特集 エネルギーマネジメントシステム（EMS）
Contents
1. LNG 1 5 Nm t 2 4 2 LNG 3 0 Nm t 2 12. EMS 5 eA
3. Z CN PSO Particle Swarm Optimization DE Defferential Evolution
4. 5 WAIVE SO 7 A E TRMRICHW TC 1 A589 kWh 5 150 kWh BAI
5. 1 A cogeneration plant provides steam and electric power required for paper factories Fuji Electric has developed and delivered an energy optimization system for the cogeneration plant of a paper factory The system is capable of monitoring the state of various facilities including power steam loads and the amount of steam produced by an exhaust heat recovery boiler which fluctuate greatly in the factory The system can thus optimize the operation in real time according to the supply demand balance of power and steam Since the system au tomatically optimizes loads so that contracted electricity limits are never excee
6. The output of renewable energy sources such as solar and wind power fluctuate frequently Therefore it is concerned that maintaining the supply demand balance in a rural area or an isolated island is difficult To solve this problem Fuji Electric has developed a hierarchical supply and demand control system with different control cycles for supply and demand planning economic load dispatching control and load frequency control The above functions of the developed system have been verified by digital simulations with promising results O FADS
7. 3 U XML J J EL He i H73 1 AJW WFT 1
8. 11 16 1 3 4 5 S 1 X lan 2 6 e 25 30 35 AO C 10 16 20 Ol O Ol 3 4 5 11 9 13
9. 2 4 2 1 MES MES EMS 2 MES MES 5
10. BBS PSAA ES 2013 vol 86 no 3 181 25 OEM PANG TUX EMH M Zm FYINVTLKUNA TENH ahah EMS EMS EMS for Large scale Commercial Facility KOMATSUBARA Shigeru JA Aap XIANG Donghui YAMADA Yasuyuki EMS
11. xEMS xEMS xEMS HEMS
12. Esje 2 lt gt 2013 vol 86 no 3 174 18 1 PLC
13. 2013 vol 86 no 3 176 20 1 2011 vol 84 no 4 D 234 236 2 2008 vol 81 no 2 p 130 134 Hl Me FEMS Awl E
14. 9 4 EAR 4 1 FeTOP
15. EMS Energy Management System oe i o NEE EMS
16. IF MPC PV F MPC PV String Monitoring Unit for Photovoltaic Power Generation Systems MACHIDA Satoshi 2012 7 CPV Photovoltaic PID Potential Induced Degradation PV 10 10 BE PV
17. EMS 2013 vol 86 no 3 191 35 DEM ENING TUXLAA HENH Ma NSM FYINVTLKUNA AENH ahah EMS 2013 vol 86 no 3 192 36 EMS
18. EV UPS PCS EE 86 4 Tt ke Re AR BE Tt amp ET K a aU FR TF ie BE R pi
19. SOC B 2013 vol 86 no 3 203 47 OEM ENING TUX HENH Ma Zm FYINVTLKUNA TENH Mdh
20. ERENIC Mini C2S 2002 FRENIC Mini C1S 2013 1 200V 400 V 200 V O ERENIC Mini C2S 2 1 200 V 400V 200 V 2 FRENIC Mini C1S 3 RS 485 FRENIC VG FRENIC Mini 0 104075 37 152230 kW 560 630 710 3 200 1 BBR YI
21. EMS J EMS EMS In the energy environment surrounding customers of electrical power in Japan major changes are underway in regards to the supply demand balance and the cost of energy usage and energy cost reducing measures such as strengthening energy management and introducing energy saving equipment are urgently needed With a proven track record for successfully installing EMSs at major customers of electrical power Fuji Electric has aggregated energy saving analysis know how accumulated in energy management operational support and has begun supplying an energy management support service based on a shared use EMS tha
22. 0 5 2 3 CEMS on HEMS Home Energy Management System BEMS Building and Energy Management System FEMS Factory Energy Management System SEMS Store Energy Management System a ie IWS AT ht OE OTT BEMS HEMS
23. F MPC PV 2 2 1 FEF MPC PV 3 2013 vol 86 no 3 211 55 F MPC PV 1 F MPC PV HE t at DC1 0 10 0 Ax 1 FS 1 fe E DC100 1 000 Vx 1 FS 196 DC24V 5 mAX O 1 Ra i a E 25 75C 5 CLIN W284xH128xD71 mm DIN MCCBISPD _ ali 1 SPD 2 MCCB 3 PCS
24. 5 4 E a 10 E b
25. CO BR BR CR 3
26. 5 1 BFG COG HEADS LDG 90 1 COG BFG 4 2 1 COG BFG
27. 03 5435 7002 2013 7 1 HH 7J m 20134885 30 H Web 2013 S04 3 2013 vol 86 no 3 221 65 MULTI VCB Vacuum Circuit Breaker Fixed Type MULTI VCB OKAZAKI Takayuki 6kV VCB Vacuum Circuit Breaker JIS C 4620 VCB
28. 2 2 EDC CEDC EDC 4 UIC EDC N Objenc gt gt a P t b P t c 88 EE EE ai 2 7 2 P e Proaa t Pk tower t lt P t lt P x upper t O P t 1 P t lt CS E A A SE E 5 2 Objrpc Prioaa t 7 Px towerltti Pr upper tti
29. Beith SOC 60 fae I4 1 2010 2 IAE 051544 NEDO 2006 3 2009 4 PTR AAI D
30. xEMS L Cs xEMS WR
31. REF SCE CARERS Mil 3 2013 vol 86 no 3 220 64 CO 400 80 CC s a b 4 3 3 CO KN 95 KK CO 5 CO ISN STKE TIA CO KN 95 CO OMT ARES S elk
32. EMS 2 2 1 1 2 CIA R HAA 3 4
33. a b 192 c a 1 EMS 30 2013 vol 86 no 3 207 51 OEM PYNC TUX EMH M Zm FYINVTRKUNA TENH ahah HF 1 gt lt 4 0 Annie f 1 A 1 J 1 3 3 1
