LEADER 02997nam 2200613Ia 450 001 9910465463903321 005 20200520144314.0 010 $a1-299-24341-X 010 $a0-253-00734-8 035 $a(CKB)2560000000098216 035 $a(EBL)1144287 035 $a(OCoLC)833046303 035 $a(SSID)ssj0000837361 035 $a(PQKBManifestationID)11457674 035 $a(PQKBTitleCode)TC0000837361 035 $a(PQKBWorkID)10769889 035 $a(PQKB)10382138 035 $a(MiAaPQ)EBC1144287 035 $a(MdBmJHUP)muse18252 035 $a(Au-PeEL)EBL1144287 035 $a(CaPaEBR)ebr10666281 035 $a(CaONFJC)MIL455591 035 $a(EXLCZ)992560000000098216 100 $a20120920d2013 ub 0 101 0 $aeng 135 $aur|||||||nn|n 181 $ctxt 182 $cc 183 $acr 200 14$aThe battle for Manchuria and the fate of China$b[electronic resource] $eSiping, 1946 /$fHarold M. Tanner 210 $aBloomington $cIndiana University Press$d2013 215 $a1 online resource (288 p.) 225 0 $aTwentieth-century battles 300 $aDescription based upon print version of record. 311 $a0-253-00723-2 320 $aIncludes bibliographical references and index. 327 $aA Note on Chinese Names -- Siping, 1946 : Decisive Battle or Lost Opportunity? -- The Manchurian Chessboard, August-September 1945 -- The Communist Retreat, October-December 1945 -- George Marshall's Mission, December 1945-March 1946 -- The Second Battle of Siping : Phase One--From Outer Defense to Stalemate, March-April 1946 -- The Second Battle of Siping : Phase Two--From Defense to Retreat, April-May 1946 -- The Chase and the Ceasefire, May-June 1946 -- Visions of the Past and Future. 330 $aIn the spring of 1946, Communists and Nationalist Chinese were battled for control of Manchuria and supremacy in the civil war. The Nationalist attack on Siping ended with a Communist withdrawal, but further pursuit was halted by a cease-fire brokered by the American general, George Marshall. Within three years, Mao Zedong's troops had captured Manchuria and would soon drive Chiang Kai-shek's forces off the mainland. Did Marshall, as Chiang later claimed, save the Communists and determine China's fate? Putting the battle into the context of the military and political struggles fought, Harol 410 0$aTwentieth-Century Battles 606 $aHistory$zChina$y20th century 607 $aChina$xHistory$yCivil War, 1945-1949$xCampaigns 607 $aSiping Shi (China)$xHistory, Military$y20th century 607 $aManchuria (China)$xHistory, Military$y20th century 608 $aElectronic books. 615 0$aHistory 676 $a951.042 700 $aTanner$b Harold Miles$0873020 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910465463903321 996 $aThe battle for Manchuria and the fate of China$91948789 997 $aUNINA LEADER 03946nam 2200985z- 450 001 9910346681403321 005 20210211 035 $a(CKB)4920000000094855 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/45286 035 $a(oapen)doab45286 035 $a(EXLCZ)994920000000094855 100 $a20202102d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDistributed Energy Resources Management 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 215 $a1 online resource (236 p.) 311 08$a3-03897-718-7 330 $aAt present, the impact of distributed energy resources in the operation of power and energy systems is unquestionable at the distribution level, but also at the whole power system management level. Increased flexibility is required to accommodate intermittent distributed generation and electric vehicle charging. Demand response has already been proven to have a great potential to contribute to an increased system efficiency while bringing additional benefits, especially to the consumers. Distributed storage is also promising, e.g., when jointly used with the currently increasing use of photovoltaic panels. This book addresses the management of distributed energy resources. The focus includes methods and techniques to achieve an optimized operation, to aggregate the resources, namely, by virtual power players, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as a main drive for their efficient use. 610 $aac/dc hybrid microgrid 610 $aadaptive droop control 610 $aadvance and retreat method 610 $aaggregator 610 $aaggregators 610 $aARIMA 610 $aautonomous operation 610 $aaverage consensus algorithm (ACA) 610 $ablack start 610 $abuilding energy flexibility 610 $abusiness model 610 $aCat Swarm Optimization (CSO) 610 $aclustering 610 $aco-generation 610 $aconsensus algorithm 610 $adecision-making under uncertainty 610 $ademand response 610 $aDemand Response (DR) 610 $aDemand Response Unit Commitment (DRUC) 610 $ademand-side energy management 610 $adiffusion strategy 610 $adiscrete wavelet transformer 610 $adistributed generation 610 $adistributed system 610 $adomestic energy management system 610 $aelectricity markets 610 $aenergy flexibility 610 $aenergy flexibility potential 610 $aenergy management system 610 $aenergy trading 610 $afault localization 610 $ahierarchical game 610 $ainterval optimization 610 $alocal controller 610 $amicrogrid 610 $amicrogrid (MG) 610 $amicrogrid operation 610 $amicrogrids 610 $amulti-agent system (MAS) 610 $amultiplier method 610 $anon-cooperative game (NCG) 610 $aoptimal bidding 610 $aoptimal operation 610 $aPowell direction acceleration method 610 $apower system restoration (PSR) 610 $apricing strategy 610 $aprobabilistic programming 610 $areal-time simulation 610 $arenewable energy 610 $ascheduling 610 $astochastic programming 610 $astorage 610 $athermal comfort 610 $atime series 610 $atransmission line 610 $auncertainty 610 $aUnit Commitment (UC) 610 $avirtual power plant 700 $aFaria$b Pedro$4auth$01312838 906 $aBOOK 912 $a9910346681403321 996 $aDistributed Energy Resources Management$93031013 997 $aUNINA