Semidefinite programming solution of economic dispatch problem with non-smooth, non-convex cost functions

Alawode, Kehinde O.; Jubril, Abimbola M.; Kehinde, L K; Ogunbona, Philip

doi:10.1016/j.epsr.2018.07.026

Cited by 41 publications

(16 citation statements)

References 36 publications

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“…SDP is a generalization of the linear program (LP) in which the vector variables are modified by matrix variables and the element-wise non-negativity by positive semidefiniteness of the matrices [21,22]. In this paper, an optimization problem is characterized by using primal SDP form [12]:…”

Section: Semidefinite Programmingmentioning

confidence: 99%

“…Thus, the resulting SDP problem is rough to solve to global optimality. The relaxation of the SDP problem means that the non-convex constraints are embedded in a larger convex constraint set [12]. Contemplate the problem with non-convex constraint set .…”

Section: Semidefinite Programmingmentioning

confidence: 99%

“…SDP has recently received much attention for various problems solution in power system analysis. Some applications are: In [12], it has been shown that SDP can effectively solve high dimension, non-smooth power system problems. In [13], the authors used an SDP method to solve the economic emission dispatch (EED) problem.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Investigation the Success of Semidefinite Programming for the Estimating of Fuel Cost Curves in Thermal Power Plants

Güvenç

Bakır²,

Duman³

2021

Politeknik Dergisi

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Section: Semidefinite Programmingmentioning

confidence: 99%

Section: Semidefinite Programmingmentioning

confidence: 99%

See 1 more Smart Citation

Investigation the Success of Semidefinite Programming for the Estimating of Fuel Cost Curves in Thermal Power Plants

Güvenç

Bakır²,

Duman³

2021

Politeknik Dergisi

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“…As shown in Table 10, the optimal cost obtained by the CGQBA is $121406.8912/hr. Table 11 provides the comparison between the results obtained by the CGQBA and those obtained by the other methods (the CHK [18], SSA [21], MSSA [46], CSA, MCSA [50], PPSO [51], SSA, ESSA [53], θ-MBA [64], CBA [67], CE-SQP [87], BA [97], FMILP [91], BSA [94], AAA, HAAA [99], IGA, MPSO, GWO, GWOI, GWOII, NGWO, NPSO [100], CJAYA, PSO-LRS [101], BBO, HBMO, IHBMO , MABC [102], SQPSO [103], OIWO [104], CSO, OLCSO [105], PI-CBA [106], AGWO [107], SDP [108],QPSO, QPSO-M1 [109], IODPSO-G, and IODPSO-L [110]). The statistical results reveal that the CGQBA can compete with many optimization methods; only the PI-CBA, HAAA and AGWO perform better than the CGQBA.…”

Section: E Test Systemmentioning

confidence: 99%

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

et al. 2020

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In this paper, a novel Cauchy-Gaussian quantum-behaved bat algorithm (CGQBA) is applied to solve the economic load dispatch (ELD) problem. The bat algorithm (BA) is an acknowledged metaheuristic optimization algorithm owing to its performance. However, the classical BA presents some weaknesses, such as premature convergence. To withstand the drawbacks of the BA, quantum mechanics theories and Gaussian and Cauchy operators are integrated into the standard BA to enhance its effectiveness. Since the economic load dispatch is a nonlinear, complex and constrained optimization problem, its main objective is to reduce the total generation cost while matching the equality and inequality constraints of the system. The validity of the CGQBA is tested on six standard benchmark functions with different characteristics. The numerical results indicate that the CGQBA is effective and superior to many other algorithms. Moreover, the CGQBA is applied to solve the ELD problems on various test systems including 3,6,20, 40,110 and 160 implemented generating units. The simulation results illustrate the strength of the CGQBA compared with other algorithms recently reported in the literature.

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“…In non-smooth problems, the impact of the valve system is considered in the power generation cost function. Both smooth and non-smooth problems aresuccessfully solved using heuristic techniques as reported, respectively, in [5][6] and [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Solving Non-Smooth Economic Load Dispatch Problem via Flower Pollination Algorithm

2020

IJETER

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This paper discusses the generator optimization method for non-smooth economic dispatch (ED) in power systems using the Flower Pollination Algorithm (FPA). The generating value of each unit is determined without compromising the power limits of each generator and the amount of energy demand. The objective of this study is to provide the minimumgenerating costs based on the seamless cost function of the ED. The feasibility of the FPA method is compared with particle swarm optimization (PSO) and moth flame optimizer (MFO). Two types of power system networks, 10and 40-generators, are tested using MATLAB. Simulation results show that compared with PSO and MFO,FPA provides better results in optimizing energy generation with minimum generation cost and power loss.

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Semidefinite programming solution of economic dispatch problem with non-smooth, non-convex cost functions

Cited by 41 publications

References 36 publications

Investigation the Success of Semidefinite Programming for the Estimating of Fuel Cost Curves in Thermal Power Plants

Investigation the Success of Semidefinite Programming for the Estimating of Fuel Cost Curves in Thermal Power Plants

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

Solving Non-Smooth Economic Load Dispatch Problem via Flower Pollination Algorithm

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