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| 050 | 4 | _aTK1005 -- .O625 2008eb | |
| 082 | 0 | _a621.3191 | |
| 100 | 1 | _aCastronuovo, Edgardo D. | |
| 245 | 1 | 0 | _aOptimization Advances in Electric Power Systems. |
| 250 | _a1st ed. | ||
| 264 | 1 |
_aHauppauge : _bNova Science Publishers, Incorporated, _c2009. |
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| 264 | 4 | _c©2009. | |
| 300 | _a1 online resource (307 pages) | ||
| 336 |
_atext _btxt _2rdacontent |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 505 | 0 | _aIntro -- OPTIMIZATION ADVANCESIN ELECTRIC POWER SYSTEMS -- OPTIMIZATION ADVANCESIN ELECTRIC POWER SYSTEMS -- CONTENTS -- PREFACE -- ABOUT THE EDITOR -- Chapter1AMATHEMATICALPROGRAMMINGAPPROACHTOSTATEESTIMATION -- Abstract -- 1.Introduction -- 2.Formulation -- 3.Observability -- 4.ClassicalSolution -- 5.MathematicalProgrammingSolution -- 6.BadMeasurementDetection -- 7.IdentificationofErroneousMeasurements -- 8.Sensitivity -- 9.Decomposition -- 10.Conclusions -- A.VectorsandMatricesforSensitivityAnalysis -- References -- Chapter2TRUSTREGIONOPTIMIZATIONMETHODSVIAGIVENSROTATIONSAPPLIEDTOPOWERSYSTEMSTATEESTIMATION -- 1.Introduction -- 2.StateEstimationBackground -- 2.1.MeasurementModelandWeightedLeastSquaresEstimator -- 2.2.SolutionthroughGauss-NewtonMethod -- 2.3.APrioriStateInformationinLeast-SquaresProblems -- 2.4.SolutionthroughGivensRotations -- 2.4.1.AMacroViewofPSSEviaGivensRotations -- 2.4.2.TheElementaryG3MGivensRotations-InterpretationofScalingFactors -- 3.TrustRegionTheoreticalBasis -- 3.1.RationaleofTrustRegionApproach -- 3.2.BasicTrustRegionAlgorithm -- 3.3.EnsuringStepFeasibilityvia > -- 0 -- 4.TrustRegionMethodsthroughGivensRotations -- 4.1.The −RefactorizationMethod -- 4.2.TheAPSIMethod -- 4.3.QualitativeAppraisal -- 5.SimulationResults -- 5.1.6-busSystem -- 5.2.30-busSystem -- 5.3.118-busand300-busSystems -- 5.4.ComparisonofNumericalPerformance -- 6.Conclusions -- Appendix -- A.DefinitionoftheTrustRegion -- Computationof°′2 -- Computationof -- B.Dataforthe6-BusTestSystem -- References -- Chapter 3THE IMPACT OF DEREGULATION ONMATHEMATICAL MODELS USING OPTIMIZATIONTECHNIQUES TO AID SYSTEM PLANNINGAND OPERATIONS -- Abstract -- The Issue of Reactive Power -- Transmission Rights -- Generation and Transmission additions -- Relation between Mathematical Models and Markets, andOperating Philosophy -- Greenhouse Gases -- Unit Commitment. | |
| 505 | 8 | _aEpilogue -- References -- Chapter 4METAHEURISTIC-BASED OPTIMIZATION METHODSFOR TRANSMISSION EXPANSION PLANNINGCONSIDERING UNRELIABILITY COSTS -- Abstract -- 1. Introduction -- 2. Heuristic-Based Methodologies -- 2.1. Evolution Strategies -- 2.1.1. Basic Concepts -- 2.1.2. Application to TEP Problems -- 2.2. Tabu Search -- 2.2.1. Basic Concepts -- 2.2.2. Application to TEP Problems -- 2.3. Ant Colony Optimization -- 2.3.1. Basics Concepts -- 2.3.2. Application to TEP Problems -- 3. Proposed Methodologies -- 3.1. Initialization Process -- 3.2. Transmission Loss Costs -- 3.3. Chronological Aspects -- 3.4. Unreliability Costs -- 3.5. Proposed Algorithms -- 3.5.1. ES and TS Algorithms -- 3.5.2. ACO Algorithm -- 4. Results -- 4.1. Small Test System -- 4.1.1. ES Results -- 4.1.2. TS Results -- 4.1.3. ACO Results -- 4.1.4. Performance Comparison of ES, TS and ACO Algorithms -- 4.2. Brazilian Sub-transmission Network -- 4.2.1. ES Results -- 4.2.2. TS Results -- 4.2.3. ACO Results -- 4.2.4. Performance Comparison of ES, TS and ACO Algorithms -- 5. Conclusion -- 6. Appendix: Simple Test System Data -- References -- Chapter 5A VOLTAGE CONTROL OPTIMIZATION FORDISTRIBUTION NETWORKS WITH DG ANDMICROGRIDS -- Abstract -- Acronyms and Abbreviations -- 1. Introduction -- 2. Hierarchical Voltage Control -- 3. Characterization of the Voltage Control Optimization Problem -- 3.1. Mathematical Formulation -- 3.1.1. Defining an Objective Function -- Reducing Active Power Losses -- Maintaining Voltage Profiles -- 3.1.2. Defining the Control Variables -- 3.1.3. Optimization Tool -- EPSO Description -- 3.2. Algorithm -- 4. Test Networks -- 5. Main Results -- 5.1. Objective Function 1 -- 5.2. Objective Function 2 -- 6. Conclusion -- Annex I. Electrical Distance Calculation -- References -- Chapter 6TOOLS FOR THE EFFECTIVE INTEGRATIONOF LARGE AMOUNTS OF WIND ENERGYIN THE SYSTEM. | |
| 505 | 8 | _aAbstract -- 1. Introduction -- 2. Wind Generation Bids in Pool-Based Electricity Markets -- 2.1. Nomenclature -- 2.2. Justification -- 2.3. Mathematical Model for the Individual Wind Power Bid -- 2.4. Mathematical Model for the Combined Bid -- 2.5. Results for Individual Wind Power Bid -- 2.6. Results for Combined Hydro-wind Power Bid -- 2.6.1. Hydro Generation Data -- 2.6.2. Wind Generation Data -- 2.6.3. Results -- 3. Coordination among Wind Farms and Water Pump Stations -- 4. Coordination among Different Wind Farms, DelegatedDispatches -- 5. Voltage Stability in Power Networks with Large Amount ofWind Energy -- 5.1. Two bus system with a Wind Farm -- 5.1.1. Increasing the Demand -- 5.1.2. Loss of Transmission and Generation Equipments -- 5.2. Voltage Stability Enhancement in Network with Wind Farms -- 5.3. Optimal Power Flow (OPF) Formulation -- 5.4. Modified IEEE 14-bus System -- 6. Conclusion -- References -- Chapter7APPLICATIONOFCOSTFUNCTIONSFORLARGESCALEINTEGRATIONOFWINDPOWERUSINGAMULTI-SCHEMEENSEMBLEPREDICTIONTECHNIQUE -- Abstract -- 1.Introduction -- 2.TheOptimisationProblem -- 2.1.EnergyPricesandMarketStructures -- 3.OptimisationObjectives -- 3.1.MarketConsiderations -- 3.2.TransitionfromFixedPricestotheLiberalisedMarket -- 3.3.TheSkewCompetitionintheTradingofWind -- 3.4.UncertaintyConsiderations -- 4.OptimisationSchemes -- 4.1.PoolingofEnergy -- 4.2.The"PriceMaker"OptimisationProblem -- 4.3.The"PriceTaker"OptimisationProblem -- 4.4.TheCombi-PoolOptimisationScheme -- 5.WindPowerForecastingMethods -- 5.1.DifferentApproachestoForecastPowerOutput -- 5.2.EnsemblePredictionSystems -- 5.3.TheMSEPSForecastingSystem -- 6.AspectsoftheForecastingError -- 6.1.WindPowerErrorDecomposition -- 7.ReservePredictionandOptimisation -- 7.1.OptimisationofReservePredictions:ExampleDenmark -- 7.2.OptimisationoftheReservePrediction:ExampleCanada. | |
