ERASMUS INTENSIVE PROGRAMME – EQUI-AGRI
Efficiency and Equity Trade Off In European AgroEnergy Districts
Planning the value chain:
approaches to the techno-economical efficiency
Monteleone M. , Cammerino A.R.B., Garofalo P., Kami Dlivand M.
STAR-AgroEnergy Research Group, University of Foggia (IT)
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
SYLLABUS
ERASMUS INTENSIVE PROGRAMME – EQUI-AGRI
Efficiency and Equity Trade Off In European AgroEnergy Districts
1 - THE CONCEPT OF PRODUCTIVE EFFICIENCY
2 - HOW TECHNOLOGY AND MARKET INTERACT
3 - DO MARKET INFLUENCE THE RESOURCE USE ?
4 - FIRST SIMULATION MODEL: THE JEVON PARADOX
5 - SECOND SIMULATION MODEL: THE LOW OF DIMISHING RETURN
6 - FINAL CONSIDERATIONS AND CONCLUTION
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
THE JEVON’S PARADOX: WHAT WAS OBSERVED



As technology progresses, the increase
in efficiency with which a resource is
used tends to increase (rather than
decrease) the rate of consumption of
that resource
Technological improvements that
increased the efficiency of coal-use led
to the increased consumption of coal
in a wide range of industries
He argued that, contrary to common
intuition, technological improvements
could not be relied upon to reduce
fuel consumption
Erasmus Intensive Programme EQUI-AGRI
The English economist
William Stanley Jevons (1865)
Foggia, 04/07/2014
THE JEVON’S PARADOX: THE MODEL
Investment
AGRICULTURAL
CAPITAL
Lifetime
Depreciation
Technical
Efficiency
Investment
Rate
Rg
Price
Profit
Rigeneration
AGRICULTURAL
RESOURCES
Agricultural
Production
Regeneration
Rate
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
THE JEVON’S PARADOX: THE MODEL STRUCTURE
Investment
AGRICULTURAL
CAPITAL
Lifetime
Depreciation
Investment
Rate
Technical
Efficiency
Two renewable
stocks are
considered: one is
a technological
capital, the other is
a natural resource
AGRICULTURAL
RESOURCES
Rigeneration
Agricultural
Production
Regeneration
Rate
Erasmus Intensive Programme EQUI-AGRI
Each stock is
characterized by
two flux rates: one
is an input, the
other is an output
Foggia, 04/07/2014
THE JEVON’S PARADOX: THE MODEL STRUCTURE
TECHNICAL EFFICIENCY = ((1+EXP(-0.01*(AGRICULTURAL_RESOURCES-Rg)))^(-1))
PRICE= 1.2+8.8*EXP(-3.5*TECHNICAL EFFICIENCY)
Erasmus Intensive Programme EQUI-AGRI
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THE JEVON’S PARADOX: THE MODEL BEHAVIOUR
RG = 800
RG = 700
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
THE JEVON’S PARADOX: THE MODEL BEHAVIOUR
RG = 600
RG = 500
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
THE JEVON’S PARADOX: THE MODEL BEHAVIOUR
RG = 400
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
THE JEVON’S PARADOX: THE EXPLANATION



The issue has been re-examined by
modern economists studying the so
called “rebound effects” from
improved energy efficiency
In addition to reducing the amount
needed for a given use, improved
efficiency lowers the relative cost of
using a resource, which tends to
increase the quantity of the resource
demanded, potentially counteracting
any savings from increased efficiency
Additionally, increased efficiency
accelerates economic growth, further
increasing the demand for resources
Erasmus Intensive Programme EQUI-AGRI
The English economist
William Stanley Jevons (1865)
Foggia, 04/07/2014
SUSTAINABILITY CRITERIA
ENERGY
WATER
NITROGEN
CROP PRODUCTIVITY
FOOD
Erasmus Intensive Programme EQUI-AGRI
BIOMASS
Foggia, 04/07/2014
SUSTAINABILITY CRITERIA



