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An Assessment of Unutilized Heat Sources and Distributed Energy Technologies by an Energy Network Model with 151 Subregions of Tokyo Koto Area

Shunsuke Mori* Yasutomo Tejima Shiho Nakayama Satoshi Ohnishi (Tokyo Univ. of (Mitsubishi Elec. (Tokyo Univ.of (Tokyo Univ.of

Science) Information Systems Co.,) Science) Science)

(*) Professor, Department of Industrial Administration, Tokyo University of Science Yamasaki 2641, Noda, Chiba 278-8510, Japan

Phone:+81 4 7124 1501 fax:+81 4 7122 4566 eMail: Sh_mori@rs.noda.tus.ac.jp

1. Introduction It is well understood that the energy conservation of the commercial buildings in the metropolitan area is one of the

key issue under the environmental constraints. Especially in Tokyo, since Olympic is being held in 2020, distributed energy technologies including CGS, Photovoltaics, new heat-pumps etc., will play a main role to mitigate the increasing energy demand and environmental issues. The unutilized heat sources such as the underground and the river are reconsidered because of the improvement of the heat pump (HP) technologies. The potential contribution of heat transportation among buildings should be also taken into account when we pursue the energy efficiency.

In this study, we investigate the contribution of new energy technologies for the commercial buildings by developping a energy flow model which explicitly deals with the potentials of unutilized energy sources and energy transportation among regions in the following manner: first, we divide Koto-area in Tokyo into 151 sub-regions in around 250m by 250m meshes specifying the building types, i.e. commercial buildings (co), office buildings (of), detached houses (dh), apartment houses (ah), sport gymnasium(sp), hospitals(hos), and hotels(hot). Second, we estimate the energy demand by purpose and then apply an energy flow model following our previous research (Mori et.al.,2013). The potentials of unutilized energy sources such as underground heat, river heat sources, waste incineration heat, the possible contributions of these technologies and energy transportation among regions as well as the CGS are then evaluated. Third, the energy flow model modules are then connected with each other when considering the possibility of energy transportation among sub-regions. Our model with the unused energy sources and new technologies demonstrates the potential and the limit of these new sources. 2. Outline of District Energy Systems 2.1 Survey on the District Heat Supply Utilities

District Heat Supply Business Association (JHSBA) provides various statistics on the district heat supply companies. We extract the annual heat supply energy and whole sales series from the Handbook of District Heat Supply Business 2016[JHSBA, 2016] for 119 cities as shown in Figure.1. By applying regression analysis, we estimate the 20.7 (¥/kWh) as the heat sales price. It should be noted that the effects of scale of economy can hardly found and that no significant differences among heat sources is observed. Similarly, we estimate the energy sales price by type. We obtain 23.0 (yen/kWh), 14.1 (yen/kwh) and 33.6(yen/kWh) for room heating warm water, room cooling chilled water and hot water, respectively. We employ these numbers in the simulation scenario where the consumer minimizes the total cost under the given energy demand. The monetary transaction term between DHC and consumers disappears in the minimization of total cost scenario including both consumers and district heat suppliers.

Figure 1 Relationship between whole supplied energy (GJ) and whole sales of district heat supply utilities

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Annual W

hole Sales (million yen

 per yea

r)

Whole Supplied Energy（ＧＪ/Year）

●Boiler ●Waste incineration ●Subway ● Power substations●Substations+Temperature difference●Wood waste ●Sewer heat●River heat●Sea water ●Ground water ● Steam extraction

Y=0.0057X R2=0.953 N=119

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2.2 Property and energy demand estimation of the Tokyo Koto Area

This study deals with the evaluation of the efficient use of unused energy sources as well as distributed energy technologies in the Tokyo Koto area. Koto area locates just next to the center of Tokyo with around 500 thousand habitats and 40.16km2. Koto area is surrounded by river and Tokyo-bay and has many canals. So many high office, residential and commercial buildings are recently developed, new options for the increasing energy demand as well as the high transportation intensity are needed especially in 2020.

The first step of our research is to estimate the energy demand by purpose to assess the potential contribution of energy technologies in detail. We extract the detailed building data for Koto area specifying the building floor area and commercial type described in the above based on the GIS data. We estimate the energy demand by end-use, i.e. heating, cooling, hot water and other general electric demand according to Mori et.al (2013). We then aggregate the building data into 151 sub-regions which represent approximately 250m by 250m meshed, where each of sub-regions consists of seven building categories and corresponding four type energy demand. Figure 2 shows the fraction of floor area of each building type in Koto area. This figure suggests the high density of energy demand for air conditioning. Furthermore, in 2020 summer when Tokyo Olympic is held, accommodation facilities for the players and some sport stadiums are to be constructed. To meet such large air-conditioning demand, efficient utilization of all available energy sources is indispensable.

