optimiztion of development of district heating system andrzej reŃski phd department of power...
Post on 21-Dec-2015
218 views
TRANSCRIPT
OPTIMIZTION OF DEVELOPMENT OF DISTRICT HEATING SYSTEM
ANDRZEJ REŃSKI PhD
Department of Power Engineering
TECHNICAL UNIVERSITY of GDANSK
Introduction
The share of district heat demand in domestic district heating systems
Projections of meeting the demand on district heat
The role of combined heat and power production (cogeneration)
The share of meeting the demand on district heat(industrial utilities are excluded)
Professional CHPs 19,0CHPs & industrial heating plants 4,0Municipal boilers 11,0 Local boilers (solid fuels) 26,5Local boilers (fuel oil, gas) 6,0Accumulative electric heating systems 0,5Coal furnaces 33,0 100,0 %
The projection of demand on district heat in the reference scenario (Poland)
0
200
400
600
800
1000
1200
1400
1997 2005 2010 2015 2020
Residential sector
Industry
Other consumption
PJ
Scope of the research work
Presentation of research methods to anable effectivness optimization of a large DHS
Presentation of computer based software to analyze and optimize complex DHS
Main thesis and goals
Small increase of heat demand or even demand decrease in large DHS as a result of modernizations on demand side
Main thesis and goals
The first issue to protect competitiveness of the DHS with other heat supply systems is modernization of DHS but usually not completely new investments
Main thesis and goals
Development of centralized heat sources should go towards higher level of heat and electricity cogeneration and effectiveness of primary energy use
Energy Supply and DHS
Definition and parameters of DHS
Heat supply from DHS to consumers in residential sector on background of other heat supply systems
Structures of DHS in large urban areas
Definition of DHS
REGION
CHP – combined heat and power plantMP – main pipelines (transport line)SR – distribution system
SR
MP
CHP
tz tp
pz pp
Gz Gp
consumer
house substation
DHS share in heat supply to consumers in residential sector
DHS34 %
solid fuel boiler stations26,5 %
oil or gas-fired boiler stations
6 %
electric heating with
accumulation 0,5 %
coal-fired furnaces
33 %
DHS share in heat supply to consumers in residential sector in cities
coal-fired furnaces 25,9%
solid fuel boiler stations17,4%
DHS53%
oil or gas-fired boiler stations
3%
electric heating with
accumulation 0,7%
Hierarchic structure of DHS
CHP2
CHP1
Tasks of the DHS optimization
Medium term optimization (month)
Short term optimization (one day)
A few year optimization
Strategic planning of the development
Short term optimization
Time horizon: 1 day ÷ 1 week
Expected effects: load timetable of heat generation units
flows of water in distribution net
pressures in distribution net
Medium term optimization
Time horizon: 1 week ÷ 1 year
Expected effects: primary energy demand plans of starts and stops of heat source and distribution net timetable of repairsdistribution of heat and power costs
A few year optimization
Time horizon : 1 year ÷ 5 years
Expected effects: primary energy demand financial schedules
timetable of repairs distribution of heat and power costs polluting emissions
from heat sources
Strategic planning of the development
Time horizon : 5 years ÷ 20 years
Expected effects: primary energy demand financial schedules
timetable of repairs distribution of heat and power costs polluting emissions
from heat sources power and energy
balances investment plans
Algorithms for the choice of optimal parameters in a developing DHS
Cogeneration factor
Supply water temperature in the transport system
Operation at constant or sliding outflow temperature
Methods for the choice of large energy supply systems structure
Multivariant analysis
Mathematical programming (linear, mixed integer programming)
Optimization criterion of DHS development
Criterions classic:
unit heat supply cost annual costs of DHS
modern: net present value method ( NPV ) internal rate of return method ( IRR )
Proposed optimization criterion : objective function as discounted sum of total DHS costs
taking into account supply and demand sides of the system
Choice of optimal parameters in DHS with condensing power plant
Hot water temperature at the plant outlet
Operation at constant or sliding outflow temperature of hot water
Technical capabilities of applying power plants in district heating systems
