Linear Programming as an Aid in Planning Kilovar Requirements

Maliszewski, Raymond M.; Garver, L. L.; Wood, Allen J.

doi:10.1109/tpas.1968.292155

Cited by 36 publications

(9 citation statements)

References 3 publications

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“…So far, the approaches used to address reactive power reserve mainly range from the linear programming technique to nonlinear programming techniques [7][8][9][10][11][12][13]. However, the challenge for these optimisation techniques is the nonlinear, non-convex nature of the problem formulation [14].…”

Section: Introductionmentioning

confidence: 99%

Reactive Power Reserve Improvement Using Power Systems Inherent Structural Characteristics

Sikiru¹,

Jimoh²,

Hamam³

et al. 2013

EPE

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This paper considers the use of the inherent structural characteristics of power system networks for improving the reactive power reserve margins for both topologically weak and strong networks. The inherent structural characteristics of the network are derived from the Schur complement of the partitioned Y-admittance matrix using circuit theory representations. Results show that topologically strong networks, operating close to the upper voltage limit could be made to increase their loadability margin by locating reactive power compensators close to generator sources, whereas topologically weak (ill conditioned) networks could be made to operate within the feasible operating limits by locating reactive power compensators on buses farther from generator sources.

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Section: Introductionmentioning

confidence: 99%

Reactive Power Reserve Improvement Using Power Systems Inherent Structural Characteristics

Sikiru¹,

Jimoh²,

Hamam³

et al. 2013

EPE

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“…More systematic solution methods that are based on optimization techniques have since been developed. These techniques include different variations of successive linear programming (SLP) [1][2][3] and successive quadratic programming (SQP) [4]; however, integer variables, which are desirable to model discrete sizes and fixed costs, were not handled in [1][2][3][4]. An approach that is capable of handling such variables is Bender's decomposition [5].…”

Section: Introductionmentioning

confidence: 99%

“…Unlike the AI/hybrid methods [9][10][11][12][13][14][15], which are limited to a single network configuration, both the hybrid window schema simulated annealing approach in [16] and the evolutionary particle swarm optimization in [17] consider contingency cases; testing was, however, demonstrated on a single contingency case. References [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] were concerned with correcting the voltage profile and did not include constraints on voltage stability. Reactive power planning formulations that guard against voltage collapse were more recently proposed in [18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Reactive Power Expansion Planning

Jabr

2011

Electric Power Components and Systems

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This article presents a penalty successive linear programming approach for optimum investment of reactive power in networks. Unlike many successive linear programming algorithms, the proposed approach is based on a successive linear programming framework that admits a convergence proof for non-linearly constrained problems of general form. The penalty successive linear programming approach produces a pattern of new reactive sources that satisfy voltage profile requirements in normal and contingent states of operation, and it also accounts for voltage stability constraints that guard against voltage collapse. Numerical test results are presented and compared with an optimal power flow based planning method that processes the system states sequentially.

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Section: Introductionmentioning

confidence: 99%

“…In the past, load-flow studies, trial and error and engineering judgment have been combined in planning the reactive requirement. More recently optimisation techniques have been introduced to select the best alternative in supplying reactive power using linear, nonlinear, continuous or discrete programming [2][3][4].In long-range planning, there is uncertainty inherent in demand projections, equipment and fuel costs, and available rights of way. Recognising the importance of these uncertainties, the authors have found that chance-constrained programming [5-9] is a suitable technique for solving the VAR compensation planning problem.…”

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confidence: 99%

Voltampere reactive compensation using chance-constrained programming

Sharaf¹,

Berg²

1982

IEE Proc. C Gener. Transm. Distrib. UK

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A new technique is developed for solving the voltampere reactive (VAR) compensation problem under uncertain operating conditions. The technique employs chance-constrained programming (CCP), and transforms the problem into a standard linear programming problem. In providing optimal allocation of VAR support, busbars with unacceptably high probability of violating voltage limits are identified and assigned appropriate chance-constraints. Two cases are considered using the new technique. In the first case, capacitive compensation is evaluated for peak load conditions. Inductive compensation is considered in the second case, assuming light load conditions. The method in its general form can be applied in cases where there is uncertainty with respect to equipment cost and/or the coefficients of the voltage-magnitude/reactive power relationships. Normal distributions are not necessary conditions and, if desired, dependent variates can be assumed. The method has been applied to the AEP 30-busbar test system for both heavy and light load conditions, and sample results are presented in the paper. IntroductionKiloVARs, as well as kilowatts, must be provided to the customer as part of a utility's electricity service, and the analysis of the technically most desirable and economically most attractive way to supply this reactive power requirement is one of the system planner's objectives. Whereas the kilowatts can be supplied only from an energy source or power plant, kilovars are automatically produced as well as consumed by the electric network itself. This, of course, results from the inherent shuntcapacitive and series-inductive characteristics of the transmission lines. For this reason planning of reactive power supply is subject to a greater range of system variables [1 ] . For long-range power system transmission planning, VAR compensation is an important aspect. In the past, load-flow studies, trial and error and engineering judgment have been combined in planning the reactive requirement. More recently optimisation techniques have been introduced to select the best alternative in supplying reactive power using linear, nonlinear, continuous or discrete programming [2][3][4].In long-range planning, there is uncertainty inherent in demand projections, equipment and fuel costs, and available rights of way. Recognising the importance of these uncertainties, the authors have found that chance-constrained programming [5-9] is a suitable technique for solving the VAR compensation planning problem. Although the technique in its general form can be applied to a problem with all the previous uncertainties, only voltage magnitude variation resulting from uncertainty in demand projection is considered in this paper.The significance of the new approach is that it accounts for those voltage deviations likely to occur because of uncertain operating conditions, and the probability levels provide a measure of the degree of confidence in meeting the voltage specifications. These advantages are not provided by the VAR allocation techniq...

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Linear Programming as an Aid in Planning Kilovar Requirements

Cited by 36 publications

References 3 publications

Reactive Power Reserve Improvement Using Power Systems Inherent Structural Characteristics

Reactive Power Reserve Improvement Using Power Systems Inherent Structural Characteristics

Optimization of Reactive Power Expansion Planning

Voltampere reactive compensation using chance-constrained programming

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