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1 Powered by TCPDF ( Title 太陽光発電に併設する蓄電池共有によるCO2 削減効果の推定 Author 辻, 英美子 (Tsuji, Emiko) 佐々木, 正一 (Sasaki, Shoichi) Publisher 慶應義塾大学大学院システムデザイン マネジメント研究科 Jtitle 修士論文 ( ) Abstract Genre Thesis or Dissertation URL

2 2009 CO 2 ( )

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4 論文要旨 学籍番号 氏名辻英美子 論文題目 : 太陽光発電に併設する蓄電池共有による CO2 削減効果の推定 ( 内容の要旨 ) 発電過程で CO2 を一切排出しない太陽光発電は, 近年深刻化している地球温暖化問題に大きく貢献できると考えられている しかし, 今後太陽光発電が大量普及した場合, 日中の余剰電力が大量に配電系統に逆潮流することによる電力品質の低下が危惧されている そのため, 太陽光発電の大量普及に備え, 然るべき対策が必要である 系統安定化対策の一つとして, 蓄電池を併設することが挙げられる その蓄電池の所有形態について, 資源エネルギー庁は単世帯で所有することは複数世帯で所有することに比べて非効率であると指摘している しかし, 複数の世帯で蓄電池を所有することの効果について定量的に示したものはない その理由は家庭における詳細な電力消費データを何百件も実測することが困難であるからと言われている そこで本研究では人間のばらついた生活行動からボトムアップで生成された電力消費データを 300 軒分利用した 毎時間間隔の発電量データと消費量データから蓄電池残量を計算し, 詳細な解析を行った そして, 蓄電池の設置形態について 3 種類のシステムを想定し, 各々の効果を検証した まず, 太陽光発電に蓄電池を併設した場合, 蓄電池を導入することのメリットが表れる蓄電池単価を計算した 蓄電池価格が 3 万円 /kwh, 太陽光発電が 15 万円 /kw 程度であれば蓄電池導入によってコストが抑えられるという結果が得られた 続いて, 蓄電池を複数世帯で共有した場合の CO2 排出量削減効果を検証した その結果, 複数世帯で蓄電池を所有する場合, 個別に蓄電池を設置した場合と比較して,1 世帯当たり年間 4% 程度 CO2 排出量を削減できることが分かった 複数世帯間で蓄電池を共有することで, 蓄電池を介して電力を融通し合える そのため, 同じ容量の蓄電池でも, 太陽光エネルギーを有効活用できるため,CO2 排出量をより低減できることが示された 最後に, スマートグリッドの場合について検討した スマートグリッドとは IT 技術を駆使し, 電気の需要と供給をバランスさせることができる次世代送電網であるとした スマートグリッド化された場合を含めた複数シナリオで, ある地域のコストに対する CO2 削減効果を求めた PV と蓄電池が 100% 普及した時, なにも設置しなかった場合と比較して,CO2 排出量を半減できることがわかった また, スマートグリッド化することによって, 系統を介して仮想的に蓄電池を共有する効果が示された 以上 本研究は家庭用太陽光発電に併設する蓄電池の所有形態について複数シナリオ挙げるとともにそれらの効果をコスト面と CO2 排出量の面から解析を行った キーワード : 太陽光発電, 蓄電池, 共有, スマートグリッド

5 SUMMARY OF MASTER S DISSERTATION Student Identification Number Title Name Emiko Tsuji Study of Carbon Dioxide Reduction by Sharing Battery Set with Photovoltaic System Abstract Photovoltaic power generation (PV), which does not emit any CO 2 during generation, is believed to contribute to curb global warming. If PV becomes wide spread, if is feared that reverse power flow from PV will reduce electric quality. Measures to deal with mass dissemination of PV are needed. Coupling a battery with PV is one way to make the power system stabilize. Energy Agency pointed out that battery ownership by single household is inefficient than that of several houses. But there is no research that shows the effect of sharing the battery quantitatively. This is because it is difficult to measure hundreds of households power consumption. Therefore, in this study we used 300 houses power consumption data accumulated from a variety of life-styles. We calculated battery balance by taking difference between power consumption and power generated and analyzed in depth. We studied about 3 systems to distinguish their efficiency. First system is setting battery with PV. We were able to prove that there is cost-merit to couple battery and PV if the battery price is 30,000 yen / kwh, and PV is 150,000 yen / kw. Second system is sharing battery with several houses. We examined the effect of reducing CO 2 emission by changing the battery ownership pattern. As a result, by sharing battery, one house can reduce CO 2 emission by 4% compared to battery ownership by single household. The third system is smart grid system. If we assume that every household in the area sets PV and battery, they can reduce half of the CO 2 emission than setting nothing. And we also found that smart grid technology can realize the virtual sharing of the battery. Thus, we analyzed 3 cases of making use of battery in view of the cost and CO 2 emission effects.

