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A Study on Energy-Load Management in Residential and Commercial Sectors
Copyright © IFAC Energy Systems, Management and Economics, Tokyo, Japan 1989
A STUDY ON ENERGY·LOAD MANAGEMENT IN RESIDENTIAL AND COMMERCIAL SECTORS Y. Nishikawa, T. Tezuka, H. Kita, A. Mizutani and N. Uehara Department of Electrical Engineering, Faculty of Engineering, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606, Japan
Abstract. Energy-load management in residential and commercial sectors is defined as syste ms management for improving energy-load characteristics of electricity , town-gas and petroleum refinery products. The energy-load characteristics include load factor and amount of energy consumpion . This study aims to estimate how much the load characteristics of the three sorts of energy can be modified in the residential and commercial secto rs when various measures for energy-load management are introduced in presumably appropriate mann ers. An energy demand model is developed , by utilizing a variety of statistics open to t.he public , IIpOll assumption that the energy-load management causes substitution among various appiU'atous used for space-cooling, space-heating, and water-heating in those sectors. Simulation stlldies by using the model make the change in energy-load characteristics and th en the effect of load management clear quantitatively. Furthermore, practicability of the desirable measures and resultant scenarios is discussed . Keywords. Energy-load management ; energy-demand model; residential and commercial sectors; scenario analysis.
INTRODUCTION
may be useful measures for energy-load management. However, in examining effectiveness of introducing those measures, it is most important to estimate how sensitively energy consumers will respond to them . In this study we assume that the energy-load management causes meaningfully substitution among various apparatus used for thermal demands. Then by taking the Kinki District of Japan as a study area, we investigate the following problem .
The demands of electricity and town-gas in Japan vary with season and time-of-day, primarily due to change of thermal demands , i.e., demands for spacecooling, space-heating and water-heating, in residen tial and commercial sectors. The variations of those energy demands increase cost and instability of the energy supply, recently causing a critical problem especially in the electricity supply system. In future , the energy demand in those sectors is anticipated to increase remarkably. Hence , in planning the energy supply and demand system in Japan , it is very important to examine quantitatively manageability of the energy demand in those sectors.
How much the energy-load characteristics of the three sorts of energy will actually be manageable in the residential and commercial sectors through energy substitution? The Kinki District , which includes Osaka, Kyoto and Kobe cities, is the second most active and densely inhabited area in Japan. It consumes 17 percents of electricity and 31 percents of town-gas of the whole Japan . Particularly in this district , the peak load of electricity is sharpened extraordinarily by the spacecooling demand in summer. Hence this district is considered appropriate as the study area.
A ce rtain measure, a time-of-use rate for instance , has been enforced as a test in Japan , as well as in U.S.A. and some European coun tries, in order to improve the load factor of electricity supply. It is called "load management" to improve load factor of electricity demand. However, in an investigation for searching measures of load management in the residential and com mercial sectors, the effect of substitution among three sorts of energy , i.e ., electricity, town-gas and petroleum refinery products including LPG , kerosene and fuel oil, should not be ignored. Furthermore , it is noted that improving the load factor of electricity will affect the demands of the other sorts of energy.
The con ten ts of the paper are as follows . In section 2, briefly explained are the energy rates and various regulations related to energy utilization which have been enforced for load leveling in Japan. Some examples are shown to illustrate the effect of these measures on prevalence of apparatus. Section 3 outlines the structure of the energy demand model developed in this study. This model is built based on various energy-demand estimates, which are discussed in some detail, and aims to investigate how much the energy-load characteristics of the three sorts of energy can be managed by apparatus selection . In section 4, the results of simulations under various conditions are shown. Especially, the effects of spread of heat pump and/or gas-cooler are evaluated quantitatively , and
The "energy-load management" in the residential and commercial sectors is, here, defined as systems management for improving energy-load characteristics of all the three sorts of energy used in those sectors. The energy-load characteristics implies the load factor and the amount of energy consumption in each sort of energy. Various time-of-use energy-rates and/or deregulation policies related to the energy utilization
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Y. Nishikawa et al.
320 the realizability of the preferable scenarios is discussed . Finally, concluding remarks are summarized in section 5.
ON MEASURES FOR LOAD-MANAGEMENT ALREADY ENFORCED IN JAPAN Some measures have been already taken to deal with such problems of load leveling in Japan. In early days, electric power companies made various special contracts with big consumers in order to increase load factor of supply. For example, there is a contract that the consumption in the daytime of summer needs much more payment than usual. Another example is that some consumers should pay much penalty when they violate the contracts related to the peak-kW demand. As for the residential sector, that is, for small consumers, electricity with special discounted rate for midnight use is supplied to the water-heater with storage exclusively. Not only in electricity supply but also in gas supply, some measures for load leveling have been enforced. Recently the price of gas consumed for space-cooling has been set much cheaper than that for the other uses , and the taxes on gas-coolers are also reduced by the government. These measures have much affected prevalence of the proper apparatus. Some examples are such as shown in the following . 1) The gas-coolers, i.e., gas-absorption machine and gas-engine heat-pump, have prevailed in about 80 % of newly-constructed buildings with floorarea more than 3000m 2 2) In recent years, the amount of electricity consumed in buildings has been rapidly increasing due to prevalence of office computers, and hence the maximum kW-value contracted with the power company is getting insufficient in some buildings. It is advantageous for the owners of such buildings to replace an electric cooler with a gas-cooler because of big expense to change the contracts. 3) As mentioned before , an electric water-heater with storage can consume electricity with a special rate for midnight use. But it cannot consume electricity with normal rate in the daytime if it does not have double heaters, one for midnight use and the other for daytime use. This regulation makes the water-heater for double uses expensive and prevent it from prevailing . These interesting observations indicate that energy rates and regulations related to energy utilization may change the load characteristics of the three sorts of energy drastically. Thus, the problem is to estimate how much the energy-load characteristics will be changed. The authors developed an energy demand model particularly for this purpose.
