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Tralli Tralli Presentation Transcript

  • The Smart Electric Power Grid:An Aerospace Approach
    Dr. David M. Tralli
    Manager, Civil Programs
    National Space Technology Applications Office
    Bob Easter, Dr. Martin Feather, and Dr. Gerald Voecks
    Jet Propulsion Laboratory, California Institute of Technology
    February 9-10, 2011
    NASA Project Management Challenge 2011
    Long Beach, CA
    Used with permission
  • Overview
    Major changes are needed in infrastructure to meet anticipated energy needs and to address climate issues in the next decade and beyond.
    The smart (advanced) electric power grid is driving development and integration of advanced energy conversion and storage technologies, renewables and clean transportation.
    The smart grid is an engineering system whose complexities span technological, operational, policy, regulatory and market factors.
    Planning for its design, development, deployment and sustainability must be driven by objective, top-down systems analyses.
    The practice of systems engineering and architectural trade off analysis, as used by the aerospace community, is applied to the design and evaluation of architectural options for the smart electric power grid.
    Agreement # 500-09-021: “Roadmapping the California Smart Grid through Risk Retirement”  Space Act Agreement 82-13715 between NASA and the California Energy Commission (CEC) entitled “Defining the Pathway to the California Smart Grid 2020 (Technology Perspective)”
  • The Smart Grid is the seamless integration of an electric grid, a communications network, and the necessary software and hardware to monitor, control and manage the generation, transmission, distribution, storage and consumption of energyby any customer type.Moreover, we share a broader vision of the smart grid that encompasses the integration of renewable energy and electric vehicle infrastructure.
    Austin Energy
  • Outline
    The Technology Infusion and Maturation Assessment (TIMA) process developed by the NASA Jet Propulsion Laboratory is used to design and evaluate architectural options for the smart electric power grid and to define corresponding technology roadmaps
    Initial Planning
    2010 California Smart Grid Baseline
    Review/capture of 2020 objectives
    Key Technology Roadmaps
    Use Case Development
    TIMA Campaign Phase Project Team Workshops
    Analysis, Final Reporting, Recommendations and Integration
  • Approach
    Technology Infusion and Maturation Assessment (TIMA) process and software tool captures top-level energy policy priorities and functional and business objectives from key technology use cases.
    TIMA was developed by the NASA Jet Propulsion Laboratory over the last decade and applied successfully to technology developments and complex system designs.
    The TIMA process and methodology comprise a suite of innovative software tools for risk balancing and risk management in the context of designing system architecture.
    The TIMA process, combining elicitation, consensus-building, analysis and information visualization, leads to an energy technology roadmap characterized as an optimal set of risk retirement investments addressing R&D and demonstration needs over time, for a given smart grid architecture.
    Presentation Synopsis: The Technology Infusion and Maturation Assessment (TIMA) process developed by the NASA Jet Propulsion Laboratory is used to design and evaluate architectural options for the smart electric power grid and to define corresponding technology roadmaps for distributed energy resources, grid-scale energy storage, command and control for distribution automation, among others.
  • Systems Engineering
    System architecture includes separate but related viewpoints for describing organizational, functional, physical, informational, and lifecycle aspects of system design.
    An exploration of alternatives in a complex design space helps to highlight key design issues, provides a basis for comparing architectures and selecting an architecture, and promotes finding better design solutions for the project.
    A structured approach to decomposition within each viewpoint (requirements, functional, physical...) provides an effective means of defining complex systems.
    Maintaining consistency between corresponding elements in related viewpoints ensures design integrity.