6 PV PV

7 PV PV + Battery Smart Grid Smart Grid + Battery

8 5 V (1) V 1 7 Fig.1 V 1 V V Code C 300 3

9 6 3 5 V (Verification) 3 4 CO 2 5 IT PV CO 2 6 V (Validation) Definition Sequence and Elaboration of Detail Stakeholder Requirements CVCA System Architecting Analysis Procedure System Simulating Cost and Design CO 2 Emission PVand Battery System Battery Sharing System Smart Grid System Code C++ Validation Verification Assembly and Performance Assurance Sequence Fig. 1 V model for this study (1).

10 (2) 9 CO 2 (3) CO G (4) %

11 8 1 PV:Photovoltaic (5) Fig.1.1 GDP:Gross Domestic Product Energy Consumption and GDP (1990's consumption and GDP=100) Industrial Sector Transportation Sector Civilian Sector Real GDP Year Fig. 1.1 Energy Consumption and GDP (5).

12 1.1 9 Energy Consumption (1973's consumption and households=100) Energy Consumption Number of the Households Personal Consumption Year Fig. 1.2 Energy Consumption for Residential Sector (5). 2 43% 57% Fig

13 PV 1m 2 1kW PV CO 2 PV /kwh PV PV PV (6) PV (101 6V) PV

14 (7) PV (8) (9) PV (10) (11) (12) IT PV CO PV PV CO 2 3 PV- IT

15 Fig.1.3 (13) (14) (15) PV- PV PV PV PV PV PV 1

16 IT PV CO 2

17 14 1 Battery (a) Owning Battery Inividualy Battery (b) Sharing Battery Battery Battery... Battery (c) Smart Grid Fig. 1.3 Conceptual Illustration of Three System (a)owning Battery Individualy (b)sharing Battery (c)smart Grid.

18 PV CVCA(:Customer Value Chain Analysis) CVCA CVCA Fig.1.4 (Government) PV (Citizen with PV) PV (Citizen without PV) (Electric Power Company) PV (Solar Panel Maker) (Battery Maker) PV % PV 2 48 /kwh PV PV PV PV

19 16 1 Electrical Power Charge Electric Power Company Regulation Tax Government Selling power generated from PV Citizen Tax Subsidy Reducing CO 2 Fund for R&D Without PV With PV Battery Maker Solar Panel Maker : Information : Money : Electric Fig. 1.4 Customer Value Chain Analysis(CVCA)

20 PV PV PV PV CO 2 PV CO 2 PV

21

22 (Fig.2.1) PV PV Consume Use the Energy Generated from PV Shortage of Power Supply Use the Energy from Battery Shortage of Power Supply Buy from Electric Power Company Fig. 2.1 Order of Power Consumption.

23 20 2 (Fig.2.2) Generated Energy from PV Use the Energy for Electric Demand in the House Surplus Power Charge the Battery Full Charge Opportunity Loss Fig. 2.2 Order of generated Energy. 1

24 start t 1 P Gt Generate Data P Ct Consumer's Data D P Gt - P Ct D > 0 No t t+1 Yes Charge Discharge Yes t = 365 No end Fig. 2.3 Analysis Procedure Fig.2.3 P Gt P Ct t Fig.2.3 (P Gt >P Ct ) (P Gt <P Ct ) 365

25 Charge B t-1 + D B EFF < SOC U No Yes Battery Charge B t B t-1 + D B EFF Opportunity Loss P Lt P L(t-1) +{(B t-1 + D B EFF ) - SOC U } B t SOC U Fig. 2.4 Analysis Procedure (Charge) Fig2.4 B t t SOC U SOC L B EFF P Lt SOC U (Fig.2.4 ) B t 1 D( ) (Fig.2.4 )