efficiency of apparatus easy. 2) The energy demands are treated in a time division of month . The matter of concern in the energyload management is the characteristics of energy load, especially its peak and off-peak demands. By use of the present model, seasonal changes of the energy demands can be analyzed. In electricity supply, load fluctuation by time-of-day is an important matter as well as that by season . The authors are extending the model to take the time-of-day characteristics of electricity load in{o account. 3) The influences of the climatic factors on the energy demands are considered. The energy demands for air-conditioning and water-heating depend largely on the climatic factors. The model takes atmospheric temperature into consideration as the most significant factor. The model is constructed through the following three procedures: 1) Decomposition of the Energy Demand into Usages Four types of secondary energy are considered, i.e., electricity, town-gas , LPG and kerosene. The kerosene includes fuel-oil in the following. The data sources of these energy demands are the monthly demands for electricity and town-gas, the annual demands for LPG and kerosene and the monthly residential expenditures for these sorts of energy. In the residential sector, solar energy is considered additionally. These energy demands are decomposed into five usages , i.e., space-cooling , space-heating, water-heating, cooking and lighting-and-others based on the seasonal changes of the demands and other informations. 2) Estimation of Stocks In order to obtain basic units of the energy demands, we estimate the number of households and the floor areas of the buildings for commercial use. The decomposed secondary-energy demands must be converted into the final thermal demands. For this conversion, the annual change of the energy efficiency of the air conditioners is also evaluated by estimating the stocks of apparatus. 3) Regression Analysis with Climatic Factors In order to explain the fluctuations of the spacecooling, space-heating and water-heating demands, their regression analysis in terms of the atmospheric temperature is carried out. Cooking and lighting-and-other demands are assumed to have no seasonal changes. Figure 3.1 illustrates schematically the above procedures , and TABLE 3.1 summarizes the substitutabilities among apparatus considered in the model. In the following , each sub model is described briefly. [Residential Sector]
ENERGY-DEMAND MODEL In order to investigate the effects of energy substitution in air-conditioning and other usages on energy-load management , we construct an energydemand model in the residential and commercial sectors. The features of the model are as follows : 1) The energy demands are separated in to the final usages, i.e ., space-cooling, space-heating, etc. They are represented in terms of the final thermal loads. It makes considerations of the energy substitution and improvement of the energy
1) Space-Cooling Demand Submodel Recently, in the residential sectors , air conditioners have been spread remarkably . At the same time, their energy efficiencies have been improved drastically after the oil crises. The incremental electricity load in summer is assumed the energy demand for space-cooling, and is converted into the final thermal demand by multiplying energy efficiency of the air-conditioners in stock. The energy demand for space-cooling per air conditioner is taken as a basic unit of the
Energy-load Management
321
4ilI1l
350
~
:c ~
3IiJIl 250
.i::
20il
~
150
~
~
lOO 50
Space-Coo.1 .ins D..-nd.
Cookina Deaand.
Suba ·Jdd
Su-.oc!el
Spac.e-B ••ting D--.nd
Lilhtina a Dthu
Subllod..l
D-.an4 Sut.odel
Water-B ••ting Deaand
0 29 31 33 3S 2S ~ Mean Mexif1lJm Temperature ["Cl
Fig. 3.2. Regression analysis of the residential space-cooling demand. . ~r-------------------~
Sut.odel
Fig. 3.1. Schematic diagram of energy demand model.
..
15
C\J~
TABLE 3.1 Apparatus for Inter-energy Substitution in Residential and Commercial Sectors RESIDENTIAL SECTOR Apparatus
Usage
Energy Substitution
Electric Heat-pump
SC j SHjWH
TGjLPjKE -+ EL
Electromagnetic Cooker
CO
TG j LP -+ EL
.i:: ~
10
~
5
~
o
"
'.
.
~~~~~~~~~~~~
16
18
~
22
24
26
28
30
Mean Temperature ['Cl
COMMERCIAL SECTOR Apparatus
Usage
Energy Substitution
Electric HP with Storage A bsorption Chiller jHP
SC j SH
TG j KE -+ EL
SC j SH SC j SH SC j SH j LO
EL -+ TG j KE EL -+ TG EL -+ TGjKE
Gas-engine HP Co-generation
SC: space cooling, SH: space heating, WH: water heating, CO: cooking , LO: lighting and others EL: electricity , TG: town-gas, LP : liquefied petroleum gas, KE: kerosene
residential space-cooling demand. The submodel of the demand is obtained by a linear regression of the space-cooling demand to the mean maximum atmospheric temperature. See Fig. 3.2. 2) Water-Heating Demand Submodel The electricity demand for water-heating is captured easily because of its contract , i.e. , it is supplied with a special discount in midnight . By using the seasonal change of the water-heating demand in electricity , we separate the demand for this usage from the town-gas , LPG and kerosene demands. The procedure of the separation is mentioned in Appendix A. The amount of solar energy for water-heating is estimated based on the sales of solar heaters. The basic unit of waterheating demand is made by summing these energy demands up , and dividing it by the number of households equipped with baths. The model is obtained by a linear regression of the basic unit to the mean atmospheric temperature. 3) Space-Heating Demand Submodel The energy demands for space-heating consists of the incremental electricity demand in winter and
Fig. 3.3. Regression analysis of the commercial space-cooling demand. remainders of town-gas, LPG and kerosene demands after subtraction of the demands for the water-heating and cooking demands. The electricity demand in winter has been growing remarkably since 1983. We have assumed this growth is owing to use of electric heat pumps for space-heating, and treat it separately from the conventional electricity demand for space-heating because of difference in the energy efficiencies. The energy demand for space-heating per household is taken as a basic unit. The model is obtained by a linear regression of the basic unit to the mean minimum atmospheric temperature. 4) Cooking , Lighting-and-Other Demand Submodels A part of town-gas and LPG demand is treated as the demand for cooking. Its amount is determin ed according to the reference [1]. The base part of the electricity load is assumed to be the demand for lighting and other usages. we assume that th e both demands do not change by season and that their basic units, i.e. , the demands per household grow by constant amounts a year. [Commercial Sector] In this sector , the basic unit of thermal demand is defined as the demand per unit floor area [rn 2] . 1) Space-cooling Demand Submodel The amount of town-gas consumption for spacecooling in the Kinki District is estimated by the town-gas supplier; On the other hand , the electricity demand for space-cooling is estimated by the same procedure as in the residential sector. Then the basic unit of the commercial spacecooling demand is obtained by multiplying the effeciency of apparatus . The result of regressional analysis of this basic unit to monthly mean temperature is shown in Fig3.3 .
