Reserve constrained economic dispatch with prohibited operating zones

Lee, F.N.; Breipohl, A.M.

doi:10.1109/59.221233

Cited by 252 publications

(147 citation statements)

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“…Bee Hive algorithm, proposed by Karaboga in 2005 for real parameter optimization, is a recently introduced optimization algorithm and simulates the foraging behavior of bee colony [2] for unconstrained optimization problems [1]- [5]. For solving constrained optimization problems, a constraint handling method was incorporated with the algorithm [7].…”

Section: Optimization Using Bee Hive Algorithmmentioning

confidence: 99%

“…Improvement in scheduling the units output can lead to significant cost savings. In traditional ELD problems, the cost function of each generator is approximately represented by a simple quadratic function and is solved using mathematical programming based on several optimization techniques such as dynamic programming, Linear programming, homogenous linear programming and quadratic programming methods [2], [3], [4]. However none of these methods may be able to provide an optimal solution and they usually get stuck at a local optimum.…”

Section: Introductionmentioning

confidence: 99%

“…However none of these methods may be able to provide an optimal solution and they usually get stuck at a local optimum. Normally the input-output characteristic of modern generating units are highly nonlinear in nature due to valve-point effect [1], [14], [15], [16], [18], [19] ramp-rate limits, Fuel switching [11], [20] etc, having multiple local minimum points in the cost function.…”

Section: Introductionmentioning

confidence: 99%

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Bee Hive Algorithm to Optimize Multi Constrained Piecewise Non-Linear Economic Power Dispatch Problem in Thermal Units

Padmanabhan¹,

S²

2011

ijeei

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This paper presents application of a Bee Hive Algorithm to Economic Load Dispatch which considers practical constraints and non linear characteristics. The proposed ED formulation includes ramp rate limits, valve loading effects, multiple fuels, equality and inequality constraints, which usually are found simultaneously in realistic power systems. Conventional methods such as Lambda iteration and Base point participation are not able to obtain optimal solution for units having discontinuous fuel cost functions. Bee Hive Algorithm can overcome the difficulties and provides an almost global optimal solution, since they don't get stuck up at local optimum.Keywords: Economic load Dispatch, Bee Hive Algorithm, Valve-point loading, Ramp rate limits, Multiple Fuels IntroductionECONOMIC Load Dispatch (ELD) seeks "the best" generation for the generating plants to supply the required demand plus transmission losses with the minimum production cost. Improvement in scheduling the units output can lead to significant cost savings. In traditional ELD problems, the cost function of each generator is approximately represented by a simple quadratic function and is solved using mathematical programming based on several optimization techniques such as dynamic programming, Linear programming, homogenous linear programming and quadratic programming methods[2],[3], [4]. However none of these methods may be able to provide an optimal solution and they usually get stuck at a local optimum. Normally the input-output characteristic of modern generating units are highly nonlinear in nature due to valve-point effect [ [19], etc., have been proposed to solve ELD problem. These techniques can be used to search the global optimum with any type of objective function and constraints [22]. In this paper, two ED problem for 3 and 10 thermal units with a non smooth fuel cost function [8] are employed to demonstrate the performance of the proposed method with BHA and the results were compared with GA.The rest of this paper is organized as follows: Section II describes the formulation of an ED problem; while section III explains the standards in BHA. Section IV then details the procedure of handling the BHA. Section V gives the flow chart. Section VI gives the Data and gives the results of the optimization. Section VII outlines our conclusion and future research.

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Section: Optimization Using Bee Hive Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bee Hive Algorithm to Optimize Multi Constrained Piecewise Non-Linear Economic Power Dispatch Problem in Thermal Units

Padmanabhan¹,

S²

2011

ijeei

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“…The resulting ELD is a non-convex optimization problem, which is a challenging one and cannot be solved by the traditional methods. An ELD problem with valve point loading has also been solved by dynamic programming (DP) [7,8]. Though promising results are obtained in small sized power systems while solving it with DP, it unnecessarily raises the length of solution procedure resulting in its vulnerability to solve large size ELD problems in stipulated time frames.…”

Section: Introductionmentioning

confidence: 99%

Economic Load Dispatch Using a Chemotactic Differential Evolution Algorithm

Biswas¹,

Dasgupta²,

Panigrahi³

et al. 2009

Lecture Notes in Computer Science

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Abstract. This paper presents a novel stochastic optimization approach to solve constrained economic load dispatch (ELD) problem using Hybrid Bacterial Foraging-Differential Evolution optimization algorithm. In this hybrid approach computational chemotaxis of BFOA, which may also be viewed as a stochastic gradient search, has been coupled with DE type mutation and crossover of the optimization agents. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

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“…Operating in those zones may cause amplification of vibrations in a shaft bearing, which must be avoided in practice. The PED problem becomes a non-convex optimization problem because the prohibited regions separate the decision space into disjoint subsets constituting a non-convex solution space [1]. Furthermore, utilities must maintain some generation capacity as spinning reserve to serve loads in the event that operating units or other equipment suddenly or unexpectedly failed.…”

Section: Introductionmentioning

confidence: 99%

Artificial Immune Algorithm for Practical Power Economic Dispatch Problems

Chiang¹

2013

IJMLC

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Abstract-This paper proposes an artificial immune algorithm with a multiplier updating method (AIA-MU) for practical power economic dispatch (PED) considering units with prohibited operating zones (POZ). The AIA equipped with a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the system constraints. To show the advantages of the proposed algorithm, two examples are investigated, and the computational results of the proposed method are compared with that of the previous methods. The proposed approach integrates the AIA and the MU, revealing that the proposed approach has the following merits -ease of implementation; applicability to non-convex fuel cost functions of the POZ; better effectiveness than previous methods, and the requirement for only a small population in applying the optimal PED problem of generators with POZ.Index Terms-Power economic dispatch, artificial immune algorithm, prohibited operating zones.

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Reserve constrained economic dispatch with prohibited operating zones

Cited by 252 publications

References 1 publication

Bee Hive Algorithm to Optimize Multi Constrained Piecewise Non-Linear Economic Power Dispatch Problem in Thermal Units

Bee Hive Algorithm to Optimize Multi Constrained Piecewise Non-Linear Economic Power Dispatch Problem in Thermal Units

Economic Load Dispatch Using a Chemotactic Differential Evolution Algorithm

Artificial Immune Algorithm for Practical Power Economic Dispatch Problems

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