Improving Lagrangian Relaxation Unit Commitment with Cuckoo Search Algorithm

Zeynal, Hossein; Hui, Lim Xiao; Jiazhen, Yap; Eidiani, Mostafa; Azzopardi, Brian

doi:10.1109/pecon.2014.7062417

Cited by 18 publications

(6 citation statements)

References 14 publications

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“…Mixed-binary Unit commitment problem based on LR approach which in fact embrace decoupling constraints is formulated in (8)(9)(10)(11)(12)(13)(14)(15)(16). The object is to minimize the total quadratic cost of power production including a, b, c as the cost coefficients and the main variable which is ( ) plus with start-up cost of the unit ( ) for all the generators (NG) over the study period (T) [1][2][3][4][5].…”

Section: Objective Functionmentioning

confidence: 99%

“…As a part of the prime intent of this paper, electric vehicle operations are incorporated into the UC model to further jeopardize LR solution mechanism when it comes to an increased number of coupling constraints stated in (12)(13)(14)(15). The power delivered/withdrawn (+/-) to/from the grid is given in (12). As of the dual mode of EV fleets when connected to the grid, in (13) stresses that the charging and discharging operational mode of EV are mutually exclusive.…”

Section: Objective Functionmentioning

confidence: 99%

“…However, it offers a dichotomy in optimal operation of the system. It is adventurous if EVs can be scheduled to connect and disconnect to the power grid in suitable time and optimal place to improve the security of the power grids [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Improved Lagrangian relaxation generation decision-support in presence of electric vehicles

Zeynal¹,

Zakaria

Kor

2021

IJEECS

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Decision making strategies for resources available in macro/micro scales have long been a critical argument. Among existing methods to address such a mixed-binary optimization model, Lagrangian relaxation (LR) found universal acceptance by many utilities, offering a fast and accurate answer. This paper aims at retrofitting the solution way of LR algorithm by dint of meta-heuristic cuckoo search algorithm (CSA). When integrating CSA into LR mechanism, a tighter duality gap is catered, representing more accurate feasible solution. The key performance of CSA exhibits a head start over other classical methods such as gradient search (GS) and Newton Raphson (NR) when dealt with the relative duality gap closure in LR procedure. Further, electric vehicles (EV) with its associated hard constraints are encompassed into model to imperiling the proposed CSA-LR if encountered with nonlinear fluctuation of duality gap. Simulation results show that the proposed CSA-LR model outperforms the solution quality with/without EV as compared with conventional NR-LR method.

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Section: Objective Functionmentioning

confidence: 99%

Section: Objective Functionmentioning

confidence: 99%

See 1 more Smart Citation

Improved Lagrangian relaxation generation decision-support in presence of electric vehicles

Zeynal¹,

Zakaria

Kor

2021

IJEECS

Self Cite

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“…Various solution techniques were proposed in the literature. While AI-based approaches have received increased attention [4], utilities and independent system operators (ISOs) widely use Dynamic Programming 2733 (DP) [5], Lagrangian Relaxation (LR) [3,6] and Mixed-Integer Linear Programming (MILP) methods [7][8][9][10][11][12][13]. DP is a stage-wise search for an optimal solution, upon dividing the main problem into smaller subproblems.…”

Section: Introductionmentioning

confidence: 99%

“…As compared with DP, LR does not suffer from the curse of dimensionality, albeit encountering instances of unnecessary commitment of units; rendering higher production costs [15]. Additionally, heuristic reasoning is required to meet the duality gap [6].…”

Section: Introductionmentioning

confidence: 99%

MILP-Based Short-Term Thermal Unit Commitment and Hydrothermal Scheduling Including Cascaded Reservoirs and Fuel Constraints

Shaaban¹,

Zeynal²,

Nor³

2019

IJECE

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Reservoirs are often built in cascade on the same river system, introducing inexorable constraints. It is therefore strategically important to scheme out an efficient commitment of thermal generation units along with the scheduling of hydro generation units for better operational efficiency, considering practical system conditions. This paper develops a comprehensive, unit-wise hydraulic model with reservoir and river system constraints, as well as gas constraints, with head effects, to commit thermal generation units and schedule hydro ones in the short-term. A mixed integer linear programming (MILP) methodology, using the branch and bound & cut (BB&C) algorithm, is employed to solve the resultant problem. Due to the detailed modelling of individual hydro units and cascaded dependent reservoirs, the problem size is substantially swollen. Multithread computing is invoked to accelerate the solution process. Simulation results, conducted on various test systems, reiterate that the developed MILP-based hydrothermal scheduling approach outperforms other techniques in terms of cost efficiency.

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A reliable and efficient holomorphic approach to evaluate dynamic available transfer capability

Eidiani

2021

Int Trans Electr Energ Syst

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Summary In the present paper, the static approximate Newton‐Raphson‐Sidel (ANRS) and the developed down‐hill (DDH) algorithm methods were used. To take advantage of both methods, ANRS‐DDH and the revised holomorphic embedding load flow (RHELF) were combined. An approximation of the potential energy boundary surface (APEBS) was also employed in combination with determine transient stability and correct the previous methods. A combination of static method and transient stability led to a combined approach for dynamic available transfer capability (C‐DATC) computation. It is shown that a small correction for these four methods makes the proposed method faster or more accurate. The average root mean square error of the proposed method is half the other methods and the average relative speed of calculations in the proposed methods is 10% higher than the other method. These were confirmed in the networks of Iowa State (145 bus), modified IEEE 118‐bus, and the west of Iran (848 bus) with a large number of wind farms. Finally, the present paper demonstrated that the suggested approach is ideal not only for the operation mode but also for the planning mode and the existence of wind farms.

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Improving Lagrangian Relaxation Unit Commitment with Cuckoo Search Algorithm

Cited by 18 publications

References 14 publications

Improved Lagrangian relaxation generation decision-support in presence of electric vehicles

Improved Lagrangian relaxation generation decision-support in presence of electric vehicles

MILP-Based Short-Term Thermal Unit Commitment and Hydrothermal Scheduling Including Cascaded Reservoirs and Fuel Constraints

A reliable and efficient holomorphic approach to evaluate dynamic available transfer capability

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