26 Discharge B t-1 + D B EFF > SOC L No Yes Discharge from the Battery Buy from Electronic Power Company P Et P E(t-1) +{SOC L - (B t-1 + D B EFF )} B t B t-1 + D B EFF B t SOC L Fig. 2.5 Analysis Procedure (Discharge) Fig.2.5 P Et SOC L (Fig.2.5 ) Fig.2.5 SOC Fig.2.6 (a) (d) 4 Fig Fig.2.6(a) (b) (c) ( ) (c) (d)

27 24 2 consume generate Battery Generate and Consume Battery Generate and Consume 5:00 12:00 19:00 t 5:00 12:00 19:00 t SOC U SOC L SOC U SOC L (a) (c) Charge t t SOC U SOC L SOC U SOC L Discharge 5:00 12:00 t 12:00 Opportunity Loss Buy from Electoric Power Company (b) (d) t t t Fig. 2.6 (a)battery Charge (b)discharge from the Battery (c)opportunity Loss (d)buy from Electronic Power Company.

28 METPV-3 (15) P (2.1) P = η X Y (2.1) Table. 2.1 Parameter for (2.1) P Output from PV [kw] η PV Conversion Efficiency 15[%] X PV Panel Area 1.323[m 2 ] Y Insolation Intensity [kw/m 2 ] PV η PV 1.323m 2 (=1.318m 1.004m) 0.191[kW] (17) Fig kW Electricity Generated[kW] Hour[h] Fig. 2.7 Calculated Value of Electricity Generated.

29 PV 1 (9) (10) (12) (12) (13) (14) 300 (Fig.2.8) NHK 1

30 start generate objects start month loop start day loop generate personal schedule start family unit loop control schedule between family members set room tag calculate energy consumption per a family unit end family unit loop calculate energy consumption end day loop end month loop end Fig. 2.8 Analysisi Procedure to Generate Consumption Data. (13)

31 NHK NHK Fig NHK Fig.2.9(a) 5.9 Fig.2.9(b) 1.3 NHK

32 Fig. 2.9 Comparing Acction Rate between Simulation Data and NHK Research (13).

33 30 2 Fig (16) Fig Comparing Consumption Energy between Simulation Data and Statistics (13) (16).

34 Fig Electricity Consumption[kW] Spring(April.10) Summer(Sep.10) Autumn(Oct.10) Winter(Jan.10) Hour[h] Fig Example of Electricity Consumption of a house.

35

36 33 3 PV- 3.1 PV- PV Electric Power System Photovoltaic Cell Power Meter Distribution Switchboard Electrical Appliance Joint Box Li-ion Battery Power Conditioner Fig. 3.1 Concept of PV-Battery System. Fig.3.1 PV- PV PV

37 34 3 PV- 3.2 Fig.3.3 (a) (b)co 2 (c)co 2 (d) BU 1 SOC SOC SOC 100% (Fig.3.2) SOC(:State Of Charge) SOC BA[%] Upper SOC max charge discharge BA Lower SOC min 1 min 2 0 t 23 Fig. 3.2 Battery State of Charge BU (3.1) BU[%] = (max min 1) + (max min 2 ) 2BA 100 (3.1) CO 2 PV CO 2 CO [kg-CO 2 /kwh] (18) PV [kg- CO 2 /kwh] (19) CO 2 PV

38 CO 2 kwh 20 Fig.3.3 (a) CO 2 20kWh (c)co 2 CO 2 CO 2 20kWh

39 36 3 PV- Battery Utilization [%] (a) CO Emission Reduction[Ton] 2 Opportunity Loss of CO Emmition Reduction[Ton] 2 Cost of Battery [10,000yen] (b) (c) (d) Battery Capacity[kWh] Fig. 3.3 Battery Capacity and (a)battery Utilization (b)co 2 Emission Reduction (c)opportunity Loss of CO 2 Emission Reduction (d)cost of Battery.