The scale of activities undertaken in Poland Electric power plants cooperating with existing
(or future) heating systems Modification of heating system in power plant
is necessary and changes in turbine system are required
Condensing Power Plant cooperating with peak load boiler in district heating
system
EK – electric power plant as base load heat source; ZS – peak load boiler; t1, t2 – temperature of water in
main pipelines: supply and return
Heat supply system
t 1
EK t 1s
t 2st 2
EK
ZS
ZSEK
ZS
The unit with condensing turbine adapted to heat production
NPS PWP
Schematic heat flow diagram of power plant
Permanent annual curve of heat output q and outflow and return flow temperatures t1,, t2 at sliding operation for the supply region
1000 2000 3000 4000 5000 6000 7000 8000 8760 h/a
τ00
2020
40
5060
80
100
120125
40
60
80
100
50
t1, t2
t2
t 1
EK
t 1
EK
t 1
ZS
t
t1s
t2s
Characterization of supply region and heat transport system
%
oC
q
q
Economic criterion and methodology of heat parameters calculation
Specific cost of heat supplied to the end-consumers
where:
ss
r
r
r
TQ3,6
K
W
Kk
PLN/GJ
annual delivery costs, PLN/yr
k min
K r annual amount of delivered heat, GJ/yrWr
Qs peak load in MJ/s and annual peak load utilization period in
hrs/yr
.,Ts
Elements of objective function
PLN/GJ where:
Specific costs:
K(t) = kEK + kEK + kCC + kMP + kZS + kZS
difference between supply and return water temperatures during peak load, K
P A Q W
kMP = kL + kP + kstr where:
t
kEK,P
kEK
A
fixed and variable costs of heat production in condensing power plant
kCC cost of heating unit in power plant
kMP cost of main pipeline including the following:
kL fixed cost of pipeline
kP cost of water pumping station
kstr cost of heat losses due to pipeline transmission
kZS , kZS
Q W
fixed and variable cost of heat production in peak load boiler
Costs of heat production in power plants
Specific fixed cost:
where:
kP =
es kSE rcSE
3,6 Ts
relative electrical power loss in condensing power plant, MW/MW
n s PLN/GJ
es
kSE
n
specific capital cost of equivalent power plant in electrical power system, PLN/MW
the rate of fixed costs for equivalent power plant , 1/yrrcSE
s cogeneration factor
Ts annual peak load utilization period, hrs/yr
Costs of heat production in power plants
Specific variable cost:
where:
kEK = 103
eA kSE
EK Wu
relative electricity loss in condensing power plant, MWh/(MWh)
B A PLN/GJ
eA
kSE
B
standard fuel (coal equivalent) price for equivalent power plant, PLN/t ce
A annual cogeneration factor
EK overall efficiency of equivalent power plant
Wu calorific value for standard fuel, kJ/kg ce
Hot water temperature
topt = 0,731
where :
B2
distance of heat transmission in main pipeline, m
B1
0,623
( ) L0,623
Qs0,246
K
L
Qs peak load of heat power, MJ/s
B1, B2 constants for heating system and dependent
on method of operation
Sample calculation results
Optimal temperature difference at sliding and constant operation
102030
50
80
100
150
10 20 30 40 km
L
K t
100 MJ/s
100 MJ/s500 MJ/s
1000 MJ/s500 MJ/s
1000 MJ/s
32
sliding operationconstant operation
First conclussions
Results of sample calculations: lower level of temeprature for supply water in
main pipeline lower temperature of hot water when constant
operation occurs
Comments: condensing power plants are competitive heat
source in district heating systems detailed research in specifying transmission and
distribution losses is justified tThe role of cogeneration factor
Proposed optimization criterion in research of the developing DHS
min)(
)()(
)1(
,,,,,,
,,,,
m b
cmbi
o
vmoi
cmoi
o or
vori
cori
voi
coi
i
i CCC
CCCC
pC
Variables: - constant and variable costs in year i
Bottom indexes / sets: i – years; o, or – units; m – modernizations; b – construction technologies of buildings; r – consumers regions; mp – sections of main pipe lines
vi
ci CC ,
Constraints
Variables:
mp
MP s,mp i,
r b or
sror,i,
ods,rb,i,
wcs,r
SRs,r
z
szz i, QQQQQQ
mp
MPmp i,
r b orr or, i,
odr b, i,r
z
zz i, WWWWW wc
rSR W
QQ , - power and loss of power
- annual heat production and heat lossesWW ,
Uppper indexes define parts of DHS (distribution net, house substations, main pipe lines, consumers)
Scheme of DHS balance
region
WEC = Wod + Wod + WSR + WMP
QEC = Qod + Qod + QSR + QMP
Qod
Wod
SR
MP
CHP
losses:QMP
WMP
Qr, Wr
QSR
WSR
Qwc
Wwc
consumer
QEC, WEC
house substation Qod
Wod
Optimization of modernization and development of DHS
Small CHP
Heat only boilers
Individ. sources.
