heating/cooling systems and appliances could result in electricity use increases as low as 28%, potentially avoiding the installation of new generation capacity. We therefore recommend aggressive energy effficiency, in combination with low-carbon generation sources, to offset projected increases in residential energy demand.

54 ENVIRONMENTAL SCIENCES↗

Implementation of Advanced Grid Support Functionalities by Smart Operation of Residential Loads with low Cost Converter Interface

This paper investigates a grid-supportive load concept for small-scale residential appliances, focusing on a residential refrigerator. Power consumption is adjusted based on grid conditions to achieve IEEE-1547 grid support functions. Two key aspects are presented: a low-cost refrigerator converter with Lyapunov energy function-based local controllers for speed control, and the impact on a standard microgrid system, demonstrating advanced grid support from the load side. This method enhances grid resilience and reliability and can be extended to other residential loads. The study contributes to efficient and robust grid-supportive load management systems, showing promising performance. This approach has the potential to improve overall grid stability and can be adapted for various types of residential appliances. The modeling and simulations in MATLAB/Simulink and PLECS confirm the feasibility and effectiveness of the proposed solution. Future work will explore real-world implementation and scalability of this concept for broader applications.

grid supportive loads (GSL)↗

A Comprehensive Scheduling Framework using SP-ADMM for Residential Demand Response with Weather and Consumer Uncertainties

This paper presents a comprehensive scheduling framework for residential demand response (DR) programs considering both the day-ahead and real-time electricity markets. In the first stage, residential customers determine the operating status of their responsive devices such as heating, ventilation, and air conditioning (HVAC) systems and electric water heaters (EWHs), while the distribution system operator (DSO) computes the amount of electricity to be purchased in the day-ahead electricity market. In the second stage, the DSO purchases insufficient (or sells surplus) electricity in the real-time electricity market to maintain the supply-demand balance. Due to its computational complexity and data privacy issues, the proposed model cannot be directly solved in a centralized manner, especially with a large number of uncertain scenarios. Therefore, this paper proposes a combination of stochastic programming (SP) and the alternating direction method of multipliers (ADMM) algorithm, called SP-ADMM, to decompose the original model and then solve each sub-problem in a distributed manner while considering multiple uncertain scenarios. The simulation study is performed on the IEEE 33-bus system including 121 residential houses. Here, the results demonstrate the effectiveness of the proposed approach for large-scale residential DR applications under weather and consumer uncertainties.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Scalable and Distributed Algorithm for Managing Residential Demand Response Programs using Alternating Direction Method of Multipliers (ADMM)

For effective engagement of residential demand-side resources and to ensure efficient operation of distribution networks, we must overcome the challenges of controlling and coordinating residential components and devices at scale. To overcome this challenge, we present a distributed and scalable algorithm with a three-level hierarchical information exchange architecture for managing the residential demand response programs. First, a centralized optimization model is formulated to maximize community social welfare. Then, this centralized model is solved in a distributed manner with alternating direction method of multipliers (ADMM) by decomposing the original problem to utility-level and house-level problems. The information exchange between the different layers is limited to the primary residual (i.e., supply-demand mismatch), Lagrangian multipliers, and the total load of each house to protect each customer’s privacy. Simulation studies are performed on the IEEE 33 bus test system with 605 residential customers. The results demonstrate that the proposed approach can save customers’ electricity bills and reduce the peak load at the utility level without much affecting customers’ comfort and privacy. Finally, a quantitative comparison of the distributed and centralized algorithms shows the scalability advantage of the proposed ADMM-based approach, and it gives benchmarking results with achievable value for future research works.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Empirically Derived Strength of Residential Roof Structures for Solar Installations

Engineering certification for the installation of solar photovoltaic (PV) modules on wood roofs is often denied because existing wood roofs do not meet structural design codes. This work is intended to show that many roofs are actually sufficiently strong given the conservatism in codes, documented allowable strengths, roof structure system effects, and beam composite action produced by joist-sheathing interaction. This report provides results from a testing program to provide actual load carrying capacity of residential rooftops. The results reveal that the actual load carrying capacity of structural members and systems tested are significantly stronger than allowable loads provided by the International Residential Code (IRC 2009) and the national structural code found in Minimum Design Loads for Buildings and Other Structures (ASCE 7-10). Engineering analysis of residential rooftops typically ignores the system affects and beam composite action in determining rooftop stresses given a potential PV installation. This extreme conservatism combined with conservatism in codes and published allowable stress values for roof building materials (NDS 2012) lead to the perception that well built homes may not have adequate load bearing capacity to enable a rooftop PV installation. However, based on the test results presented in this report of residential rooftop structural systems, the actual load bearing capacity is several times higher than published values (NDS 2012).

Dwyer, Stephen F.↗

Impact of Rate Design Alternatives on Residential Solar Customer Bills. Increased Fixed Charges, Minimum Bills and Demand-based Rates

With rapid growth in energy efficiency and distributed generation, electric utilities are anticipating stagnant or decreasing electricity sales, particularly in the residential sector. Utilities are increasingly considering alternative rates structures that are designed to recover fixed costs from residential solar photovoltaic (PV) customers with low net electricity consumption. Proposed structures have included fixed charge increases, minimum bills, and increasingly, demand rates - for net metered customers and all customers. This study examines the electricity bill implications of various residential rate alternatives for multiple locations within the United States. For the locations analyzed, the results suggest that residential PV customers offset, on average, between 60% and 99% of their annual load. However, roughly 65% of a typical customer's electricity demand is non-coincidental with PV generation, so the typical PV customer is generally highly reliant on the grid for pooling services.