  • Smart GridSystem Tradeoff Space
    Defined across RD&D, investment and smart grid functionality parameters captured in legislation (i.e. CA Integrated Energy Policy Reports, Energy Policy Act of 2005, Energy Independence and Security Act 2007) and addressing diverse parameters:
    Energy consumption, measurement and efficiency
    Energy supply, including distributed energy resources
    Energy storage for transportation and stationary sectors
    Component and systems technologies, including C3
    Infrastructure (monitoring, storage, transmission, distribution)
    Environmental impact
    Economic and regulatory considerations
  • Intellectual Property: Technology Infusion and Maturity Assessment (TIMA) Software Tool Suite
    NPO-21091: Risk Balancing Profiles. Intended as a decision making aid early in the project planning phase.
    NPO-40226: Probabilistic Risk Reduction. Risk is an important and recurring concern in system development. The field of probabilistic risk analysis (PRA) has developed methods to assess risks within complex systems, to deduce the system reliability from knowledge both of the system structure and of the individual system components.
    A risk-based planning approach can be combined with traditional PRA to yields an integrated approach we call “probabilistic risk reduction.” This is well-suited to planning the development of complex systems.
  • NPO-20741: Defect Detection and Prevention (DDP). User-friendly environment to generate a tree of failure modes and a tree of requirements and evaluate the impact of each failure mode on each requirement. This weighs the failure modes by the relative importance.
    The product of the failure mode importance and the effectiveness of the planned PACT provides the residual risk for each failure mode.
    NPO-43474: End-to-End Project Engineering. If risk assessment is done only at the culmination of the design process, the space of remaining options among which to decide is severely constrained. If done early and continued throughout the design process, it can be used to look ahead at the development plan and operational/functional scenarios before large and irrecoverable investments are made.
    Intellectual Property: Technology Infusion and Maturity Assessment (TIMA) Software Tool Suite
  • NPO-40456: Using Dissimilarity Metrics to Identify Interesting Designs. Finding a preferred solution to a complex design problem is challenging. On the one hand the problem space is too large and convoluted for human comprehension, while on the other hand it is infeasible to elicit the entirety of design knowledge required for fully automatic problem solving.
    We face this challenge repeatedly when planning the development of technologies for spacecraft applications!
    Search, data mining, and visualization capabilities are features of the risk management tool suite to support this risk-centric design methodology developed and applied at NASA/JPL.
    Numerous risk abatement options give rise to a huge space of potential design solutions.
    Demonstrated on the selection of risk abatement solutions for design of advanced technology, and to plan technology development for future spacecraft missions.
    Intellectual Property: Technology Infusion and Maturity Assessment (TIMA) Software Tool
  • Smart Grid Technology RoadmapUse Cases
    Evaluation of the potential impact of GHG reduction goals, as defined in Assembly Bill 32 (Nunez, Chapter 488, Statutes of 2006), on meeting the energy growth needs of California through new and innovative smart grid technologies. 
    Objective: Reduce GHG emissions to 1990 levels across all sources in 2020
    Natural gas impacts and benefits of the smart grid, including consideration of CHP.
    Objective: Additional 5,400MW of combined heat and power in 2020. 
    Command and communications technologies (C2), Distribution Automation, including consideration of AMI.
    Objectives: Electricity peak demand reduction goal of 4,885MW in 2013; DR: Demand response that reduces TBD % of peak demand in 2020. 
    C2 and PHEVs
    Objective: Accommodation of PHEVs into smart grid.
    Bio-sources and Fuel Cell energy storage.
    Objective: 20% of renewable power supplied by biopower sources in 2020 (~20,000 GWh/year). 
    Large scale battery storage, integration of solar and wind, intermittency. 
    Objective: 33% of generation by renewables (~104,000 GWh/yr) in 2020. 
  • EPRI Report 2008
    Integrating New and Emerging Technologies
    Integrated Energy Policy Report
    Top-Level Requirements/Objectives
    Use Case #1
    TIMA
    Use Case #2
    Objectives
    System Architecture Options
    Risks/Barriers
    Investments/Demos/Actions
    Use Case #3
    Trade Space Analysis
    Use Case #4
    Residual Risk Profiles
    Investment Options & Actions
    Use Case #5
    GHG Reductions
    Risk Retirement
    Use Case #6
    Natural Gas Ratepayer Impacts
    RD&D Roadmap
    Analytical process flow for integration of top-level requirements with a nominal (illustrative here) minimal number of use case objectives for developing a California Smart Grid 2020 system architecture and recommended RD&D roadmap. GHG reductions and natural gas ratepayer cases also developed as part of this Project.
