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Estimating Real-Time Emissions from Electricity Use via Locational Marginal Prices

This presentation discusses a project aimed at minimizing environmental impacts on the Great Lakes through real-time emissions estimation linked to electricity usage. Utilizing locational marginal prices (LMP), the method assesses emissions based on the type of energy generation and environmental conditions specific to location and time. The approach has significant implications for optimizing energy use in water distribution systems and potentially broader applications in reducing emissions for various power users.

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Estimating Real-Time Emissions from Electricity Use via Locational Marginal Prices

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  1. Using locational marginal prices to estimate real-time emissions from electricity use IEEE Alternate Energy Presentation May 3, 2012 URS Corp., Southfield, MI Michelle Rogers & Ian Hutt

  2. Team Background • Michelle Rogers • Master’s student at Wayne State studying Civil & Environmental Engineering • B.S. Chemical Engineering from Michigan State • Ian Hutt • Electric Engineer at Commonwealth Associates, Inc • Expertise in electrical power systems & power marketing

  3. Team Background • Other Team Members: • Wayne State: Dr. Carol Miller, Dr. Caisheng Wang, Dr. McElmurry, Tim Carter • Commonwealth Associates: Stephen Miller • TYJT: AwniQaqish, Steve Jin, Carrie Smalley

  4. Outline • Introduction to the project • How project was started • Purposes of development • How it works • LMP • Marginal Generating Unit • Emissions • Application for water distribution systems • Wider applications: household electricity use • HERO smartphone App

  5. Introduction • Algorithm estimates real-time emissions based on locational marginal price (LMP) • Started as a project for sustainable water delivery • Also has wider implications / uses

  6. Why was this project started? • GLPF, Great Lakes Protection Fund grant • Grant title: “Real-Time System Optimization for Sustainable Water Transmission and Distribution” • Purpose: minimize environmental impacts to the Great Lakes • Optimize energy use in water system distribution (pumping)

  7. Why was this project started? • GLPF, Great Lakes Protection Fund grant • Became clear that emissions, not just energy use, was the key in minimizing environmental impact • Not all energy use is equal (from emissions standpoint) • Emissions vary with type of generation fuel • Depends on time and location

  8. Applications • Not all energy use is equal (from emissions standpoint) • Any power user that has ability to vary timing of energy use could save emissions • Timing does not affect economics, but could still affect emissions • Industrial or commercial users that have storage capacity (like compressed air or pumps)

  9. Methodology • Use LMP to predict the marginal fuel type • Calculate emissions associated with that fuel type for a specific area

  10. Locational Marginal Prices • LMPs available from MISO • (Midwest Independent System Operator) • LMPs for select Commercial Pricing Nodes (CPNs) available every 5 minutes

  11. Locational Marginal Prices • 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

  12. Locational Marginal Prices

  13. Locational Marginal Prices

  14. Locational Marginal Prices • Key Assumptions: • Any change in electricity use is small enough to not affect generation mix • LMP cost takes into account electrical transmission constraint • Model predicts the marginal unit type

  15. Locational Marginal Prices • LMP Accounts for: • physical aspects of transmission system (constraint in transmission lines) • Within a small focus area, can assume constraint in the physical transmission system = ~ zero • Cost of marginal power losses • Assume marginal power losses = ~ zero • Generation marginal cost (fuel cost) • Left with LMP = ~ fuel cost

  16. Locational Marginal Prices • LMP = ~ fuel cost Price ($/MWh) LMP at time ti Hydro & Nuclear Coal Natural Gas Oil

  17. Fuel Prices • LMP = ~fuel cost • Find fuel price data (EIA – public sources) • Heat Rate (efficiency) of each plant: • Weighted average of monthly fuel price calculated from plant fuel purchases • Cost of electric generation computed:

  18. Fuel Prices • Get price ranges for Fuel types • For Example: DTE Power plants in SE Michigan • LMP  Marginal Generator Type  Air Emissions

  19. 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

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

  21. Application for water distribution systems • GLPF Grant: “Real-Time System Optimization for Sustainable Water Transmission and Distribution” • Emissions estimation algorithm used in optimization program for pumping stations. • Two pilot water systems:

  22. Hydraulic Model • Use EPANet hydraulic models • Input: • Pipe length • Pipe diameter • Demand at each node • Diurnal demand pattern • Pump power • Pump efficiency curves • Elevation • Tanks and reservoirs

  23. Hydraulic Model • City of Monroe

  24. Hydraulic Model • DWSD

  25. Sustainable Water Transmission • Need to combine: • Hydraulic Model + Emissions Estimation Model • PEPSO: Pollutant Emissions Pump Station Optimization •  Uses hydraulic model to output optimized pumping schedule • Optimization based on: • Emissions • Energy Cost • Pressure constraints in system

  26. PEPSO Input: Load Hydraulic Model

  27. PEPSO Input: Load Pressure Monitoring Nodes

  28. PEPSO Input: Select Commercial Pricing Nodes (CPNs)

  29. PEPSO Input: Select Pollutants of Interest

  30. PEPSO Output • Energy use per hour for each pump station. • Pounds of pollutant emissions per hour for optimized operation of each pump station. • Pressure violations, if any.

  31. PEPSO Output

  32. Sustainable Water Transmission • PEPSO will be used to evaluate many scenarios • High/low demand • Different pollutants • Availability of raised storage • Optimization based on cost vs. emissions • Use as a tool to make policy and operational recommendations

  33. Reaching a broader audience: the HERO app • HERO = Home Emissions Read-Out • (LMP  Marginal Generator Type  Air Emissions) • Applying this concept to household energy use • App for smart phones

  34. HERO • Uses location to determine marginal emissions in real-time • Knowledge of current emissions empowers consumers to reduce emissions just by changing the timing of electricity use

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

  36. HERO Output • Current, Past, and Projected Future emissions • CO2, NOX, SOX, Mercury, Lead

  37. HERO Output • User can view more to see background information on CO2, NOX, SOX, Mercury, Lead • Environmental Effects, Human Health Effects • Example: NOX & SOX

  38. HERO Status • Still under development • Preliminary version should be finished in Fall • After small test audience makes recommendations, fix all bugs, then beta version release in Google Play App Store

  39. Questions?

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