LEADER 04173nam 2200601 450 001 9910830531203321 005 20230331015810.0 010 $a1-118-15074-0 010 $a1-118-15073-2 035 $a(CKB)1000000000014028 035 $a(EBL)1562419 035 $a(SSID)ssj0001041101 035 $a(PQKBManifestationID)11589743 035 $a(PQKBTitleCode)TC0001041101 035 $a(PQKBWorkID)11009796 035 $a(PQKB)10742506 035 $a(MiAaPQ)EBC1562419 035 $a(EXLCZ)991000000000014028 100 $a19860825h19871987 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMultivariate statistical simulation /$fMark E. Johnson 210 1$aNew York :$cWiley,$d[1987] 210 4$dİ1987 215 $a1 online resource (248 p.) 225 1 $aWiley Series in Probability and Statistics 225 0$aWiley series in probability and mathematical statistics.$pApplied probability and statistics 300 $aDescription based upon print version of record. 311 $a1-306-14096-X 311 $a0-471-82290-6 320 $aIncludes bibliographical references and indexes. 327 $aCover; Title Page; Copyright Page; Preface; Contents; 1. Introduction; 1.1. Robustness of Hotelling's T2 Statistic; 1.2. Error Rates in Partial Discriminant Analysis; 1.3. Foutz' Test; 1.4. Overview; 2. Univariate Distributions and their Generation; 2.1. General Methods for Continuous Univariate Generation; 2.2. Normal Generators; 2.3. Johnson's Translation System; 2.4. Generalized Exponential Power Distribution; 2.5. Gamma Generators; 2.6. Uniform 0-1 Generators; 3. Multivariate Generation Techniques; 3.1. Conditional Distribution Approach; 3.2. Transformation Approach 327 $a3.3. Rejection Approach4. Multivariate Normal and Related Distributions; 4.1. Multivariate Normal Distribution; 4.2. Mixtures of Normal Variates; 5. Johnson's Translation System; 5.1. Plots for the SLL Distribution; 5.2. Plots for the SUU Distribution; 5.3. Contour Plots for the SBB Distribution; 5.4. Analytical Results; 5.5. Discriminant Analysis Applications; 6. Elliptically Contoured Distributions; 6.1. General Results for Elliptically Contoured Distributions; 6.2. Special Cases of Elliptically Contoured Distributions; 7. Circular, Spherical, and Related Distributions 327 $a7.1. Uniform Distributions7.2. Nonuniform Distributions; 8. Khintchine Distributions; 8.1. Khintchine's Unimodality Theorem; 8.2. Identical Generators; 8.3. Independent Generators; 8.4. Other Possibilities; 9. Multivariate Burr, Pareto, and Logistic Distributions; 9.1. Standard Form and Properties; 9.2. Generalizations; 10. Miscellaneous Distributions; 10.1. Morgenstern's Distribution; 10.2. Plackett's Distribution; 10.3. Gumbel's Bivariate Exponential Distribution; 10.4. Ali-Mikhail-Haq's Distribution; 10.5. Wishart Distribution; 11. Research Directions; References; Supplementary References 327 $aAuthor IndexSubject Index 330 $aProvides state-of-the-art coverage for the researcher confronted with designing and executing a simulation study using continuous multivariate distributions. Concise writing style makes the book accessible to a wide audience. Well-known multivariate distributions are described, emphasizing a few representative cases from each distribution. Coverage includes Pearson Types II and VII elliptically contoured distributions, Khintchine distributions, and the unifying class for the Burr, Pareto, and logistic distributions. Extensively illustrated--the figures are unique, attractive, and reveal very n 410 0$aWiley Series in Probability and Statistics 606 $aMultivariate analysis$xData processing 606 $aMathematical statistics 615 0$aMultivariate analysis$xData processing. 615 0$aMathematical statistics. 676 $a519.5350724 700 $aJohnson$b Mark E.