Voltage stability modelling and real-time monitoring using expert system for operation assistance

Belhadj, C.A.; Mohamedi, R.; Lefebvre, S.; Lagacé, P.J.; Do, X.D.

doi:10.1109/59.496192

Cited by 20 publications

(15 citation statements)

References 19 publications

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“…The aim of RPD problem is to minimize the network real power loss and to reduce the cost of control variable adjustments by regulating generator bus voltages, switching and changing transformer tap-settings [20]. With the increased loading of existing power transmission systems, the problem of voltage stability and voltage collapse, has become a major concern in power system planning and operation [22,14,3].…”

Section: Introductionmentioning

confidence: 99%

Application of Modified NSGA-II Algorithm to Reactive Power Optimization

Ramesh

Kannan

Baskar³

2011

Communications in Computer and Information Science

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Abstract. The optimal Reactive Power Dispatch (RPD) problem is a nonlinear constrained optimization problem. This paper presents true multi-objective solution set for multi-objective RPD problem. The objective functions are real power loss minimization and control variable adjustment costs. In this paper, a Modified Non-Dominated Sorting Genetic Algorithm version II (MNSGA-II) is proposed for solving RPD problem. For maintaining good diversity in the performance of NSGA-II, the concept of Dynamic Crowding Distance (DCD) is implemented in NSGA-II algorithm and given name as MNSGA-II. The standard IEEE 30-bus and IEEE 118 bus test systems are used. The results obtained using MNSGA-II are compared with NSGA-II and validated with reference Pareto front generated by conventional weighted sum method using Covariance Matrix Adapted Evolution Strategy (CMA-ES). The performance of NSGA-II and MNSGA-II are compared with respect to best, mean, worst and standard deviation of multi-objective performance measures.The results show the effectiveness of MNSGA-II and confirm its potential to solve the multi-objective RPD problem.

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Section: Introductionmentioning

confidence: 99%

Application of Modified NSGA-II Algorithm to Reactive Power Optimization

Ramesh

Kannan

Baskar³

2011

Communications in Computer and Information Science

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“…Em um SEP a aplicação de análise de sensibilidade vem sendo utilizada com grande destaque sendo, amplamente, aplicada no planejamento de potência reativa (Iba et al, 1998; e Kishore et al, 1971). Os autores Belhadj et al (1996) Neste trabalho nós utilizaremos a análise de sensibilidade para determinar o novo ponto de operação para o problema de FPO depois de ocorrida alguma perturbação no sistema. A função objetivo utilizada é minimizar as perdas de potência ativa na transmissão, está função é não linear, não convexa e não separável.…”

Section: Introductionunclassified

Determinação da solução ótima do problema de fluxo de potência ótimo via análise de sensibilidade

et al. 2005

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ResumoNeste trabalho propomos uma abordagem para a resolução do problema de Fluxo de Potência Ótimo (FPO) perturbado. A metodologia consiste na utilização de análise de sensibilidade para estimar novas soluções depois de ocorridas algumas perturbações no problema a partir de uma solução ótima obtida via um programa de FPO. Estas perturbações podem ser variações de carga em uma ou mais barras do sistema. A técnica de análise de sensibilidade é baseada nas informações de segunda ordem e nas condições de Karush-Kuhn-Tucker (KKT). A obtenção da solução após ocorrerem perturbações no sistema é direta e não necessita de parâmetros iniciais e de correção como os de penalidade e de barreira, utilizados nos programas de FPO convencionais. Os resultados numéricos apresentados evidenciam o potencial desta metodologia para resolução do problema de FPO para pequenas perturbações.Palavras-chave: análise de sensibilidade; fluxo de potência ótimo; perturbação; condições de Karush-Kuhn-Tucker. AbstractWe propose in this work an approach for solving the perturbated Optimal Power Flow (OPF) problem. The methodology consists in the use of sensitivity analysis to estimate new solutions after occurring some perturbations in the problem starting from optimal solution obtained via an OPF program. These perturbations consist in loading variations in some busses of the system. The sensitivity analysis technique is based on the information of second order and in the Karush-Kuhn-Tucker conditions. The obtaining of the solutions after the occurrence of perturbations in the system is direct and it doesn't need initial parameters and correction parameters as other methods like penalty and barrier used in the conventional OPF programs need. The numerical results demonstrate the potential of this methodology for the solution of the perturbated OPF problem.

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“…For voltage stability bus evaluation in connection with transmission path, an indicator L-index is used [9]. The indicator value varies in the range between 0 (the no load case) and 1 which corresponds to Magnitude and phase along with the power network information provided by the load flow program.…”

Section: Fast Voltage Stability Indicatormentioning

confidence: 99%

“…L k : L-index voltage stability indicator for bus k [8,9] Stability requires that L k < 1 and must not be violated on a continuous basis. Hence a global system indicator L describing the stability of the complete system is L=L max {L k }, where in {L k } all L bus indexes are listed.…”

Section: Fast Voltage Stability Indicatormentioning

confidence: 99%

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An optimized fast voltage stability indicator

Belhadj

Abido²

PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376)

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This paper proposes a simulated annealing optimization technique for optimal voltage stability profile through out the whole power network. The technique is applied to control the power elements of major influence on the voltage stability profile. Elements such as generator reactive generation, adjustable shunt compensation devices, transformer tap settings are optimally adjusted at each operating point to reach the objective of minimizing the voltage stability index at each individual bus as well minimizing the global voltage stability indicator. Because of the optimal setting of the control elements, the maximum possible MVA voltage stable loading has been achieved and a the best voltage profile was obtained. Results of tests conducted on the 6 bus Wale and Hale system are presented and discussed.

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Voltage stability modelling and real-time monitoring using expert system for operation assistance

Cited by 20 publications

References 19 publications

Application of Modified NSGA-II Algorithm to Reactive Power Optimization

Application of Modified NSGA-II Algorithm to Reactive Power Optimization

Determinação da solução ótima do problema de fluxo de potência ótimo via análise de sensibilidade

An optimized fast voltage stability indicator

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