Debra Reinhart Hamid Amini. University of Central Florida

Transcription

1 Landfill Gas to Energy Projects: Incentives and Benefits Debra Reinhart Hamid Amini

2 Overview Project Objectives Completed Phases Methodology Results & Conclusions Future Tasks Economic Benefits and Sensitivity Analysis

3 Project Objectives Evaluate LFG generation through best-approach modeling Quantify the uncertainty involved in LFG generation modeling Predict Florida LFG and LFGTE potential Study economic benefits from Florida LFGTE projects

4 Phases Phase 1: LFG Generation Modeling Select best approach Quantify model parameters Quantify uncertainty of model outcomes Phase 2: Florida LFG & LFGTE Potential Potential under base case conditions Sensitivity analysis Phase 3: Economic Analysis

5 Phase 1: LFG Generation Model First-order generation model (LandGEM) n 1 M Q = αk i Le g 0 10 i= 1 j= 0.1 where: Q g = Generated LFG flow rate, m 3 yr -1 k = Methane generation rate constant, yr -1 M i = Disposed waste tonnage in year i, Mg kt L 0 = Methane generation potential, m 3 CH 4/Mg waste (wet basis) t = Time, yr α = Inverse ratio of methane content ij

6 LFG Collection Collection efficiency applies based on: Applied cover material and installation timing Gas collection system design and installation timing Q c =η η Q g where: η = Collection efficiency, fraction

7 Collection Efficiencies: Compiled from literature Description Average Collection Efficiency No LFG collection system 0% Active landfill with active LFG collection system of vertical wells and daily cover only Active landfill with active LFG collection system of vertical wells + intermediate cover or active LFG collection system of horizontal trenches + daily cover Active landfill with active LFG collection system of vertical wells + engineered final soil cover or active LFG collection system of vertical wells and horizontal trenches + intermediate cover Active landfill with active LFG collection system + geomembrane, subtitle D or equivalent cover 67% 75 % 87% 90 %

8 Case-Study Landfills Landfill Waste Year Year Operational LFG Collection Type Opened Closed Practice System Landfill 1 MSW 1985 Open Traditional Active; Vertical wells + Horizontal trenches Landfill 2 MSW 1978 Open Traditional Active; Vertical wells Landfill 3 MSW Traditional, Wet-cell Active; Vertical wells Landfill 4 MSW + C&D 1977 Open Traditional Active; Vertical wells + Horizontal trenches Traditional, Landfill 5 MSW 1986 Open Active; Vertical wells University Bioreactor of Central Florida

9 Linear Regression Generation model outcomes, Q mg, were converted to model collected, Q mc, by applying year-by-year collection efficiency factors Q mc was compared to the actual LFG collection data, Q ac, using linear regression of the Q ac vs. Q mc trend line forced through zero Statistical parameters were evaluated: Slope of Q ac vs. Q mc regression line Regression correlation coefficient (R 2 ); R 2 >0.5 considered statistically significant Probability-value (p-value); p-value<0.2 considered statistically significant

10 Generation Model Approaches to Determine k and L 0 Approach 1: Fixed EPA AP-42 default values Approach 2: Composition Calculated L 0 - Variable k Approach 3: Site Calculated L -Variable k 0 Approach 4: Simultaneously Variable L 0 and k

11 Landfill 1 Phase 1 Landfill 1 Phase 2 Landfill 3 Landfill 4

12 Uncertainty Oracle Crystal Ball was used to study the uncertainty in L 0 and Q and Q mg Uses Monte-Carlo simulation method to calculate range of variations and probabilities for a certain parameter Used Crystal Ball to estimate potential variations in L 0 by applying ±30% variations to waste composition k was adjusted to a minimum and a maximum value so that when applying those values to model Q mc, boundaries were generated which captured a maximum number of Q ac data points

13 Uncertainty Results

14 Phase 1 - Conclusions The optimum method to estimate LFG model parameters is to determine L 0 using disposed MSW composition and laboratory component methane potential values (site specific conditions can be considered). k can be selected by regression for best slope using the first-order model and actual LFG collection data. When such data are not available, k can be selected from technical literature, based on site conditions related to climate and landfilling operations. L 0 varied from 56 to 77 m 3 /Mg; k varied from 0.04 to 0.11 yr -1 for the traditional landfills/cells and was 0.10 yr -1 for the wet-cell

15 Conclusions - Cont d Model predictions of LFG collection rates were on average lower than actual LFG collected (approximately 10%). The uncertainty (Coefficient of Variation) in modeled LFG generation rates varied from ±17% to ±30% while landfills were open, ±9% to ±18% at end of waste placement, and ±16% to ±203% fifty years after waste placement ended. Average life-to-date LFG collection were calculated based on actual LFG collected and modeled LFG generation, and were found to vary from 19% to 64% for the case study landfills.

16 Conclusions - Cont d The first order model cannot always be applied to full-scale landfill gas collection data with statistical significance. Collecting accurate waste composition and disposal rate data is critical to successful LFG generation modeling. Uncertainty in LFG collection efficiency reduced the ability to accurately model LFG generation in many cases.