$f1952-$059373 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830531203321 996 $aMultivariate statistical simulation$9197723 997 $aUNINA LEADER 03351nam 2200733 a 450 001 9910817313203321 005 20240516134042.0 010 $a9786613617170 010 $a9781118275863 010 $a1118275861 010 $a9781280587344 010 $a1280587342 010 $a9781118275825 010 $a1118275829 010 $a9781118274880 010 $a1118274881 035 $a(CKB)2670000000161504 035 $a(EBL)875736 035 $a(OCoLC)775591924 035 $a(SSID)ssj0000640568 035 $a(PQKBManifestationID)11364172 035 $a(PQKBTitleCode)TC0000640568 035 $a(PQKBWorkID)10611797 035 $a(PQKB)10466743 035 $a(MiAaPQ)EBC875736 035 $a(DLC) 2012005281 035 $a(Au-PeEL)EBL875736 035 $a(CaPaEBR)ebr10630538 035 $a(CaONFJC)MIL361717 035 $a(PPN)192130838 035 $a(Perlego)1014355 035 $a(EXLCZ)992670000000161504 100 $a20120202d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aResearching education through actor-network theory /$fedited by Tara Fenwick and Richard Edwards 205 $a1st ed. 210 $aMalden, Mass. $cJohn Wiley & Sons$d2012 215 $a1 online resource (145 p.) 225 0$aEducational philosophy and theory special issue book series 300 $aDescription based upon print version of record. 311 08$a9781118274897 311 08$a111827489X 320 $aIncludes bibliographical references and index. 327 $aIntroduction / Tara Fenwick and Richard Edwards -- Devices and educational change / Jan Nespor -- Translating the prescribed into the enacted curriculum in college and school / Richard Edwards -- Unruly practices: what a sociology of translations can offer to educational policy analysis / Mary Hamilton -- ANT on the PISA trail: following the statistical pursuit of certainty / Radhika Gorur -- Assembling the "accomplished" teacher: the performativity and politics of professional teaching standards / Dianne Mulcahy -- Reading educational reform with actor network theory: fluid spaces, otherings, and ambivalences / Tara Fenwick. 330 $aResearching Education Through Actor-Network Theory offers a new take on educational research, demonstrating the ways in which actor-network theory can expand the understanding of educational change. An international collaboration exploring diverse manifestations of educational changeIllustrates the impact of actor-network theory on educational researchPositions education as a key area where actor-network theory can add value, as it has been shown to do in other social sciencesA valuable resource for anyone interested in the socio 410 0$aEducational Philosophy and Theory Special Issues 606 $aEducation$xResearch$xMethodology 606 $aActor-network theory 615 0$aEducation$xResearch$xMethodology. 615 0$aActor-network theory. 676 $a370.72 701 $aFenwick$b Tara J$0913052 701 $aEdwards$b Richard$f1956 July 2-$0913053 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910817313203321 996 $aResearching education through actor-network theory$93949404 997 $aUNINA LEADER 09398nam 22005773 450 001 9911007178703321 005 20231214080229.0 010 $a1-83724-439-1 010 $a1-5231-6318-6 010 $a1-83953-808-2 035 $a(MiAaPQ)EBC30663171 035 $a(Au-PeEL)EBL30663171 035 $a(CKB)29350451300041 035 $a(OCoLC)1414467868 035 $a(EXLCZ)9929350451300041 100 $a20231214d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPower System Strength $eEvaluation Methods, Best Practice, Case Studies, and Applications 205 $a1st ed. 210 1$aStevenage :$cInstitution of Engineering & Technology,$d2023. 210 4$dİ2024. 215 $a1 online resource (225 pages) 225 1 $aEnergy Engineering Series 311 08$a1-83953-807-4 327 $aIntro -- Title -- Copyright -- Contents -- About the editors -- Foreword -- Introduction -- 1 Power system strength assessment with high penetration of inverter-based resources - a conceptual approach -- 1.1 Introduction -- 1.2 Work in progress for determination of power system strength in a large grid -- 1.2.1 Method of assessing power system strength -- 1.2.2 Relationship between SCR and power system voltage stability -- 1.2.3 Effect of IBR dynamics on power system strength assessment -- 1.2.4 Outline of a new method for assessing power system strength -- 1.2.5 Summary and future directions -- References -- 