Two-layer optimization methodology for wind distributed generation planning considering plug-in electric vehicles uncertainty: A flexible active-reactive power approach

2016 ◽  
Vol 124 ◽  
pp. 231-246 ◽  
Author(s):  
Ali Ahmadian ◽  
Mahdi Sedghi ◽  
Masoud Aliakbar-Golkar ◽  
Michael Fowler ◽  
Ali Elkamel
Keyword(s):  
Distributed Generation ◽  
Electric Vehicles ◽  
Reactive Power ◽  
Generation Planning ◽  
Optimization Methodology

Optimization of Real Power Loss and Voltage Stability Index for Distribution Systems with Distributed Generation

2017 ◽  
Vol 33 ◽  
pp. 100-114 ◽  
Author(s):  
Mostafa Elshahed ◽  
Mahmoud Dawod ◽  
Zeinab H. Osman
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Reactive Power ◽  
Optimization Problems ◽  
Stability Index ◽  
Mixed Integer ◽  
Voltage Profile ◽  
Voltage Stability Index

Integrating Distributed Generation (DG) units into distribution systems can have an impact on the voltage profile, power flow, power losses, and voltage stability. In this paper, a new methodology for DG location and sizing are developed to minimize system losses and maximize voltage stability index (VSI). A proper allocation of DG has to be determined using the fuzzy ranking method to verify best compromised solutions and achieve maximum benefits. Synchronous machines are utilized and its power factor is optimally determined via genetic optimization to inject reactive power to decrease system losses and improve voltage profile and VSI. The Augmented Lagrangian Genetic Algorithm with nonlinear mixed-integer variables and Non-dominated Sorting Genetic Algorithm have been implemented to solve both single/multi-objective function optimization problems. For proposed methodology effectiveness verification, it is tested on 33-bus and 69-bus radial distribution systems then compared with previous works.

scholarly journals An Enhanced Quantum-Behaved Particle Swarm Algorithm for Reactive Power Optimization considering Distributed Generation Penetration

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Runhai Jiao ◽  
Bo Li ◽  
Yuancheng Li ◽  
Lingzhi Zhu
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Reactive Power ◽  
Power Optimization ◽  
Particle Swarm ◽  
Active Power ◽  
Particle Swarm Algorithm ◽  
Reactive Power Optimization ◽  
Distributed Generations ◽  
Better Than

This paper puts forward a novel particle swarm optimization algorithm with quantum behavior (QPSO) to solve reactive power optimization in power system with distributed generation. Moreover, differential evolution (DE) operators are applied to enhance the algorithm (DQPSO). This paper focuses on the minimization of active power loss, respectively, and uses QPSO and DQPSO to determine terminal voltage of generators, and ratio of transformers, switching group number of capacitors to achieve optimal reactive power flow. The proposed algorithms are validated through three IEEE standard examples. Comparing the results obtained from QPSO and DQPSO with those obtained from PSO, we find that our algorithms are more likely to get the global optimal solution and have a better convergence. What is more, DQPSO is better than QPSO. Furthermore, with the integration of distributed generation, active power loss has decreased significantly. Specifically, PV distributed generations can suppress voltage fluctuation better than PQ distributed generations.

Identification of the best topology of delta configured three phase induction generator for distributed generation through experimental investigations

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Vanka Bala Murali Krishna ◽  
Sandeep Vuddanti
Keyword(s):  
Distributed Generation ◽  
Reactive Power ◽  
Voltage Regulation ◽  
Reactive Power Compensation ◽  
Induction Generator ◽  
Experimental Investigations ◽  
Small Scale ◽  
Empirical Formulas ◽  
Simple Method ◽  
Main Challenge

Abstract Research on Self –excited induction generator (SEIG) brings a lot of attentions in the last three decades as a promising solution in distributed generation systems with low cost investment. There are two important fixations to attend in the operation of SEIG based systems, a) excitation and b) voltage regulation. Many procedures are reported regarding selection of excitation capacitance in the literature, based on state-state analysis, dynamic modeling, empirical formulas and machine parameters which involve various levels of complexity in findings. Moreover, the voltage regulation is the main challenge in implementation of SEIG based isolated systems. To address this problem, many power electronic-based schemes are proposed in the literature and but these solutions have few demerits importantly that additional cost of equipment and troubles due to failure of protection schemes. In particular, the installation of SEIG takes place at small scale in kW range in remote/rural communities which should not face such shortcomings. Further in case of off-grid systems, the maximum loading is fixed based on connected rating of the generator. This paper presents the various methods to find excitation capacitance and illustrates an experimental investigation on different possible reactive power compensation methods of delta connected SEIG and aimed to identify a simple method for terminal voltage control without power electronics. In this experimental work, the prime-mover of the generator is a constant speed turbine, which is the emulation of a micro/pico hydro turbine. From the results, it is found that a simple delta connected excitation and delta configured reactive power compensation limits voltage regulation within ±6% while maintaining the frequency of ±1%, which make feasible of the operation successfully in remote electrification systems.

Fuzzy logic-based hybrid active filter for compensating harmonic and reactive power in distributed generation

2021 ◽  
Vol 14 (4) ◽  
pp. 405
Author(s):  
Buddhadeva Sahoo ◽  
Sangram Keshari Routray ◽  
Pravat Kumar Rout
Keyword(s):  
Fuzzy Logic ◽  
Distributed Generation ◽  
Reactive Power ◽  
Active Filter

Reactive power compensation using electric vehicles considering drivers’ reasons

2018 ◽  
Vol 12 (20) ◽  
pp. 4407-4418 ◽  
Author(s):  
Su Su ◽  
Yong Hu ◽  
Shidan Wang ◽  
Wei Wang ◽  
Yutaka Ota ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Reactive Power ◽  
Reactive Power Compensation
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