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35. POD Fae POD 3 2 J EZAT AEC ACTS YA PIF EI paar KE 1
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37. 0kW 5 30 CL 30 30 ak Clk AHL SOC 60 i 4 kW 0 1 800 3 600 s 5 2 SOC LT 30 3 30 5 39 6 7
38. xEMS xEMS xEMS Off xEMS
39. 2011 2011 10 ER Ic 2013 vol 86 no 3 172 16 6 2012 2014 1 http www meti go jp committee summary 0004668 011_03_00 pdf 2013 6 28 2 CPP 2012
40. SPC Set Point Control SPC DSPC EeTOP 2
41. EH PA Mew nie E 5 1 COD 1 1 6 EMS CPU DYME KU BIE SEBLU Fe
42. 3 2 20 EMS 30 EMS Clk D 2 1 ABT
43. IEEE 2013 vol 86 no 3 201 45 OEM PHN TUX EMH M Zm FYINVTRLKUNA TENH ahah TIR EMS Supply and Demand Control System for Power Systems with Distributed Power Supplies 444 KATSUNO Tohru IIZAKA Tatsuya Fe HAYASHI Naoki
44. 2 COBDS BEG EMS au CC 2 EMS 1 E EMS EMS EMS EMS DIZ 1 Fuji Service Bus EMS Fuji Service Bus
45. Fo tee Innovating Energy Technology 86 3 879 2013 9 30 Innovating Energy lechnology 3 ae ti Mii say lig f e r a i f P F F r G F ee wa sh z eee mi hili E gr ce 5 a F EB 07797 9 735 700
46. Cconsumer Crosumer Oi oo 1 K EMS 2
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48. Web EMS 2 BA HA AR A 3 Field Connector Field Connector 4 EMS 2013 vol 86 no 3 197 41 OEM PYNC TUX EMH M Zm FYINVTRLKUNA AENH ahah 1 mA EMS
49. 4 3 BEMS BEMS Building and Energy Management System 1 BEMS Slik BEMS 2013 vol 86 no 3 195 39 OEM PANG TULA EMH M Zm FYINVTRLKUNA TENH ahah EMS an BEMS P UJ BEMS BEMS
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52. 3E EC SCN 2010 6 2020 10 2020 2 800 kW 490 kW
53. 30 30 1 2 CPU CPU CPU 3 4 30 1
54. SX Net 0 5 30ms DOA CIR GW HE CHU 8K ms 64 128K 2013 vol 86 no 3 226 70 2048 2 1 SX Net LO SX Net 3 2 E SX MICREX SX SPH3000MG E SX
55. 2 5 13 900 Tobes TIY FARVA TI ML EDo TLALI 2 1 SH 1 18 14 16 31 3 4 3 3 4 3 4 O 4 3 5 3 O 5 3 5 2 O 2 0 1 8 q q 1 6 1 4 S l2 Z Rk KE 0 8 0 6 Da U bb 02 5 0 6 he 18 24 Elle 1 28 5 1 3 X 4 5 kW CC 13 9 20 F 5 lt fH 10 T F 5
56. 2013 vol 86 no 3 160 4 3 HEMS Home Energy Management System O CHD K BWA Fly HEMS BN yh ee NES Ce Es E 4 5 EMS Energy Management System O CHS wee BEMS CEMS PEMS HEMS REMS 7 3 6 CEMS
57. EMS EMS 1 FROWNED 2011 vol 84 no3 p 214 218 2 B 2004 vol 124 no 5 p 679 682 3 Kennedy J and Eberhart R Particle Swarm Optimiza tion Proceedings of IEEE International Conference on Neural Networks 1995 vol IV p 1942 1948
58. 2013 vol 86 no 3 210 54 1 2010 vol 193 no 3 p 217 221 2 2011 MES 11 004 3 B 2007 vol 127 no 7 p 847 853 4 2009 p 127 130 5 2010 no 6 076 6 2012 no 6 021 7 B 2011 vol 131 no 3 p 64 71 8
59. 1 a b c d e 2 a b c 2 2 EMS T EMS EMS
60. a et 9 Koh KU b EMS Clk eR EIS 1
61. ee KURAJ EY BERRICKS BEEN E THDNOW A 2 TF DAR CHAD CWS 6 2013 vol 86 no 3 173 17 OEM PANG TUX EMH at Zm FYINVTRLKUNA TENH ahah
62. 2 2 12 2 2 5 10 11 42 3 5 18 5 1 28 20
63. 2009 no 161 5 Any Je VU ZAC th 4H 2002 no 869 6 1989 no 302 7 2006 8 2010 no 227 9 ELD B 1988 vol 108 no 4 p 141 148 0 E 2010 no 225 2010 no 106 2013 vol 86 no 3 205 49 OEM PANG TULARE MH M Zm FYINVTRLKUNA TENH ahah 2
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65. Fe FSE 30min Merwe ewa COPY ee ERA epg wee HTAR e a TNEB Dmh ET ee md i Em eE EE a ma EE a ee ee Em 1 ham a i E 4 2013 vol 86 no 3 200 44 TL Joa ww EE es yema SSS ain HA R tt AA L__ By iat Banh Tange arein c COONOCrsiBPtOLT Ho To osm OTs OMe gt u m TF E E3 a i 5 4 EMS cues EMS BRE EMS 177 CPR EMS EMS 6
66. 2 2012 no 6 119 3 2005 vol 78 no 6 p 423 430 ae gt N NS 2013 vol 86 no 3 206 50 ee
67. 32 2010 FEDD 5 163 CEMS Cluster Energy Management System T 2012 le 2 1 120ha 1D 2013 vol 86 no 3 166 10 1
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69. 8 5 CEMS CEMS LAN NS 30 44 ADRESS AA al ae PT JEMIC Japan Electric Meters Inspection Corporation 2013 3 225 50
70. 11 1 2010 We ae A a OO Cee 120ha 2014 COME CHS OMI 2013 vol 86 no 3 163 7 DEM ENING TUX KENH Ma Zm FYINVTLKUNA AENH ahah EMS CHU BRICHDSZHAAZPA eS ill ee ae se BEND Tapers OD le al We
71. 2013 vol 86 no 3 185 29 DEM ENING TUX HENH Ma I Zm FYINVTRLKUNA TENH Aah EMS 25 C 65 Pith 207 Se en 1 1800 mma HF T nae m zaman m BANHA 27 81 HAR Richa 7 66 iA HE 226 Ah 9 lt c EMS 4d
72. xEMS 2013 vol 86 no 3 159 3 OEM PYNC TUX EMH M TIR EMS EMS Energy Management System EMS Current Status and Future Outlook SHIRAKAWA Masahiro KOBAYASHI Naoto z KUWAYAMA Jimpei Zm FYINVTRLKUNA AENH Midh 0 FADS 4 LNG 1 COs Oe HB MS