Figure 2 Composition of building floor area by purpose in Koto-ku

The energy flow model is applied to each building. Since 151 sub-regions are often separated by river, canal or

highway, heat transportation possibility is limited. We draw a potential transportation network among sub-regions. Table 1 shows a part of the floor area of sub regions of five building categories.

Table 1 Floor area of 151 sub-regions by building category (in m2)

We then apply the energy demand intensity data provided by SHASE (1994) to the floor area by type and season, namely lighting and general use, cooling, heating, and hot water. Hourly energy demand is categorized into four groups,

Office18%

Commerce25%

Hotels2%

Detached houses10%

Apartment Houses44%

Hospitals1%

Athletic Gyms0%

Office bldg.Commercial

bldg.Hotels &hospitals

Residentialbldg.

AthleticGyms

of co ho hs sp1 5109 885 0 5542 02 21143 2925 33 25669 03 6998 0 63 16376 04 3394 2819 8 10901 05 3461 7803 0 17536 06 20617 4122 0 28462 07 18510 4706 986 14255 08 612 5633 0 36176 09 7390 11347 0 41963 280

149 60008 26 0 0 0150 33900 398 3797 4174 1089151 8402 0 17 0 2504

total 5198420 5782399 526108 12780668 133083

sub-region

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i.e., hot water supply (D_hw), room heating (D_ho), room cooling (D_rc) and other electric power demand (D_eo). We aggregate the 365 days into seven season groups, namely summer workdays (Sum_WD), summer holidays (Sum_HD), winter workdays (Win_WD), winter holidays (Win_HD), middle season, i.e. spring and fall, workdays (Mid_WD), middle season holidays (Mid_HD), and three summer peak days (Sum_PK). Thus, we estimate the energy demand 7 seasons, 24 hours, seven building categories, four demand types and 151 sub-regions. We show aggregated energy demand on Koto area total by seven categories in Figure 3(a) – Figure 3(g).

(a)Summer-peak (b)Winter-Working day

(c)Middle-Working day (d)Summer-Working day

(e)Winter-Holiday (f)Summer Holiday

(g)Middle-holiday

Figure 3 Aggregated energy demand by purpose and seasons for Koto area total D_hw:hot water D_hc:room heating D_rc:room cooling D_eo:other electric power demand

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ayenergy demand [kW

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2.3 Unused energy sources 2.3.1 River heat utilization

Thanks to the recent progress on the heat pumps (HP), such unused heat sources as underground heat, river heat, thermal source of subways, etc. have already found the practical opportunity. Some new buildings in Japan have already implemented these new technologies. Since the potential of these sources depends on the geographical conditions, we carefully extract the possible consumers. First, we extract some sub-regions which face Sumida river. Next, we focus on the buildings within 500m distance from the river side according to the “Green Tokyo - Global Warming Mitigation Project”[Institute for Tokyo Municipal Research, 2014]. In this step, we exclude some cases where highways or large roads lie across between the river side and buildings. We thus employ 8 sub-regions from 151 sub-regions.

Figure 4 exhibits how the utilization of river heat improves the COP, showing that the COP increases by around 35% for heating and 25% for cooling [JHSBA, 2016].

Figure 4 Comparison of COP improvement by river heat

Case of Hakozaki area (JHSBA, 2016) Furthermore, IBEC [ibec, 2016] indicates the COP of next generation HP for cooling to be 5.2 (ambient temperature 35℃) - 6.5 (ambient temperature 25℃) and heating to be 4.8 (ambient temperature 0℃) - 6.7 (ambient temperature 15℃). 2.3.2 Underground heat utilization

Next, we assess the potentials of underground heat. The temperature under 10m in the ground is almost constant and same as the average ambient temperature. Thus we can make use of the temperature difference between the average and the temporal one by applying heat pumps improving the energy efficiency. Based on the “Potential Underground Heat Utilization Map for Tokyo” provided by Tokyo Environmental Division [Tokyo, 2016] as shown in Figure 5 and Figure 6, we extract sub-regions where the stakeholders can expect the high potential of underground heat sources.

