OPTIMIZTION OF DEVELOPMENT OF DISTRICT HEATING SYSTEM

1
OPTIMIZTION OF DEVELOPMENT OF DISTRICT HEATING
SYSTEM

• ANDRZEJ RENSKI PhD
• Department of Power Engineering
• TECHNICAL UNIVERSITY of GDANSK

2
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)

3
Professional CHPs 19,0 CHPs industrial
heating plants 4,0 Municipal boilers 11,0
Local boilers (solid fuels) 26,5 Local boilers
(fuel oil, gas) 6,0 Accumulative electric
heating systems 0,5 Coal furnaces 33,0

100,0
The share of meeting the demand on district
heat (industrial utilities are excluded)
4
The projection of demand on district heat in the
reference scenario (Poland)
PJ
1400
1200
1000
Other consumption
800
Industry
600
400
Residential sector
200
0
1997
2005
2010
2015
2020
5
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

6
Main thesis and goals

• Small increase of heat demand or even demand
  decrease in large DHS as a result of
  modernizations on demand side

7
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

8
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

9
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

10
Definition of DHS
CHP
REGION
tz tp pz pp Gz Gp
consumer
SR
house substation
CHP combined heat and power plant MP main
pipelines (transport line) SR distribution
system
11
DHS share in heat supply to consumers in
residential sector
12
DHS share in heat supply to consumers in
residential sector in cities
13
Hierarchic structure of DHS
CHP2
CHP1
14
Tasks of the DHS optimization

• Short term optimization (one day)

• Medium term optimization (month)

• A few year optimization

• Strategic planning of the development

15
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

16
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 repairs ?distribution of
  heat and power costs

17
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

18
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

19
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

20
Methods for the choice of large energy supply
systems structure

• Multivariant analysis
• Mathematical programming (linear, mixed integer
  programming)

21
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

22
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

23
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

24
Condensing Power Plant cooperating with peak load
boiler in district heating system
t 1s
EK
t 2s
t 2
Heat supply 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
25
Schematic heat flow diagram of power plant
WP
S
P
NP
The unit with condensing turbine adapted to heat
production
26
Permanent annual curve of heat output q and
outflow and return flow temperatures t1,, t2
at sliding operation for the supply region
Characterization of supply region and heat
transport system
oC
t1, t2
t1s
125
q
120

100
100
?t
80
80
q
60
60
t2s
50
50
t2
40
40
20
20
t
0
0
1000
2000
3000
4000
5000
6000
7000
8000
h/a
8760
27
Economic criterion and methodology of heat
parameters calculation
Specific cost of heat supplied to the
end-consumers
K
K
r
r


k
PLN/GJ



W
T
Q
3,6
r
s
s
k ? min
where
K r

• annual delivery costs, PLN/yr

• annual amount of delivered heat, GJ/yr

Wr
.
Qs
,Ts

• peak load in MJ/s and annual peak load
  utilization period in hrs/yr

28
Elements of objective function
Specific costs
PLN/GJ
K(?t) kEK kEK kCC kMP kZS kZS
P
A
Q
W
where
kMP kL kP kstr
where
?t

• difference between supply and return water
  temperatures during peak load, K

kEK,
kEK

• fixed and variable costs of heat production in
  condensing power plant

P
A
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

• fixed and variable cost of heat production in
  peak load boiler

Q
W
29
Costs of heat production in power plants
Specific fixed cost
es ? kSE ? rcSE
n
kP
?s
PLN/GJ
3,6 Ts
where
es

• relative electrical power loss in condensing
  power plant, MW/MW

kSE

• specific capital cost of equivalent power plant
  in electrical power system, PLN/MW

n
rcSE

• the rate of fixed costs for equivalent power
  plant , 1/yr

?s

• cogeneration factor

Ts

• annual peak load utilization period, hrs/yr

30
Costs of heat production in power plants
Specific variable cost
eA ? kSE
B
kEK 103
?A
PLN/GJ
?EK ? Wu
where
eA

• relative electricity loss in condensing power
  plant, MW?h/(MW?h)

kSE

• standard fuel (coal equivalent) price for
  equivalent power plant, PLN/t ce

B
?A

• annual cogeneration factor

?EK

• overall efficiency of equivalent power plant

Wu

• calorific value for standard fuel, kJ/kg ce

31
Hot water temperature
0,623
B2
L0,623
(
)
?topt 0,731
K
?
?
B1
Qs0,246
where

• distance of heat transmission in main pipeline, m

L
?
Qs

• peak load of heat power, MJ/s

• constants for heating system and dependent on
  method of operation

B1, B2
32
Sample calculation results
sliding operation
K
?t
constant operation
150
100 MJ/s
100 MJ/s
100
500 MJ/s
80
1000 MJ/s
500 MJ/s
1000 MJ/s
50
30
20
L
10
10
20
30
40
km
Optimal temperature difference at sliding and
constant operation
32
33
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