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Y. Nishikawa et al. TABLE 3.3 Estimates of Basic Units
TABLE 3.2 Energy-Demand Models for Residential and Commercial Sectors RESIDENTIAL SECTOR
SC
Usage
Model
Unit
Space Cooling Space Heating Water Heating
35.37T.,.. - 906.5
(I)" (2) (2)"
Cooking Lighting & Others
- 21.85 T min + 439.7 -6.69T...... + 334.4 206 + 5.16{y - 1983) 72.5
+ 0.80{y
- 1983)
(2) (2)
(1):[Mcal/month'machine] (2):[Mcal/month 'household]
COMMERCIAL SECTOR Unit
Usage
Model
Space Cooling Space Heating Water Heating
1.44 T ..... n
Cooking Lighting & Others
-
+ 7.58
(3)
-0.16T.....n 18.99
+ 8.03
(3)
+ 1.21{y
(3) - 1986)
(3)
(3):[Mcal/month 'm'] Tma.x:
Tmin : Tf"I\eGn:
y: •
WH CO LO
EL 240 14.3 272 3.3 285
TG
LP
KE
5.4 523 8.8 1551 5.6 554 16.4
40 2.0 599 13.9 316 2.1
1469 82.2 209 57.8
2477 113.9
SO
126
' .
upper : of the residential sector [Mcal/ household,year] lower : of the commercial sector [Meal/ m' year]
District at the year of 2000 are estimated under several scenarios of apparatus selection. Then, the results are analyzed from the view point of energyload management.
(3)'"
25.66
-0.47T.....n
113.86
SH
Total 240 19.7 2203 96.3 2770 77.3 870 18.5 2477 113.9
mean maximum atmospheric temperature of the month. mean minimum atmospheric temperature of the month. mean atmospheric temperature of the month. year.
Demand per air conditioner .
•• Water-heating demand per household equipped with a bath . ... All the models for commercial sector indicate the demands
Process of the Simulation Analysis First , with assumptions of the number of households, the floor area in 2000 etc., the energy demand of each usage is estimated. Then , with assumptions of the shares and efficiencies of apparatus for each usage, the energy demand is distributed to the secondary energies. TABLE 4.1 shows the households and the floor areas in 2000 used in the simulation . The efficiencies of several sorts of heat pumps considered in the simulation is listed in TABLE 4.2. The climatic conditions are assumed as those in an average year. Scenarios
per unit floor area.
The simulation is carried out under the following two scenarios in the residential and comme rcial sectors: 2) Water-heating Demand Submodel, Space-heating Demand Subm'.>del and Cooking Demand Submodel The electiricity demand for space-heating is estimated by evaluating the incremental electricity demand in winter, under the assumption that electricity is not used for water-heating, partly because there is no data about it . Town-gas and LPG demands are decomposed into space-heating, water-heating and cooking usages by almost the same procedure as in the residential sector. The basic unit of cooking is taken from [2]. Kerosene demand, which includes fuel-oil demand, is also decomposed into thermal demands according to [2], because its distribution channel is very complicated and even the monthly demand data is not available. 3) Lighting-and-Other Demand Submodel The base part of the electricity load is assumed to be the demand for this usage as in the residential sector. Formulas of the submodels are shown in TABLE 3.2, and the estimates of basic units are shown in TABLE 3.3. Although some of these estimates are based on the results of various questionaires , most of them are evaluated based on the data source open to the public. Therefore these procedures may be employed by anyone who wants to analyze the energy demand in the residential and commercial sectors in Japan.
[Residential Sector] Standard Scenario Until 2000, selection of the apparatus in recent years continues. The number of ai r condition ers grows at the speed of rec ent years. In 2000, it reaches to two machines per hou se hold . Electricity-Oriented Scenario To compare with the standard scenario , the electricity is preferred to other sorts of energy much more in this scenario. The air conditioners spread more than in the standard scenario ( 2.4 machine paer household in 2000) , too. The electric heat pump has a large share in space- heating demand . Water-heating with electric heat pump is also introduced. [Com mercial sector] Standard Scenario The shares of apparatus in the thermal usages do not change until 2000. These shares are shown in TABLE 4.3. Gas-oriented scenario The gas-absorption machin es a re installed in all of the newly-constructed or reconstructed buildings whose floor areas are more than 3000m 2 This means that the recent trend of gas-cooler installation continues till 2000. Meanfile , the gasengine heat-pumps are used in 10 % of the constructed buildings whose floor areas are less than 3000m 2 • The calculated shares of the apparatus in 2000 is shown in TABLE 4.4. Simulation Results
ENERGY-LOAD CHARACTERISTICS IN FUTURE Based on the energy-demand submodels obtained in the previous section, the energy demands in the Kinki
Simulation results are shown in Fig . 4.1 through 4.6 and also in TABLE 4.5. Seeing the town-gas oriented scenario in TABLE 4.5 , it is observed that
Energy-load Management TABLE 4.1 Households and Floor Areas in 2000 Households [million]
7.56 291.4
323
TABLE 4.3 Share(%) of Apparatus in 1986
(6.38 in 1983) Electric HP Package Type Chilling Unit Gas-absorption Gas-engine HP Gas boiler LPG boiler Oil boiler
(209.6 in 1986)
TABLE 4.2 Energy Efficiencies (COPs) of Apparatus Residential
Space-Cooling Space-Heating Water-Heating
Commercial
Electric HP only for Space Cooling Package Type Air Source 3.26/Water Source 3.56/Chilling Unit Air Source 3.36/Water Source 3.76/Electric HP for both Cooling and Heating Package Type Air Source 2.93/3.38 Water Source 3.20/3.80 Chilling Unit Air Source 3.02/3.72 Water Source 3.76/4.18 Gas Absorption HP 1.02/0.87 Gas Engine HP 1.10/1.50
3.22 2.90 2.90
• The ftrst and the second figures are the COPs for space-cooling and space-heating, respectively.
Electric HP Package Type Chilling Unit Gas-absorption Gas-engine HP Gas boiler LPG boiler Oil boiler
As for the town-gas , increasing the amount of consumption is a matter of more concern than improving the load factor, because the gasdistribution capacity in the Kinki District has still much margin. From this view point, the gas-oriented scenario is considered preferable, and there will be no needs to introduce any new load-management measure to realize this scenario . However, there remain some issues to be examined as follows. 1) The heat pump should be improved to put it into confortable use. 2) A way for increasing gas pressure should be investigated in order to increase the capacity of
WH
34.9 54.1 10.9 0.0 0 0 0
5.7 6.5 4.5 0.0 3.9 1.9 77.5
0 0 3.5 0.0 3.0 18.1 75.4
SC
SH
WH
22.4 34.8 36.4 6.4 0 0 0
3.6 4.2 32.3 6.4 2.5 1.2 49.7
0 0 24.9 6.4 2.1 12.9 53.6
RESIDENTIAL Standard Electricity Oriented
Scenario
LPG
According to some investigations, the ratio , hourly electricity demand at 13:00 I average hourly electricity demand , is about 1.9 in the commercial sector and about 1.1 in the residential sector. Upon use of these values, the decrease of hourly peak demand in Fig. 4.5 is estimated as 4.7 %. This indicates that the prevalence of heat pump in the residential sector does not deteriorate the load factor of electricity so much . It is also interesting that the increase of heat pump in the residential sector compensates the decrease of electricity demand caused by the increase of gas-cooler in the commercial sector.
