An efficient global technique for solving the network constrained static and dynamic economic dispatch problem

Nawaz, Aamir; Saleem, Nasir; Mustafa, Ehtasham; Khan, Umair Ali

doi:10.3906/elk-1503-236

Cited by 18 publications

(12 citation statements)

References 23 publications

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“…For more rational and precise modelling of fuel cost function, the above expression of cost function is to be modified suitably. The generating units with multivalve steam turbines exhibit a greater variation in the fuel-cost functions [18]. The valve opening process of multi-valve steam turbines produces a ripple-like effect in the heat rate curve of the generators.…”

Section: Valve-point Loading Effectmentioning

confidence: 99%

Optimal load scheduling of Nigerian power system with valve point effect using Jaya optimization algorithm

Abanihi

Ndunagu

2019

Nig. J. Tech.

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Economic load dispatch is a non-linear optimization problem which is of great importance in power systems. This paper proposes the optimal scheduling of the Nigeria Integrated Power System considering valve point loading effect using Jaya Optimization Algorithm (JOA).Data was collected from national control centre Osogbo and was used to develop cost function for the thermal stations actively contributing power to the national grid. M file was written in MatLab R2012a environment using Jaya Optimization Algorithm, Pattern Search Algorithm (PSA) and Genetic Algorithm (GA) to optimally schedule power generation by the power system. Result obtained showed that scheduling with JOA produced a cost of 210.8092N/hr, PSA produced a cost of 211.9579N/hr and GA produced a cost of 212.6687N/hr. The simulation result shows the advantage of the proposed method for reducing the total cost of power generation by the system over the other methods.

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Section: Valve-point Loading Effectmentioning

confidence: 99%

Optimal load scheduling of Nigerian power system with valve point effect using Jaya optimization algorithm

Abanihi

Ndunagu

2019

Nig. J. Tech.

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“…The cost is minimized by incorporating energy market prices, supply demand and inclusion of renewable energy sources. Nelder–Mead algorithm is presented in [ 45 ] to address the EDP with generator constraints and transmission losses. In electrical networks, different plants feed multiple loads, and this scenario is tackled in [ 46 ] through evolutionary particle swarm optimization to determine the optimal dispatch problem by including spinning reserve constraints and failure of any generating unit.…”

Section: Introductionmentioning

confidence: 99%

A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines

et al. 2022

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The reformations of the electrical power sector have resulted in very dynamic and competitive market that has changed many elements of the power industry. Excessive demand of energy, depleting the fossil fuel reserves of planet and releasing the toxic air pollutant, has been causing harm to earth habitats. In this new situation, insufficiency of energy supplies, rising power generating costs, high capital cost of renewable energy equipment, environmental concerns of wind power turbines, and ever-increasing demand for electrical energy need efficient economic dispatch. The objective function in practical economic dispatch (ED) problem is nonlinear and non-convex, with restricted equality and inequality constraints, and traditional optimization methods are incapable of resolving such non-convex problems. Over the recent decade, meta-heuristic optimization approaches have acquired enormous reputation for obtaining a solution strategy for such types of ED issues. In this paper, a novel soft computing optimization technique is proposed for solving the dynamic economic dispatch problem (DEDP) of complex non-convex machines with several constraints. Our premeditated framework employs the genetic algorithm (GA) as an initial optimizer and sequential quadratic programming (SQP) for the fine tuning of the pre-optimized run of GA. The simulation analysis of GA-SQP performs well by acquiring less computational cost and finite time of execution, while providing optimal generation of powers according to the targeted power demand and load, whereas subject to valve point loading effect (VPLE) and multiple fueling option (MFO) constraints. The adequacy of the presented strategy concerning accuracy, convergence as well as reliability is verified by employing it on ten benchmark case studies, including non-convex IEEE bus system at the same time also considering VPLE of thermal power plants. The potency of designed optimization seems more robust with fast convergence rate while evaluating the hard bounded DEDP. Our suggested hybrid method GA-SQP converges to achieve the best optimal solution in a confined environment in a limited number of simulations. The simulation results demonstrate applicability and adequacy of the given hybrid schemes over conventional methods.

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“…Reference [15] discussed about the employment of Dragonfly algorithm to solve DED problem for just IEEE 5 unit test case. Aamir Nawaz et.al discussed about the constrained globalized Nelder-Mead algorithm to solve DED test cases for both convex and non-convex problems [16]. Reference [17] discussed about Memory-based Global Differential Evolution (MGDE) algorithm to solve DED problem.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Economic Dispatch of Power System Network Having Thermal Units and Electric Vehicles using IGWO

Jain

Mani

Siddiqui

2021

mjee

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Grey Wolf optimizer is a well-known metaheuristic technique but it faces the problem of premature convergence, trapping in local optima and poor balance between exploration and exploitation. Hence, various modifications have been proposed over past few years. One such modification is modelling the prey position as dynamic in nature as shown in GWOLF. However, still it has been observed that to get better solution, GWOLF needs to be modified too, hence an improved version of GWO (IGWO) is proposed. IGWO has the advantage of both GWO and GWOLF. In this paper, IGWO is used to solve Dynamic Economic Dispatch (DED) problem. IGWO is having a better balance between exploitation and exploration for the complex problem such as Dynamic Economic Dispatch (DED) taking into account of valve-point effect, transmission losses and ramp-rate limits with and without Electric Vehicles (EVs). The efficiency of the algorithm is demonstrated on solving different DED problems for 5 generator and 15 generator test systems with and without losses along with different charging profile distribution of electric vehicles. The results showcased by IGWO is compared with the other algorithm. The results obtained by IGWO algorithm adopted in solving dynamic economic dispatch problem is giving competitive results as compared to the results given by other algorithm present in literature.

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An efficient global technique for solving the network constrained static and dynamic economic dispatch problem

Cited by 18 publications

References 23 publications

Optimal load scheduling of Nigerian power system with valve point effect using Jaya optimization algorithm

Optimal load scheduling of Nigerian power system with valve point effect using Jaya optimization algorithm

A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines

Dynamic Economic Dispatch of Power System Network Having Thermal Units and Electric Vehicles using IGWO

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