17 Phase 2: Florida LFG & LFGTE Potential Assumptions: LFG Generation: i. Study period: ii. k=0.07 yr -1 for traditional landfilling operation (Phase 1 outcomes) iii. iv. L 0 calculated from 2007 disposed waste composition data for each County Disposal tonnage, M, based on 2007 data; extrapolated into past and future years with regards to population growth factor v. Methane content: average 50% over the study period vi. LFG generation uncertainty applied based on Phase 1 outcomes

18 Florida LFG & LFGTE Potential Assumptions: LFG Collection: i. Start gas collection after five years ii. Collection efficiency fixed at 75% from 2010 to 2035 LFGTE: i. All Florida landfills operate a LFGTE facility ii. Energy content of 5.2 kwh/m 3 LFG (~18,000 Btu/m 3 CH 4 ) iii. Energy conversion efficiency of 90% iv. Energy generation efficiency of 35%

19 Current vs. Future Potential

20 Sensitivity Analysis Scenario Population growth rate Recycle ratio k, yr -1 Start gas collection LFG collection efficiency Energy conversion efficiency Energy generation efficiency Scenario 1. Base case +2% 49% years Scenario 2. Early gas collection +2% 49% years Scenario 3. Bioreactor operation +2% 49% years Scenario 4. 65% recycle goal +2% 65% years Scenario 5. 75% recycle goal +2% 75% years Scenario 6. Minimum population growth +1% 49% years Scenario 7. Maximum population growth +3% 49% years Scenario 8. Improved energy conversion and energy generation efficiencies +2% 49% years Scenario 9. Maximum energy generation (moderate population growth) +2% 49% years

21 Florida Recycle Ratio Current practice (state-wide average) is 49% of generated (by weight): Recycled = 29% (13% of degradable and 9% of non-degradable) Combusted = 12% Landfilled = 59% o o 40% of landfilled waste goes to landfills that have a LFGTE facility 54% of disposed waste in biodegradable o LFG collection efficiency is assumed to be 75% o Assuming 90% of collected gas goes to LFGTE facility = = (or 49%)

22 75% Recycle Goal If we add 30% to recycle ratio of degradable material and 35% to recycle ratio of non-degradable d material Recycled = 48% (43% of degradable and non-degradable) Combusted = 12% (combustion capacity assumed to be fixed) Landfilled = 41% o o All landfills operate a LFGTE facility 55% of disposed waste in biodegradable o LFG collection efficiency is assumed to be 75% o Assuming 90% of collected gas goes to LFGTE facility = = (or 75%)

23 Scenarios Outcomes ( ) 2035) Scenario Q c x10 9, m 3 (min-max) E g x10 9, kwh (min-max) Portion of projected energy demand, % Scenario 1. Base case (13-41) (21-67) 0.18% Scenario 2. Early gas collection 35 (17-53) 58 (28-88) 0.24% Scenario 3. Bioreactor operation 42 (20-63) 69 (33-100) 0.29% Scenario 4. 65% recycle goal 26 (12-40) 43 (21-64) 0.18% Scenario 5. 75% recycle goal 24 (12-37) 40 (20-61) 0.17% Scenario 6. Minimum population growth 25 (13-37) 41 (21-61) 0.17% Scenario 7. Maximum population growth 30 (13-47) 50 (22-78) 0.21% Scenario 8. Improved energy conversion and energy generation efficiencies 27 (13-41) 70 (33-110) 0.29% Scenario 9. Maximum energy generation (moderate population growth) 42 (20-63) 110 (52-170) Florida energy demand predicted to be approximately 24 trillion kwh during %

24 Operation Strategies

25 Increased Recycle Goals

26 Phase 2 - Results Applying base case LFGTE practice to all Florida landfills can approximately triple E g compared to 2009 production level l Min. and max. population growth rates resulted in 7% reduced and 14% increased ΣE g, respectively, compared to the moderate population growth rate Starting LFG collection after two years can increase ΣE g by 32% compared to base case Operating all landfills as bioreactor landfills can increase ΣE g by 57% compared to base case

27 Results - Cont d Increasing the statewide recycle ratio to 65% or 75% by 2020 will reduce ΣE g by 3% or 8%, respectively, compared to base case Applying improved methods to increase LFG collection at the 75% recycle ratio scenario can increase ΣE g by 35% compared to base case Furthermore, improving energy conversion and energy generation efficiencies can increase ΣE g by a factor of 2.5 compared to base case

28 Future Tasks Phase 3: Model costs and benefits of Florida LFGTE potential with and without a Cap-&-Trade program under different scenarios o o Costs: Construction, Operation & maintenance, Leachate treatment, Closure and Post-closure costs Benefits: Air space recovery, Energy generation, Carbon credits, Tax credits

29 Future Tasks Phase 3: Economic sensitivity analysis o o o o To what size of landfill is it economically feasible to operate a LFGTE facility (compare total cost, TC, to total benefits, TB, under each scenario for TB>TC) What is the profit threshold for different parameters (gas collection efficiency, energy generation efficiency,...)? What is the marginal benefit, MB, and marginal cost, MC, of increasing gas collection efficiency or going to 75% recycle goal? What is the marginal rate of substitution, MRS, for bundled parameters, e.g. gas collection efficiency and energy generation efficiency?

30 Questions?