14 SOLAR ENERGY↗

VersiCharge-SG - Smart Grid Capable Electric Vehicle Supply Equipment (EVSE) for Residential Applications

In his 2011 State of the Union address, President Obama called for one million electric vehicles on the road by 2015 [1]. With large-scale Electric Vehicle (EV) or Plug-in Electric Vehicle (PEV or EV for short) or Plug-in Hybrid Electric Vehicle (PHEV) penetration into the US market, there will be drastic reduction in fossil fuel consumption, thus significantly reducing our dependency on foreign oil [2-6]. There will also be significant reduction on Green House Gas (GHG) emissions and smog in the major US cities [3, 7, 8]. Similar studies have also been done other industrial counties [9]. For the fuel cost, with the home electricity rate around $0.13 per kWh, it would cost about $0.05 per mile for DC operation and $0.03 cents per mile for AC operation. But, assuming 25 miles per gallon for a typical vehicle and $4 per gallon, fossil fuel will cost $0.16 per mile [10]. The overall lifecycle cost of PEVs will be several folds lower than the existing fossil fueled vehicles. Despite the above advantages of the EVs, the current cost of EVSE is not affordable for the average consumer. Presently, the cost of installing state-of-the-art residential EVSE ranges from $1500 to $2500 [11]. Low priced EVSE technology, which is easy to install, and affordable to operate and maintain by an average consumer, is essential for the large-scale market penetration of EVs. In addition, the long-term success of this technology is contingent on the PEVs having minimal excessive load and shift impact on the grid, especially at peak times. In a report [2] published by the Pacific Northwest National Laboratory (PNNL), the exiting electric power generation infrastructure, if used at its full capacity 24 hours a day, would support up to 84% of the nation’s cars, pickup trucks and SUVs for an average daily drive of 33 miles. This mileage estimate is certainly much below what an average driver would drive his/her vehicle per day. Another report [3] by the National Renewable Energy Laboratory (NREL) shows that an increased PEV penetration would significantly increase pressure on the peak generation, if no controlled charging strategy was put in place. Investigations from Oak Ridge National Laboratory (ORNL) show that in many regions, additional power generation facilities must be put in place and operate in evening times to recharge the EVs [12]. By all accounts, large PEV penetration will bring to the power grid enormous challenges due to the excessive and stochastic demand, and can entirely change the peak time distribution and behavior, perhaps, into a bi-modal distribution capable of exhausting primary, secondary and even reserves (spinning or non-spinning). To minimize the infrastructure upgrade costs and risks to the grid, and to ensure that power quality and reliability remain within the set standards, the demand for EV plug-ins must then be controlled and coordinated locally and at regional levels. Novel control techniques must be devised to allow for close collaboration between neighboring plug-in requestors, between neighboring communities, and between these and more central power authorities. The concept of electric drive vehicle is not new. The development of electric vehicle has been around since 19th century [13]. But due to a number of reasons and practical limitations at the time, including lower cost of gasoline compared to electricity, excessive refueling times, and abundance of gasoline, the automobile industry embraced gasoline-powered vehicles worldwide [13]. With the global warming, ever reducing reservoirs of fossil oil around the world and increasing political pressure to reduce the national dependency on foreign oil, the last decade of the 20th century witnessed major technological breakthroughs in Alternative Fueled Vehicle (AFV) technologies, including electric vehicles. With GHG emissions and carbon footprint in the minds of many more consumers and politicians, the first decade of the 21stCentury witnessed more breakthroughs with some real life experimentation and sporadic deployment of these technologies [14]. By many accounts, the second decade of the 21st Century is expected to be the time when mass volume production and popular usage of these AFV technologies, especially EV, will materialize. The current DOE request for proposals recognizes the need for major technological changes to ensure that the above national goal is realizable. Two major challenges have been identified: (1) major reduction in the cost of ownership of EVSEs, and (2) managing additional EV loads in the power grid while maintaining power quality, reliability, and affordability. We note that the two challenges are closely linked – A holistic approach to true lifecycle cost of EVSE ownership will certainly include any taxes and surcharges that can be put in place for major potential investments in the grid, and higher electricity charges in case of more frequent and longer peak periods. From a societal perspective, this cost could also include the lost GDP (computed on a local basis) and revenue for businesses at local and regional levels when the grid is no longer capable of meeting the demand and unexpected outages occur. A typical end-point electrical distribution system delivers power to a residential EVSE from the neighborhood distribution pole, as shown in Fig.1. This pole has a transformer (neighboring step-down transformer) that steps down the utility medium voltage to dual 120VAC single phase (also called 240VAC split phase). This voltage is fed through a meter into the residential load control center. The load control center consists of branch circuit breakers and distributes the power supply within various areas of the residential unit. One of the branch circuits from the load control center feeds EV charging station for the unit. An electric vehicle charger is plugged into the socket of the EV charging station and other end of this charger is connected to the vehicle during charging. Figure 1 illustrates a typical configuration of the power grid. The left side of the figure shows the power grid from the power generation to the neighboring step-down transformer, while the right side of the figure shows multiple EVs with the respective charging stations. The typical step-down transformer has an upper limit representing the maximum load that can be requested from these neighboring houses altogether (typically 24 kW). In case the total load increases beyond the supported limit, the protection system (e.g. a circuit breaker) attached to the step-down transformer gets activated automatically.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