  • Key Technologies Identified Through Series of Study Workshops
    Fast Storage
    Rooftop Photovoltaics
    Demand Aggregation
    Biomass, Biogas and Fuel Cells
    Microgrid accommodation
    Combined Heat and Power (CHP)
    Command, Control & Communications (C3)
    Distribution Automation
    Advanced Metering Infrastructure (AMI)
    PHEV/PEV accommodation
    Intermittent solar & wind integration (RPS)
    14
  • Key California Energy Policy Goals
    33% of generation by renewables (~104,000 GWh/yr) in 2020
    20 % of renewable power supplied by biopower sources in 2020 (~20 GWh/year)
    3,000 MW of new rooftop Solar PV by 2016 (~5000 GWh/yr) 
    10% reduction in total forecasted electrical energy consumption in 2016
    5,400MW of combined heat and power in 2020 
    Demand response that reduces TBD % of peak demand in 2020 
    Electricity peak demand reduction goal of 4,885MW in 2013 
    All new residential construction is net zero energy in 2020 
    Reduce GHG emissions to 1990 levels across all sources in 2020 
     
    15
  • Interrelationships between the 9 High-Level Goals
    9
    GHG
    NG
    8
    Net zero
    construction
    Energy demand/
    consumption
    Energy supply/
    generation
    4
    1
    33% RPS
    Peak redux
    Demand
    Response
    Total forecasted
    consumption
    reduction
    2
    7
    3
    Biomass
    6
    Rooftop PV
    5
    CHP
  • Biomass
    [~ 20 GWh/yr by 2020]
    Other
    Sources
    Wastewater
    Treatment
    Forest
    Byproducts
    Agricultural
    Waste
    Solid Muni-
    cipal Waste
    [1-5 MW]
    [2-20 MW]
    [5-50 MW]
    Gasification, pyrolysis, anerobic digestion – gas cleanup/concentration
    Renewable Sources
    CHP
    [Goal - 33% of Total Electricity]
    [Additional 5.4 GW by 2020]
    Wave/Hydro
    Geothermal
    Natural Gas
    Solar
    Wind
    Remote
    Central
    Local
    Distributed
    Local
    Distributed
    Remote
    Central
    Rooftop
    PV
    Thermal - PV
    Commercial
    Gas Turbine
    (~50-100’s kW)
    Reciprocating
    Engines
    (~50-100’s kW)
    Steam
    Turbine (MWs)
    Fuel Cells
    (~1-5 MW)
    Microturbine
    (~10’s kW)
    Co-gen
    Electricity
    Electricity
    CHP
    Electricity
    Electricity
    Electricity
    CHP
    CHP
    CHP
    Residential Microgrid
    Commercial Microgrid
    Industrial Microgrid
    Storage
    Storage
    Storage
    [No micro-
    grid con-
    nection]
    Batteries, H2, EV
    Batteries, H2, Thermal, EV
    Batteries, H2, Thermal, EV, Ultracaps
    Storage (ESG)
    Batteries, capacitors,
    thermal, flywheels
    Storage (ESG)
    Batteries, CAES,
    capacitors, flywheels
    Passive
    Passive
    Transmission
    Passive
    Active
    Active
    Active
    UTILITY GRID
    Passive = utility integrated and utility owned, controlled and operated
    Active = utility integrated, but consumer &/or third party owned/controlled/operated
  • GEV
    18
    Total Electricity System Power in California
    Source: 2008 Net System Power Report - Staff Report, Publication number CEC-200-2009-010, to be considered for adoption
    July 15, 2009. (PDF file, 26 pages, 650 kb)
    EIA, QFER, and SB 105 Reporting Requirements
    *Note: In earlier years the in-state coal number included coal-fired power plants
    owned by California utilities located out-of-state.