SH
TABLE 4 5 Energy Demands in 2000
Energy Demand Electricity Town-Gas
the energy substitution between the town-gas and the kerosene is striking. In future the amount of oil production will certainly decrease, but it is difficult to say that this extraordinary substitution is preferable in 2000. However, the fact that the demand of petroleum refinery products can be much reduced naturally, if needed, is important. As for the electricity demand, the monthly maximum demand decreases with increase of the gas-absorption machine. In Fig. 4.3, the monthly peak demand is less than that in the standard scenario of Fig. 4.1 by about 6 %. This indicates that the gas-absorption machine (cooler) can afford much saving of the power plants. In Fig. 4.5, the case where the heat pump prevails in the residential sector, the monthly demand is less than that in Fig. 4.1 by only 2.8 %. But in evaluating the effects of peak electricity load in this sector, the hourly elecricity load pattern should be considered.
SC
Kerosene
Solar
35 .5 21.6 7.6 8.4 1.1
37.5 20.1 7.5 5.5 1.1
COMMERCIAL Standard Town-Gas Oriented 43.5 10.4 4.8 35.4
41.6 28.7 3 .5 23.8
[IO'Meal/ year]
gas distribution. 3) If the decrease of kerosene demand is not preferable, some new apparatus, such as t he absorption machin e consuming kerosene, should be prevailed . CONCLUDING REMARKS In this study a new concept of energy-load management by apparatus substitution is presented , and the amount of change in energy-load characteristics of the three sorts of energy is estimated through modelling and simulations. The results of simulation indicate that there is a nice possibility of preferable change of energy-load cha racteristics, and especially prevalence of the gas-cooler has much potential for load leveling of electricity. The following issues are open to be investigated in future. 1) The hourly energy demand should be taken into the demand model. 2) As prevalence of the heat pump results in drastic changes of the load patterns especially in winter, the effects on the economic load dispatching should be considered. 3) A way to evaluate the simulation results from various aspects should be developed , and the practical measures to realize preferable scenarios should be investigated. ACKNOWLEDGEMENTS This study has been pursued under the grant-in-aid on priority-area research supported by the Ministry of Education , Science and Culture of Japan. The authors express their sincere gratitude to Mr. T.Sera, ,Mr. T.Matsuura, Mr. H.Iwai , Mr. H.Nakagami, Mr. N.Shige, Mr. T.Hayashi, Mr. K.Kawahara and Mr.
324
Y. Nishikawa et al.
A.Kume for their valuable discussions and presenting various data on energy demand, and also to Mr. H. Terada, a graduate student of Kyoto Univ., for his making simulation programs.
,.,._.-"', ',-
~'
6IiB! ----... ---.... --• .,. .. ..-
REFERENCES [lJ Jyukankyo Res. Ins. Inc.,"Statistics of Residential Energy Demand" (1986).(in Japanese) [2] Ins. Energy Economics,"Enquete and Hearing survey on Energy Consumption in Commercial Sector"(1988).(in Japanese)
.......... ----.
50IilIl 4alIiI
30il0
~----;.,,
__
2000
f
11!1!l0
Appendix A Decomposition of Town-gas, LPG and Kerosene Demands The town-gas demand is decomposed into the three usages, i.e., cooking, water-heating and space-heating as follows: 1) The amount of the town-gas demand for cooking is determined according to the reference [1] under the assumption that the demand has no seasonal fluctuation . From the monthly town-gas demand , the demand for cooking are subtracted. 2) Then, the demand for water-heating is estimated. It is assumed that the seasonal change is proportional to that of electricity, and that the demand coincides with the remainder of the towngas demand in step 1) at the month of bottom consumption (usually July or August). 3) The remainder of the town-gas demand, after subtranction of cooking and water-heating demands, is taken as the demand for spaceheating. To LPG and kerosene, the same procedure is adopted except that the the demand for cooking is not considered in the decomposition of the kerosene demand.
01~~~~3~~~5~~~7~~~9~~~I-l~
I'lonth
residential sector: standard scenario commercial sector : gas-oriented scenario
Fig. 4.3. Monthly electricity demand. 71'.1110
....,
6IBl
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50IilIl
~
4alIiI
t:
~
... \
....
\
30il0
.. ",-_...........) ........ ~..... \. __ ... .-~.A" ................ ~
2IlIil0
~./
\
" I
...........
....•.... 'w"''':
3
5
7
9
11
I'lonth
residential sector: standard scenario commercial sector: gas· oriented scenario
Fig. 4.4. Monthly town-gas demand.
801'.0
71'.1110
71'.1110
~~-----------------------,
..................
.............. ...... .....
.•.....•.....
30il0 r·~"·-··-·"·.. ··-"-"':;··_"_"··._ .....
!
1000
:demand in the residential Bector :demand in the commercial sector :demand in the residential and commercial sectors ~.------------------------, 801'.0
••••• K
/
2000 II!I!l0 0~~~~~~~LL~~~~~
I
3
7
5
9
3
11
5
9
7
11
I'lonth
I'lonth
residential sector: standard scenario commercial sector : standard scenario
residential sector: electricity· oriented scenario commercial sector : gas· oriented scenario
Fig. 4.1. Monthly electricity demand .
Fig. 4.5. Monthly electricity demand . 7I!I!l0~----------------------~
6IBl .c
~
~
-
...... ..... """
,
' .......... _ _ .. _ _ .. _
.. _ . . _ .. _ _ _ 4 " .. .,11
--
2000 II!I!l0
.................................................................... 3
5
7
9
11
I'lonth
residential Beet or : standard scenario commercial sector : standard scenario
Fig. 4.2. Monthly town-gas demand.
3
5
9
7
11
I'lonth
residential sector: electricitY 0riented scenario commercial sector : gas· oriented scenario 8
Fig. 4.6. Monthly town-gas demand.
