A Multi Scale Design and Control Framework for Dynamically Coupled Sustainable and Resilient Infrastructures, with Application to Vehicle to Grid Integration PI Prof. Jeffrey L. Stein ME U of M Co PI Prof. Zoran Filipi ME Clemson Prof. Greg Keoleian SNRE U of M Prof. Huei Peng ME U of M Prof. Mariesa Crow EE Missouri U. of Sci. & Tech. Particip. Invest. Prof. Duncan Callaway Energy Resources Group UC Berkeley Prof. Hosam K. Fathy ME Penn State Prof. Carl Simon MMPEI/Math U of M Prof. Jing Sun Naval U of M Prof. Ian Hiskens EE U of M
Stochastic Resources and Loads Jarod Kelly Research Scientist Chiao Ting Li Ph.D. Student Renewable Resources Exhaustible Resources Mobility/Energy Demands Power Generation PHEVs Storage & Distribution Power Infrastructure Transportation Infrastructure
Environmental assessment of plug in hybrid electric vehicles using naturalistic drive cycles and travel pattern information Jarod C. Kelly From presentation at 6 th International Conference on Industrial Ecology by Brandon M. Marshall, Jarod C. Kelly, Gregory A. Keoleian, Tae Kyung Lee, Zoran Filipi 3
Understanding sustainability Sustainable energy definition from United Nations Development Programme (2000) energy produced and used in ways that support human development over the long term, in all its social, economic, and environmental dimensions. 4
Some sustainability indicators Environmental Indicators Greenhouse gases (GHG) Per unit emissions of GHG expressed in CO 2 equivalents Local emissions / criteria pollutants Deposits of SO 2 per kilometre Energy Supply Indicators Reliability % of time that source is available Import dependency Energy diversification Sum of squares of shares of different sources in effective energy consumption Economic Indicators Average subsidy per effective unit of energy Consumption Social Indicators Affordability Education Health Source: Based on World Bank (2000), op. cit., p. 39 and IEA Energy Statistics Division.; Keoleian Univ. Michigan 5
Life cycle analysis Well-to-wheel analyses total fuel cycle for feedstocks powertrain efficiency Full life cycle assessment well-to-wheel analysis vehicle production Tank to Wheels Well to Tank Well to Tank Source: Argonne National Lab; Keoleian Univ. Michigan 6
Goal Evaluate the sustainability performance of PHEVs in Michigan using two different evaluation methods. Characterize sustainability performance using fuel cycle energy and emissions quantifications. 7
PHEV energy consumption model comparison Naturalistic drive cycles Average consumption rates PHEV NDC Based on energy consumption curves generated with naturalistic drive cycles PHEV AVG Based on an average of vehicle efficiencies from HEV/PHEV literature 32 mpg; 0.274 kwh/mile Image: 2011 Chevrolet Volt, Courtesy General Motors 8
One week of PHEV charging from the Michigan grid PHEV charging from the Michigan (2009) electrical grid: electricity consumption from the PHEV NDC model shows a 12.6% increase over electricity consumption from the PHEV AVG model 9
Total Fuel Cycle (TFC) energy per mile Total fuel cycle energy Includes all life cycle energy used to drive the vehicle, from mining, processing and transporting fuels to vehicle propulsion Allocation methods Average (AA): Portion of every power plant attributed to PHEVs based on proportion of PHEV load to total load Marginal (MA): Only the energy from added plants dispatched to provide power for vehicle charging are assigned to PHEVs CS: charge sustaining mode, engine only CD: charge depleting mode, battery only All light duty conventional vehicles Midsize PHEV (CV) in Michigan, 2010 based on 2009 Michigan grid Midsize PHEV based on 2020 western states grid 10
Greenhouse gas emissions The PHEV environmental assessment for Michigan * tracks three greenhouse gases (GHGs): Carbon Dioxide (CO 2 ), Methane (CH 4 ), and Nitrous Oxide (N 2 O), and use IPCC 4 th Assessment Report to calculate mass of CO 2 e = m CO2 + 25 * m CH4 + 298* m N2O *(Keoleian et al, 2010) 11
Criteria pollutant emissions Five other air pollutants defined as criteria pollutants are tracked by the PHEV environmental assessment in Michigan * Nitrogen Oxides (NO X ) Carbon Monoxide (CO) Sulfur Dioxide (SO X ) Volatile Organic Compounds (VOC) Particulate Matter (PM 10 ). *(Keoleian et al, 2010) 12
Summary Evaluated environmental impacts of PHEVs in Michigan using two approaches Find that even using a more aggressive (and realistic) energy consumption characterization, PHEVs outperform conventional vehicles in total fuel cycle energy and GHG emissions PHEVs increase emissions of SO x, NO x and particulate matter Primarily due to contribution from coal based electricity 13