73. 80 us SX Net TC TS MMSGMTCl TS IMSG Ill DB HMI SX Net Hy JA E JA SPH3000MG ESX SPHG3000MG RSX RSX TC TS MSG 4 ISX Net E SX 2013 S06 2 a MICREX SX SPH3000MG 042 585 6239 2013 10 2013 9 HB 30 H Web 2
74. EMS 3 2 1342577 RBH SBD ATA CEMS a 4i Ethernet 5 Ic 300kW
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76. 40 000 KIE 1 gt PCI Express PCI SIG QE 2 Ethernet 2013 S06 1 2013 vol 86 no 3 225 69 HH 7J A a PDCS 7 1 7 1 l a EE i ELE 22009 Lagu hi E MI Z 2 x PDCS Process Data Collection System 2 PDA Process Data Acquisition 3 a b c MICREX SX SPH3000MG MICREX NN KU
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81. To promote further energy savings the demand for electrical thermal and other types of energy and the amount of energy supplied by self generation facilities must be integrally managed and planned Fuji Electric has developed a framework for optimal planning systems that runs on the integrated EMS platform This framework has a uniform energy network model that automatically generates a plant model according to the arrangement and connection of equipment on a display screen and an optimal planning function that develops operational plans As a result the configuration and properties of the equipment can be changed and maintenance can be performed without the need for a professional engineer and operational planning becomes easier 0 CO
82. FeTOP 2003 Wears 9SU000MEMSSae a Voy Sp HS 3 EMS 2013 vol 86 no 3 162 6 TK t RZ EMS 2000 2010 8019 2014 3 o 1998 11 2005 o2011 ISO i o 2000 o 2005 2008 02012 IE
83. PC O gt 2013 vol 86 no 3 186 30 ii ee o s o S estas TE eae o GER JOP o HUE o Li 10 3 2 ei HERE as Se EBMS EMS 4
84. eC Z aa a le 300 kW EMS xEMS 159 3 EMS 160 4 166 10 AB Oe 173 17 EMS J 177 21 EMS 182 26 I se EMS 188 32 EWO EMS 193 37 EMS 197 41
85. J 4 2 Net LCD fe C amp S 1 1
86. Da ee ee 2013 vol 86 no 3 165 9 OEM PNG TUXLAA EMH M EMS Public Demonstration of Dynamic Pricing in the Kitakyushu Smart Community Creation Project AG OGA Eiji e KABASAWA Akihiro 4 CEMS Cluster Energy Management System CO 50 2012 15 150 kWh 5 FIL C9 13
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89. EMS 1 p 2 http www shindan net jp pdf commercial_bldg pdf 2013 07 19 2 20 3 p 2 http www enecho meti go jp topics 080804 3 pdf 2013 07 19 3 2011 vol 84 no 4 p 234 238 4
90. CO 2 2 1 PDCA 1 KITS 2 3 4
91. Pou YP ae Erans Bemp ee 5 Pu y Piae Frans no E LOL 3 B C 10 20 25 30 35 C 3 4 4 5 Sik 3 GSM 4 3 24 4 7
92. 3 5 2 LDG 4 2 2 LDG 3 1 4 5 2 A 8 5 5 2 8 i CSS Loohey fa ae 4 2013 vol 86 no 3 180 24 ma ET Se e ee bd CT si Kia at xl
93. 2013 vol 86 no 3 175 19 OEM PNT EMH M NSM FYINVTRLKUNA TENH ahah 5 2012 11 GR
94. CEMS Energy Management System 2 1 2013 vol 86 no 3 202 46 ee lt a f 3 ER Sal Aal ea sal A 1 EREE AT LORE
95. EMS Photovoltaic Power Generation Forecasting Technology for Supporting Energy Management Systems ISHIBASHI Naoto IIZAKA Tatsuya KATSUNO Tohru With the aim of realizing a low carbon society photovoltaic power generation is being promoted worldwide The amount of photovoltaic power generation will fluctuate dramatically according to the weather conditions and may adversely affect the power system if introduced in large quantities Therefore it is nec
96. 4 EMS 2 4 B BB CO 6 4 B 2013 vol 86 no 3 184 28 PULTS 4 P
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98. F MPC PV 1 PV 2 PV CCS Power Conditioner DC500V 1MVW DC10 A 1 DC10A 200 PV 1 F MPC PV E ea pe Ar tll ARS LAE AEE ATH BH 6 CHG BB Pe FED 2013 S01 1 ence EZE EEE Pcs 2 MCCB BR a yii ae 1 MCCB EL PCS
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104. Seth EMS EMS A Framework for Optimal Planning Systems on the EMS Platform iff KAWAMURA Yu 46 HORIGUCHI Hiroshi ONO Takeshi EMS KU
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106. Q0 3 1 1 48 30 PC CPU Pentium4 3GHz 1GB 1 5 BARR mate 3 LINGO 1 100
107. Se le I a IKE CEMS Eero CAT RIE 200 ie BS i EnersoyG Alh OY 7 os 7a a7 gl EMS H le o iene ENS Bia 2 Er EMS 3 EnergyGATE CRED UDG 29 mea BMS Z gt So ap Clee A eas emo ie EMSS Zo Sse SO Eee Fuii Service Bus
108. 3 4 U 1 2 1 000 30 800 E DOF amp 600 S 400 in 10 Q BH O 200 0 O 0 1 000 2 000 3 000 s 1 5 CO 2013 S04 2 CO IKN 95 D
109. NEDO Tre 2008 p 425 429 9 B 2013 vol 133 no l p 304 312 10 4 2000 841p 2004 vol 48 no 5 p 165 170 moe 0
110. N T T TED 3 4 5 2 3 LFC 6 TOK
111. 8 TUE i A 0 i Uf i a xi x wi 2 2013 vol 86 no 3 193 37 OEM PNG TUX EMH M NSM FYINVTRLKUNA TENH ahah EWO EMS EN 1AOIYbFO F EMS a VAT LAE b c da a Be e a oe 3 3 1
112. CU 2014 CEMS CEMS EMS Wr Bo BEMS HEMS 4 GEMS