A STUDY ON ENERGY·LOAD MANAGEMENT IN RESIDENTIAL AND COMMERCIAL SECTORS Y. Nishikawa, T. Tezuka, H. Kita, A. Mizutani and N. Uehara Department of Electrical Engineering, Faculty of Engineering, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606, Japan
Abstract. Energy-load management in residential and commercial sectors is defined as syste ms management for improving energy-load characteristics of electricity , town-gas and petroleum refinery products. The energy-load characteristics include load factor and amount of energy consumpion . This study aims to estimate how much the load characteristics of the three sorts of energy can be modified in the residential and commercial secto rs when various measures for energy-load management are introduced in presumably appropriate mann ers. An energy demand model is developed , by utilizing a variety of statistics open to t.he public , IIpOll assumption that the energy-load management causes substitution among various appiU'atous used for space-cooling, space-heating, and water-heating in those sectors. Simulation stlldies by using the model make the change in energy-load characteristics and th en the effect of load management clear quantitatively. Furthermore, practicability of the desirable measures and resultant scenarios is discussed . Keywords. Energy-load management ; energy-demand model; residential and commercial sectors; scenario analysis.
INTRODUCTION
may be useful measures for energy-load management. However, in examining effectiveness of introducing those measures, it is most important to estimate how sensitively energy consumers will respond to them . In this study we assume that the energy-load management causes meaningfully substitution among various apparatus used for thermal demands. Then by taking the Kinki District of Japan as a study area, we investigate the following problem .
The demands of electricity and town-gas in Japan vary with season and time-of-day, primarily due to change of thermal demands , i.e., demands for spacecooling, space-heating and water-heating, in residen tial and commercial sectors. The variations of those energy demands increase cost and instability of the energy supply, recently causing a critical problem especially in the electricity supply system. In future , the energy demand in those sectors is anticipated to increase remarkably. Hence , in planning the energy supply and demand system in Japan , it is very important to examine quantitatively manageability of the energy demand in those sectors.
How much the energy-load characteristics of the three sorts of energy will actually be manageable in the residential and commercial sectors through energy substitution? The Kinki District , which includes Osaka, Kyoto and Kobe cities, is the second most active and densely inhabited area in Japan. It consumes 17 percents of electricity and 31 percents of town-gas of the whole Japan . Particularly in this district , the peak load of electricity is sharpened extraordinarily by the spacecooling demand in summer. Hence this district is considered appropriate as the study area.
A ce rtain measure, a time-of-use rate for instance , has been enforced as a test in Japan , as well as in U.S.A. and some European coun tries, in order to improve the load factor of electricity supply. It is called "load management" to improve load factor of electricity demand. However, in an investigation for searching measures of load management in the residential and com mercial sectors, the effect of substitution among three sorts of energy , i.e ., electricity, town-gas and petroleum refinery products including LPG , kerosene and fuel oil, should not be ignored. Furthermore , it is noted that improving the load factor of electricity will affect the demands of the other sorts of energy.
The con ten ts of the paper are as follows . In section 2, briefly explained are the energy rates and various regulations related to energy utilization which have been enforced for load leveling in Japan. Some examples are shown to illustrate the effect of these measures on prevalence of apparatus. Section 3 outlines the structure of the energy demand model developed in this study. This model is built based on various energy-demand estimates, which are discussed in some detail, and aims to investigate how much the energy-load characteristics of the three sorts of energy can be managed by apparatus selection . In section 4, the results of simulations under various conditions are shown. Especially, the effects of spread of heat pump and/or gas-cooler are evaluated quantitatively , and
The "energy-load management" in the residential and commercial sectors is, here, defined as systems management for improving energy-load characteristics of all the three sorts of energy used in those sectors. The energy-load characteristics implies the load factor and the amount of energy consumption in each sort of energy. Various time-of-use energy-rates and/or deregulation policies related to the energy utilization
319
Y. Nishikawa et al.
320 the realizability of the preferable scenarios is discussed . Finally, concluding remarks are summarized in section 5.
ON MEASURES FOR LOAD-MANAGEMENT ALREADY ENFORCED IN JAPAN Some measures have been already taken to deal with such problems of load leveling in Japan. In early days, electric power companies made various special contracts with big consumers in order to increase load factor of supply. For example, there is a contract that the consumption in the daytime of summer needs much more payment than usual. Another example is that some consumers should pay much penalty when they violate the contracts related to the peak-kW demand. As for the residential sector, that is, for small consumers, electricity with special discounted rate for midnight use is supplied to the water-heater with storage exclusively. Not only in electricity supply but also in gas supply, some measures for load leveling have been enforced. Recently the price of gas consumed for space-cooling has been set much cheaper than that for the other uses , and the taxes on gas-coolers are also reduced by the government. These measures have much affected prevalence of the proper apparatus. Some examples are such as shown in the following . 1) The gas-coolers, i.e., gas-absorption machine and gas-engine heat-pump, have prevailed in about 80 % of newly-constructed buildings with floorarea more than 3000m 2 2) In recent years, the amount of electricity consumed in buildings has been rapidly increasing due to prevalence of office computers, and hence the maximum kW-value contracted with the power company is getting insufficient in some buildings. It is advantageous for the owners of such buildings to replace an electric cooler with a gas-cooler because of big expense to change the contracts. 3) As mentioned before , an electric water-heater with storage can consume electricity with a special rate for midnight use. But it cannot consume electricity with normal rate in the daytime if it does not have double heaters, one for midnight use and the other for daytime use. This regulation makes the water-heater for double uses expensive and prevent it from prevailing . These interesting observations indicate that energy rates and regulations related to energy utilization may change the load characteristics of the three sorts of energy drastically. Thus, the problem is to estimate how much the energy-load characteristics will be changed. The authors developed an energy demand model particularly for this purpose.