Drive cycles The Environmental Protection Agency (EPA) developed federal driving schedules Speed versus time curves originally used for emissions certification testing of conventional vehicles Widely accepted analysis approach in determining fuel economy Not necessarily representative of actual driving behavior EPA continues to adjust and combine standard test cycles in an effort to achieve real world driving characteristics 14
Engineers at the University of Michigan developed synthetic naturalistic drive cycles * Characterized from a database of actual driving generated in Field Operational Tests in Southeast Michigan Procedure utilizes Markov chains to generate synthetic drive cycles statistically matched to dynamics of real world driving Used to predict energy usage as a function of trip length and reproducible for arbitrary driving distances Naturalistic drive cycles *(Filipi, et al, 2009) 15
Predicting PHEV energy consumption Previous approach: Examine driving distance distribution from travel survey * Choose PHEV all electric range (Example: PHEV30 travels 30 miles on battery power only) Split travel survey data into battery miles and gasoline miles based on all electric range Use estimated fuel economy (mpg), and electric efficiency (kwh/mile) to determine energy consumption of fleet 45% of fleet miles are battery powered, All electric range 55% are gasoline powered NSF EFRI Grant: Dynamically Coupled Sustainable = 30 miles and Resilient Infrastructures 16 *(EPRI, 2001, 2007; Samaras, et al, 2007; Elgowainy, et al, 2010)
New approach: Predicting PHEV energy consumption Examine individual vehicle trips in the travel survey * Apply a naturalistic drive cycle to each trip based on distance Calculate gasoline and battery usage from energy consumption curves Vehicle ID Trip Distance 1 15 1 10 2 30 2 37 3 12 3 4 3 16 *(Keoleian et al, 2010) 0 20 40 Trip distance 17
Sustainability & Reliability of Electricity Grid with Plug In Electric Vehicle Control Chiao Ting Li, Huei Peng, Jing Sun University of Michigan
Control Integration on Electricity Grid Synergy exists between The controllable plug in vehicle charging The renewable but intermittent wind energy Appropriate system control can exploit the synergy to Improve sustainability Retain reliability Metrics for sustainability and reliability across both the transportation and electricity sector on a common base: cost 19
Modeling Efforts The plug in vehicle (PEV) fleet Three distributions: Plug in time Plug off time Battery state of charge (SOC) Data source: UMTRI & NHTS These distributions help to Quantify the additional load imposed by PEVs Quantify the leverage power (control authority) granted by PEVs 20
Modeling Efforts The electricity grid Conventional Grid (Reference Case) Grid with Integration Grid Grid = = = = No renewables Uncoordinated PEV charging Wind energy is included Controlled PEV charging 21
Controller Structure & Realization Planning (Scheduling) = = Realization (Dispatch) The realization tells Wind energy utilization Non renewable generation utilization Load magnitude Grid frequency deviation 22
Sustainability & Reliability Metrics Sustainability: Reduction of fossil fuel use in transportation sector Penetration of renewables in electricity sector Reliability: Retain the same LOLP (loss of load probability) in electricity sector We measure how much grid reserve can be retired while retaining the same LOLP Furthermore, the improvement is converted into cost reduction/saving We count dollar saved only in the end use phase (exclude mining, fuel transporting, plant installation etc.) 23
Sustainability & Reliability Metrics Transportation Electricity Grid (25% PEV penetration) (10% wind energy penetration) ICE PEV Sustainability Reliability Sustainability ICE PEV Existing Load PEV PEVs act as the intermediary to bridge the transportation and electricity sector S & R measurement, eventually, shows up as cost reduction in both sectors This assessment can be a planning tool for investors or policy makers to set penetration targets in both sectors 24
Summary PEVs act as the intermediary to bridge the transportation and electricity sectors, and enables the control integration Models were developed to capture major dynamics on the grid, with which we test the control integration We assess sustainability and reliability across two sectors on a common base: cost Transportation Electricity Grid Fossil fuel use Cost reduction Renewable penetration Loss of load probability There are still things that can be included into the assessment Transportation Electricity Grid Emissions Energy diversity More capable of enduring disturbances/break downs 25