LEADER 00955nam0-22003251i-450- 001 990008446180403321 005 20070109112727.0 020 $aIT$b62-7379 035 $a000844618 035 $aFED01000844618 035 $a(Aleph)000844618FED01 035 $a000844618 100 $a20070109d1962----km-y0itay50------ba 101 0 $aita$ager$aeng 102 $aIT 105 $ay-------001yy 200 1 $aTestimonianze storiche sull'Alto Adige$fCarlo Barduzzi 210 $aRoma$cEdizioni Europa$dstampa 1962 215 $a423 p., [2] c. geogr.$cill$d27 cm 300 $aSulla cop.: 1 300 $aTesto anche in tedesco, inglese, francese e spagnolo 676 $a340$v11 rid.$zita 700 1$aBarduzzi,$bCarlo$0250423 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990008446180403321 952 $aSDI-XXIII B 12$b1635$fSDI 959 $aSDI 996 $aTestimonianze storiche sull'Alto Adige$9727889 997 $aUNINA LEADER 01239nam0-22003971i-450- 001 990005419560203316 005 20010829120000.0 035 $a000541956 035 $aUSA01000541956 035 $a(ALEPH)000541956USA01 035 $a000541956 100 $a20010829d1989-------|0enac50------ba 101 $aeng 102 $aGB 105 $a||||Z 1|||| 200 1 $aValue-form and the state$ethe tendences of accumulation and the determination of ecnomic policy in capitalist society$fGeert Reuten and Michael Williams 210 $aLondon$cRoutledge$d1989 - XXI$d339 p. ; 22 cm 606 $aValuta$2FI 606 $aStruttura sociale$2FI 606 $aEconomia marxista$2FI 620 $dLondon 676 $a338.9$cSviluppo economico$v21 700 1$aREUTEN,$bGeert$0129044 701 1$aWILLIAMS,$bMichael$087085 712 $aRoutledge 801 $aIT$bSOL$c20120104 912 $a990005419560203316 950 $aDIP.TO SCIENZE ECONOMICHE - (SA)$dDS 300 338.9 REU$e3531 DISES 951 $a300 338.9 REU$b3531 DISES 959 $aBK 969 $aDISES 979 $c20121027$lUSA01$h1531 979 $c20121027$lUSA01$h1612 996 $aValue-form and the state$91142848 997 $aUNISA NUM $aUSA456 LEADER 04694nam 2201009z- 450 001 9910580204303321 005 20220706 035 $a(CKB)5690000000012047 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/87492 035 $a(oapen)doab87492 035 $a(EXLCZ)995690000000012047 100 $a20202207d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSituation Awareness for Smart Distribution Systems 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (214 p.) 311 08$a3-0365-4525-5 311 08$a3-0365-4526-3 330 $aIn recent years, the global climate has become variable due to intensification of the greenhouse effect, and natural disasters are frequently occurring, which poses challenges to the situation awareness of intelligent distribution networks. Aside from the continuous grid connection of distributed generation, energy storage and new energy generation not only reduces the power supply pressure of distribution network to a certain extent but also brings new consumption pressure and load impact. Situation awareness is a technology based on the overall dynamic insight of environment and covering perception, understanding, and prediction. Such means have been widely used in security, intelligence, justice, intelligent transportation, and other fields and gradually become the research direction of digitization and informatization in the future. We hope this Special Issue represents a useful contribution. We present 10 interesting papers that cover a wide range of topics all focused on problems and solutions related to situation awareness for smart distribution systems. We sincerely hope the papers included in this Special Issue will inspire more researchers to further develop situation awareness for smart distribution systems. We strongly believe that there is a need for more work to be carried out, and we hope this issue provides a useful open-access platform for the dissemination of new ideas. 606 $aHistory of engineering and technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $aattention mechanism 610 $aattentional mechanism 610 $acapacity configuration 610 $acarbon emission 610 $aclimate factors 610 $aCNN 610 $acommunity integrated energy system 610 $acomprehensive framework 610 $aconditional value-at-risk 610 $aconvolutional neural network 610 $acorrelation analysis 610 $acritical technology 610 $aDC series arc fault 610 $adenoising auto-encoder 610 $adistributionally robust optimization (DRO) 610 $aelectric heating 610 $aelectric vehicle 610 $aenergy management 610 $ahigh-quality operation and maintenance 610 $ainertia security region 610 $aintegrated energy system (IES) 610 $ajoint chance constraints 610 $alightweight convolutional neural network 610 $alinear decision rules (LDRs) 610 $aload disaggregation 610 $aload forecasting 610 $aLSTM neural network 610 $amachine learning 610 $amulti-objective optimization 610 $an/a 610 $aphotovoltaic (PV) system 610 $apower spectrum estimation 610 $apower-to-hydrogen 610 $areceding horizon optimization 610 $aREDD dataset 610 $asecondary equipment 610 $ashort text classification 610 $ashort-term load forecasting 610 $asituation awareness 610 $asmart distribution network 610 $astorage 610 $asustainable wind-PV-hydrogen-storage microgrid 610 $atemporal convolutional network 610 $athermal comfort 610 $aTraceBase dataset 610 $auser dominated demand side response 610 $aWasserstein distance 610 $awind-photovoltaic-thermal power system 615 7$aHistory of engineering and technology 615 7$aTechnology: general issues 700 $aGe$b Leijiao$4edt$01297583 702 $aYan$b Jun$4edt 702 $aSun$b Yonghui$4edt 702 $aWang$b Zhongguan$4edt 702 $aGe$b Leijiao$4oth 702 $aYan$b Jun$4oth 702 $aSun$b Yonghui$4oth 702 $aWang$b Zhongguan$4oth 906 $aBOOK 912 $a9910580204303321 996 $aSituation Awareness for Smart Distribution Systems$93024575 997 $aUNINA