efficiency of apparatus easy. 2) The energy demands are treated in a time division of month . The matter of concern in the energyload management is the characteristics of energy load, especially its peak and off-peak demands. By use of the present model, seasonal changes of the energy demands can be analyzed. In electricity supply, load fluctuation by time-of-day is an important matter as well as that by season . The authors are extending the model to take the time-of-day characteristics of electricity load in{o account. 3) The influences of the climatic factors on the energy demands are considered. The energy demands for air-conditioning and water-heating depend largely on the climatic factors. The model takes atmospheric temperature into consideration as the most significant factor. The model is constructed through the following three procedures: 1) Decomposition of the Energy Demand into Usages Four types of secondary energy are considered, i.e., electricity, town-gas , LPG and kerosene. The kerosene includes fuel-oil in the following. The data sources of these energy demands are the monthly demands for electricity and town-gas, the annual demands for LPG and kerosene and the monthly residential expenditures for these sorts of energy. In the residential sector, solar energy is considered additionally. These energy demands are decomposed into five usages , i.e., space-cooling , space-heating, water-heating, cooking and lighting-and-others based on the seasonal changes of the demands and other informations. 2) Estimation of Stocks In order to obtain basic units of the energy demands, we estimate the number of households and the floor areas of the buildings for commercial use. The decomposed secondary-energy demands must be converted into the final thermal demands. For this conversion, the annual change of the energy efficiency of the air conditioners is also evaluated by estimating the stocks of apparatus. 3) Regression Analysis with Climatic Factors In order to explain the fluctuations of the spacecooling, space-heating and water-heating demands, their regression analysis in terms of the atmospheric temperature is carried out. Cooking and lighting-and-other demands are assumed to have no seasonal changes. Figure 3.1 illustrates schematically the above procedures , and TABLE 3.1 summarizes the substitutabilities among apparatus considered in the model. In the following , each sub model is described briefly. [Residential Sector]
ENERGY-DEMAND MODEL In order to investigate the effects of energy substitution in air-conditioning and other usages on energy-load management , we construct an energydemand model in the residential and commercial sectors. The features of the model are as follows : 1) The energy demands are separated in to the final usages, i.e ., space-cooling, space-heating, etc. They are represented in terms of the final thermal loads. It makes considerations of the energy substitution and improvement of the energy
1) Space-Cooling Demand Submodel Recently, in the residential sectors , air conditioners have been spread remarkably . At the same time, their energy efficiencies have been improved drastically after the oil crises. The incremental electricity load in summer is assumed the energy demand for space-cooling, and is converted into the final thermal demand by multiplying energy efficiency of the air-conditioners in stock. The energy demand for space-cooling per air conditioner is taken as a basic unit of the
Energy-load Management
321
4ilI1l
350
~
:c ~
3IiJIl 250
.i::
20il
~
150
~
~
lOO 50
Space-Coo.1 .ins D..-nd.
Cookina Deaand.
Suba ·Jdd
Su-.oc!el
Spac.e-B ••ting D--.nd
Lilhtina a Dthu
Subllod..l
D-.an4 Sut.odel
Water-B ••ting Deaand
0 29 31 33 3S 2S ~ Mean Mexif1lJm Temperature ["Cl
Fig. 3.2. Regression analysis of the residential space-cooling demand. . ~r-------------------~
Sut.odel
Fig. 3.1. Schematic diagram of energy demand model.
..
15
C\J~
TABLE 3.1 Apparatus for Inter-energy Substitution in Residential and Commercial Sectors RESIDENTIAL SECTOR Apparatus
Usage
Energy Substitution
Electric Heat-pump
SC j SHjWH
TGjLPjKE -+ EL
Electromagnetic Cooker
CO
TG j LP -+ EL
.i:: ~
10
~
5
~
o
"
'.
.
~~~~~~~~~~~~
16
18
~
22
24
26
28
30
Mean Temperature ['Cl
COMMERCIAL SECTOR Apparatus
Usage
Energy Substitution
Electric HP with Storage A bsorption Chiller jHP
SC j SH
TG j KE -+ EL
SC j SH SC j SH SC j SH j LO
EL -+ TG j KE EL -+ TG EL -+ TGjKE
Gas-engine HP Co-generation
SC: space cooling, SH: space heating, WH: water heating, CO: cooking , LO: lighting and others EL: electricity , TG: town-gas, LP : liquefied petroleum gas, KE: kerosene
residential space-cooling demand. The submodel of the demand is obtained by a linear regression of the space-cooling demand to the mean maximum atmospheric temperature. See Fig. 3.2. 2) Water-Heating Demand Submodel The electricity demand for water-heating is captured easily because of its contract , i.e. , it is supplied with a special discount in midnight . By using the seasonal change of the water-heating demand in electricity , we separate the demand for this usage from the town-gas , LPG and kerosene demands. The procedure of the separation is mentioned in Appendix A. The amount of solar energy for water-heating is estimated based on the sales of solar heaters. The basic unit of waterheating demand is made by summing these energy demands up , and dividing it by the number of households equipped with baths. The model is obtained by a linear regression of the basic unit to the mean atmospheric temperature. 3) Space-Heating Demand Submodel The energy demands for space-heating consists of the incremental electricity demand in winter and
Fig. 3.3. Regression analysis of the commercial space-cooling demand. remainders of town-gas, LPG and kerosene demands after subtraction of the demands for the water-heating and cooking demands. The electricity demand in winter has been growing remarkably since 1983. We have assumed this growth is owing to use of electric heat pumps for space-heating, and treat it separately from the conventional electricity demand for space-heating because of difference in the energy efficiencies. The energy demand for space-heating per household is taken as a basic unit. The model is obtained by a linear regression of the basic unit to the mean minimum atmospheric temperature. 4) Cooking , Lighting-and-Other Demand Submodels A part of town-gas and LPG demand is treated as the demand for cooking. Its amount is determin ed according to the reference [1]. The base part of the electricity load is assumed to be the demand for lighting and other usages. we assume that th e both demands do not change by season and that their basic units, i.e. , the demands per household grow by constant amounts a year. [Commercial Sector] In this sector , the basic unit of thermal demand is defined as the demand per unit floor area [rn 2] . 1) Space-cooling Demand Submodel The amount of town-gas consumption for spacecooling in the Kinki District is estimated by the town-gas supplier; On the other hand , the electricity demand for space-cooling is estimated by the same procedure as in the residential sector. Then the basic unit of the commercial spacecooling demand is obtained by multiplying the effeciency of apparatus . The result of regressional analysis of this basic unit to monthly mean temperature is shown in Fig3.3 .