| 505 | 8 | _a7.2.1.OptimisationScenarios -- 8.SummaryandDiscussion -- 9.Conclusion -- References -- Chapter 8SECURITY OPTIMIZATION OF BULK POWERSYSTEMS IN THE MARKET ENVIRONMENT -- 1.Abstract -- 2. Introduction -- 3. Optimization of the Voltage Profile in the Electricity MarketEnvironment -- 3.1. Objective Functions for ORPF Problems -- 3.1.1. Minimization of Real Losses -- 3.1.2. Modified Minimum Losses -- 3.1.3. Minimum Reactive Power Produced -- 3.1.4. Proximity to the Voltage Collapse and Voltage Control -- 3.1.5. Discussion on the Use of σmax -- 3.2. Integration of the ORPF into the Electricity Market Operation -- 4. Modern Approaches for Solving ORPF Problems -- 4.1. The Interior Point Method -- 4.2. An Artificial Intelligence Approach: Genetic Algorithms -- 4.2.1. An ORPF Based on GA: Implementation -- 4.2.1.1. Coding -- 4.2.1.2. Initial Population -- 4.2.1.3. Fitness Function and Ranking -- 4.2.1.4. Selection -- 4.2.1.5. Crossover -- 4.2.1.6. Mutation and Diversity -- 4.2.1.7. Penalty Coefficient -- 4.2.2. Tests of the GA ORPF on the Italian Power System -- 4.2.2.1. Real Losses -- 4.2.2.2. Modified Real Losses -- 4.2.2.3. Minimum Reactive Power Produced -- 4.2.2.4. Objective Function: σmax (Model 4) -- 5. Multiobjective Optimization -- 5.1. Multiobjective Methodologies -- 5.1.1. The Weight Method -- 5.1.2. The ε-Constraint Method -- 5.1.3. The Validation of the Pareto Set -- 5.1.4. The Choice of the Best Solution Using the Surrogate Worth Trade off Analysis -- 5.2. The Multiobjective Approach for the ORPF Problem -- 5.2.1. Minimization of Real Losses and Minimization of the Reactive PowerProduced -- 5.2.2. Security and Cost -- 6. Conclusions -- References -- Chapter 9OPTIMAL PLACEMENT IN POWER SYSTEM -- Abstract -- Optimal Monitoring Program for Voltage Sag Characterization ofPower Systems -- Nomenclature -- Introduction. | |
| 505 | 8 | _aAssessing Voltage Sags Performance -- Optimization Problem -- Application -- System Indices -- Redundancy -- Voltage Sag Estimation -- Conclusion -- Economic Evaluation of FACTS for Congestion Management inPool Markets -- Nomenclature -- Introduction -- Congestion Management Models -- Market Settlement of the Pool Model -- The Re-dispatch Models -- Economic Evaluation of FACTS -- Simulation Study -- Market Settlement -- Congestion Management Solutions -- Minimization of Absolute Re-dispatched Generation -- Minimization of the Congestion Cost -- Optimal Placement of FACTS Devices -- Conclusions -- Appendix -- References -- Chapter 10NON-LINEAR MATHEMATICAL PROGRAMMINGAPPLIED TO ELECTRIC POWER SYSTEMS STABILITY -- Abstract -- Introduction -- Definitions: -- Voltage Stability - Long Term Stability -- Rotor Angle Stability -- Algorithms for Rotor Angle Stability -- Incorporating Transient Stability Constraints -- Generalized Reduced Gradient method -- Successive Linear Programming Method -- Primal-Dual Interior Point Method -- Solution in the Euclidean Space -- Quasi-Newton Method -- Primal-Dual Interior Points Method -- Conclusion -- References -- INDEX -- Blank Page. | |
| 588 | _aDescription based on publisher supplied metadata and other sources. | ||
| 590 | _aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. | ||
| 650 | 0 | _aElectric power systems. | |
| 650 | 0 | _aMathematical optimization. | |
| 655 | 4 | _aElectronic books. | |
| 776 | 0 | 8 |
_iPrint version: _aCastronuovo, Edgardo D. _tOptimization Advances in Electric Power Systems _dHauppauge : Nova Science Publishers, Incorporated,c2009 _z9781606926130 |
| 797 | 2 | _aProQuest (Firm) | |
| 856 | 4 | 0 |
_uhttps://ebookcentral.proquest.com/lib/orpp/detail.action?docID=3020562 _zClick to View |
| 999 |
_c60904 _d60904 |
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