113. EMS EMS 2 2 EMS 1979 RE 9 FEMS EMS elk elike ilVCe a 1997 47 lala He ek mie Es IL Ags Ze MAREE SHEL ia oS el Viatehe SI SL o 1995 2000 P LNG 1973
114. LAN 7 3 2 V7f LAN 7 RS 485 2013 vol 86 no 3 217 61 FRENIC Mini C28 3 3 4 23 HH HRS SCE CRB ORIN TOR H OM ti OT HEC AS 2
115. MULTTL VCB 1 R 1 b 1 MULTI VCB Be E FE Be ar tl PARK Se EL BASE gt ERA BH EC HG OB bal FS H 2013 vol 86 no 3 222 66 1 IMULTI VCB xt HA12A H 3 6 7 2 kV 12 5 kA 600A 22kV 1min 60kV 50 60 Hz 20kA 31 5kA 2s 8 kA 1 5 kA semens au 0 0358 3 1 000 2ateb 3a 3b 3 E 26kg 27kg O CO O 1 1 1
116. TJs 2 8 3 EMS CORE 7
117. EMS ss ski EMS Steel EMS Package Optimizing Energy Management at Steelworks NARUMI Katsunori KIMURA Takayuki WATANABE Takuya EMS ET With the installation of an energy center and the central management of various types of large quantities of energy at a steelworks a comprehensive approach to energ
118. 4 EMS EMS CEMS 3 CEMS CEMS 2013 3 HEMS 10 tha Ic 38 A BEMS FEMS FR 8 DP Dynamic Peime 2013 vol 86 no 3 168 12 BEMS HEMS BART TIL HEMS BEMS 27 H RAST EFA
119. 2013 vol 86 no 3 228 72 Innovating Energy technology We A lt Ds ZININ os ol H ae oj FO stan F pil Bil
120. B 3 1 3 3 2 KN 95 lk CO 4 400 C 80 C CO
121. A CRS 485 Ethernet LonWorks JETB Q 1 Ethernet lt 7 2 gt LonWorks Echelon Corporation a m La CED g aml oS ee LCD Ethernet 4 T 1
122. 2013 vol 86 no 3 183 27 OEM PING TUX EMH M NSM FYINVTLKUNA TENH ahah EMS Fu u EMS Sooo msl se Poses Yet ei A Stace sas J 4 sims ASh ES A ET 3 EMS CEMS DRA la Ff BER A AE T Baie
123. EMS BEMS EMS mo Ein 25 4 QEG En 5 EMS QE Er NBER 10 DE Gl ae BEMS 2012 MEMS EMS 2013 188 2 7D SEIS eds 52 ny eN 3 4 REMS See ee ee ESD
124. EMS 177 RR EMS R ATV NS 22N 5 lon SD OY eT AS As Ae Ue 73 2 DE A 3 3 EMS 50kW 500 kW mp Ik EMS OA IE SA Ee OD INNIS Or i ede EMS 5 EMS OEMS 2 2 2 2 0 wae So U
125. 6 CEMS EMS EMS CEMS I4 4 1 2012 RT BW ICR AEE HABE ID oA RCT Randomized Controlled Trial
126. e GAs 3 2 EMS EMS 1 3 2 Excel KE Excel Microsoft Corp 2013 vol 86 no 3 189 33 OEM PNET EMH M Zm FYINVTLKUNA TENH Mdh EMS et i gee aa MER bam Zi to ae ried MD AT ARM sap sdg ahs Eee raut yr TE a Qe Bo wee dgra i ie my ah bp eel me ee FMW
127. 2 2 eee aS Bl a NY Se ae ee L ee MILA oe a PS a ees Reis a BEMS Z 7 07 AC FRS oe NS ME L Fr EART I E Emea PEED ae e se JE sea a oe aS les REMS 6 REMS 22 GMA ea 022 0 EMS OWS A AOD EMS ese ulcer IIL a ey oy 2 DY SDs wee O EY ASS ew ae Seale EMS 13 LNG E 30 CO 1
128. 2002 vol 75 no 11 p 625 629 5 2008 vol 81 no 2 p 130 134 6 Kitagawa S et al Development of an optimal opera tion planning system for energy plants in steelworks Proceeding of the 17th World Congress The International Federation of Automatic Control Seoul Korea July 6 11 2008 p 13950 13951 mA EMS 7 2011 vol 84 no 3 p 214 218 8 Kennedy J and Eberhart R Particle Swarm Optimiza tion Proceeding of IEEE International Conference on Neural Networks 1995 vol IV p 1942 1948 9 Storn R et al Differential evolution A simple and efficient adaptive scheme for global optimization over con tinuous spaces J Global Optimization 1997 vol 11 p 341 359 10 Suzuki R et al The Constrained Differential Evolution Approach for Optimal Operational Planning of Energy Plants WCCI 2010 IEEE World Congress on Computational Intelligence 2010 p 4312 4317 2007 BP IVAW ABORT a ae Sa PAO
129. 2012 A lee 8 avs eer ave les NE He BEMS HEMS HE Be A ie 2 zie DOU RUD aS Olek FREEZE
130. 5 pil 2013 vol 86 no 3 177 R1 OEM YING TUX EMH M NSM FYINVTRLKUNA TENH ahah EMS 3 o o o oO 2 RS I BFG Blast Furnace Gas COG Coke Oven Gas LDG LD Gas FJZ 4 1 BFG COG LDG 5 1 3 EMS
131. CERD CO KN 95 CO 22 30cm 50cm gt 8m 2 KN 85 2013 vol 86 no 3 219 63 HH J CO KN 95 KN 95 KN 95 2 K K CL
132. TZU 2 3 EMS 2 2 EM a b NN c d PO e f EMS o o
133. The Kitakyushu Smart Community Creation Project being conducted in the Yahatahigashida region of Fukuoka Kitakyushu cel ebrated its fourth year since inception This project utilizes a regional energy management system based on a cluster energy management system and aims to reduce CO emissions by at least 50 compared to that of typical urban areas As part of this project the first public demonstration of dynamic pricing in Japan was conducted in 2012 The price of electric power during peak hours was varied in five stages Zm FYINVTLKUNA AENH ahah from 15 to 150 yen kWh and an average reduction in demand of 9 to 13 was confirmed O 2010 4 4 ie Pe of SAR eS Vick ae Ese H 60
134. o o 100 75 200kW 4 4 D EMS 7 E a Emis pani Lr J samtprani ti H ua elf aT any EE a o S i 8 3 vray be CA Le Hoi bh
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136. 6 TP Incentive Program Eld 3 LU REL 2 UPI hoa Goo o 3
