Directional Derivative-Based Transient Stability-Constrained Optimal Power Flow

Pizano-Martínez, Alejandro; Fuerte‐Esquivel, Claudio R.; Zamora-Cárdenas, Enrique A.; García, José Merced Lozano

doi:10.1109/tpwrs.2016.2633979

Cited by 22 publications

(13 citation statements)

References 22 publications

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“…The comparisons validate the good performance of the proposed framework in terms of practicability, searching for economical solutions, and computational efficiency. Given that most TSC-OPF works [4]- [5], [7], [16], [18] rely on TDSs and thus may have difficulty handling massive fault scenarios, the proposed method has more advantages for dealing with networks with high wind power penetration.…”

Section: Validating the Results Using Tdssmentioning

confidence: 99%

“…One of the most popular solutions is to discretize the DAEs into algebraic constraints by small time steps and then apply nonlinear programming techniques [2]- [3]. Another prevalent method is trajectory sensitivity-based techniques, which iteratively adjust the dispatch based on the sensitivity of the stability index of interest to system control variables with the aid of time-domain simulations (TDSs) [4]- [5]. The evolutionary algorithm-based technique is also a feasible approach that seeks the optimal solution of the TSC-OPF problem via mechanisms inspired by biological evolution [6]- [7].…”

Section: Introductionmentioning

confidence: 99%

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A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints

Chen

Mazhari

Chung

et al. 2021

IEEE Open J. Power Energy

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This paper proposes a probabilistic transient stability-constrained preventive dispatching method for power systems under a high inclusion of wind power. First, a set of instability mode (IM)-categorized probabilistic transient stability constraints (PTSCs) are constructed, which facilitate the development of a dispatching plan against various fault scenarios. Next, to avoid massive transient stability simulations in each dispatching operation, a machine learning-based model is trained to predict the critical clearing time (CCT) and IM for all preconceived fault scenarios. Based on the predictions, the system operation plan is assessed with respect to the PTSCs. Then, the sensitivity of the probabilistic level of the CCT is calculated to the active power generated from the critical generators for each IM category. Accordingly, the implicit PTSCs are converted into explicit dispatching constraints, and the dispatch is rescheduled to ensure the probabilistic stability requirements of the system are met at an economical operating cost. The proposed approach is validated on two modified IEEE test systems, reporting high computational efficiency and high-quality solutions. Index Terms-Critical clearing time (CCT), machine learning, optimal power flow, power dispatch, probabilistic transient stability, uncertainties, wind power.

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Section: Validating the Results Using Tdssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints

Chen

Mazhari

Chung

et al. 2021

IEEE Open J. Power Energy

View full text Add to dashboard Cite

show abstract

“…On the one hand, it improves numerical differentiation with interior point methods (IPM), such as reduced space IPM [6], two-level parallel decomposition [7], and primal-dual Newton IPM [8]. On the other hand, transient stability constraints are transformed into other forms, such as transient sensitivity analysis [9], independent transient stability assessment [10], OMIB reference trajectory [11], and energy sensitivity method [12]. However, for TSCOPF, transient voltage stability constraint is rarely considered, while static voltage stability constraint is studied chiefly [13,14].…”

Section: Introductionmentioning

confidence: 99%

Data‐model driven rescheduling considering both rotor angle stability and transient voltage stability constraints

Wang

Tang

2022

IET Renewable Power Gen

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Facing the problem of workforce and time costs caused by the rescheduling of large‐scale power grids with renewable energy penetration, and the lack of parallel control research on rotor angle instability and transient voltage instability, a rescheduling method based on trajectory sensitivity and deep reinforcement learning (DRL) is proposed to meet the requirements of rotor angle stability and transient voltage stability at the same time. By introducing the process of rescheduling to meet the transient stability constraint, the Markov decision‐making process of rescheduling is first constructed. Then, a simple dominant instability type identification method is proposed according to the occurrence time, location, voltage pattern, and position of the oscillation centre. Moreover, a rescheduling strategy is formulated based on the dominant instability mode identification, trajectory sensitivity calculation, actionable device selection, action amount computation, and action of the device. Next, according to the improved distributed distributive deep deterministic policy gradients (D4PG), a DRL model is established to map the action to actionable generator pairs and capacitors/reactors, so as to realize parallel rescheduling of rotor angle instability and transient voltage instability. Finally, the improved New England 39‐bus system and an actual power grid are used to verify the effectiveness and advantages of the method.

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“…In a competitive economic environment that has placed the need for reconciliation of economic and transitional stability conditions, the cost of losing synchronism by transient instability is exceptionally high and of significant importance. For this reason, the traditional optimal power flow (OPF) approach has been extended to take into account the transient stability constraints of the system, giving a new transient stability constrained optimal power flow (TSC-OPF) approach [1]. The TSC-OPF procedures are classified in either global or sequential approaches [2,3].…”

mentioning

confidence: 99%

“…The global TSC-OPF approaches are reported in [4][5][6][7]. The sequential TSC-OPF approaches perform a standard OPF analysis to assess an optimal operating point [1]. A transient stability analysis is then carried out independently from the optimization process to check if the optimum point is transiently stable, so that the time domain simulation-related set of differential algebraic equations is not embedded in the traditional OPF problem [2,[8][9][10].…”

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confidence: 99%

Multi-objective optimal power flow considering the multi-terminal direct current

Bilel¹,

Boukra²,

Mezhoud³

2021

Electrical Engineering & Electromechanics

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Introduction. In recent years, transmission systems comprise more direct current structures; their effects on alternating current power system may become significant and important. Also, multi-terminal direct current is favorable to the integration of large wind and solar power plants with a very beneficial ecological effect. The novelty of the proposed work consists in the effects of the aforementioned modern devices on transient stability, thus turn out to be an interesting research issue. In our view, they constitute a new challenge and an additional complexity for studying the dynamic behavior of modern electrical systems. Purpose. We sought a resolution to the problem of the transient stability constrained optimal power flow in the alternating current / direct current meshed networks. Convergence to security optimal power flow has been globally achieved. Methods. The solution of the problem was carried out in MATLAB environment, by an iterative combinatorial approach between optimized power flow computation and dynamic simulation. Results. A new transient stability constrained optimal power flow approach considering multi-terminal direct current systems can improve the transient stability after a contingency occurrence and operate the system economically within the system physical bounds. Practical value. The effectiveness and robustness of the proposed method is tested on the modified IEEE 14-bus test system with multi-objective optimization problem that reflect active power generation cost minimization and stability of the networks. It should be mentioned that active power losses are small in meshed networks relative to the standard network. The meshed networks led to a gain up to 46,214 % from the base case.

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Directional Derivative-Based Transient Stability-Constrained Optimal Power Flow

Cited by 22 publications

References 22 publications

A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints

A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints

Data‐model driven rescheduling considering both rotor angle stability and transient voltage stability constraints

Multi-objective optimal power flow considering the multi-terminal direct current

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