322
Y. Nishikawa et al. TABLE 3.3 Estimates of Basic Units
TABLE 3.2 Energy-Demand Models for Residential and Commercial Sectors RESIDENTIAL SECTOR
SC
Usage
Model
Unit
Space Cooling Space Heating Water Heating
35.37T.,.. - 906.5
(I)" (2) (2)"
Cooking Lighting & Others
- 21.85 T min + 439.7 -6.69T...... + 334.4 206 + 5.16{y - 1983) 72.5
+ 0.80{y
- 1983)
(2) (2)
(1):[Mcal/month'machine] (2):[Mcal/month 'household]
COMMERCIAL SECTOR Unit
Usage
Model
Space Cooling Space Heating Water Heating
1.44 T ..... n
Cooking Lighting & Others
-
+ 7.58
(3)
-0.16T.....n 18.99
+ 8.03
(3)
+ 1.21{y
(3) - 1986)
(3)
(3):[Mcal/month 'm'] Tma.x:
Tmin : Tf"I\eGn:
y: •
WH CO LO
EL 240 14.3 272 3.3 285
TG
LP
KE
5.4 523 8.8 1551 5.6 554 16.4
40 2.0 599 13.9 316 2.1
1469 82.2 209 57.8
2477 113.9
SO
126
' .
upper : of the residential sector [Mcal/ household,year] lower : of the commercial sector [Meal/ m' year]
District at the year of 2000 are estimated under several scenarios of apparatus selection. Then, the results are analyzed from the view point of energyload management.
(3)'"
25.66
-0.47T.....n
113.86
SH
Total 240 19.7 2203 96.3 2770 77.3 870 18.5 2477 113.9
mean maximum atmospheric temperature of the month. mean minimum atmospheric temperature of the month. mean atmospheric temperature of the month. year.
Demand per air conditioner .
•• Water-heating demand per household equipped with a bath . ... All the models for commercial sector indicate the demands
Process of the Simulation Analysis First , with assumptions of the number of households, the floor area in 2000 etc., the energy demand of each usage is estimated. Then , with assumptions of the shares and efficiencies of apparatus for each usage, the energy demand is distributed to the secondary energies. TABLE 4.1 shows the households and the floor areas in 2000 used in the simulation . The efficiencies of several sorts of heat pumps considered in the simulation is listed in TABLE 4.2. The climatic conditions are assumed as those in an average year. Scenarios
per unit floor area.
The simulation is carried out under the following two scenarios in the residential and comme rcial sectors: 2) Water-heating Demand Submodel, Space-heating Demand Subm'.>del and Cooking Demand Submodel The electiricity demand for space-heating is estimated by evaluating the incremental electricity demand in winter, under the assumption that electricity is not used for water-heating, partly because there is no data about it . Town-gas and LPG demands are decomposed into space-heating, water-heating and cooking usages by almost the same procedure as in the residential sector. The basic unit of cooking is taken from [2]. Kerosene demand, which includes fuel-oil demand, is also decomposed into thermal demands according to [2], because its distribution channel is very complicated and even the monthly demand data is not available. 3) Lighting-and-Other Demand Submodel The base part of the electricity load is assumed to be the demand for this usage as in the residential sector. Formulas of the submodels are shown in TABLE 3.2, and the estimates of basic units are shown in TABLE 3.3. Although some of these estimates are based on the results of various questionaires , most of them are evaluated based on the data source open to the public. Therefore these procedures may be employed by anyone who wants to analyze the energy demand in the residential and commercial sectors in Japan.
[Residential Sector] Standard Scenario Until 2000, selection of the apparatus in recent years continues. The number of ai r condition ers grows at the speed of rec ent years. In 2000, it reaches to two machines per hou se hold . Electricity-Oriented Scenario To compare with the standard scenario , the electricity is preferred to other sorts of energy much more in this scenario. The air conditioners spread more than in the standard scenario ( 2.4 machine paer household in 2000) , too. The electric heat pump has a large share in space- heating demand . Water-heating with electric heat pump is also introduced. [Com mercial sector] Standard Scenario The shares of apparatus in the thermal usages do not change until 2000. These shares are shown in TABLE 4.3. Gas-oriented scenario The gas-absorption machin es a re installed in all of the newly-constructed or reconstructed buildings whose floor areas are more than 3000m 2 This means that the recent trend of gas-cooler installation continues till 2000. Meanfile , the gasengine heat-pumps are used in 10 % of the constructed buildings whose floor areas are less than 3000m 2 • The calculated shares of the apparatus in 2000 is shown in TABLE 4.4. Simulation Results
ENERGY-LOAD CHARACTERISTICS IN FUTURE Based on the energy-demand submodels obtained in the previous section, the energy demands in the Kinki
Simulation results are shown in Fig . 4.1 through 4.6 and also in TABLE 4.5. Seeing the town-gas oriented scenario in TABLE 4.5 , it is observed that
Energy-load Management TABLE 4.1 Households and Floor Areas in 2000 Households [million]
7.56 291.4
323
TABLE 4.3 Share(%) of Apparatus in 1986
(6.38 in 1983) Electric HP Package Type Chilling Unit Gas-absorption Gas-engine HP Gas boiler LPG boiler Oil boiler
(209.6 in 1986)
TABLE 4.2 Energy Efficiencies (COPs) of Apparatus Residential
Space-Cooling Space-Heating Water-Heating
Commercial
Electric HP only for Space Cooling Package Type Air Source 3.26/Water Source 3.56/Chilling Unit Air Source 3.36/Water Source 3.76/Electric HP for both Cooling and Heating Package Type Air Source 2.93/3.38 Water Source 3.20/3.80 Chilling Unit Air Source 3.02/3.72 Water Source 3.76/4.18 Gas Absorption HP 1.02/0.87 Gas Engine HP 1.10/1.50
3.22 2.90 2.90
• The ftrst and the second figures are the COPs for space-cooling and space-heating, respectively.
Electric HP Package Type Chilling Unit Gas-absorption Gas-engine HP Gas boiler LPG boiler Oil boiler
As for the town-gas , increasing the amount of consumption is a matter of more concern than improving the load factor, because the gasdistribution capacity in the Kinki District has still much margin. From this view point, the gas-oriented scenario is considered preferable, and there will be no needs to introduce any new load-management measure to realize this scenario . However, there remain some issues to be examined as follows. 1) The heat pump should be improved to put it into confortable use. 2) A way for increasing gas pressure should be investigated in order to increase the capacity of
WH
34.9 54.1 10.9 0.0 0 0 0
5.7 6.5 4.5 0.0 3.9 1.9 77.5
0 0 3.5 0.0 3.0 18.1 75.4
SC
SH
WH
22.4 34.8 36.4 6.4 0 0 0
3.6 4.2 32.3 6.4 2.5 1.2 49.7
0 0 24.9 6.4 2.1 12.9 53.6
RESIDENTIAL Standard Electricity Oriented
Scenario
LPG
According to some investigations, the ratio , hourly electricity demand at 13:00 I average hourly electricity demand , is about 1.9 in the commercial sector and about 1.1 in the residential sector. Upon use of these values, the decrease of hourly peak demand in Fig. 4.5 is estimated as 4.7 %. This indicates that the prevalence of heat pump in the residential sector does not deteriorate the load factor of electricity so much . It is also interesting that the increase of heat pump in the residential sector compensates the decrease of electricity demand caused by the increase of gas-cooler in the commercial sector.
