The document discusses using the Technology Infusion and Maturation Assessment (TIMA) process developed by NASA's Jet Propulsion Laboratory to design and evaluate architectural options for the smart electric power grid in California. TIMA involves identifying key technologies, developing use cases, analyzing risks and barriers, and defining a technology roadmap. The goal is to meet California's energy and climate policy objectives through 2030 and beyond in a cost-effective manner.

1. 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

2. 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)”

3. 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

4. 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

5. 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.

6. 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.

7. 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

8. 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.

9. 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

10. 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

11. 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.

12. 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.

14. 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

15. 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

16. 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

17. 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

18. 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.

20. Transmission lines will be required to transfer electricity to customers

21. New transmission lines will need to be built and current transmission lines will need to be expanded or updated

22. Some form of storage (batteries, hydrogen, fuel cells, turbines, etc.) will be required to accommodate this expansion

23. Where is the best storage location – at the generator or near the customer (DR, CC, and microgrids)

24. Local – Distributed Source

25. Smaller windmills in Valleys and in close proximity to towns

27. New transmission lines will need to be built and current transmission lines will need to be expanded or updated

28. Some form of storage (batteries, hydrogen, fuel cells, turbines, etc.) will be required to accommodate this expansion for continuity of power

29. Where is the best storage location – at generation or at load (DR, CC, and microgrids)?

30. Local – Distributed Source

31. Smaller PV sites in residential, commercial and industrial that are close proximity to consumer

33. 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

34. 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.

35. 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

38. PV

41. Storage quantity level

42. C2

43. MEM

45. Size of electrical source

46. Cost of storage

47. Integration with grid

48. Controls complexity

49. Local electricity source

51. Li ion

52. NaSH2 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

53. 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

54. 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).

55. 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.

56. 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

57. 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!

58. 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)

59. 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.

60. Actions and Objectives Attainment Each row corresponds to one of the Objectives – color indicates proportion of that objective’s attainment

61. 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

62. Documentation Generation

63. 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.

64. 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.

65. 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.