137. EMS 6 4 EMS ORS 4 1 1 PITRE CET
138. http www city kitakyushu lg jp files 000128666 pdf 2013 6 28 3 CPP 2012 http www city kitakyushulg jp files 000141802 pdf amp Ha 2013 6 28 4 AS HAR EMS Energy Optimization System for Cogeneration Plant of Paper Factory BH fas TATTA Naoto AA KANEHIRA Yoshii
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141. 2013 vol 86 no 3 199 43 OEM PANG TUX EMH M NSM FYINVTRLKUNA TENH Mdh mA EMS DWC 30 1 A a E wae 3 5 ee ene T
142. EMS EMS 3 4 EMS WETU EMS 1 E 4 A 5 TAL Ik ie Wt
143. CEMS 20 BEC CO 50 lt UN 2 2 CEMS Energy Management System
144. 20 FS SEWROHST IY CHS 2 0 5W 1 2 W EL E WATANABE Tadashi 1 KN 95 2013 S04 1 1 KN 85 Peer CO en a 1 100 25 300 ppm g 1 4 ULCS 6V eee 12V n CO 18V OV 50 3 4 lg
145. SX Net SX Net SX Net 3 3 1 SX Net SX Net Ethernet Ethernet SX Net 1 SX Net SX Net
146. 3 1 DC1 000 V 2 1 10A x12 3 a Di x2 MCCB az SPD Surge Protective Device b Ai x2 0 10 V 4 20mA 1 c x1 4 5 RS 485 MODBUS RTU F MPC Net 3 3 1 F MPC PV PV lt i gt MODBUS Schneider Automation Inc 2013 vol 86 no 3 212 56 70C 10 PV
147. BAC AN E MPC PowerSATELITE 10 8 REMS Retail Energy Management System Factory Energy Management System O 1998
148. km MWY PKZ GSM GSM MSM 1 FAMA 1 _ cece naps eek 0 5 ee 0 5 6 192 1 0 25 GSM 60 50 a eee mato 6 192 120 150 hi A 0 05 MSM 68 4 47 6 0 0625 3 33
149. VCB 2 41 a 1 4 1 5
150. ZigBee Arild OF Oh CFT Oe eis D O O 2 2013 vol 86 no 3 213 157 HH JJ A Azos GFI 2 Azos GFI a 1 3 1 n 1 45 30 30 45 _ HERE DLP Demand kW Limiting Period B
151. FRENIC Mini CC1S EMC 100V 5 2 6 RRM PRE 2013 S03 2 FRENIC Mini C28 b Bu SHS r h c e f 6 3 3 1 RS 485 FRENIC Mini C1S RS 485 RT 45 DA
152. EMS PSO Particle Swarm Optimization 43 PSO P i HZ eco H BF Blast Furnace CO Coke Oven LD BFE Q i Rs
153. E SX LSI a 100m CRER Ikm 238 4 096 b 67 025ms 512 1ms 32 c 32 1 us 3 3 MICREX SX SPH3000MG SX Net E SX L SX MICREX SX SPH3000MG SX Net E SX 4 SX Net E SX SX Net MICREX SX SPH3000MG E SX SX Net amp E SX NA
154. IMICREX SX SPHSOOOMGI MICREX SX SPH3000MG with Built in High Speed and Large Capacity Network NYUI Naoki pf YUO Yukiteru 1 SX Netl rE 126 0 5 30 ms O 5ms 128K 64 x 048 MICREX SX SPH3000MG 1 Sx Net 564 PCI D SX Net 2 SX Net MICREX SX SPH3000MG SX Net 1 SX Net a
155. RIE EMS Energy Management D O R m 2000 2010 FE 23 450 300 kl 1 System YV 2
156. Z EV 2 4 8 EMS BEMS HEMS FEMS SEMS RMR ATA LT ae a in ad 2 2013 vol 86 no 3 167 11 OEM PNT EMH M Zm FYINVTRLKUNA TENH ahah CEMS ae CEMS 1 CEMS CEMS
157. 1 1 60 CEDC Economic Dispatching Control 1 2 20 LFC Load Frequency Control 1 3 1 _ 8 2 1 i
158. 4 EMS DCS Distributed Control System MES Manufacturing Execution System ARV E 4 1 1 a EMS EMS Energy Management System FEMS BEMS I EMS 2 EMS 2013 vol 86 no 3 1 78 22 b
159. CEMS CEMS EMS EMS 2 EMS 2010 2 1 EMS eq sli le wiles UE im Ce 1 EMS 1 2 BEMS Building and Energy Management System O H RH
160. PLC mo i a 2013 vol 86 no 3 218 62 PID rf os 4 ERENIC Mini C2S Aj lek CE UL HA PUP PE NN C 4 c US LISTED 2013 7 03
161. H IVEZ ELERS RAA INY W PFCR a 2 2 BAS Building Automation System WH Hh 2013 vol 86 no 3 182 26 a b c OZ IE d EMS
162. i AVY IAA Po 2O 2 Pos Vie ees Ie a AT b Web ETP E 2 22 0 Web LCD sA 4 si 4 r EPH LCD
163. 3 3 3 1 2 IC 1 PLC MainGATE 3 C amp S
164. SoA a poH PA ZigBee Q 1 ZigBee ZigBee Alliance Inc GE 2013 S02 1 a ZigBee b 30 A JIS 60 A 22 mm We Ue c a ANSI C12 18 C12 19 e 2 Azos GFI Azos GFI 2 2
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166. 2011 vol 84 no 3 p 214 218 IA FEMS MAA EH BA MYAAH FABRA BAITS A EMS ESA Lhe 2013 vol 86 no 3 187 31 OEM PANG TUX EMH M Zm FYINVTRLKUNA TENH ahah TIR EMS EMS Energy Management Support Service with Cloud based EMS AZUMAYA Naoki
167. 1 2013 vol 86 no 3 171 G5 OEM PYNC TUX EMH M Zm FYINVTLKUNA TENH ahah 2 ekUU2A ISCA Az
168. 3 5 14 SE 2 5 F 14 9 12 ZU 5b lk
169. EMS 5 ME EMS EE 1 2010 9 p 16 19 2 FeTOP 2006 vol 79 no 3 p 274 278 3 ERHI 2004 vol 77 no 2 p 166 170 4
170. OASIS EI Energy Interoperation 1 0 OpenADR Open Automates Demand Response OpenADR OpenADR OpenADR OpenADR 3
171. 120 150 ace 2013 vol 86 no 3 208 52 3 2 8 1 3 1 Hyh sin h EGGGCO PPP 1 sin 1 sin sin cos 0 cos cos 2 Csin A 0 sin h 0 D h JRR p w 2 2
172. 171000 0 3 KW kW GT kW kW Ge kW kW G3 kW kWh G4 kW m C5 kW 1 200 3 600 p R ep my i a O 48 1 a 1 200 1 200 kW P i QO O kWh O Wr 24 36 48 1 b 3 KE 1 gt Pentium4 Intel Corporation iE 2 LINGO LINDO SYSTEMS INC 2013 vol 86 no 3 204 48 1 100 31 13 0 13 100 00 9 9077 100 00 2 a 108 15 13 51 114 DE 2 G1 G2
