An application of CHA to concurrent short-term transmission expansion &amp;amp; reactive power planning

Mahmoudabadi, Amin; Rashidinejad, Masoud; Mohammadian, Mohsen; Maymand, M. Zeinaddini; Rahmani, Mostafa; Khorasani, H.

doi:10.1109/ptc.2011.6019283

Cited by 6 publications

(10 citation statements)

References 24 publications

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“…Reactive power optimization model (call the problem A) composes by (10), (6), (14), (15) and (17). It can be broken down into two sub-problems: one is (10), (14), (15) named S, and the other is composed of linear equations (6) and (17). Problems A can be described as (1), where u is expressed as a real part and an imaginary part of the branch current vector, x is expressed in amplitude and phase angle of nodal voltage vector.…”

Section: Reactive Power Optimizationmentioning

confidence: 99%

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A New Method to Solve Reactive Power Optimization Problems of Power System by Introducing the Branch Current

Tao¹,

Wang

Xie

et al. 2013

ElAEE

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The mathematical model used in this paper is not only the traditional node voltage equation but also the introduction of the branch current equation when research the power system reactive power optimization, and so establishes a mathematical model of hybrid power network node voltages and branch currents. The state variables in this model are the node voltages and branch currents, the network flow is explicitly expressed, and they play a key role for the simplification of the solving model. Solving the model will be broken down into two sub-problems, one is a network loss minimization objective augmented Lagrange function, forming the Kuhn-Tucker conditions, and the other is a linear equation. IEEE 30-bus system example shows that the complexity and high dimension of the model solution have been significantly improved, the solving process becomes easier, and the solution is close to the global optimal solution. Compared with traditional optimal power flow algorithm, this algorithm can improve the computational efficiency of reactive power optimization.

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Section: Reactive Power Optimizationmentioning

confidence: 99%

“…( , ) 0 h x u  is the inequality constraints, in particular are (14) and (15). ( , ) 0 g x u  is the equality constraints, in particular (6) and (17). So the Kuhn-Tucker condition of problems A is:…”

Section: Reactive Power Optimizationmentioning

confidence: 99%

A New Method to Solve Reactive Power Optimization Problems of Power System by Introducing the Branch Current

Tao¹,

Wang

Xie

et al. 2013

ElAEE

View full text Add to dashboard Cite

show abstract

“…As it can be seen, in [16] the authors use a constructive heuristics algorithm to solve AC-TEP and introduce two indexes for finding weak buses for the potential location of reactive power sources. In fact, after transmission lines are constructed then reactive power sources will be allocated to weak buses.…”

Section: Introductionmentioning

confidence: 99%

An application of hybrid heuristic method to solve concurrent transmission network expansion and reactive power planning

Mahmoudabadi

Rashidinejad

2013

International Journal of Electrical Power & Energy Systems

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“…Recently an accurate AC network modeling has been proposed in [4]. The use of the complete AC model in the first phase is incipient but there are few technical literatures on the subject [4][5][6]. Owing to the large-scale nature of a transmission system and its complexities, TEP has always been a complex non-convex optimization problem.…”

Section: Introductionmentioning

confidence: 99%

“…4) AC optimal power flow with generation costs and reactive power investment is solved via Interior Point Method [6].…”

mentioning

confidence: 99%

A New Model for Transmission Network Expansion and Reactive Power Planning in a Deregulated Environment

Mahmoudabadi¹,

Rashidinejad²,

Zeinaddini-Maymand³

2012

ENG

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Transmission network expansion planning (TNEP) is a challenging issue especially in new restructured electricity markets environment. TNEP can be incorporated with reactive power planning in which the operating conditions will be satisfied. In this paper a combinatorial mathematical model has been presented to solve transmission expansion and reactive power planning problem (TEPRPP) simultaneously. The proposed model is a non-convex problem having a mixed integer nonlinear nature where the number of candidate solutions to be evaluated increases exponentially according to the system size. The objective function of TEPRPP comprises the new circuits' investment and production costs as well as load curtailment penalty payments. A real genetic algorithm (RGA) aimed to obtaining a significant quality solution to handle such a complicated problem has been employed. An interior point method (IPM) is applied to solve the proposed concurrent optimization problem in the solution steps of TEPRPP model. This paper proposes a new methodology for the best location as well as the capacity of VAr sources; it is tested on two well-known systems; the Garver and IEEE 24-bus systems. The obtained results show the capability and the viability of the proposed TEPRPP model incorporating operating conditions.

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An application of CHA to concurrent short-term transmission expansion & reactive power planning

Cited by 6 publications

References 24 publications

A New Method to Solve Reactive Power Optimization Problems of Power System by Introducing the Branch Current

A New Method to Solve Reactive Power Optimization Problems of Power System by Introducing the Branch Current

An application of hybrid heuristic method to solve concurrent transmission network expansion and reactive power planning

A New Model for Transmission Network Expansion and Reactive Power Planning in a Deregulated Environment

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