    In-state generation: Reported generation from units 1 MW and larger.
    Net electricity imports are based on metered power flows between California
    and out-of-state balancing authorities. The resource mix is based on utility power source disclosure claims, contract information, and calculated estimates on the remaining balance of net imports.
    Source:
    EIA, QFER, and SB 105 Reporting Requirements
    Note: Due to legislative changes required by Assembly Bill 162 (2009),
    the California Air Resources Board is currently undertaking the task of
    identifying the fuel sources associated with all imported power entering
    into California.
    In-state generation: Reported generation from units 1 MW and larger.
  • GEV
    19
    Wind Energy Contribution to 2020 CA Grid
    Wind Energy Production Status
    Remote - Central Source
    Large windmills/farms in desert, for example
    Local – Distributed Source
    Smaller windmills/farms in Valleys and in close proximity to towns
    2009 Total is 4.949 TWh (2.43% of Total in-state Electrical Energy)
    Wind Energy Status
    • Remote – Central Source
    • Transmission lines will be required to transfer electricity to customers
    • New transmission lines will need to be built and current transmission lines will need to be expanded or updated
    • Some form of storage (batteries, hydrogen, fuel cells, turbines, etc.) will be required to accommodate this expansion
    • Where is the best storage location – at the generator or near the customer (DR, CC, and microgrids)
    • Local – Distributed Source
    • Smaller windmills in Valleys and in close proximity to towns
    • Suitable for microgrid architecture and DR, CC operations
  • GEV
    20
    Solar Energy Contribution to 2020 CA Grid
    Solar Energy Production Status
    Remote - Central Source
    Large solar panels (PVs) in Desert
    Large solar-thermal generators in Desert
    Local – Distributed Source
    Rooftop PVs in residential, commercial and industrial settings
    2009 Total is 846 GWh (2.43% of Total In-state Electrical Energy)
    5000 GWh rooftop by 2016 (an increase of 5.9 times 2009 total level, 4.8% of 2020 total)
    Solar Energy Status
    • Remote – Central Source
    • New transmission lines will need to be built and current transmission lines will need to be expanded or updated
    • Some form of storage (batteries, hydrogen, fuel cells, turbines, etc.) will be required to accommodate this expansion for continuity of power
    • Where is the best storage location – at generation or at load (DR, CC, and microgrids)?
    • Local – Distributed Source
    • Smaller PV sites in residential, commercial and industrial that are close proximity to consumer
    • Suitable for microgrid architecture and DR, CC operations
  • GEV
    21
    Natural Gas as Source of Electricity and CHP
    Advantages of Fuel Cells
    Direct conversion to electricity
    Electrochemical conversion from hydrogen to DC electricity
    No mechanical generator required
    Conversion efficiency is high (direct conversion ~50% or higher)
    Waste heat can be used in various scenarios
    Different fuel cell types have different amounts and grades of heat
    Demonstrations of waste heat recovery and use have illustrated this feature for the past thirty years
    Various operating conditions possible
    Some fuel cells can be efficiently operated over a range of output
    Many fuel cells can be modularized and combined to provide a range of outputs as a function of the demand
    Some fuel cells can simultaneously generate electricity, heat and hydrogen for added flexibility in consumer demands
  • GEV
    22
    Fuel Cell System Options (Electrochemical Conversion of Fuel Directly into DC) for Biomass CHP/Electricity
    Molten Carbonate Fuel Cells
    Operate at 600 C (Provide high-grade waste heat)
    Can provide internal fuel processing to operate fuel cell
    Operate at ~60% efficiency (heating value of fuel to electricity)
    Operate on range of gaseous fuels (methane, low Btu gases, propane, liquid fuels)
    Phosphoric Acid Fuel Cells
    Operate at 200 C (Provide both high and low grade waste heat)
    Can be integrated with SMR as external fuel processor
    Operate at ~ 50% thermal efficiency
    Operate on range of gaseous fuels
    Proton Exchange Membrane (PEM) Fuel Cells
    Operate at 80 C (Provide low-grade waste heat)
    Operates from hydrogen
    Operates at ~ 60% thermal efficiency
    Solid Oxide Fuel Cells
    Operate at 800 C
    Can provide internal fuel processing to operate fuel cell
    Operate at ~60% efficiency
  • Microgrids
    From DOE-CEC Microgrid Workshop / Navigant Consulting:
    A microgrid is an integrated power delivery system consisting of interconnected loads and distributed energy resources (DER) which as an integrated system can operate in parallel with the grid or in an intentional island mode.