The potential power of the underground heat is represented by H= C*D*N where H,C,D and N represent

recoverable energy (MW), recoverable heat per length of heat extraction pipe (MW/m), length of heat extraction pipe (m), and number of extraction pipes, respectively. In this paper, we assume C=310*1e-6 MW/m, D=20m and that heat

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extraction holes can be developed by every 6m on the area. Due to the additional cost on the drilling and boring, the utilization of underground heat source has not been

favored. However, according to the cost assessment of Ohoka [Ohoka,2017], the overall repayment duration of the underground heat utilization has been shortened from 28.3 years to 8.0-8.6 years thanks to the technological progress. Ohoka also summarized the construction cost and other facility costs as summarized in Table.2. Based on them, we assume COP to be 4.3 and 6.0 for heating and cooling respectively. This assumption derives 5.8 yen/kwh.

It is remarkable that the Ministry of Environment Japan shows that the COP of HP for the underground heat is increasing or constant as the load factor decreases in the demonstration program [Ministry of Environment Japan, 2015]. Although this study fails to include such non-linear and non-convex technical properties, this should be evaluated by more mathematically sophisticated model.

Figure 7 summarizes the sub-regions where river heat and underground hear sources are potentially available.

Table 2 Estimation on the initial cost of conventional ambient HP and underground heat HP in thousand yen (Ohoka, 2017)

(*) Boring and drilling: 20m * 30 points

Figure 7 Sub regions with potential river heat and underground heat

blue: river heat orange: underground heat

2.4 Other renewable energy sources Furthermore, we take into account other renewable energy sources, i.e. waste incineration heat, sewage, wind

power and photovoltaics(PV). We employ only the existing wind power, i.e.2.8MW and 5200MWh per year in total. In this study, we assume almost constant power generation through the year, since hourly average wind speed is almost constant as shown in Figure 7. Needless to say, the shorter term intermittency of wind power should not be neglected unless power storage system is implemented. We also assume PV panels are located on the building roof area.

There are two waste incineration plants in Koto area. The amount of annual waste disposal, heat endowment and power conversion efficiency are summarized in Table 3. Potentials of sewage heat are shown in Table 3 where recoverable heat is estimated by {(average sewage temperature=16℃)-(ambient temperature)}*(Specific heat of water)*(volume of treated water). Figure 8 shows the annual heat supply potentials of Sunamachi Sewage Treatment plant in 2015. Although potentials of sewage treatment is not negligible, heat transportation issue could be the barrier due to the distance between the plant and the consumer.

Ambient HPUndergrround heat

HPHP (180kW) 9,900 6,900

Construction cost 259 236Pump -- 300Piping -- 313

Additional construction -- 8688,738 Conventional3,692 New

17,415 Conventional12,369 New

Boring and Drilling --

Total 10,159

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Table 3 Potential of waste incineration energy in Koto area Plant Name In operation Annual disposal

(kt) Power generation

(GWh/year) Conversion Efficiency

Ariake 1995 110.0 3.968 0.17% Sin-Koto 1998 401.9 14.54 6.32%

Figure 7 Average wind velocity in m/s in Koto area

Table 4 Assessment of potential sewage heat supply

Plant name Sewage treatment (m3/day)

Heat endowment (TJyear)

Recoverable heat (TJ/year)

Ariake 30,000 2,163 12.2 Sunamachi 658,000 18,184 274.0

Figure 8 Annual potential of sewage treatment heat supply in Sunamachi plant

3 Model development and simulation scenarios 3.1 Model development

We investigate the contribution of new energy technologies for the commercial buildings by developing a energy flow model which explicitly deals with the potentials of unutilized energy sources and energy transportation among regions. The outline of the energy flow model for the consumer is shown in Figure 9. The model includes the unutilized energy sources described in the previous section as well as the energy transportation among regions and CGS are then evaluated. The energy flow model modules for sub-region are then inter-connected with each other when considering the possibility of energy transportation among sub-regions. The formulation of the energy flow model for each building is basically similar to our previous paper [Mori et.al., 2013] except for the additional sources on the unused heat sources. The model consists of (1) energy input–conversion–output balance equations, (2) technological properties such as heat conversion and operation conditions, and (3) cost definition equations. Given the final energy demand by purpose, the model generates the optimal installation of energy equipment and hourly operation and the demand for electric power and gas from utilities by minimizing the total costs.

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It should be noted that this study explicitly formulate the transaction between district heating and cooling energy supply center (DHC) and consumers. Thus the cost for the consumers is represented by

(Cost for Consumers) = (Capital cost) + (fuel and electricity purchasing cost) + (thermal energy purchase from DHC) (Cost for DHC) = (Capital cost) + (fuel and electricity purchasing cost) - (thermal energy sales to consumers) . (thermal energy sales to consumers)= (thermal energy purchase from DHC) In our previous study, we minimize the social cost, i.e. min. Σ (Cost for Consumers) +Σ (Cost for DHC), while this study additionally calculate the case to minimize the consumer cost only, i.e. min. Σ (Cost for Consumers) assuming that thermal energy is sold at 23.0 (yen/MWh), 14.1 (yen/Mwh) and 33.6(yen/MWh) for room heating hot water, chilled water and hot water, respectively as described in section 2.1. We can compare these above two cases, while this paper focuses on the consumer cost minimization to reflect the heat sales price described in 2.1. The potential contribution of unused energy sources and CO2 emission mitigations are also generated.

