Optimization of Power System Problems - Methods, Algorithms and MATLAB Codes
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40,00 €
| Verlag | Springer |
| Auflage | 2020 |
| Seiten | 382 |
| Format | 15,9 x 2,9 x 24,4 cm |
| Gewicht | 742 g |
| Artikeltyp | Englisches Buch |
| Reihe | Studies in Systems, Decision and Control 262 |
| ISBN-10 | 303034049X |
| EAN | 9783030340490 |
| Bestell-Nr | 03034049A |
This book presents integrated optimization methods and algorithms for power system problems along with their codes in MATLAB. Providing a reliable and secure power and energy system is one of the main challenges of the new era. Due to the nonlinear multi-objective nature of these problems, the traditional methods are not suitable approaches for solving large-scale power system operation dilemmas. The integration of optimization algorithms into power systems has been discussed in several textbooks, but this is the first to include the integration methods and the developed codes. As such, it is a useful resource for undergraduate and graduate students, researchers and engineers trying to solve power and energy optimization problems using modern technical and intelligent systems based on theory and application case studies. It is expected that readers have a basic mathematical background.
Inhaltsverzeichnis:
Modelling for Composite Load Model Including Participation of Static and Dynamic Load.- A novel forward-backward sweep based optimal DG placement approach in radial distribution systems.- Optimal capacitor placement in distribution systems using backward-forward sweep based load flow method.- Optimal capacitor placement and sizing in distribution networks¬.- Binary Group Search Optimization for Distribution Network Reconfiguration.- Combined heat and power economic dispatch using particle swarm optimization.- Combined heat and power stochastic dynamic economic dispatch using particle swarm optimization considering load and wind power uncertainties.- Economic dispatch of multiple-chiller plants using Wild Goats algorithm.- Optimization of tilt angle for intercepting maximum solar radiation for power generation.- Probabilistic power flow analysis of distribution systems using Monte Carlo simulations.- Long-Term Load Forecasting Approach Using Dynamic Feed-Forward Back-Propagation Ar tificial Neural Network.- Multi-objective economic and emission dispatch using MOICA: a competitive study.- Voltage Control by Optimized Participation of Reactive Power Compensation Using Fixed Capacitor and STATCOM.- Backward-forward sweep based power flow algorithm in distribution systems.