Solution of an ELD problem with valve-point effect using artificial intelligence techniques

Sharma, Ansil; Goyal, Govind Rai

doi:10.18280/mmep.040304

Cited by 3 publications

(3 citation statements)

References 10 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This section presents and formulates the objective functions viz. cost, emission and combined objective function satisfying multiconstraints involving price penalty factor .The basic economic load dispatch problem incorporating valve point loading described by Sharma and Goyal et al, [11] is formulated through (1) and (2) as under;…”

Section: Methodsmentioning

confidence: 99%

Dual objective multiconstraint swarm optimization based advanced economic load dispatch

Maharana¹,

Dash²

2021

IJECE

View full text Add to dashboard Cite

In electric power system, the vital topic to be mooted is economic load dispatch (ELD). It is a non-linear problem with some unavoidable constraints such as valve point loading and ramp rate constraint. For solving ELD problem distint methods were devised and tried for different electric supply systems yielding slow convergence rates. To achieve fast convergence, dual objective multi constraint swarm optimization based advanced economic load dispatch (DOMSOBAELD) algorithm is proposed making use of simulated values of real power outages of a thermal power plant as initial estimates for PSO technique embedded in it and used for optimizing economic dispatch problem in this article. DOMSOBAELD method was developed in the form of amalgamating fluids. Presence of power line losses, multiple valves in steam turbines, droop constraints and inhibited zones were utilized to optimize the ELD problem as genuinely approximate as possible. The results obtained from DOSOBAELD are compared with particle swarm optimization (PSO), PSOIW and differential particle swarm optimization (DPSO) techniques. It is quite conspicuous that DOMSOBAELD yielded minimum cost values with most favourable values of real unit outputs. Thus the proposed method proves to be advantageous over other heuristic methods and yields best solution for ELD by selecting incremental fuel cost as the decision variable and cost function as fitness function.

show abstract

Section: Methodsmentioning

confidence: 99%

Dual objective multiconstraint swarm optimization based advanced economic load dispatch

Maharana¹,

Dash²

2021

IJECE

View full text Add to dashboard Cite

show abstract

“…As well as the cost function, a second-order function can be simple or considering the effect of opening and closing fuel valves or other items. Different methods of these restrictions are considered to solve the problem of economic dispatch [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Optimization of the Economic Dispatch problem by considering the emission dispatch with using the AMPSO

Neyestani¹,

Farsangi²

2018

AMA_C

View full text Add to dashboard Cite

In this paper, the problem of economic dispatch (ED), which is a problem with a nonlinear cost function, is solved using the proposed method. The ED problem, in addition to having a nonlinear function, also has a series of equal and unequal constraints that must be respected. Another important consideration when generating energy by power plants is, in addition to the cost, the issue of polluting the environment. In other words, in order to provide the power needed by consumers, in this issue two goals, reducing production costs and reducing the amount of emission, can be raised. This article covers all of the above issues. In this paper, an ultra-innovative algorithm is proposed to solve the problem. The proposed algorithm is based on the Particle Swarm Optimization algorithm. The proposed method is implemented on the systems under study with different conditions and the results obtained by AMPSO method are evaluated by other methods such as SA, NSGA-II and NSGA-III. The results show that the AMPSO produces optimal or nearly optimal solutions for the study systems.

show abstract

“…Flood Prevention Decision Support System (DSS) is a real-time flood forecasting and assessment system developed on the basis of artificial intelligence, which achieves an objective, scientific and accurate flood forecasting based on numerical simulation and artificial intelligence technology (Legono, 2003;Hames, Woodward and Gouldby, 2012;Dastorani, 2007;Sharma and Goyal, 2017). At present, researchers have applied the DSS technology to flood damage assessment, risk prediction, and flood disaster levels, and some results have been achieved (Muste and Firoozfar, 2016).…”

Section: Introductionmentioning

confidence: 99%

Intelligent Flood Disaster Forecasting Based on Improved Neural Network Algorithm

Zhang

Feng

Wang³

2018

Neuroquantology

View full text Add to dashboard Cite

Based on the existing researches, and in combination with the knowledge of artificial intelligence, management decision science, and theoretical derivation, this study constructs a flood forecasting model based on the improved neural network algorithm, applies it to flood forecasting and flood damage assessment, proposes a flood decision support system consisting of external conversion layer, information processing application layer and database layer, and optimizes BP neural system in view of its defects of slow convergence speed and long iteration time by genetic algorithm. The actual forecasting results show that the improved BP neural network proposed in this study has higher forecasting accuracy, and the correlation coefficient between forecasting results and actual monitoring results reaches 96%, far exceeding the forecasting accuracy of RBF neural network algorithm (68%), which proves the feasibility and rapidity of the proposed algorithm. The improved BP neural network algorithm is used for rapid flood disaster assessment, and the needs of flood disaster assessment in different stages are specifically analyzed. In terms of accuracy, the RBF algorithm's disaster assessment grades are relatively small, and the assessment effect using the algorithm proposed in this paper is the best.

show abstract

Solution of an ELD problem with valve-point effect using artificial intelligence techniques

Cited by 3 publications

References 10 publications

Dual objective multiconstraint swarm optimization based advanced economic load dispatch

Dual objective multiconstraint swarm optimization based advanced economic load dispatch

Optimization of the Economic Dispatch problem by considering the emission dispatch with using the AMPSO

Intelligent Flood Disaster Forecasting Based on Improved Neural Network Algorithm

Contact Info

Product

Resources

About