If biomass energy is to be used as a substitute of fossil fuels, the
energy provided should be clearly much larger than the fossil
energy needed to produce it
Determine the overall energy balance means taking into
account both the energy required to produce the biomass
(agricultural phase) and the energy demanded to convert the
biomass feedstock into energy (industrial phase)
Detect quantitatively the optimum agro-technical energy inputs
(amount of fertilizer and irrigation supplied to an energy crop)
in order to satisfy alternatively one of the following objective
functions:


maximum energy gain:
ΔEn = Eout - Ein
maximum economic return:
ΔEc = Revenues - Costs
Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
EFFICIENT USE OF AGRICULTURAL RESOURCES


The “law of diminishing marginal returns” is stating that, as the
quantity of a productive factor increases, the marginal (or perunit) product of an additional amount of the same factor will
decrease.
Another way to express the same meaning is to assume that the
productivity of a variable input factor declines as more is used
(in the short-run production and holding other inputs fixed)

 

Y  Ymax  1  exp  
 N 
 Ymax


Erasmus Intensive Programme EQUI-AGRI
Foggia, 04/07/2014
EFFICIENT USE OF AGRICULTURAL RESOURCES

 

Y  Ymax  1  exp  
 N 
 Ymax


Considering the effect of an
increasing availability of
irrigation water
Ymax =  * W
Erasmus Intensive Programme EQUI-AGRI
Foggia, 03/07/2014
EFFICIENT USE OF AGRICULTURAL RESOURCES

The simple empirical model can be further elaborated by
converting the physical amounts of both biomass output and
agro-technical inputs into their corresponding energy content
𝐸𝑜𝑢𝑡 = 𝐸𝑚𝑎𝑥 ∗ 1 − exp −
𝜀
𝐸𝑚𝑎𝑥
∗ 𝐸𝑖𝑛 − 𝐸0
Ein = N eN + W e W
OPTIMAL USE OF AGRICULTURAL RESOURCES
Energy Gain:
DE = Eout – Ein
DEmax= Eout – E*in
Energy Ratio:

= Eout / Ein
max = Eout / E °in
OPTIMAL USE OF AGRICULTURAL RESOURCES
Eout =Emax 1-exp E*out
E*in
E*app
ε
Emax
𝜂𝑐𝑢𝑙𝑡 Ein -E0
OPTIMAL USE OF AGRICULTURAL RESOURCES
Max Benefit
E*in
dC / dE = dR / dE
OPTIMAL USE OF AGRICULTURAL RESOURCES
Three set of parameters have been identified:
a) physiological and genetic features of the energy crops;
 Emax (GJ/ha) is the horizontal asymptote of maximum energy
production and quantifies the energy potential of the crop
  (-) is the initial energy conversion efficiency of the considered
crop, in other words, the slope of the curve at Eout = 0
b) technological efficiencies :
 cult (-) is the technological efficiency of the crop cultivation
(agricultural phase)
 conv (-) is the technological efficiency of the biomass-to-energy
conversion (industrial phase)
 E0 (GJ/ha) is the minimum amount of energy inputs required
for the basic crop operations (such as tillage, sowing, herbicide
spraying, etc.)
OPTIMAL USE OF AGRICULTURAL RESOURCES
Three set of parameters have been identified:
c) economic and market conditions:
 PE (€/GJ) is the market price of electricity
 UCcult (€/GJ) is the cost of the energy input unit in the
cultivation phase
 UCconv (€/GJ) is the cost of the energy output unit in the
conversion process
Technical and economic coefficients
assumed for the model
LHV - Lower Heating Value
Biomass dry matter
Biogas Yield
Methane content
Electricity Conversion Efficiency
Gross Electricity Yield
Process Energy Required
Energy Yield (for sale)
Overall conversion efficiency
Comprehensive Feed-In Tariff
Revenues from electricity sales
Unitary cost of the energy agricultural input
Cost of Biogas Plant
Investment Costs
Maintenance Costs
Cost CHP Unit
Investment Costs
Maintenance Costs
Unitary cost of energy conversion (total)
Maximum Biomass Cost
Units
€/kWh
€/GJ
€/t
€/GJ
Biomass
SNFL
16,9
0,35
180
0,53
0,36
328,65
0,10
295,79
1,06
0,18
0,19
50,00
47,33
48,95
Biomass
SRGH
16,9
0,30
200
0,53
0,36
365,17
0,10
328,65
1,18
0,23
0,19
50,00
52,58
47,79
€/t
€/t
12,00
2,10
12,00
2,10
€/t
€/t
€/t
€/GJ
€/t
€/GJ
3,90
5,20
23,20
21,79
24,13
22,66
3,90
5,20
23,20
19,61
29,38
24,84
GJ/t
m3/t
kWh/t
kWh/t
GJ/t
AGROENERGY CHAIN RESOURCE OPTIMIZATION
Max Benefit
E*in
TECHNICAL OPTIMIZATION:
*
Ein
=
Emax
E0 +
* ln ε ηcult
ε ηcult
ECONOMIC OPTIMIZATION:
*
Ein
=
Emax
PE - UCconv
E0 +
* ln ε ηcult ηconv
ε ηcult
UCcult
AGROENERGY CHAIN RESOURCE OPTIMIZATION
SUNFLOWER (SNFL)
SORGHUM (SRGH)
W
W
N
N
Mathematical fitting of the proposed model to the energy yield
data obtained from the simulation of both sunflower and sorghum.
The same model was applied to fit the unique productive
“frontier” for each crop (green curves), defining the boundary
conditions of maximum energy output from the combined use of
the two productive factors (nitrogen and irrigation water)
AGROENERGY CHAIN RESOURCE OPTIMIZATION
SUNFLOWER (SNFL)
SORGHUM (SRGH)
W
W
N
Parameters
Emax

