Methodological Priority List for Unit Commitment Problem

Tingfang, Yang; Ting, T. O.

doi:10.1109/csse.2008.714

Cited by 29 publications

(9 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, a new approach is proposed, with the implementation of a repair mechanism based on the priority list method (which is formed at the beginning of the algorithm), based on the principle of economics of thermal power plants [30,31]:…”

Section: Fitness Function Evaluationmentioning

confidence: 99%

Adaptive Genetic Algorithm for Hydro-thermal Unit Commitment Considering the Security Constraints

Postolov

Iliev²

2020

IJEEC

View full text Add to dashboard Cite

This paper proposes a new approach with two efficient metaheuristic algorithms, in combination with quadratic programming, to solve the nonlinear optimization problem Unit Commitment in a complex hydro-thermal power system i.e. Hydrothermal Unit Commitment (HTUC). The main goal is to minimize the total costs (which are a very non-linear and non-convex problem), while satisfying the many hydro-thermal constraints. Such constraints, together with the nonlinear non-convex and mixed-integer objective function, make the search space extremely complex. To solve such a complicated system, the paper proposes a hybridization of a developed binary-coded genetic algorithm (in which quadratic programming is integrated), with a particle swarm optimization (PSO) algorithm. PSO is applied to the final economic load dispatch (ELD), based on the optimal binary combination obtained from the genetic algorithm. A new approach has been proposed through the application of a repair mechanism, which is based on a priority list, in order to maintain the diversity of the population and prevent premature convergence. The entire algorithm was developed and tested in MATLAB and then applied to the IEEE 30 BUS test system. The experimental results show better performance of the proposed algorithm compared to the recently published algorithms, in terms of convergence, constraint handling, as well as better solution quality.

show abstract

Section: Fitness Function Evaluationmentioning

confidence: 99%

Adaptive Genetic Algorithm for Hydro-thermal Unit Commitment Considering the Security Constraints

Postolov

Iliev²

2020

IJEEC

View full text Add to dashboard Cite

show abstract

“…Initially, the method used is a conventional and simple method in the form of conventional iterations such as integer programming, dynamic programming, priority list (PL), lagrangian relaxation, etc. [3] [4] [5]. As technology advances, this method is often trapped in local optimal and various other optimization methods are introduced in the form of metaheuristics such as genetic algorithm (AG), fuzzy logic, ant colony, etc.…”

Section: Introductionmentioning

confidence: 99%

Unit Commitment-Security Constraints Using the Priority List-Genetic Algorithm Method in the IEEE 6 Bus and IEEE 14 BUS Case Studies

Apribowo

Erriyanto

Sutrisno

et al. 2021

JEEICT

View full text Add to dashboard Cite

Unit commitment (UC) is the scheduling of on-off operation of a power plant unit to meet the demand for electrical power over a certain period of time in order to obtain an economical total cost of generation The PL method is used for scheduling and the AG is optimized using DOE for ED problems. The results obtained from the research that there are still improvements in the calculation of ED problems using load flow constraints and can be corrected. The results of the comparison of the total percentage cost of IEEE 6 buses used in ED problems without considering the load flow constraints with those considering this problem amounted to 26.30%. The result of the comparison of the total percentage cost of IEEE 14 buses used in ED problems without considering load flow constraints with those considering this problem is 11.55%. The load flow calculation using Newton-Rapshon uses a smaller number of iterations and a shorter time than Gauss-Seidel.

show abstract

“…Subsequently, an improved pre-prepared power demand was combined with the Muller method [18]. There are other priority list methods such as ranking units based on the full-load average production cost of each unit [19] and on the incremental cost rate of each unit [20] or on the maximum load production cost as well [21]. However, the issue of increasing computational effort for systems with low residual demand has not been effectively addressed so far.…”

Section: Introductionmentioning

confidence: 99%

Netload-constrained Unit Commitment Considering Increasing Renewable Energy Penetration Levels: Impact of Generation Schedules and Operational Cost

Abujarad

Mustafa

Jamian

et al. 2018

IJAPE

View full text Add to dashboard Cite

In the context of low carbon power systems, the penetration levels of Renewable Energy Sources (RES) are expected to increase dramatically. In this regard, this paper investigates the maximum RES penetration level constrained by net load while considering an inflexible Unit Commitment (UC) model. To solve the UC problem, an enhanced priority list (EPL) based method is developed. In the proposed method, the plants were activated sequentially based on the operational price. The system constraint violations were repeatedly corrected until all system constraints (such as net load and spinning reserves) were satisfied. The proposed EPL method was efficient to achieve a near optimal solution under high shares of RES. Furthermore, the research work investigates three different scenarios representing penetration levels of 10% solar-only, 14.5% wind-only and 27.5% mixture of both solar and wind. The impact of each penetration level on the system scheduling and operational cost were analyzed in detail. The analysis presented shows that a potential operational cost savings of 21.6 $/MW, 20 $/MW and 11.1 $/MW is feasible under each of the represented scenarios, respectively.

show abstract

Methodological Priority List for Unit Commitment Problem

Cited by 29 publications

References 7 publications

Adaptive Genetic Algorithm for Hydro-thermal Unit Commitment Considering the Security Constraints

Adaptive Genetic Algorithm for Hydro-thermal Unit Commitment Considering the Security Constraints

Unit Commitment-Security Constraints Using the Priority List-Genetic Algorithm Method in the IEEE 6 Bus and IEEE 14 BUS Case Studies

Netload-constrained Unit Commitment Considering Increasing Renewable Energy Penetration Levels: Impact of Generation Schedules and Operational Cost

Contact Info

Product

Resources

About