173. 02013 O PPS EMS BEMS MEMS EMS FOCUS EMS EnereyGATE FEMS MES MainGATE Goins EMS REMS gt a EMS EnergyGATE REMS NIV BEF Hl ome FeTOP EMS a z AA e J Bron 5 2 F MPC PowerSATELITE FeMiel MEMS EMS
174. a b a c b 1 T N N Obju gt aP t b P cU E Au K 1 Objuc P t u t 7 CO 1 Au K N 7 TK COs aay dks De Ck
175. HERDS 2 NO IR TOG PLS Partial Least Squares PLS S A P ASAE PS Sa II iC S 7 4a p N SS wm Q 3 2 2 1 000 hPa 925 hPa 850 hPa 700 hPa 600 hPa 500 hPa
176. b 12 EAR JYJ P ar ICH CWS F MPC PV 100ms A 5 10 15 30 2013 8 19 H
177. 1 3 1 A EMS 10 30 2030 1 0p u 0 33 p u 1 3 KW m 5 OMORO S O a ae gt _ gt pial g AL ares a 7 B B 4 2013 vol 86 no 3 209 53 OEM PHN TUX EMH a Zm FYINVTRLKUNA TENH Aah 5
178. 1 1 rhe Gd i m Emr E Tf O weer eh u 1 it i FT FET TT mee NO No 3 No 2 E kter ais EF gt a oe ES ESE IANI No 3 A A7 3 5 6 EMS COU EA
179. 6 30 C 7 9 2 5 10 40 8 7 10 AOA de eo CUS 1 7A 8 9 QO A A RO N kW 0 6 he 18 24 8 8 0 i KW N 5 0 6 12 18 24 9 2013 vol 86
180. 5 BORKA ZY h Se F 5 2013 vol 86 no 3 196 40 EMO EMS CEMS 2013 DS 5
181. LAY OAD Y PASH dis V ore 1 PMV Predicted Mean Vote EMS PMV m 2 CO
182. THLE SE ASME B m H73 ERA E Ha Hja E HAS 3 moa EMS JSN 3 3 wb WAL Ze PIL TU ALOR ETE SARE CHS T CO CO GE
183. 1 CGD 2 2 15 114 CHU 30 3 2 K 1 500 kW 4 2 1
184. EMS Energy Management System EMS 2012 2 EMS 2 1 LEDS BF ZED FS 2013 vol 86 no 3 188 32 a b
185. e 202 46 th Be 207 51 ety FS ae Vai SZ F MPC PV 211 55 Azos GFI 213 57 FRENIC Mini C29 216 60 CO KN 95 219 63 MULTILVCB 222 66 225 69 MICREX SX SPH3000MG See 228 72 FUJI ELECTRIC JOURNAL 2013 Vol 86 No Contents Energy Management System EMS Preface Expectation for development of xEMS 159 3 BABA Jumpei Energy Management System EMS Current Status and Future 160 4 Outlook SHIRAKAWA Masahiro KOBAYASHI Naoto KUWAYAMA Jimpei Public Demonstration of Dynamic Pricing in the Kitakyushu Smart 166 10 Community Creation Project OGA Eiji KABASAWA Akihiro Energy Optimization System for Cogeneration Plant of Paper Factory 173 17 TATTA Naoto KANEHIRA Yoshij Steel EMS Package Optimizing Energy Management at Steelworks 177 21 NARUMI Katsunori KIMURA Takayuki WATANABE Takuya EMS for Large sc
186. Ethernet b BK ms c PCI Express a 10 1K ms MICREX SX SPH3000MG MICREX SX a SX Net 1 MICREX SX SPH3000MG b E SX 512 ms 32 c SX Net E SX al SX Net MICREX SX SPH3SOOOMG 3 8 SX Net ms THU
187. o o CSS Pi 9 oS o 2 EMS B EMS 3 1 EMS EMS 8 a EMS b c d J AOA
188. 400 hPa 300 hPa PLS t W Pec Wx 3 y Oct O W P W x TCT ee Cr ee i 4 x t y W Pot O 3 2 3 3
189. 2 2 I2 pa 2 1 1 RER 1 COS CHU
190. EMS The ECOMAX Controller Realizes an EMS for Use in Stores KIDO Takeshi Seth KANZAKI Katsuya 85 Zed RE OD ee BE hl BA 1 EMS 9 According to energy consumption trends by sector in Japan energy consumption in the consumer product sector which includes retail business is increasing at a high rate Moreover 85 of the energy consumed by retail business activities is in the form
191. Gan Gas Dee ea a i VINE DG KY Se 2013 vol 86 no 3 161 5 DEM ENING TUX HENH MA NSM FYINVTRLKUNA TENH Aah 2 EMS fe Ses Zo IS eae LIE 5 er 2
192. RI RMSE p u 0 01 0 04 0 07 0 12 0 15 0 18 0 20 MAE p u 0 01 0 03 0 06 0 09 0 12 0 15 0 15 13 14 15 16 1Z 18 RMSE p u 0 18 0 16 0 16 0 12 0 08 0 04 0 12 MAE p u 0 14 0 12 0 12 0 09 0 06 0 03 0 09 RMSE Root Mean Square Error MAE Mean Absolute Error p u per unit 0 2p u 5 EMS
193. eum IE sg sy are eel Casini lo CEMS HCE EMS OD Fo a lt CEMS EMS eal de Cone CGS Se eign AS Sat Se beet scle ly OS A SY ae 3 2 FEMS aree IMainGATE FEMS lk
194. oo Ke TT 1O 20 209 1kW 1MW 01 1kW 1 000 PV RRL ROD 2 F MPC PV 2 1 F MPC PV lk
195. 03 5847 8060 2013485 19 H Web 2013 S01 2 Azos GFI Azos GFI New Type Electrical Watt Hour Meter BE ENOMOTO Takashi Azos GFI Azos GFI It GE General Electric Company Azos GFI ZigBee 00 2 30 O Azos GFI 1 1 Azos GFI 1 Azos GFI nay ae Z F2YWF RA
196. Ae ie NTP Web FTP DHCP Telnet 3 2013 vol 86 no 3 194 38 GRR 3
197. 3 7 Azos GFI DLP Demand Limiting Period DLP kW 2013 8 1 GE 0263 72 8385 20134885 19 H Web 2013 vol 86 no 3 215 59 HH JJ A IFRENIC Mini C2S Line Up Expansion of Compact Inverter FRENIC Mini C2S Series MIZUNO Osamu ERENIC Mini C2S 400 V 200 V 1 EFRENIC
198. 20 ae 3 Azos GFI 2013 vol 86 no 3 214 58 a b 4 3 3 5 a 5 1 11 5x5 6 mm b Eis ee HEBEL CT c A 1 C 3 3 4 30 00
199. 4 2 BEMS a by 4 4 ELC 1 CEMS Cluster Energy Manage ment System EMS
200. EAN 3 USB 2013 S03 1 00 4 3Hz 5Hz 10Hz 100 1 amp Sg 72 r min R H 100 200 1 4 OE 04 075 IS 22 S7 kW 8200V 0 1 3 7k W BRR RRR 400 V 0 4 3 7 kW a i apcoovyo 1 22kw SP 449100 V 0 1 0 75 kW i A EMC 8200V 0 1 3 7kWV BIRR 1 400 V 0 4 3 7kW 200 V 0 1 2 2kw SDD 5 8 a 200 at 3Hz BA b CPU CPU 2 9