E0
Technical E*in
Economic E*in
Unit
GJ/ha
GJ/ha
GJ/ha
GJ/ha
N
Sunflower
111,72
53,13
5
13.35
8,59
Sorghum
153,33
45,33
5
17.90
11,40
AGROENERGY CHAIN RESOURCE OPTIMIZATION
Sensitivity Analysis on the value of the optimal input
(E*in)
Model
Parameters
Emax

E0
cult
conv
PE
CUcult
CUconv
Unit
-
Reference
value
150.00
50.00
10%
Increase
5.11
-2.56
10%
Reduction
-5.69
2.67
GJ/Ha
5.00
4.41
-4.84
-
1.00
-
7.30
-
0.25
2.57
-3.00
€/GJ
50.00
4.35
-5.76
€/GJ
50.00
-2.71
2.83
€/GJ
22.00
-2.32
2.05
GJ/ha
AGROENERGY CHAIN RESOURCE OPTIMIZATION
Emax

E0
 cult
 conv
Energy Price
Energy Conv. Costs
Energy Colt. Costs
Ein Optimal
GREEN LINE
150
RED LINE
100
25
5,00
1
0,25
50
22
45
13,15
50
5,00
1
0,25
50
22
45
9,10
FINAL CONSIDERATIONS AND CONCLUSION
 The crop energy inputs should be optimized with
reference to the overall bioenergy chain conditions,
from the field to the market, passing through the
biomass facility
 Along the value chain, influential effects are exerted
downstream (from the top to the bottom of the chain)
but also in the opposite direction (rebound effect).
These latter conditions are frequently ignored but it
was proved they are of the uppermost importance
FINAL CONSIDERATIONS AND CONCLUSION
 Market conditions are of great influence in
determining the optimal cultivation energy input (E*
 Highly expansive market conditions allow an
in)
acceleration of the production processes and an
increase in the agro-technical inputs. These conditions
are characterized by a strong growth in the price
regimes of the energy products and a decrease in the
production costs (both agricultural and industrial
ones)
 The reverse occurs in case of recessionary market
conditions, with product prices in stagnation and a
general trend to an increase in the productive cost
profiles
ERASMUS INTENSIVE PROGRAMME – EQUI-AGRI
Efficiency and Equity Trade Off In European AgroEnergy Districts
Thank you very much
for your kind attention
prof. Massimo Monteleone
University of Foggia
[email protected]
www.star-agroenergy.eu
Erasmus Intensive Programme EQUI-AGRI
Foggia, 03/07/2014