2 Power system strength assessment with inverter-based resources: challenges and solutions -- 2.1 Introduction -- 2.2 Power system strength with grid-following inverter and grid-forming inverter and its relation to weak grids -- 2.3 Power system strength definitions -- 2.4 System strength metrics -- 2.4.1 SCR index -- 2.4.2 Weighted short circuit ratio -- 2.4.3 Composite SCR -- 2.4.4 Effective SCR -- 2.4.5 SCR with interaction factors -- 2.4.6 Site-dependent SCR (SDSCR) index -- 2.4.7 Inverter interaction level SCR (IILSCR) -- 2.4.8 Attributes of power system strength assessment methodologies -- 2.5 Impact of power system components on power system strength -- 2.5.1 Impact of phase-locked loops on the system strength -- 2.5.2 Impact of flexible alternating current transmission system devices on the power system strength -- 2.5.3 Impact of synchronous condensers on the system strength -- 2.6 Applicability of SCR index: case study -- 2.6.1 EMT simulations on SCR index -- 2.6.2 Discussion of simulation results -- 2.7 Research gaps and new research directions -- References -- 3 Voltage sensitivity-based system strength metric -- 3.1 Introduction -- 3.2 System description -- 3.3 Power transfer limit of IBR -- 3.3.1 Angle stability limit. 327 $a3.3.2 Voltage stability limit -- 3.3.3 Impact of the local load -- 3.3.4 Impact of synchronous condenser -- 3.3.5 Discussion -- 3.4 Simulation results -- 3.5 Discussion -- 3.6 Conclusion -- References -- 4 Dynamic model reduction of power networks for fast assessment of power system strength - part 1: classical techniques -- 4.1 Introduction to system strength -- 4.2 Model reduction strategies -- 4.2.1 Background -- 4.2.2 Overview -- 4.2.3 Classical reduction techniques -- 4.2.4 Classical dynamic equivalent techniques -- 4.2.5 Limitations of classical reduction techniques -- 4.2.6 Research gaps and conclusions -- References -- 5 Dynamic model reduction of IBRs-rich power networks for fast assessment of power system strength - part 2: data-driven techniques -- 5.1 Data-driven techniques -- 5.2 Black-box identification of the ES -- 5.2.1 Non-parametric techniques -- 5.2.2 Parameter estimation techniques -- 5.3 Application of measurement-based techniques to IBR-integrated networks -- 5.3.1 Measurement-based coherency identification -- 5.4 Case study - identification of the ES coherent generators in the AU14G system using the dynamic time warping technique -- 5.5 Measurement-based reduction of wind power plants, solar power plants, microgrids, and ADNs -- 5.5.1 Wind farms -- 5.5.2 Solar farms -- 5.5.3 Microgrids -- 5.5.4 ADNs -- 5.6 Case study: dynamic model reduction of the ES using LSTM recurrent neural networks -- 5.7 Research gaps and conclusions -- References -- 6 Inverter-based resources and their impact on power system inertia and system strength -- 6.1 Introduction -- 6.1.1 What is inertia, and why is it important in the power system? -- 6.1.2 Historical perspectives -- 6.1.3 How IBRs impact power system inertia? -- 6.1.4 How IBRs impact power system strength? -- 6.2 Frequency response and inertia -- 6.3 Inertia requirement. 327 $a6.4 Estimation methods of power system inertia -- 6.5 Power system inertia estimation -- 6.6 Case study of a power system with integrated wind energy plant -- 6.6.1 Frequency response to different IBR integration levels -- 6.6.2 System inertia estimation at different IBR integration levels -- 6.7 Research gaps, industry challenges, and future research directions -- 6.7.1 Research gaps -- 6.7.2 Industry challenges -- 6.7.3 Future research directions -- 6.8 Conclusions -- References -- 7 The effect of power system strength on the calculation of available transmission capacity -- 7.1 Introduction -- 7.1.1 The basics of power systems strength -- 7.1.2 Concepts and definitions of ATC -- 7.1.3 