Table 5 summarizes the cost and the technological parameter assumptions.

Figure 9 Energy flows for the commercial building

Table 5 Cost and technical parameters

Efficiency Cost

CGS 0.4 (elec. power) 30 (thousand yen/kW)

0.45 (heat utilization)

Boiler 0.95 3.2 (thousand yen/kW)

Ambient air HP 4.7(cooling COP) 50.3 (thousand yen/skw)

3.1 heating COP)

3.0 (hot water COP in winter) 32.6 (thousand yen/kW)

4.7 (hot water COP in others)

River heat HP 5.2 (cooling COP） 62.8 (thousand yen/kw

4.2 (heating COP)

Underground heat HP 6.0 (cooling COP) 68.7 (thousand yen/kw)

4.3 (heating COP)

Gas heater 0.9 10.6 (thousand yen/kW)

Absorption refrigerator 0.7 21.4 (thousand yen/kW)

PV 0.13 3.94 (thousand yen/m2)

3.2 Simulation scenarios The simulation scenarios in this study are summarized in Table 6. We also compare two cost-minimization cases described in 3.1, say the Social cost minimization and the Consumer cost minimization scenario.

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Table 6 Simulation cases

PV CGS DHC Unused-A Unused-BHeat

Transport

Base n.a n.a n.a n.a n.a n.a

Case-1 Available n.a n.a n.a n.a n.a

Case-2 Available Available n.a n.a n.a n.a

Case-3 Available Available Available Available n.a n.a

Case-4 Available Available Available Available Available n.a

Case-5 Available Available Available Available Available Available (*) Unused-A includes sewage heat, waste incineration and windpower, and Unused-B includes river and underground heat sources. 4 Simulation results 4.1 Consumer cost minimization scenario Firstly we show the simulation results on the consumer cost minimization scenario by seven building categories, i.e., commercial buildings (co), office buildings (of), detached houses (dh), apartment houses (ah), sport gymnasium(sp), hospitals(hos), and hotels(hot) as well as district heating and cooling energy supply center (DHC). Figure 10 exhibits the annual cost for seven consumer buildings and DHC in Koto area total. The contribution of CGS counts for around 15 billion yen per year especially for commercial buildings. However, consumers cost reduction is negligible small in Case-3, 4 and 5. Figure 11 shows the total CO2 emissions and reduction rates in this case. Figure 11 indicates that the CGS contributes to reducing CO2 emission by 17% while other options can additionally reduce 3% even if available total amount of unused energy is limited.

Figure 10 Annual cost for seven consumer buildings and DHC in consumer cost minimization: Koto area

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Figure 11 Annual CO2 emissions for seven consumer buildings and DHC in consumer cost minimization : Koto area

4.2 CO2 emission minimization Figure 12 shows the annual CO2 emission patterns in case of CO2 minimization scenario. This scenario suggests the potential contribution of technology options to reduce CO2 emission. We can observe that the potential CO2 emission reduction comes to 30% in Case-4.

Figure 12 Annual CO2 emissions for seven consumer buildings and DHC in CO2 minimization : Koto area

. 4.3 Sensitivity analysis on the heat transportation price In this subsection, we show some results on the sensitivity analysis on the heat transportation price. We calculate the model by changing the heat transportation price from 100% to 1% (HTR_X_VR_Rate) in the case-5 of the consumer cost minimization scenario. Figure 13 shows how the annual costs of consumers and DHC change. In this case, since the income of DHC decreases as the price goes down, the total cost increases. Figure 14 shows the changes in the heat transportation demand by purpose. The demand for the chilled water increases firstly and then warm water for room heating follows. This figure suggests that the social planner should seriously consider the utilization of various unutilized energy sources as well as the energy transportation facilities since the air conditioning demand in Tokyo in summer is substantial, especially in the Olympic game year. The demand for hot water occurs when the price is less than 3.4 yen/kwh.