SH
TABLE 4 5 Energy Demands in 2000
Energy Demand Electricity Town-Gas
the energy substitution between the town-gas and the kerosene is striking. In future the amount of oil production will certainly decrease, but it is difficult to say that this extraordinary substitution is preferable in 2000. However, the fact that the demand of petroleum refinery products can be much reduced naturally, if needed, is important. As for the electricity demand, the monthly maximum demand decreases with increase of the gas-absorption machine. In Fig. 4.3, the monthly peak demand is less than that in the standard scenario of Fig. 4.1 by about 6 %. This indicates that the gas-absorption machine (cooler) can afford much saving of the power plants. In Fig. 4.5, the case where the heat pump prevails in the residential sector, the monthly demand is less than that in Fig. 4.1 by only 2.8 %. But in evaluating the effects of peak electricity load in this sector, the hourly elecricity load pattern should be considered.
SC
Kerosene
Solar
35 .5 21.6 7.6 8.4 1.1
37.5 20.1 7.5 5.5 1.1
COMMERCIAL Standard Town-Gas Oriented 43.5 10.4 4.8 35.4
41.6 28.7 3 .5 23.8
[IO'Meal/ year]
gas distribution. 3) If the decrease of kerosene demand is not preferable, some new apparatus, such as t he absorption machin e consuming kerosene, should be prevailed . CONCLUDING REMARKS In this study a new concept of energy-load management by apparatus substitution is presented , and the amount of change in energy-load characteristics of the three sorts of energy is estimated through modelling and simulations. The results of simulation indicate that there is a nice possibility of preferable change of energy-load cha racteristics, and especially prevalence of the gas-cooler has much potential for load leveling of electricity. The following issues are open to be investigated in future. 1) The hourly energy demand should be taken into the demand model. 2) As prevalence of the heat pump results in drastic changes of the load patterns especially in winter, the effects on the economic load dispatching should be considered. 3) A way to evaluate the simulation results from various aspects should be developed , and the practical measures to realize preferable scenarios should be investigated. ACKNOWLEDGEMENTS This study has been pursued under the grant-in-aid on priority-area research supported by the Ministry of Education , Science and Culture of Japan. The authors express their sincere gratitude to Mr. T.Sera, ,Mr. T.Matsuura, Mr. H.Iwai , Mr. H.Nakagami, Mr. N.Shige, Mr. T.Hayashi, Mr. K.Kawahara and Mr.
324
Y. Nishikawa et al.
A.Kume for their valuable discussions and presenting various data on energy demand, and also to Mr. H. Terada, a graduate student of Kyoto Univ., for his making simulation programs.
,.,._.-"', ',-
~'
6IiB! ----... ---.... --• .,. .. ..-
REFERENCES [lJ Jyukankyo Res. Ins. Inc.,"Statistics of Residential Energy Demand" (1986).(in Japanese) [2] Ins. Energy Economics,"Enquete and Hearing survey on Energy Consumption in Commercial Sector"(1988).(in Japanese)
.......... ----.
50IilIl 4alIiI
30il0
~----;.,,
__
2000
f
11!1!l0
Appendix A Decomposition of Town-gas, LPG and Kerosene Demands The town-gas demand is decomposed into the three usages, i.e., cooking, water-heating and space-heating as follows: 1) The amount of the town-gas demand for cooking is determined according to the reference [1] under the assumption that the demand has no seasonal fluctuation . From the monthly town-gas demand , the demand for cooking are subtracted. 2) Then, the demand for water-heating is estimated. It is assumed that the seasonal change is proportional to that of electricity, and that the demand coincides with the remainder of the towngas demand in step 1) at the month of bottom consumption (usually July or August). 3) The remainder of the town-gas demand, after subtranction of cooking and water-heating demands, is taken as the demand for spaceheating. To LPG and kerosene, the same procedure is adopted except that the the demand for cooking is not considered in the decomposition of the kerosene demand.
01~~~~3~~~5~~~7~~~9~~~I-l~
I'lonth
residential sector: standard scenario commercial sector : gas-oriented scenario
Fig. 4.3. Monthly electricity demand. 71'.1110
....,
6IBl
' .c
50IilIl
~
4alIiI
t:
~
... \
....
\
30il0
.. ",-_...........) ........ ~..... \. __ ... .-~.A" ................ ~
2IlIil0
~./
\
" I
...........
....•.... 'w"''':
3
5
7
9
11
I'lonth
residential sector: standard scenario commercial sector: gas· oriented scenario
Fig. 4.4. Monthly town-gas demand.
801'.0
71'.1110
71'.1110
~~-----------------------,
..................
.............. ...... .....
.•.....•.....
30il0 r·~"·-··-·"·.. ··-"-"':;··_"_"··._ .....
!
1000
:demand in the residential Bector :demand in the commercial sector :demand in the residential and commercial sectors ~.------------------------, 801'.0
••••• K
/
2000 II!I!l0 0~~~~~~~LL~~~~~
I
3
7
5
9
3
11
5
9
7
11
I'lonth
I'lonth
residential sector: standard scenario commercial sector : standard scenario
residential sector: electricity· oriented scenario commercial sector : gas· oriented scenario
Fig. 4.1. Monthly electricity demand .
Fig. 4.5. Monthly electricity demand . 7I!I!l0~----------------------~
6IBl .c
~
~
-
...... ..... """
,
' .......... _ _ .. _ _ .. _
.. _ . . _ .. _ _ _ 4 " .. .,11
--
2000 II!I!l0
.................................................................... 3
5
7
9
11
I'lonth
residential Beet or : standard scenario commercial sector : standard scenario
Fig. 4.2. Monthly town-gas demand.
3
5
9
7
11
I'lonth
residential sector: electricitY 0riented scenario commercial sector : gas· oriented scenario 8
Fig. 4.6. Monthly town-gas demand.