Combined cycle power plant.Figure 14.2 Block diagram of ANN structure.Figure 14.3 Neural network model.Figure 14.4 Regression plot.Figure 14.5 Performance plot.Figure 14.6 Error Histogram.Figure 14.7 Training state plot.Figure 14.8 Forecast results for the month of March.
15 Chapter 15Figure 15.1 Basic work model of global aggregator (GA).Figure 15.2 Proposed charging scheme cycle.Figure 15.3 Flowchart of scenario 1.Figure 15.4 Flowchart of scenario 2.Figure 15.5 Fitting result of on time arrival.Figure 15.6 Fitting result of late arrivals.Figure 15.7 Fitting result of daily driving distance.Figure 15.8 SUV’s average waiting time in both scenarios.Figure 15.9 Hatchback’s average waiting time in both scenarios.Figure 15.10 Total charged hatchback in both scenarios.Figure 15.11 Total charged SUV in both scenarios.
List of Tables
1 Chapter 1Table 1.1 CEC 2005 benchmark function [67].Table 1.2 Parameters of different algorithms for benchmark functions.Table 1.3 Optimization result of CEC-2005 benchmark functions.Table 1.4 Variation of load demand (pu) and solar power generation (pu) with loa...Table 1.5 Cost and lifetime of different DGs.Table 1.6 Optimum placement of RDGs and shunt capacitors to the 33-bus distribut...Table 1.7 Optimum placement of RDGs and shunt capacitors to the 69-bus distribut...
2 Chapter 2Table 2.1 List of one-dimensional chaotic maps.Table 2.2 Unimodal and multimodal test problems and their details.Table 2.3 Results of the test problems with the proposed methods.Table 2.4 Non-parametric test outcomes (part-1).Table 2.5 Non-parametric test outcomes (part-2).Table 2.6 Datasheet values of PV modules at STC conditions.Table 2.7 Estimated parameters of the three-diode model for Kyocera (KC200GT mul...Table 2.8 Optimal parameter identification of the three-diode model for Canadian...Table 2.9 Normalized statistical analysisof the error function for the three-dio...Table 2.10 Normalized results of the sum of square error (SSE) for the three-dio...
3 Chapter 3Table 3.1 Comparison of machine learning and artificial intelligence based islan...
4 Chapter 4Table 4.1 Rule base for fuzzy logic controller.
5 Chapter 5Table 5.1 Application of Genetic Algorithms for Hybrid Renewable Energy system o...
6 Chapter 6Table 6.1 Pulse pattern of H-bridge.Table 6.2 Specifications of SunPower SPR-305E-WHT-D module at STC.Table 6.3 Simulation parameters.Table 6.4 Harmonic distortion of line voltage w.r.t M.
7 Chapter 7Table 7.1 Electrical characteristics data of sun power SPR-305E-WHT-U module.Table 7.2 Parameter of wind turbine model.
8 Chapter 8Table 8.1 Values of exponential parameters for commercial, industrial and reside...Table 8.2 Load demand, candidate buses to access, and year of connection of the ...Table 8.3 Economic and environmental data.Table 8.4 Alternatives for substation and feeder upgradation.Table 8.5 Cost of upgrading feeders (×103USD).Table 8.6 Different planning cases.Table 8.7 Stage-wise investment plans for different planning cases.Table 8.8 Obtained values of objectives for different planning cases.Table 8.9 Detail analysis of economic performances of planning cases 1−3.Table 8.10 Detail analysis of Economic performances of planning cases 1−3.Table 8.11 Comparison of different optimization techniques.Table 8.12 WSRT based comparison between different algorithms.
9 Chapter 9Table 9.1 Cost estimate of PV system.Table 9.2 Market survey data for PV system design.Table 9.3 Module cost estimate.Table 9.4 Standards for PV installations.Table 9.5 Panel efficiencies.Table 9.6 Load description of a household consumer.Table 9.7 Lumped load data for a household.Table 9.8 Load consumption pattern.
10 Chapter 10Table 10.1 Fault class corresponding to fault type.Table 10.2 Training data set with known fault class.Table 10.3 Initial weight vector.Table 10.4 Updated weight vector after training.Table 10.5 Euclidean distance test data.
11 Chapter 11Table 11.1 Conventional grid versus smart grid.
12 Chapter 12Table 12.1 Consumers type and their connected nodes.Table 12.2 DG data at different nodes.Table 12.3 Allocated losses (kW) at 4 AM with different load models in scenario ...Table 12.4 Allocated losses (kW) at 11 AM with different load models in scenario...Table 12.5 Node-wise allocated energy losses (kWh) without DGs for entire day on...Table 12.6 Allocated losses (kW) at 4 AM with different load models in scenario ...Table 12.7 Allocated losses (kW) at 11 AM with different load models in scenario...Table 12.8 Node-wise allocated energy losses (kWh) with DGs for entire day on di...Table 12.9 Summary of total allocated energy losses (kWh) ahead of a day.
13 Chapter 13Table 13.1 Eigenvalues of 2-level STATCOM with PI controller.Table 13.2 Eigenvalues of 2-level STATCOM with nonlinear feedback for suboptimal...Table 13.3 Parameters used for optimization with genetic algorithm.Table 13.4 Eigenvalues of 2-level STATCOM with nonlinear feedback for suboptimal...Table 13.5 Eigenvalues of 3-level STATCOM with optimal controller parameters bas...Table 13.6 Parameters used for optimization with PSO.Table 13.7 Eigenvalues of 2-level STATCOM with nonlinear feedback for optimal co...Table 13.8 Operating combinations of VSC HVDC controllers.Table 13.9 Eigenvalues of the combined system in case-1 to case-4.Table 13.10 Eigenvalues of the combined system in case-5 to case-8.
14 Chapter 14Table 14.1 Gas turbine specifications.Table 14.2 Comparison between the actual load and predicted load.
15 Chapter 15Table 15.1 Car specification.Table 15.2 Nomenclature table.
Guide
1 Cover
5 Preface
8 Index
Pages
1 v
2 ii
3 iii
4 iv
5 xv
6