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Figure 13 Sensitivity of the annual costs by consumers and DHC in the different heat transportation price

Figure 14 Sensitivity of the heat transportation demand in the different heat transportation price

Figure 15 and Figure 16 show how the heat transportation price influences the implementation of the river heat and the underground heat utilization. These two figures apparently show the trade-offs between heat transportation and unutilized energy sources. When heat transportation price decreases to 40% of current average one, the HP implementation decreases rapidly, especially for office buildings. It should be noted that the DHC has not implemented HP for unutilized heat sources even in the base case. These figures also show that office buildings implement river heat HP largely while commercial buildings employ underground heat mainly. Figure 17 and Figure 18 show the changes in the HP implementation in the major sub-regions. We can see that the potential utilization of underground heat is much larger than that of river heat. Second, unutilized energy sources largely vary among regions even if these availability depends on the geographical conditions. The tradeoffs between the heat transportation and the utilization of those heat sources also vary among region to region. Figure 19 and Figure 20 exhibit the installed HP capacity for river heat and underground heat by sub-region and consumer. Underground heat sources are widely introduced in the commercial buildings while office buildings are the major user of the river heat.

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Figure 15 Sensitivity of the river heat utilization (implemented HP capacity) in the different heat transportation price;

by consumer

Figure 16 Sensitivity of the underground heat utilization (implemented HP capacity) in the different heat transportation

price; by consumer

Figure 17 Sensitivity of the river heat utilization (implemented HP capacity) in the different heat transportation price;

by sub-region

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清澄1 常盤1 新大橋1 新大橋2

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ー Kiyosumi ーTokiwa－Shinohashi‐a－Shinohashi‐b－Saga‐a －Saga‐b －Fukusumi －Ecchujima

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Figure 18 Sensitivity of the underground heat utilization (implemented HP capacity) in the different heat transportation

price; by sub-region

Figure 19 Installed HP capacity for river heat utilization in MW ; by sub-region and consumer

Figure 20 Installed HP capacity for underground heat utilization in MW ; by sub-region and consumer

5. Conclusion

We developed a model for the evaluation of unutilized energy sources for Tokyo area dealing with the detailed building energy demand dividing the Koto-area into 151 sub-regions. Firstly we estimate the current sales prices of district heating and cooling energy supply based on the literature.

The model simulations show the contribution of DHC is limited under the current heat price. Each consumer building prefers to implement HP and other facilities by himself rather than to purchase thermal energy from DHC.

Our current results also show that thanks to the progress in the HP and the drilling technologies, such unutilized energy sources as underground heat and river heat have potential to improve both the economic and environmental efficiency.

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豊洲2 豊洲5 東雲2 辰巳1 東陽2ー Toyosu‐a  ーToyosu‐e－Shinonome‐b－Tatsumi‐a －Toyo‐b

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However, we can also find strong trade-offs between DHC and unutilized energy sources. Our simulations suggest that the unutilized energy sources are apparently substituted by DHC when the heat price from DHC is cut by 60%.

It is also suggested that the contribution potentials vary significantly among sub-regions. Thus, detailed potential survey is essential to evaluate them. Acknowledgement This research is supported by the Grant-in-Aid for Scientific Research (B) (grant No. 15H02975) from Japan Society for the Promotion of Science. REFERENCES Ishida,T. and S. Mori (2008), “Integrated Assessment Model for Urban Energy Network System”, Environmental Informatics and Industrial Ecolohy - 22th International Conference on Informatics for Environmental Protection, PP.132/141, ISBN 978-3-8322-7313-2, Shaker Verlag, Germany, 2008

Institute for Tokyo Municipal Research (2014), “Guideline for the Smart Community”, http://all62.jp/saisei/top2014.html

Mori, S., Y. Hori, M.Ohkura and K.Kamegai(2013), "Data Center as a Key Player of a District Electric Power and Heat Network System: A Comparison in Urban and Suburb Regions", Computer Technology and Application 4 (2013) 548-555

SHASE(1994), Design, Planning and Evaluation of City-gas based CGS, The Society of Heating, Air-Conditioning and Sanitary Engineering of Japan, 1994 (in Japanese).

JHSBA (2016), Handbook of District Heat Supply Business 2016, JHSBA, 2016 (in Japanese)

Tokyo, (2016), http://www.kankyo.metro.tokyo.jp/energy/renewable_energy/ne2/tichumap/map.html

Ohoka (2017), Utilization of underground heat in Kanto area, http://www.geohpaj.org/old_information/doc/ohoka.pdf, (retrieved 23, Jan, 2017)

IBEC (2016), http://www.ibec.or.jp/best/program/m_131_kikitokusei.pdf

Ministry of Environment (2016) ,http://www.env.go.jp/policy/etv/pdf/list/h27/052-1502a.pdf