34
Proposed optimization criterion in research of
the developing DHS
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
35
Constraints

• Variables

- power and loss of power
- annual heat production and heat losses
Uppper indexes define parts of DHS (distribution
net, house substations, main pipe lines,
consumers)
36
Scheme of DHS balance
CHP
QEC, WEC
region
losses ?QMP ?WMP
MP
Qod Wod
consumer
Qr, Wr
SR
house substation
?Qod ?Wod
?QSR ?WSR
?Qwc ?Wwc
WEC Wod ?Wod ?WSR ?WMP QEC Qod ?Qod
?QSR ?QMP
37
Optimization of modernization and development of
DHS
Heat demand forecasts
Small CHP
A
CA
CI
DHS
Heat demand from DHS
CII
CB
Heat only boilers
(Supply side)
B
demand
CIII
side
Individ. sources.
C
CC
CIV
Modernizations and development technologies in DHS
DSM
Supply and demand optimization
38
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

39
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
                                                 
         
 
W, Ael-,E variablesBW, ?, s objective
function parameters
s
TP
Ael-
SB
Bp
Ep
WB
Bs
Es
Wp
Ws- Wp
Wod
40
Objective function component on supply side
41
Development/modernization technology within
centralized heat source combined steam and gas
(stag) cogeneration plant
                                                 
                                                 
 
                                                 
e
?
s Ael-
TP
HRSG
?
WB
 
 
Bs
Wp
Ws-Wp
TG
Bp
Wod
e

42
Simplified view of district heating system
presenting moderniziation activities
                                       
 
distribution network
-
CHP
Main pipeline MP
CHP Plant
House substation wc
buildings b
DHS
43
Development technology in the decentralized
district heating system simplified view of small
unit with gas engine cooperating with peak load
boiler
 
                                               
                                               
                                               
                                             
s
Wp
Bp
Bs
Es
W
s
Wod
44
Modernization activities on the demand side
a,b,e,?em,Am parameters variables concerning
demand devices and modernization activities
120
Am1
a1,b1
?e
m
a2,b2
Am2
120
e1 180

• Modernization technologies
• roof and wall insulation
• windows replacement
• thermostatic valves
• heat consumption measurement on the demand
  side
• complex thermo-renovation

e2 240
180
Am3
a3,b3
180
e3 300 kWh/(m2yr)
Energy savings
costs
45
Objective function component on demand side
46
Optimization problem
and constraints
If the objective function
are linear functions, and xj are integer
varaibles, then the objective function is
minimized
under constraints
where J vectors with real and integer
elements A - matrix and it is a mixed integer
programming problem
47
Flow chart of calculations
Defining development
options
1
j

Data, charts
0

Initial value
c


1
j

j

1
k
DEMAND
TD
SUPPLY


1
k

k
k
0

c
c
NO
0
k
c
c
e
lt
-
c
YES
NO
gt
n
j
YES
Results
48
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

49
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

50
The model of district heating system for the
agglomeration
51
Permanent annual curve of heat output for given
centralised heat source with peak capacity
Qsz100 MJ/s, and cogeneration factor ?0,5
100,0
Qsz100 MJ/s
80,0
60,0
40,0
QpzQsz/2
Qs
Ws-Wp
20,0
QpQsQpz/Qsz
Wp
0,0
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
52
Cumulative annual heat production curve for given
centralized heat source with peak capacity
Qsz100 MJ/s and for unit with capacity Qs30
MJ/s
W
Wf(Q)
GWh/a
300,0
250,0
200,0
150,0
100,0
50,0
Q
0,0
0,0
20,0
40,0
60,0
80,0
100,0
MJ/s
53
Option no. 1 system development modernization
of centralized heat source
54
Option no. 4 system development modernization of
whole supply system along with demand side
modernization (thermo-renovation in buildings)
55
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
56
Modified option no. 4 system development share
of annual thermo-renovation activities on the
demand side increased to 60
57
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)

58
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

59
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 (TD)
  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

60
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)

61
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 TD systems, and 3) activities related to
  investments in new base loaded utilities
  supplying heat