    The integrated DER are capable of providing sufficient and continuous energy to a significant portion of the internal load demand even in island mode.
    The microgrid possesses independent controls and can island with minimal service disruption.
    From DOE-CEC Microgrid Workshop / Navigant Consulting: “What unique value(s) does a microgrid provide beyond DG alone, and who would pay for it?”
    The microgrid allows operation with a larger power system; this provides two key capabilities:
    Flexibility in how the power delivery system is configured and operated
    Optimization of a large network of load, local Distributed Energy Resources and the broader power system
    These two capabilities can deliver three important value propositions:
    Custom Energy Solutions: Provide customized power to individual customers/tenants or groups of customers/tenants
    Independence/Security: Support enhanced energy and infrastructure availability and security
    Reduced energy cost: Provide end users with less expensive energy over current rates.
  • Passive
    Passive
    Active
    Active
    MicrogridDesign, Construction, Interconnection and Operation
    All microgrids connected to grid operations
    Stand alone microgrids
    Residential
    Microgrid
    Commercial
    Microgrid
    Industrial
    Microgrid
    Transmission
    Passive
    Active
    [1-5 MW]
    [2-20 MW]
    [5-50 MW]
    NG CHP, storage,
    PV, PHEV, EV
    NG/biomass CHP, storage,
    H2, PV, Wind, PHEV, EV
    NG/biomass CHP, storage,
    H2, PV, Wind, PHEV, EV
    Interconnection, within each microgrid and across the grid, is integrated to permit uniform
    communication, control, load distribution, demand response, etc. according to customers’
    needs and overall electricity availability. Islanding among microgrids is possible.
    Passive = utililty integrated and utility owned, controlled and operated
    24
    Active = utility integrated, but consumer &/or third party owned/controlled/operated
  • GEVoecks
    Residential Microgrid
    Electrical Source
    To Residences
    • Local generation
    • Baseload supply
    Local Electrical Source
    • Renewables
    • PV
    • Natural gas
    Goal Focus
    - Improved Appliances
    - Demand Response
    - Grid Peak Reduction
    - Grid Distribution Loss Reduction
    - Generator Efficiency
    - Conversion Efficiency
    - Fault Isolation
    - Safety
    • Efficient Use (EV)
    • GHG Reduction
    Interface between local electrical source and storage/distribution
    (Batteries, H2, EV) within a
    microgridcommunity
    Controls
    At the local source of
    electricity interconnect:
    • HAN, AMI
    • Storage quantity level
    • C2
    • MEM
    • Microgrid control
    At the grid interconnect:
    - Storage quantity level
    - DA, Microgrid control
    - Central Manager
    Storage [1-5 MW]
    Size and type of storage
    device is a function of
    several parameters:
    • Community needs
    • Size of electrical source
    • Cost of storage
    • Integration with grid
    • Controls complexity
    • Local electricity source
    • Location
    Batteries
    • Flow type
    • Li ion
    • NaS
    H2 production
    - Fuel Cell
    - Electrolysis
    CHP
    Efficiencies =
    Interface between grid
    connect and storage/
    Distribution within amicrogrid community
    Remote Storage (ESG)
    Batteries, Capacitors, Thermal,
    Flywheels, Ultracapacitors,
    CAES, Hydro
    Peaking supply from local storage
    UTILITY GRID
    Baseload electricity supply via grid
    [Goal – Demand response reduces peak demand ]
    [Goal - 10% Total Electricity by 2016]
