Optimization of Power System Problems Methods, Algorithms and MATLAB Codes / [electronic resource] :
edited by Mahmoud Pesaran Hajiabbas, Behnam Mohammadi-Ivatloo.
- 1st ed. 2020.
- XII, 382 p. online resource.
- Studies in Systems, Decision and Control, 262 2198-4190 ; .
- Studies in Systems, Decision and Control, 262 .
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 Artificial 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.
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.
9783030340506
10.1007/978-3-030-34050-6 doi
Electric power production.
Computational intelligence.
Electrical Power Engineering.
Mechanical Power Engineering.
Computational Intelligence.
TK1001-1841
621.31
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 Artificial 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.
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.
9783030340506
10.1007/978-3-030-34050-6 doi
Electric power production.
Computational intelligence.
Electrical Power Engineering.
Mechanical Power Engineering.
Computational Intelligence.
TK1001-1841
621.31