Accurate, simultaneous and Real-Time screening of N-1, N-k, and N-1-1 contingencies

Heidari, Hassan; Hagh, Mehrdad Tarafdar; Salehpoor, Pedram

doi:10.1016/j.ijepes.2021.107592

Cited by 11 publications

(3 citation statements)

References 41 publications

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“…LODF and LODF provide information about line loadings under normal and contingency scenarios. Though fast computation is achieved in this way, the results are less accurate, because the impact of reactive power flow on the line loading is omitted, and bus voltage violations cannot be checked [ 84 ]. To reliably describe the static security status of the power grid at any operating scenario, SSA must include real and reactive flows as well as bus voltages [ 72 ].…”

Section: Methods Of Power System Security Assessmentmentioning

confidence: 99%

Techniques of power system static security assessment and improvement: A literature survey

Hailu¹,

Nyakoe²,

Muriithi³

2023

Heliyon

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Section: Methods Of Power System Security Assessmentmentioning

confidence: 99%

Techniques of power system static security assessment and improvement: A literature survey

Hailu¹,

Nyakoe²,

Muriithi³

2023

Heliyon

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“…However, this problem is a nonlinear, non-convex, mixed variable and large scale, being their solution a changeling task and time consuming. Therefore, different approximations, methods and assumptions such as k = 1, DC power flows, contingency screening [5] and high-performance computing [6], among others, are used to solve SCOPF in a reasonable time. More advanced methods suggest quantum computation to deal with the computational complexity of the N − k contingency analysis problem [7].…”

Section: Introductionmentioning

confidence: 99%

N − k Static Security Assessment for Power Transmission System Planning Using Machine Learning

Alvarez,

Gaha,

Prévost

et al. 2024

Energies

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This paper presents a methodology for static security assessment of transmission network planning using machine learning (ML). The objective is to accelerate the probabilistic risk assessment of the Hydro-Quebec (HQ) TransÉnergie transmission grid. The model takes the expected power supply and the status of the elements in a N−k contingency scenario as inputs. The output is the reliability metric Expecting Load Shedding Cost (ELSC). To train and test the regression model, stochastic data are performed, resulting in a set of N−k and k=1,2,3 contingency scenarios used as inputs. Subsequently, the output is computed for each scenario by performing load shedding using an optimal power flow algorithm, with the objective function of minimizing ELSC. Experimental results on the well-known IEEE-39 bus test system and PEGASE-1354 system demonstrate the potential of the proposed methodology in generalizing ELSC during an N−k contingency. For up to k=3 the coefficient of determination R2 obtained was close to 98% for both case studies, achieving a speed-up of over four orders of magnitude with the use of a Multilayer Perceptron (MLP). This approach and its results have not been addressed in the literature, making this methodology a contribution to the state of the art.

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“…However, in real-time security assessment, the time window for system operators to analyze the problem and take corrective actions is quite limited. Therefore, the main challenge is to find an efficient method to significantly reduce the resolution time without compromising solution accuracy [6].…”

Section: Introductionmentioning

confidence: 99%

Unique Symbolic Factorization for Fast Contingency Analysis Using Full Newton–Raphson Method

2023

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Contingency analysis plays an important role in assessing the static security of a network. Its purpose is to check whether a system can operate safely when some elements are out of service. In a real-time application, the computational time required to perform the calculation is paramount for operators to take immediate actions to prevent cascading outages. Therefore, the numerical performance of the contingency analysis is the main focus of this current research. In power flow calculation, when solving the network equations with a sparse matrix solver, most of the time is spent factorizing the Jacobian matrix. In terms of computation time, the symbolic factorization is the costliest operation in the LU (Lower-upper) factorization process. This paper proposes a novel method to perform the calculation with only one symbolic factorization using a full Newton–Raphson-based generic formulation and modular approach (GFMA). The symbolic factorization retained can be used during the iterations of any power flow contingency scenario. A computer study demonstrates that reusing the same symbolic factorization greatly reduces computation time and improves numerical performance. Power system security assessment under N-1 and N-2 contingency conditions is performed for the IEEE standard 54-bus and 108-bus to evaluate the numerical performance of the proposed method. A comparison with the conventional power flow method shows that the time required for the analysis is shortened considerably, with a minimum gain of 228%. The comparative analysis demonstrates that the proposed solution has better numerical performance for large-scale networks.

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Accurate, simultaneous and Real-Time screening of N-1, N-k, and N-1-1 contingencies

Cited by 11 publications

References 41 publications

Techniques of power system static security assessment and improvement: A literature survey

Techniques of power system static security assessment and improvement: A literature survey

N − k Static Security Assessment for Power Transmission System Planning Using Machine Learning

Unique Symbolic Factorization for Fast Contingency Analysis Using Full Newton–Raphson Method

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