201. IF EMS CO In large scale commercial facilities that consume vast amounts of energy power conservation energy savings and the efficient utilization of energy are challenges requiring urgent attention and the introduction of an EMS is being promoted as a solution Fuji Electric has developed a large scale commercial facility EMS to generate optimal supply and demand management plans based upon demand forecasts and power generation forecasts and to realize the optimal application of energy With the introduction of this system operation can be guided precisely toward power conserving and energy saving behaviors energy management can be implemented by area by application and by basic unit or the like and a reduction in energy consumption and CO emissions can be expected PE sa
202. 2013 vol 86 no 3 198 42 9 LP QP OAS Ba VAs 177 GA PSO DE m 2 a XML Extensible Markup Lan guage b XML c EMS da T TO e EMS 2
203. 30 45 3 5 Azos GFI 5 2013 S02 2 3 6 QR 38 QR BAB 6 QR lt 2 QR 2013 S02 3 Azos GFI QR
204. 8 5 0 1 6 39 MIC SOC Bell QU Cee Ss 8 1 800 3 000 HOR Clk BW SOC 60 600 3 000 60 600 1 800 O O O ol 0 05 5 0 10 1 800 3 600 s 6 5 250 LFC EDC 100 kW 0 1 800 3 600 s 7 BRC BHO 100 SOC 60 S O D 50 HE SSeS O 1 800 3 600 s 8
205. m e 9 a _ b 2 CAD 3 Tes 3 2013 vol 86 no 3 223 67 FSB Regs MULTI VCB a m E a Se ar Hl PARTS FL 2013 5 03 5847 8060 2013 9B 9 H Web 2013 vol 86 no 3 2013 S05 3 224 68
206. 1 EMS 2 EMS EMS EMS CCN 1 EMS nul ob cdo oo 1985 Flag m7 av Dal MICREX F Suite Zi 2 a Ys oe le DCR SX MICREX NX ly leas 1995
207. Cluster Energy Management System EMS BEMS MEMS 1 EMS CEMS Te pO as iL Ee EMS EnergyG ATS SW 2 Ele wl lessee Be EMS REMS EMS CFEMS S lt EMS
208. Field Connector POWS5 GVawysnaedo Wl sesso 2s ee EMS ROD EAD PD Pee ao 9 Se 97 X EMS Poy Koa Ace 13 EMS 3 1 2010 4 CO a CEMS CEMS 202 207 MAT EMS EM
209. 5435 7190 20134885 30 H Web 2013 S03 3 CE HA CO Bthas KN 95 Residential fire Gas and Carbon monoxide Alarms KN 95 fil KAMIOKA Tsuyoshi GE CO KN 95 Fi AS halk CO KN 95 20 50 O 1 KN 95 1 1 41mm
210. i F Fille om all SR Sintering BFG Blast Furnace Gas COG Coke Oven Gas gt 4 LDG LD Gas ACC Accumulator 38 MXG Mix Gas a yous CDQ Coke Dry Quenching 3 lt gt 2013 vol 86 no 3 179 23 OEM PANG TUX EMH M Zm FYINVTRLKUNA TENH ahah EMS
211. 400 300 CHU EMS Energy Management ie 550 0 EMS KAR seh Sel IS ICRMEL 7 EMS ot ea a a E 1 le 2 1 me e IC 2
212. Ei ub ss EF FE EE E BeEpRER ER Ema NJA onl i JP E O et g m b TRIL ARIIS7 3 fren sal Pe ee ee ee ae fff fee oP PPS SP JP JP FPP 4 3 4 4 5 6 2013 vol 86 no 3 190 34 Manan 7 r r r r ee O F r ee r Er ee EREEREER ERRE EREE EE ERE E E oF 6 5 7
213. no 3 170 14 F B91 5 OSF 8 20 2 5 10 16 00 7 9 1 7 2 5 OTI 4
214. o 6 REMS I4 CEMS EMS EMS NA EBMS BnergyGATE IVA OULD 5b Baa CDOAY riba ai i a 7 e 5
215. of electric power and power savings is increasingly being requested Fuji Electric has developed the ECOMAX Controller that collectively manages and controls refrigeration freezer air conditioning and lighting equipment inside a store to realize comprehensive energy savings A configuration that is compatible with various interfaces is used in order to enable collective control of the equipment to reduce installation costs and to increase the efficiency of the management and operation of the equipment Additionally infrastructure management functions for electricity water and gas are incorporated so that a store use EMS may be configured easily with a single controller 0 41 23 HH SH 85 M1
216. 013 S06 3 2013 vol 86 no 3 227 71 SIGH DHAR f BAS Building Automation System BEMS Building and Energy Management System CAD Computer Aided Design IVEI CEMS Cluster Energy Management System CPU Central Processing Unit DCS Distributed Control System DE Defferential Evolution DLP Demand Limiting Period EDC Economic Dispatching Control EMS Energy Management System ESB Enterprise Service Bus FEMS Factory Energy Management System Ly pe HVS A FTP File Transfer Protocol GSM Global Spectrum Model HEMS Home Energy Management System Die I a es a HTTP Hyper Text Transfer Protocol LAN Local Area Network LCD Liquid Crystal Display Wa FEAR EE LFC Load Frequency Control LNG Liquefied Natural Gas MCCB Molded Case Circuit Breaker MES Manufacturing Execution System MSM Meso Scale Model PCS Power Conditioner INO Aor a aS
217. 2 1 EN WRT OAs 2 km