Static ATC -- 7.1.4 Dynamic ATC -- 7.2 DATC and holomorphic approach -- 7.2.1 DATC and holomorphic hybrid method -- 7.2.2 Example network -- 7.2.3 Simulation and comparison -- 7.2.4 Wind farms In Iran -- 7.2.5 Approximate NRS algorithm -- 7.2.6 Developed DH algorithm -- 7.2.7 Revised method of holomorphic embedded load flow -- 7.2.8 APEBS method -- 7.2.9 Conclusion -- 7.3 DATC and DELF -- 7.3.1 SATC and DELF -- 7.3.2 DELF -- 7.3.3 AMD method -- 7.4 DATC and HVDC and wind -- 7.4.1 Importance of HVDC network -- 7.4.2 Mathematical model of AC/DC network -- 7.4.3 Solving the AC/DC load flow equation -- 7.4.4 SATC and holomorphic method -- 7.4.5 Conclusion -- 7.5 ATC and state estimation -- 7.6 ATC and cyber security -- 7.6.1 Power system cybersecurity -- 7.6.2 WLS method -- 7.6.3 The suggested algorithm -- 7.6.4 With/without cyberattacks in ATC -- 7.7 Conclusion -- References -- 8 Advanced control approach for providing system strength -- 8.1 Introduction -- 8.2 Fuzzy approximation controller for MIMO system -- 8.2.1 Input-output feedback linearization -- 8.2.2 General MIMO system fuzzy approximation controller -- 8.2.3 Stability of the closed-loop. 327 $a8.3 PV grid-connected inverter adaptive fuzzy controller -- 8.3.1 PV grid-connected inverter system model -- 8.3.2 Input-output feedback linearization for PV grid-connected inverter system -- 8.3.3 PV grid-connected inverter adaptive fuzzy controller -- 8.4 Simulation situations and results -- 8.4.1 Situation I: unity power factor -- 8.4.2 Situation II: tracking of reactive current changes -- 8.4.3 Situation III: tracking of active current changes -- 8.4.4 Situation IV: robust tracking -- 8.5 Research gaps and future work -- 8.6 Conclusions -- References -- 9 The impact of renewable energy on voltage stability and fault level -- 9.1 Introduction -- 9.2 Highlights -- 9.3 Power system strength -- 9.4 Short-circuit analysis and converters -- 9.5 Reference grid codes -- 9.6 Iterative short-circuit analysis -- 9.7 The Sicilian grid: a real case study -- 9.8 Procedure testing and dynamic simulations -- 9.9 Fault level of Sicilian power system -- 9.10 Fault level of 100% RES power system -- 9.11 Comparison of grid forming and grid following operation -- 9.12 Future research -- 9.13 Conclusions -- Bibliography -- 10 New smart devices-based strategies for optimal planning and operation of active electric distribution networks -- 10.1 Introduction -- 10.1.1 The AEDN concept -- 10.1.2 The basics of power systems strength -- 10.1.3 Original contributions -- 10.2 Technologies integrated into the AEDNs -- 10.2.1 Advanced meter infrastructure -- 10.2.2 Distributed energy resources -- 10.2.3 Demand response -- 10.2.4 Electric mobility -- 10.3 Smart devices-based strategy in the optimal planning and operation of the AEDNs -- 10.3.1 Database module -- 10.3.2 Decision-making module -- 10.4 Testing the strategy -- 10.5 Research gaps, challenges, and future research directions -- 10.6 Conclusions -- References -- Index. 330 $aThe comprehensive resource on measuring and improving the strength of power systems with distributed generation and loads. Covering the latest evaluation methods, best practice, case studies, and applications, the book enables researchers to advance the movement towards stable clean power systems. 410 0$aEnergy Engineering Series 606 $aSmart power grids$xTechnological innovations 606 $aElectric power systems 606 $aRe?seaux e?lectriques (E?nergie) 615 0$aSmart power grids$xTechnological innovations. 615 0$aElectric power systems. 615 6$aRe?seaux e?lectriques (E?nergie) 676 $a621.31 700 $aAlhelou$b Hassan Haes$01823035 701 $aHosseinzadeh$b Nasser$01823036 701 $aBahrani$b Behrooz$01823037 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911007178703321 996 $aPower System Strength$94389460 997 $aUNINA