40 C I C DI PV C E min C I = C DI + C E (3.2) (3.2) C DI C E (3.3) (3.4) C DI = (X Bat C Bat + X PV (C PV + C CON )) (1 + µ) Y (3.3) C E = W C Buy (3.4) Table. 3.1 Parameter for (3.2)-(3-4) X Bat Capacity of Li-ion Battery [kwh] C Bat Initial Investment for Li-ion Battery 200,000[yen/kWh] (20) X PV Capacity of PV 4.5[kW] C PV Initial Investment for PV 650,000[yen/kW] (21) C CON Cost of Power Conditioner 40,000[yen/kW] µ Maintenance Cost 1% of Equipment cost C DI Y Durable Years 20[years] W Energy buying from Power Company [kwh] C Buy Electricity Expence 23[yen/kWh] SOC State of Charge 15-80[%] B EFF Battery Charge Efficiency 90[%] B t=1 Initial Capacity of the Battery 50[%] 15% 85% PV 4.5kW 300 AC/DC

41 38 3 PV Fig kW PV 20 /kwh PV Total Cost Panel Cost Electric Cost Battery Cost Cost[10,000yen] (Equipment+Electricity Expense) Capacity of the Battery[kWh] Fig. 3.4 Cost per year.

42 (20) NEDO 2030 (21) PV PV 4 Table.3.2 Table. 3.2 Future Scenario (13)(14) Scenario Battery PV PV Conversion [10,000yen/kWh] [10,000yen/kW] Efficiency[%] Fig kwh 3 /kwh kWh /kw PV 15 /kwh PV

43 40 3 PV- Current Cost 2010 prediction prediction 2030 prediction Cost[10,000yen] (Equipment+Electricity Expense) Capacity of the Battery[kWh] Fig. 3.5 Comparing the Cost for 4 scenario. 3.5 PV PV (PV:65 /kwh :20 /kwh) PV PV 15 3

44 Fig [kW 2 ] 0.29[kW 2 ] [kW 2 ] Fig.4.2

45 Variance s 2 =0.42 s 2 =0.66 s 2 = s 2 = s 2 =0.13 s 2 = Averaging Consumers energy Averaged Consume Energy per family unit[kw] 5 4 s 2 = Time[h] Fig. 4.1 Smoothing Effect by Combining 6 Family s Energy Consumption Electric Power System Photovoltaic Cell Li-ion Battery Fig. 4.2 Concept of Battery Sharing System.

46 Fig.4.3 Battery A[kWh] Battery C[kWh] Battery B[kWh] Battery D[kWh] Battery A+B+C+D [kwh] Owning Battery Individualy Sharing Battery Fig. 4.3 Analysis the Effect of Sharing Battery( with 4 Family ). PV PV PV (3 /kwh) PV 300 Fig.4.4(a)

47 kWh (Fig.4.4(b)) 2 PV PV PV 2

48 PV size Capacity of the Battery 40 Capacity of the Battery[kWh] Power Consumption per year[kwh] (a) PV size[kw] Capacity of the Battery[kWh] Power Consumption per year[kwh] (b) PV size[kw] Fig. 4.4 Capacity of the Battery and PV for 300 Family. (a)individual Battery Capacity. (b) Same Battery Capacity.

49 C S (4.1) (4.2) C DS PV C E min C S = C DS + N C Ek (4.1) k=1 C DS (4.2) C E (3.4) C DS = (X S Bat C Bat + X PV (C PV + C CON )) (1 + µ) Y (4.2) Table. 4.1 Parameter for (4.1)-(4.2) X SBat Capacity of the Sharing Battery [kw] N Family Unit Number Sharing the Battery C Bat Initial Investment for Li-ion Battery 30,000[yen] C PV Initial Investment for PV 150,000[yen] C Bat C PV Table C (4.3) C I (3.2) C S (4.1) N N C = C S N k=1 C I k (4.3) OL (4.4) N N OL = L S N k=1 L I k (4.4)

50 Table. 4.2 Parameter for (4.3)-(4.4) L S Opportunity Loss(Sharing Battery) [kwh/year] L I Opportunity Loss(Owning Individually) [kwh/year] OL C 100% 4.4 (Fig.4.5(a)) (Fig.4.5(b)) Fig4.5(a) 3316[kWh/ ] [kWh/ ] 1.3% [kWh] 3.5%