DSM
Heat demand
from DHS
Heat demand forecasts
demandside
DHS
(Supply side)
Modernizations and development technologies in DHS
A
B
C
CI
Supply and demand optimizationmin ( ... )C A C B C C C I C II C III C IV
CII
CIII
CIVCC
CB
CA
Algorithm of optimization of DHS development
General characteristic of mathematical models of basic DHS components model of centralized heat source model of transport and distribution net model of demand structures model of decentralized heat sources
Methodology Computer tool
Simplified heat flow diagram of combined heat and power unit BC-50 with back-pressure turbine TP and steam boiler
SB in cooperation with peak load water boiler WB
σ Ael-
WpWs- Wp
Wsb
Bs
Wod
TP
Bp
Wpb
WB
Ep
p
Es
s
W, Ael-,E – variablesBW, ξ, σ – objective function parameters
SBp
Objective function component on supply side
z
s
eksi,
ksz,i,
ensi,
nsz,i,i
elzi,i
elzi,
f
o
ezoz,i,f,oz,i,
p
oz,i,soz,i,
ezoz,i,f,oz,i,
p
oz,i,
fi,zmi
kEkEkAkA
kbWW
kbW
k
K
AA
ss
Wsss
pop
Wpp
B
Development/modernization technology within centralized heat source: combined steam and
gas (stag) cogeneration plant
TP
ε
σ
Ael-
ε
Bp
Wpb
TG
HRSG
Wp Ws-Wp
Wsb
Bs
WB
Wod
ξ
ξ
Simplified view of district heating system presenting moderniziation activities
-
distribution network
buildings b
House substation wc
Main pipeline MP
CHP
DHS
CHP Plant
Development technology in the decentralized district heating system: simplified view of small unit with
gas engine cooperating with peak load boiler
σ
)( elnA
Bp
cp
Es
s Bs
cs
Wp
WodsW
Modernization activities on the demand side
e2 = 240e1 = 180
e3 = 300 kWh/(m2·yr)
120180
180
120
costsEnergy savings
Modernization technologies:-roof and wall insulation -windows replacement-thermostatic valves- heat consumption measurement on the demand side-complex thermo-renovation
a1,b1a2,b2
a3,b3
Am1
Am2
Am3
a,b,e,Δem,Am– parameters & variables concerning demand devices and modernization activities
Δem
Objective function component on demand side
b m
ii'
i'm,br,,i'
maxm,b
ii'
i'br,i,rb,
maxb
odri, AeaΔaeW
155
11000/1
Optimization problem
If the objective function )(xf and constraints mi ,...,2,1,)(xigare linear functions, and xj are integer varaibles, then the objective function is
minimized:
minx )(f
under constraints
Jx
bxA
where: J – vectors with real and integer elements A - matrix
and it is a mixed integer programming problem
mn RbRx ,,nm
Flow chart of calculations
Data, charts Initial value
Defining development options
1j
0c1k
T&D DEMAND
NO
NO
YES
YES
Results
SUPPLY
1j:j
1k:k
k0 cc
c0k cc
nj
Example of district heating system optimization algorithm
Basic assumptions and input data – calculations for development and modernization technology options
Scope of research – development options are analyzed Option no. 1: modernization activities
undertaken only for centralized heat sources Option no. 2: modernization activities
undertaken for centralized heat sources and for transmission and distribution system
Example of district heating system optimization algorithm
Option no. 3: modernization activities undertaken in whole supply system and on the demand side (thermo-renovation in buildings), at the level of 10% of whole dwelling resources, in the base year
Option no. 4: modernization activities undertaken in whole supply system and on the demand side (thermo-renovation in buildings), at the level of 20% of whole dwelling resources, in the base year
The model of district heating system for the agglomeration
CHP
CR1CR2
ZR
ZR
source
unit
Permanent annual curve of heat output for given centralised heat source with peak capacity Qsz=100 MJ/s, and cogeneration factor =0,5
0,0
20,0
40,0
60,0
80,0
100,0
0 1000 2000 3000 4000 5000 6000 7000 8000 9000
Qpz=Qsz/2
Qp=QsQpz/Qsz
Qsz=100 MJ/s
Qs
Wp
Ws-Wp
Cumulative annual heat production curve for given centralized heat source with peak capacity Qsz=100 MJ/s and for unit with capacity Qs=30 MJ/s
W=f(Q)
0,0
50,0
100,0
150,0
200,0
250,0
300,0
0,0 20,0 40,0 60,0 80,0 100,0
Q
GWh/aW
MJ/s
source
unit
Option no. 1 system development: modernization of centralized heat source
OPCJA 1
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
