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A A Smar Smart-Phone Phone Applica pplication tion for Hom or - - PowerPoint PPT Presentation

May 23, 2023 179 likes •482 views

op Water ter Su Sustaina stainabili bility ty Wor orksh kshop A A Smar Smart-Phone Phone Applica pplication tion for Hom or Home e Emissions Emissions Estima Estimates tes Michelle M. Rogers, Michigan Department of Environmental

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COLLEGE OF ENGINEERING

Michelle M. Rogers, Michigan Department of Environmental Quality Carol J. Miller, Shawn P. McElmurry, Guoyao Xu, Weisong Shi, Caisheng Wang, Cheng-Zhong Xu, PhD Wayne State University – College of Engineering

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Total generation: 4,120 billion (kWh)

3,950 billion (kWh) in 2009

Source: http://www.eia.doe.gov

WHY? WHY? Ener Energy y –Emissions Emissions

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Polluting Emissions from Electricity Generation

http://www.gpo.gov/fdsys/pkg/FR-2012-02-16/pdf/2012-806.pdf http://www.epa.gov/mats/actions.html

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 Air Quality

 Visual  Health (asthma)  GHG………Climate (?)

 Contaminant Deposition

 Surface Water  Soils  Vegetation

 Food Chain

 Fish Consumption

 And,….Even for the “non-environmentalist”………

 Policy: Government Specified Caps

Emissions Effects

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Problem: How to identify emission potential?

Locational Marginal Price as Proxy for Generator Type

LMP at time ti

Hydro & Nuclear Coal Natural Gas Oil Price ($/MWh)

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 LMPs based on marginal cost of supplying the next increment of electric demand at a specific location  LMP Accounts for:

 generation marginal cost (fuel cost)  physical aspects of transmission system (constraint in transmission lines)  Cost of marginal power losses

Locational Marginal Prices (LMP)

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Methodology

 Use LMP to point to the marginal fuel type  Calculate emissions associated with that fuel type for a specific area (or specific generator)

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Environmental Optimization

Linking Consumption to Emissions

  • 1. Source Identification
  • Dispatch adjusted every 5 minutes within MISO
  • 2. Emission Quantification
  • Function of generator type
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Locational Marginal Prices

 LMPs available from MISO

 (Midwest Independent System Operator)

 LMPs for select Commercial Pricing Nodes (CPNs) available every 5 minutes

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Locational Marginal Prices…spatial variation

LMP LMP = f = f (space,time) (space,time)

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Locational Marginal Prices….temporal variation

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Emission Rates

 LMP  Marginal Generator Type  Air Emissions  Measured Air Emissions Data from EPA’s eGRID

 (Emissions & Generation Resource Integrated Database)  Data on thousands of power plants in the US

 Sort by EGCL code (Electric Generating Company, Location-Based)

 i.e., all of DTE-operated plants in SE Michigan WE WANT THIS TO BE DEFINED ON THE FINEST GRID POSSIBLE….compare to an approach based on national averages of emissions/KWh

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Emission Rates

 Calculate average emission rate for entire area for each fuel type  Example, Detroit Edison: (2008 data)  LMP  Marginal Generator Type  Air Emissions

Air Emissions in pounds pollutant per MWhr generated (lb/MWh) Pollutant Nuclear Coal Natural Gas Distilled Fuel Oil SO2 10.54 1.65 2.3445 NOX 3.05 1.57 21.73 CO2 equiv 2071 2292 1862 Hg 5.26E-05 3.62E-06 5.81E-06 Pb 1.09E-07 3.10E-05 1.66E-06 3.65E-05

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Putting it Together: the HERO app

 HERO = Home Emissions Read-Out  (LMP  Marginal Generator Type  Air Emissions)  Applying this concept to household energy use  Android App for smart phones

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HERO: Home Emissions Read-Out

HERO ARCHITECTURE

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HERO Input

 HERO can automatically find nearest CPN based on phone’s GPS  User also has choice to pick location from map

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HERO Output

 Current, Past, and Projected Future emissions  CO2, NOX, SOX, Mercury, Lead

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HERO Screen Shots

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 User can view more to see background information on CO2, NOX, SOX, Mercury, Lead  Environmental Effects, Human Health Effects  Example: NOX & SOX

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LEEM: Locational Emissions Estimation Methodology

Input: Address Geographic Location Closest LMP Node Link LMP to Marginal Generator Output: Real-Time Emissions

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 HERO published in GooglePlay  https://play.google.com/store/apps/details?id=com. amaker.herotest&feature=search_result#?t=W251b GwsMSwyLDEsImNvbS5hbWFrZXIuaGVyb3Rlc3Q iXQ..

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Improvements?

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Server-Based Approach

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Test Case of Emissions Benefits

Appliance Frequency (d-1) Cycle Length (hrs) Power (kW) Energy/ cycle (kWh) Intermittent (Y/N) Preferred Time Hr (1 - 24) Water Heater 1.00 3.00 1.29 3.87 YES 4 Defrost Cycle 2.00 0.33 0.70 0.23 NO 1 Dishwasher 0.50 2.0 0.98 1.97 NO 22 Clothes Washer 1.00 0.5 0.61 0.31 NO 20 Clothes Dryer 0.86 0.75 4.59 3.44 NO 19

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BEST/WORST CASE PERFORMANCE

Region Node Location Year Based

  • n LMP

type Average change in target pollutant Greatest change achieved by any pollutant Least change achieved by any pollutant RFCM Monroe, MI 2009 RT

  • 68%
  • 84%
  • 33%

RFCM Monroe, MI 2007 RT

  • 78%
  • 88%
  • 49%

RFCM Monroe, MI 2009 DA

  • 27%
  • 61%

+1% RFCM

  • St. Clair, MI 2009

RT

  • 68%
  • 84%
  • 32%

RFCM Midland, MI 2009 RT

  • 70%
  • 86%
  • 29%

SRMW Labadie, MO 2009 RT

  • 74%
  • 80%
  • 49%

MROW Fergus Falls, MN 2009 RT

  • 70%
  • 72%
  • 64%
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Great Lakes Benefits

Great Lakes Resident Engages Energy Consuming Device LEEM Optimiza tion Change in Demand Reduction in Hg Emissions Reduced Hg in Fish Fishing Restrictio n Lifted Consumer utilizes local resources

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Extension of Project

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Thanks to Great Lakes Protection Fund

THANK YOU

COLLEGE OF ENGINEERING

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