51 48 4 4% Fig.4.5(b) / % 2279 kwh kwh 10

52 OL'[%] Individual Battery Capacity Same Battery Capacity OL'=98.7[%] Ls= [kWh] L I = [kWh] OL'=96.5[%] L S = [kWh] L I = [kWh] (a)opportunity Loss 100 4% 1.2% 0.6% C'[%] 99 C'=99.4[%] C S =109.52[10 4 yen] C I =110.18[10 4 yen] 1.5% 98 C'=98.3% C S =109.55[10 4 yen] C I =111.38[10 4 yen] (b)cost Number of the Family Unit Fig. 4.5 Effect of Sharing Battery on Opportunity Loss and Cost

53 Reduction of CO Emission [Ton] Number of the Family Unit Fig. 4.6 Effect of Sharing Battery on CO 2 Emission Fig.4.6 CO 2 1 CO 2 PV PV CO 2 (18) PV (19) CO 2 PV CO kg 4% CO 2

54 Fig.4.5 Fig C 2 = % Fig OL OL =100% 89.5% Fig Home1 SOC Home2 SOC

55 52 4 OL'[%] Number of the Family Unit OL [%] Frequency Fig. 4.7 Histgram of Opportunity Loss(Sharing Battery with 2 Family).

56 Home1 Home2 Sharing Battery(Home1+Home2) Generated Energy[kWh] Consumption Energy[kWh] State of Battery[%] Opportunity Loss[kWh] Energy Buyingfrom Electoric Company [kwh] Time[h] Fig. 4.8 Movement of 5 Factors. (Dec.10-13)

57 PV 1.2% 0.6% 4% 1.5% CO 2 4% 10%

58 IT (22) (23) PV PV CO 2 Fig.5.1 PV 300 CO 2

59 56 5 Electric Power System Battery Battery Battery Fig. 5.1 Concept of Smart Grid System. 5.2 Fig.5.2 PV PV 23 /kwh 23 /kwh PV Fig /kwh 48 /kwh

60 Consume Use the Energy Generated from PV Shortage of Power Supply Use PV Energy from Other House 23[yen/kWh] Shortage of Power Supply Use the Energy from Battery 23[yen/kWh] Shortage of Power Supply Buy from Electric Power Company 23[yen/kWh] Fig. 5.2 Order of Power Consumption. Generated Energy from PV Use the Energy for Electric Demand in the House Surplus Power Sell the Energy to Other House 48[yen/kWh] Surpluse Power Charge the Battery 48[yen/kWh] Full Charge Opportunity Loss Fig. 5.3 Order of Generated Energy.

61 Table PV PV PV+Battery Smart Grid PV Smart Grid with Battery PV Table Scenario PV Battery SmartGrid PV - - PV and Battery - Smart Grid - Smart Grid with Battery PV 4 Fig.5.4 PV 300 PV 1/4 (PV Smart Grid) CO 2 (Smart Grid and Battery PV and Battery) 1/4 PV

62 PV Battery Electronic Company Energy Consumption CO2 Emission Energy[MWh] CO2 Emission[Ton] 0 Energy Consumption PV Smart Grid Smart Grid and Battery PV and Battery 0 Fig. 5.4 Detail of Energy Consumption for 4 Scenario.

63 Table kWh PV PV C PV C D C E PV 300 C Base C PV C PV = C D + C E C Base (5.1) PV C D (5.2) C E (3.4) C D = (X PV (C PV + C CON )) (1 + µ) Y (5.2) PV + Battery PV C PV+Battery (5.3) (5.4) C Base C PV+Bat = C D + C E C Base (5.3) PV C D (5.4) C D = (X Bat C Bat + X PV (C PV + C CON )) (1 + µ) Y (5.4) Smart Grid PV C PV 48 /kwh

64 /kwh 48-23=25[ /kwh] C BS C Base C PV = C D + C E + C BS C Base (5.5) PV (5.2) 300 C BS (5.6) C BS = W Sell C Sell W Buy C Buy (5.6) Smart Grid + Battery PV (5.7) (5.8) 48 /kwh kwh 23 C SG = C D + C E + C BS C Base (5.7) PV C D (5.4) C BS (5.8) C BS = (W Sell + W Charge ) C Sell (W buy + W Discharge ) C Buy (5.8)