    Passive = utility integrated and utility owned, controlled and operated
    Active = utility integrated, but consumer &/or third party owned/controlled/operated
    [Goal – Reduce peak demand of ~4.9 GW by 2013]
    25
  • Roadmap Sectors: Reduction in Electricity Consumption
    9
    Reduction in Electricity Generation and GHG Emissions
    GHG
    to 1990 levels across all sources in 2020
    [Goal – Demand response reduces peak demand ]
    [Goal - 10% Total Electricity by 2016]
    [Goal – Reduce peak demand of ~4.9 GW by 2013]
    4
    6
    Use Reduction
    Distribution Efficiency
    Production Efficiency
    7
    Microgrids
    Remote
    Central
    Improved
    Appliances &
    other Conversion
    Demand
    Response
    Controls
    Technology
    Commun-
    ications
    Technology
    Microgrids
    Utility grid,
    commercial,
    industrial,
    residential
    Source, storage,
    network,
    Integration
    Storage, source,
    grid connection,
    transmission,
    CHP
    Network controls,
    storage, PHEV, EV
    26
  • Principal Elements of TIMA
    Objectives – the characteristics of the desired end-state
    Barriers – the impediments, risks, obstacles… that get in the way of attaining the Objectives
    Actions – the possible actions that could be taken to overcome Barriers, and thereby attain the Objectives
    Objectives and Barriers are linked, to indicate which Barriers get in the way of which Objectives, and to what extent they get in the way (referred to in the software as “impact”)
    Actions and Barriers are linked, to indicate which Actions overcome which Barriers, and to what extent they overcome them (referred to in the software as “effect”).
    In some cases, an action will make some Barriers worse (either introducing new Barriers that were not relevant before, or making existing Barriers even worse).
  • Smart Grid System Architecture
    Technology Infusion and Maturity Assessment (TIMA) Tool/Process
    “Actions” from which to pick and choose the makeup of alternate Smart Grid plans
    IEPR “Objectives” against which Smart Grid plans will be assessed
    “Barriers” – all the concerns, risks etc. that could impede attainment of objectives
    Additional information is
    kept on each item
    The industry partners will help complete these parameters, and provide the crucial interrelationships. From this information alternate Smart Grid plans and a technology roadmap can be evaluated.
  • Objectives x Barriers
    The solid blue circle is there to draw viewers’ attention to this Objective
    Rows are Objectives
    Columns are Barriers
    The cell numbers indicate “impact” - how much each Barrier obstructs each Objective.
    These impact numbers are proportions, i.e.,
    1 = total obstruction
    0.7 = major obstruction
    0.3 = modest obstruction
    0.1 = minor obstruction
    Blank = no obstruction
    Objective’s row highlighted in blue
    Barrier’s column highlighted in red
    The solid red circle is there to draw viewers’ attention to this Barrier
  • Simple model, convoluted data
    E.g., 50 objectives, 31 risks, 58 mitigations from actual JPL technology study: “topology” of this data is shown below (in addition, every link has a quantity associated with it: how much each risk detracts from each objective; how much each mitigation reduces each risk (in some cases, increases – the red lines)
    Objectives
    Risks
    Mitigations
    Mitigations incur costs; usually can’t afford them all, so must select judiciously.
    The highly cross-coupled nature of this information is the reason why successful technology acquisition is so hard to achieve!
