An Efficient Hybrid TLBO-PSO Approach for Congestion Management Employing Real Power Generation Rescheduling

Bashir, Muneeb Ul; Paul, Ward Ul Hijaz; Ahmad, Mubassir; Ali, Danish; Ali, Md Safdar

doi:10.4236/sgre.2021.128008

Cited by 15 publications

(7 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The TLBO algorithm was introduced by R.V. Rao et al in 2011 [32], [34], [37] and now has been applied for optimization problems in many engineering fields. TLBO algorithm a population-based meta-heuristic optimization algorithm inspired by the knowledge sharing approach in the classroom simulating the environment of classroom to optimize a given objective function.…”

Section: Tlbo-pid Controlmentioning

confidence: 99%

“…For the smart grid with wind power generation a robust LFC using coordinated V2G control and frequency controller is discussed in [36]. A congestion management scheme using a hybrid TLBO-PSO algorithm in a poolbased electricity market scenario is discussed in [37]. Investigation is done on the LFC of a two-area integrated power system having thermal and wind units with a PEV [38].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Load Frequency Control of Multi-Area Multi-Source Deregulated Power System with Electric Vehicles Using Teaching Learning-Based Optimization: A Comparative Efficacy Analysis

Kumar

Prasad

2023

Preprint

View full text Add to dashboard Cite

This article aims to present the efficacy analysis of electric vehicle (EV) charging/discharging process as a sink or a distributed energy source (DES) in the framework of LFC problem of multi-area multi-source deregulated power system (MAMS-DPS). The energy storage/extraction of EVs acts a noteworthy role in mitigation of deviation frequency of DPS. A problem of AGC system for two-area DPS having two thermal power generators of non-reheat type and aggregated fleet of EVs in each area is considered for study here. The electric power contract between the distribution (DISCOs) and generation (GENCOs) companies in the restructured environment of DPS is specified through a contract participation matrix named as the DPM. In DPS area deviation frequency, generated and tie-line powers fluctuate in case of variation of load. To resolve these problems the efficacy of EV is accessed applying the optimal control scheme using TLBO algorithm and compared performances with the control schemes based on the optimization algorithms of GA as well as PSO, and PI, PID control schemes. The comparative performance of responses of system variables of the deviation frequency, generated power, and tie-line power are analysed applying the control schemes as PI control for without/with EV cases, and PID control, and the GA/PSO/TLBO tuned-PI/PID control schemes for with EV case. The TLBO-PID control scheme outperforms to mitigate the deviations observing the steady-state error, undershoot, overshoot, and settling time performance indices.

show abstract

Section: Tlbo-pid Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Load Frequency Control of Multi-Area Multi-Source Deregulated Power System with Electric Vehicles Using Teaching Learning-Based Optimization: A Comparative Efficacy Analysis

Kumar

Prasad

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…On the other hand, TOU DR scheme and the RTP DR scheme are based on variable rates and both of them are non-dispatchable. All the above demand response schemes are implemented on customer side [9,10,11]. Though these schemes are very effective in achieving their purpose and primarily reducing the customer side bills, there still are some limitations to these DR schemes and there is a room for further research in this field.…”

Section: Demand Response Schemesmentioning

confidence: 99%

Demand Side Management and Demand Response for Optimal Energy Usage: An Overview

Paul

Siddiqui

Kirmani³

2022

PIJR

View full text Add to dashboard Cite

Being more than a decade old idea, the Demand-side management (DSM) is among the most vital part of the modern smart grid. DSM enables the utilities to minimize the gap between the supply and the demand by optimizing their pattern of user loads. At the same time, it helps them in achieving economic and energy efficient systems by reducing the peak to average (PAR). The implementation of DSM programs by the utilities could help them in improving their reliability, power quality, energy, and system efficiency. On the other hand, customers could be use it to improve their load profile, reduce the peak demands, save energy, and motivate them use more and more renewable energy. Thus, both the utilities and the consumers get benefitted by the implementation of DSM program in the smart grid. This study tries to understand the application of energy efficient policies and the demand response techniques with various DSM strategies. The study mainly focuses on the various characteristics that would lead to effective implementation of DSM programs with particular attention of the residential energy demand. Also, there will be a focus on enhancement of energy efficiency leading to more effective policy responses. The researchers could find this study very helpful as it could be employed to maximize the utility profits, the total load factor, peak demand and also minimize the consumer usage bills.

show abstract

“…[13] employed the dynamic programming approach for finding the best size and best placement of distribution generators in the power system for reducing energy losses, enhancing the reliability and voltage profile improvement. For the best distribution generation location and sizing, [14][15][16] used the PSO and GA technique to reduce network's active power losses in distribution system. To assess the sizing and position of different dispersed generating units in power system with various load models, authors in [17] devised an index based technique.…”

Section: Introductionmentioning

confidence: 99%

Optimal Positioning of Distributed Energy using Intelligent Hybrid Optimization

Paul,

Siddiqui,

Kirmani

2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

The renewable based energy source integration into the smart grid has seen a rapid surge lately and so has the role of distributed energy. By reducing the power losses within distribution network, the appropriate location and size of the distributed energy or distributed generation sources could be found. In this paper, it has been proposed that where the distribution generating units should be placed. An intelligent optimization technique has been utilized to position different distribution generators in the best possible way. These advancements have both the advantages and disadvantages of their own. The research employs a novel optimization technique based on a hybrid of genetic algorithm and particle swarm optimization techniques. Placing the distribution generations properly lowers the power losses and improves the profile of the voltage in the distribution system.

show abstract

An Efficient Hybrid TLBO-PSO Approach for Congestion Management Employing Real Power Generation Rescheduling

Cited by 15 publications

References 30 publications

Optimal Load Frequency Control of Multi-Area Multi-Source Deregulated Power System with Electric Vehicles Using Teaching Learning-Based Optimization: A Comparative Efficacy Analysis

Optimal Load Frequency Control of Multi-Area Multi-Source Deregulated Power System with Electric Vehicles Using Teaching Learning-Based Optimization: A Comparative Efficacy Analysis

Demand Side Management and Demand Response for Optimal Energy Usage: An Overview

Optimal Positioning of Distributed Energy using Intelligent Hybrid Optimization

Contact Info

Product

Resources

About