65 62 5 Table. 5.2 Parameter for (5.1)-(5.8). X Bat Capacity of the Battery 16[kWh] C Base Electricity Expense for 300 Family [yen] W Sell /W Buy PV Electricity Selling/Buing from Other House [kwh] C Sell Cost of Selling Electricity 48[yen/kWh] W Charge /W Discharge Electricity Charging/Discharging from the Battery [kwh]

66 CO 2 Fig.5.5 CO /kwh PV 65 /kwh PV Table.5.3 Table. 5.3 Diffusion Rate of PV and Battery. PV Diffusion Rate Battery Diffusion Rate [%] [%] C CO 2 PV 100% CO CO CO 2 CO [ ]/200[ ]=20[ / ] CO 2

67 64 5 Amount of Reduced CO [Ton] Smart Grid and Battery PV and Battery B Smart Grid C PV D Total Cost[10,000yen] A C A D B Fig. 5.5 Reduced CO 2 and Cost for 4 Scenario. 2,420 (24) PV CO 2

68 Fig.5.6 CO CO 2 3 /kwh PV 15 /kwh (Table Scenario) PV Table.5.3 (Fig.5.5) 500 Smart Grid and Battery PV and Battery Smart Grid PV Amount of Reduced CO [Ton] Total Cost[10,000yen] Fig. 5.6 Reduced CO 2 and Cost for 4 Scenario(Future Cost).

69 66 5 PV PV 300 PV CO 2 PV 100% (Smart Grid and Battery PV and Battery) CO 2 CO 2 25,000 CO / Smart Grid and Battery CO 2 10 Fig.5.7 CO 2 PV PV and Battery Smart Grid and Battey CO 2 PV CO 2 PV 100% (Fig.5.7A) PV CO 2

70 Smart Grid and Battery PV and Battery Current CO 2 Emission Amount of Reduced CO [Ton] Battery Capacity [kwh] A Fig. 5.7 Relation between Battery Capacity and CO 2 Emission.

71 PV CO 2 CO 2 PV 1000[ / ]/300[ ]=3[ / / ] Energy[MWh] Battery (W Discharge ) PV from Other House (W PV ) PV from Own House Electronic Company (W Buy ) Energy Consumption Fig. 5.8 Detail of Consumption Energy. 300 Fig.5.8 (Battery:W Discharge ) PV

72 (PV from Other House:W PV ) PV (PV from Own House) 3 PV PV PV 48 /kwh 23 /kwh 25 /kwh kwh (5.9) (W Discharge + W PV ) (C Sell C Buy ) = (W Discharge + W PV + W Buy ) (C Buy 23) (5.9) C Sell C Buy (W Discharge + W PV + W Buy ) 23 /kwh C Buy 300 (5.9) C Sell Fig /kwh 30.8 /kwh (23 /kwh) 3 PV kwh 48 PV Fig.5.9 C Buy

73 Cost of Electric Expence C [yen/kwh] Buy Cost of Electoric Power Selling C Sell [yen/kwh] Fig. 5.9 Relation between Cost of Electoric Selling and Buying.

74 kWh 32kWh CO 2 PV 100% (20% 50% 80% 100%) Fig.5.10(a) 16kWh CO 2 32kWh 32kWh 16kWh CO 2 32kWh CO 2 Fig.5.10(b) CO 2 32kWh CO 2 16 Wh 3 CO 2 (Fig.5.10) CO 2 Fig.5.9(b) (Fig.5.11) 16kWh 300 (4.8MW)

75 Battery=16kWh Battery=32kWh Amount of Reducted CO [Ton] Total Cost[10,000yen] (a) Owning Battery Individually Battery=16kWh Battery=32kWh Amount of Reducted CO [Ton] Total Cost[10,000yen] (b) Sharing Battery Fig Comparing Battery Capacity 16kWh and 32kWh. (a)owning Battery Individually (b)sharing Battery.