  • Actions x Barriers
    Rows are Actions, Columns are Barriers, cell numbers indicate “effect” - how much each Action overcomes each Barrier. The numbers are proportions, e.g., 1 = totally overcomes; 0.7 = mostly overcomes; 0.3 = moderately overcomes; 0.1 = slightly overcomes; Blank = no help; Negative means makes the Barrier worse, either it introduces it (e.g., 0.3 = introduces some) or magnifies it (e.g., -1.3 = magnifies by 1.3)
  • Cost-Benefit Tradeoff Space
    Significant improvement possible; excellent case for more investment!
    Region of diminishing returns
    Sweet spot!
    High Cost, High Benefit
    Low Cost, High Benefit
    Sub-optimal interior
    Each point represents a selection of mitigations, located by its cost (horizontal position) and benefit (vertical position).
    300,000 points plotted here
    x
    Benefit(expected attainment of objectives)
    High Cost, Low Benefit
    Low Cost,Low Benefit
    Cost
    58 mitigations = 258 (approx 1017) ways of selecting from among them.Heuristic search for near-optimal solutions extended across the entire cost range to reveal shape of the cost-benefit trade space.
  • Actions and Objectives Attainment
    Each row corresponds to one of the Objectives – color indicates proportion of that objective’s attainment
  • Comparison of Mitigation Options
    E.g., one column per risk
    Three selections of mitigations are compared – a baseline selection, an alternate, and the empty set
    Black = increase of alternate over baseline
    Yellow = decrease of alternate over baseline
    Green = unmitigated
  • Documentation Generation
  • Summary – Preliminary Findings
    Distributed generation needs distributed storage to achieve the greatest efficiency and operational benefits.
    Storage is needed for a variety of smart grid applications—such as peak shaving, islanding, VAR support, renewable energy integration, PEVs, frequency regulation
    Biomass offers significant potential for reducing the GHG and adding to the distributed generation.
    Microgrids can be assembled in many different architectures and adapted to accommodate several different electrical and thermal requirements, all resulting in significant energy and GHG savings.
    Microgrids and distributed generation/storage systems can take advantage of the NG distribution system, as well as renewable energy generation, to achieve greater savings through hybridization of operations.
    Demonstrations of microgrids and distributed generation/storage need to be pursued in different settings to illustrate the value to utilities and customers.
    Fuel cells offer significant energy savings and reduced GHG through use of NG and CHP.
  • Summary – Approach
    The smart grid is an engineering system whose complexities span technological, operational, policy, regulatory and market factors.
    Planning for its design, development, deployment and sustainability must be driven by objective, top-down systems analyses.
    Driving development and integration of advanced energy conversion and storage technologies, renewables and clean transportation.
    The practice of systems engineering and architectural trade off analysis, as used by the aerospace community, is applied herein to the design and evaluation of architectural options for the smart electric power grid.
    Technology Infusion and Maturation Assessment (TIMA) allows the linkage of top-level energy policy priorities with physical, functional and business objectives from key technology use cases, by looking at barriers to objectives attainment and actions to mitigate those barriers.
    The TIMA process, combining elicitation, consensus-building, analysis and information visualization, leads to energy technology roadmap recommendations characterized as an optimal set of risk retirement investments addressing R&D and demonstration needs over time (2010 baseline to 2020), for a given smart grid architecture.
  • Summary – Preliminary Findings
    Distributed generation needs distributed storage to achieve the greatest efficiency and operational benefits.
    Storage is needed for a variety of smart grid applications—such as peak shaving, islanding, VAR support, renewable energy integration, PEVs, frequency regulation
    Biomass offers significant potential for reducing the GHG and adding to the distributed generation.
    Microgrids can be assembled in many different architectures and adapted to accommodate several different electrical and thermal requirements, all resulting in significant energy and GHG savings.
    Microgrids and distributed generation/storage systems can take advantage of the NG distribution system, as well as renewable energy generation, to achieve greater savings through hybridization of operations.
    Demonstrations of microgrids and distributed generation/storage need to be pursued in different settings to illustrate the value to utilities and customers.
    Fuel cells offer significant energy savings and reduced GHG through use of NG and CHP.