218. 4 D 2013 vol 86 no 3 164 8 Po eee a EMS 1 24 H 2013 http www enecho meti go jp topics hakusho 2013energyhtml index html BOO 6 2 http www kantei go jp jp sin gi keizaisaise1 pdf rm_ jpn pdf 2013 07 16 3 FROWNED 2011 vol 84 no 3 p 214 218 o o o o ee 7 o BB o o
219. A 13 00 gt 17 00 8 00 10 00 18 00 20 00 6 9 30 12 3 160 140 5 150 kWh 120 4 100 kWh _ 100 BE D 3 5 kWh 80 60 50 kWh NI AG 1 15 kWh 0 6 12 18 24 a 5 150 kWh 4 100 kWh 3 Z5 kKWh FA Ap 50 kWh 1 15 kWh Wi b 7 2013 vol 86 no 3 169 13 OEM PNG TUX EMH M Zm FYINVTLKUNA TENH ahah 5 2 5 les 4 2 1 1
220. Bi 5 3 H 3 5 6 20 5 4 1 LEDS 3 30 1
221. H 86 3 879 2013 9 H 30 ISSN 2187 1817 SSD e FUJI ELECTRIC JOURNAL 8 No EMS Innovating Energy Technology FUJI ELECTRIC JOURNAL 2013 Vol 86 No EMS EMS CEMS EMS EMS EMS
222. II FRENIC 2013 vol 86 no 3 216 60 a 0 1 kW b 2 2kW c 3 7kW 2 FRENIC Mini C2S RI 4 4 5 10 40 80 50 6 GED 7 USB USB 3 a Gi Zs AB USB USBminiB LAN J
223. PDA Process Data Acquisition PDCS Process Data Collection System PID Potential Induced Degradation PLS Partial Least Squares PMV Predicted Mean Vote PSO Particle Swarm Optimization PV Photovoltaic RCT Randomized Controlled Trial REMS Retail Energy Management System NN 2 SEMS Store Energy Management System SOC State of Charge SPC Set Point Control SPD Surge Protective Device VCB Vacuum Circuit Breaker FL ZE He DT at XML Extensible Markup Language Ethernet Excel Microsoft Corp LINGO LINDO SYSTEMS INC LonWorks Echelon Corporation MODBUS Schneider Automation Inc PCI Express PCI SIG Pentium4 Intel Corporation QR ZigBee ZigBee Alliance Inc
224. ale Commercial Facility 182 26 KOMATSUBARA Shigeru XIANG Donghui YAMADA Yasuyuki Energy Management Support Service with Cloud based EMS 188 32 AZUMAYA Naoki The ECOMAX Controller Realizes an EMS for Use in Stores 193 37 KIDO Takeshi KANZAKI Katsuya A Framework for Optimal Planning Systems on the EMS Platform 197 41 KAWAMURA Yu HORIGUCHI Hiroshi ONO Takeshi Supply and Demand Control System for Power Systems with 202 46 Distributed Power Supplies KATSUNO Tohru IIZAKA Tatsuya HAYASHI Naoki Photovoltaic Power Generation Forecasting Technology for 207 51 Supporting Energy Management Systems ISHIBASHI Naoto IIZAKA Tatsuya KATSUNO Tohru New Products F MPC PV String Monitoring Unit for Photovoltaic Power Generation 211 55 Systems Azos GFI New Type Electrical Watt Hour Meter 213 57 Line Up Expansion of Compact Inverter FRENIC Mini C2S Series 216 60 Residential fire Gas and Carbon monoxide Alarms KN 95 219 63 Vacuum Circuit Breaker Fixed Type MULTI VCB 222 66 MICREX SX SPH3000MG with Built in High Speed and Large 225 69 Capacity Network Abbreviations and Trademarks 228 72 EMS xEMS Expectation for development of xEMS BABAJumpei
225. ded at times of excessive steam loads while also ensuring that there is no inverse power flow during times of steam shortages the cost of installing the system can be confirmed to be recovered in one year O0 1980 1 M x GT ay ern Bl
226. essary to forecast the amount of power generation and to control the supply and demand In order to achieve supply and demand control that is stable Fuji Electric has developed technology for forecasting the amount of power generation By predicting the amount of insolation from numerical weather forecast data and converting that prediction into an amount of power generation based on the properties of photovoltaic modules the amount of power generation can be forecasted for up to several days in the future in any region of the world 1 WU EMS Energy Management System ame SN
227. ompany tech contents3 html 2013 Fuji Electric Co Ltd Printed in Japan 230 74 Te he tia LE Fi i i BS mima lr IIc Prim FMLA HAARE E wre FLAA i FF RE on fsa fin il only Lreation Projet 1 foe I I i i i a
228. t utilizes cloud technology Because a company will not have to install maintain or manage the system the introduction of EMSs to small and medium sized power customers is expected to accelerate O FADS OR KORA
229. y savings increased operational efficiency of labor saving and motive power equipment and environmental management is being promoted Focusing on supply demand forecasting and optimization which is a basic function of an energy center Fuji Electric has developed a Steel EMS Package for improving energy management and operational efficiency which are complexly intertwined within a steelworks This package forecasts the energy fluctuation for several hours in advance or makes daily or monthly forecasts and optimally operates the energy production equipment so as to contribute to energy saving throughout the steelworks 0 FADS 10 24 365 T T
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