76 CO Emission Reduction[Ton] Battery Capacity[kWh] Fig Relation between Battery Capacity and CO 2 Emission Reduction. (Fig.3.3(b)) BT BT BT BT Battery Fig Sharing Battery using Smart Grid Network.

77 PV CO 2 PV PV PV PV 4 PV CO 2 PV PV 100% 300 CO % CO PV CO 2 PV , PV 100% /kwh /kwh 300 1

78 CO 2 PV CVCA

79 PV ( 3 ) PV ( ) CO 2 PV PV 3 /kwh PV 15 /kw PV PV PV ( ) PV ( ) PV (26) (27) Fig.6.1

80 CO 2 PV Fig.6.2 PV Hydroelectric(Pumped-Storage) Hydroelectric(Reservoir) Hydroelectric (Run-of-River) Oil Coal LNG, LPG Nuclear Hydroelectric(Pump Hydroelectric(Rese Hydroelectric (Run Oil LNG, LPG PV Power Generation Power Generation PV Hour[h] 0 12 Hour[h Fig. 6.1 Electric Power Generation (27). Fig.6.2 PV CO 2

81 78 6 (Pumped-Storage) (Reservoir) (Run-of-River) Coal Nuclear Hydroelectric(Pumped-Storage) Hydroelectric(Reservoir) Hydroelectric (Run-of-River) Oil Coal LNG, LPG Nuclear PV Power Generation PV our[h] Hour[h] Fig. 6.2 Prediction of Electric Power Generation. PV CO 2 (28) PV CO 2 PV

82 79 ( 4 ) PV CO 2 CO 2 4% PV PV PV PV PV PV 4% ( 5 ) PV

83 80 6

84 PV PV PV PV PV 3 3 PV NEDO 3 /kwh PV 15 /kw 4 NHK

85 82 7 NHK % CO CO 2 PV CO PV CO 2 PV CO 2 CO

86 Win-Win PV 3 PV CO /kwh PV15 /kw PV CO 2

87

88 85 cseed cseed 03 2

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90 87 1) Kevin Forsberg Hal mooz Howard Cotterman Visualizing Project Management (2005). 2) IPCC 4 (2009). 3) (2009). 4) (2009). 5) 2009 (2009). 6) IEEJ Journal, Vol.125 No.3 p (2005). 7) FTE (2009). 8) FTE (2009). 9) IEEJ Trans. PE Vol.123 No.3 p (2003). 10) (2) IEEJ Trans. PE Vol.124 No.10 p (2004). 11) (2007). 12) - - T99006(1999).

91 88 13) (2009). 14) P (2009). 15) METPV-3. 16) ( ) ) SHARP ND-191AV. 18) CO 2. 19) CO Y99009(2000). 20) (2006). 21) 2030 (2004). 22) - - (2009). 23) U.S. Department of Energy. 24) JBIC 2008 (2009). 25) (2005). 26) kw FTE (2009). 27) (2009).

92 89 28) Just-In-Time Modeling FTE (2009).

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94 91 :

95 FTE * Effect of Sharing Battery set with Photovoltaic System Emiko Tsuji*, Toshiyuki Seto, Shoichi Sasaki (Keio University) Tomoyuki Murakami (Tokyo Institute of Technology) Abstract Reverse power flow from the Photovoltaic system causes deviance from voltage value which is defined by law. Setting battery with Solar power system can solve this problem. In this paper I simulated the size of the battery that can minimize the cost of installation personnel, using estimated electricity consumption data based on human living activitiy pattern. I also indicated the effect of sharing battery with several family unit. (Photovoltaic(PV), Li-ion Battery, Sharing Battery ) PV:Photovoltaic PV PV (1) PV (2) (3) (4) (4) PV (7) (5) 365 PV PV 2. PV- PV- 1 PV PV 1/6