BC50-I WP70-II WP70-III WP70-I WP70-IB Rozpr
OPCJA 1
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
Budynki Rozdział Przesył Rozpr
Option no. 4 system development: modernization of whole supply system along with demand side modernization (thermo-renovation in buildings)
OPCJA 4
0,0
50,0
100,0
150,0
200,0
250,0
300,0
350,0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
BC50-I WP70-II WP70-IIC WP70-I WP70-ID WP70-III
OPCJA 4
0
50
100
150
200
250
300
350
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
Budynki Rozdział Przesył
Modified option no. 4 – system development under following conditions: fuel prices lowered to 60% of baseline price level, electricity prices lowered to 80% of baseline price level
OPCJA 4b
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
BC50-I WP70-II WP70-IIB WP70-III WP70-I WP70-IB Rozpr
OPCJA 4b
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Budynki Rozdział Przesył Rozpr
Modified option no. 4: system development –share of annual thermo-renovation activities on the demand side increased to 60%
OPCJA 4c
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
BC50-I WP70-II WP70-IIC WP70-III WP70-I Rozpr
OPCJA 4c
0
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
MJ/
s
Budynki Rozdział Przesył Rozpr
Conclusions – the analysis
The most effective option is based on complex undertaking of modernization and development activities with regard to whole elements of examined supply system
Changes on the demand side resulting from modernization activities have impact on the formulation of optimization criterion on the demand side
Modernization activities on the demand side anticipate efforts aiming for heat source extension (they are more effective than activities undertaken in the whole source of heat)
Conclusions – the analysis
The level of investment has great impact on modernization/development technology choice
New peak units are introduced to the system prior to new base loaded units, and the sequence of introducing and loading peak units depends on techno-economic factors of these utilities
The method enables to calculate optimal value of cogeneration factor for centralized source in the following years of considered time horizon
Summary and prospects
The essential advantage of this method is that it includes both supply and demand sides of heat supply system functioning under market conditions to large extent
The usefulness of modular structure applied for the mathematical model and of the structure of computer application program including demand side module, transmission and distribution (T&D) system module, and supply side module
Applying GAMS system ver. 2.25 and running the sample model using mixed integer programming (MIP)
The elaborated mathematical model is a kind of compromise between the exact image of actual structures and relationships, and the solution providing effective obtaining of the results and their easy interpretation
Summary and prospects
New formulation of objective function Proposed optimization criterion enables to calculate
specific heat delivery cost per unit of product from the examined modernized or developed supply system in considered time horizon, which makes model formulation and assumed input data a subject to revision
One of the most significant aspects of this research is to proof that the essential impact of the demand side on the obtained solution exists (solution means the choice of optimal development strategy for the system supplying heat to agglomeration)
Summary and prospects
Useful tool for many companies that are engaged in heat supply planning or concerned with investment in heat generation utilities
Proving of slight increase in peak load of heat supply system in examined time horizon; after initial decrease in cogeneration, gradual increase occurs
Among modernization/development activities, the most effective are in order: 1) activities based on thermo-renovation in buildings, 2) modernization activities of heat generation units and T&D systems, and 3) activities related to investments in new base loaded utilities supplying heat