96 Photovoltaic Cell 1 Fig. 1. Load Li-ion Battery Power Conditioner Switch Signal of Reverse Power Flow Wh Reverse Power Flow Detecting Device PV- Concept of PV-Battery System. Electoric Power System Electricity Generated[kW] Hour[h] No start PG t, PC t (t : 0 -> 365*24) trial_time=0 No t = 0 Select home data. trial_time++ P' = PG t - PC t P' > 0 Yes B t < X Bat * SOC U Yes t++ t == 365*24 trial_time==end end Yes Yes No B t = P' + B t-1 No P L += X Bat * SOC U - B t B t = X Bat * SOC U Fig B t > X Bat * SOC L Yes Analysis procedure. Calculate Battery SOC No P E += X Bat * SOC L - B t B t = X Bat *SOC L 2 P G t P C t t B t t X Bat SOC U SOC L P E Fig Calculated value of Electricity Generated (average of ). P L < > < > METPV-3 (5) P (1) P = η X Y (1) P PV [kw] η PV 15[%] X PV [m 2 ] Y [kw/m 2 ] PV η PV m 2 (= m m) kw (6) 3 4.5kW (7)(8) NHK 2/6

97 Electricity Consumption[kW] Fig Spring(April.10) Summer(Sep.10) Autumn(Oct.10) Winter(Jan.10) Hour[h] 4 1 Example of Electricity consumption of a house C I X Bat C DI PV C E min C I = C DI (1 + µ)/y + C E (2) C DI = X Bat C Bat + X P V (C P V + C CON ) (3) C E = W C Buy (4) X Bat [kwh] C Bat 20[ /kwh] X P V PV 4.5[kW] C P V PV 65[ /kw] C CON 4[ /kw] µ C DI 1% Y 20 W [kwh] C Buy 23[ /kwh] 15% 85% 90% 50% PV 4.5kW 300 Cost[10,000yen] (Equipment+Electricity Expense) Total Cost Electric Cost Panel Cost Battery Cost (200,000yen/kWh) Capacity of the Battery[kWh] 5 Fig Table 1. Cost per year. Scenario Prediction. Scenario Battery PV PV Conversion [10,000yen/kWh] [10,000yen/kWh] Efficiency[%] kW PV 20 /kwh PV PV PV 4 1 (9) NEDO 2030 (10) 3/6

98 Cost[10,000yen] (Equipment+Electricity Expense) Current Cost 2010 prediction prediction 2030 prediction Capacity of the Battery[kWh] Consume Energy per family unit[kw] 5 Variance s 2 = s 2 = s 2 =0.08 s 2 = Adding all Consumers energy... s 2 = s 2 = s 2 = Time[h] 6 Fig. 6. Comparing the Cost for 4 scenario kwh 3 /kwh kWh /kw Photovoltaic Cell 7 6 Li-ion Battery Load Fig. 8. Fig Effect of Superposition. Signal of Reverse Power Flow Switch Load Wh Reverse Power Flow Detecting Device Load Concept of Battery Sharing System. Electoric Power System [kW 2 ] 0.29[kW 2 ] [kW 2 ] 8 Battery A[kWh] Battery C[kWh] Owning Battery Individualy 9 Battery B[kWh] Battery D[kWh] Battery A+B+C+D [kwh] Sharing Battery (4 ) Fig Effect of Sharing Battery. 9 PV PV 10 PV 4/6

99 Capacity of the Battery[kWh] PV size Capacity of the Battery Power Consumption per year[kwh] 300 PV PV size[kw] Fig. 10. Capacity of the Battery and PV size for 300 data C S (5) (6) (7) C DS PV C E min C S = C DS (1 + µ)/y + C E (5) C DS = X SBat C Bat + X P V (C P V + C CON ) (6) C E = W C Buy (7) X SBat [kw] N (2-20 ) C Bat C P V C (8) C = C S P N (8) k=1 CI k OL (9) OL = L S P N (9) k=1 LI k L S [kwh] L I [kwh] [kWh/ ] 8 40[kWh/ ] 1.3% C'[%] OL'[%] Fig. 11. Reducing Opportunity Loss and Cost by Sharing Battery. N=6 L S = [kWh] L I = [kWh] OL'=98.80[%] N=6 C S =82.13[10,000yen] C I =82.61[10,000yen] C'=98.80[%] Number of the family unit / 830 / 0.6% kwh kwh PV 3 /kwh 300 PV 1% 0.6% 5/6

100 COE 1 IEEJ Journal Vol.125 No.3 p IEEJ Trans. PE Vol.123 No.3 p IEEJ Trans. PE Vol.128 No.5 p METPV SHARP ND-191AV P /6

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