Dynamic State Estimation of Medium-voltage DC Integrated Power System with Pulse Load

Xiao, Runlong; Wang, Gang; Hao, Xiaoliang; Huang, Renji

doi:10.35833/mpce.2019.000145

Cited by 10 publications

(8 citation statements)

References 18 publications

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“…2) At t 1 = 1, t 2 = 2, and t 3 = 3, we consider load transients in which the active and reactive power of the three-phase loads at buses 14,17, and 26, respectively, increase by the factor 2.…”

Section: B Simulation Setupmentioning

confidence: 99%

See 1 more Smart Citation

Time-domain Dynamic State Estimation for Unbalanced Three-phase Power Systems

Pfeifer¹,

Mueller

Jongh

et al. 2023

Journal of Modern Power Systems and Clean Energy

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In this paper, we present a time-domain dynamic state estimation for unbalanced three-phase power systems. The dynamic nature of the estimator stems from an explicit consideration of the electromagnetic dynamics of the network, i.e., the dynamics of the electrical lines. This enables our approach to release the assumption of the network being in quasi-steady state. Initially, based on the line dynamics, we derive a graphbased dynamic system model. To handle the large number of interacting variables, we propose a port-Hamiltonian modeling approach. Based on the port-Hamiltonian model, we then follow an observer-based approach to develop a dynamic estimator. The estimator uses synchronized sampled value measurements to calculate asymptotic convergent estimates for the unknown bus voltages and currents. The design and implementation of the estimator are illustrated through the IEEE 33-bus system. Numerical simulations verify the estimator to produce asymptotic exact estimates, which are able to detect harmonic distortion and sub-second transients as arising from converterbased resources.

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Section: B Simulation Setupmentioning

confidence: 99%

“…An unknown-input extended Kalman filter (EKF) is used in [16] for a robust estimation of the generator states. Other component-based DSE approaches based on an EKF have been proposed in [17]- [19]. Reference [20] presents a DSE which estimates the dynamic states of converter-interfaced generation units in microgrids.…”

Section: Introductionmentioning

confidence: 99%

Time-domain Dynamic State Estimation for Unbalanced Three-phase Power Systems

Pfeifer¹,

Mueller

Jongh

et al. 2023

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

show abstract

“…Traditional supervisory control and data acquisition system cannot obtain fast sampled synchronous measurements, while the phasor measurement units (PMU) based on the global positioning system technology, can provide real-time and synchronized measurements [11,12]. In order to estimate the dynamic states of power system, many approaches including the extended Kalman filter (EKF) [13][14][15], unscented Kalman filter (UKF) [16][17][18][19] and cubature Kalman filter (CKF) [10,[20][21][22]. In addition, the particle filter is also applied for DSE [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…A DSE method using the maximum posterior criteria and EKF is proposed to identify and discard the abnormal values in the measured data [15]. However, the EKF is only suitable for slightly nonlinear systems since it is easy to lose accuracy for highly nonlinear systems [14]. Therefore, a series of UKF based algorithms are proposed to eliminate the errors caused by linearization of nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic state estimation of power systems considering maximum correlation entropy and quadratic function

Chen

Liu

Sun

et al. 2023

Meas. Sci. Technol.

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Uncertainties such as abnormal system inputs, strong model nonlinearities, outliers and impulsive noise unavoidably exist in the power system dynamic state estimation (DSE). The existing Kalman filter-based DSE methods cannot deal with the uncertainties well and can be improved further. In this paper, a robust DSE method based on the maximum correlation entropy (MCE), quadratic function (QF) and the cubature Kalman filter (CKF) is proposed to reduce the effects caused by the uncertainties. The MCE-QF based estimator is robust and can alleviate the influence of uncertainties. A new state estimation error covariance is derived by using the robust statistical tool, influence function. The robustness and estimation precision of the proposed DSE method is demonstrated by conducting simulations on a synchronous generator under different cases.

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“…3 In addition, due to the limitation of ship model caused by the diesel generator system, the traditional optimization strategy can not solve the energy management problem. 4 Therefore, it is crucial to develop an appropriate optimal scheduling strategy for the HESPS under the cost and emission constraints.…”

Section: Introductionmentioning

confidence: 99%

An energy dispatch optimization for hybrid power ship system based on improved genetic algorithm

Wang,

Zhu,

Luo

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part A:

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Due to the energy crisis and environmental deterioration, the emerging hybrid energy ship power system gradually replaced the traditional ship power system to keep environmental friendliness by employing the clean energy. However, the increase of energy storage and photovoltaic generation system brings enormous challenge to the optimization scheduling of hybrid energy ship power system. For this reason, an improved genetic algorithm-based optimal scheduling strategy for the hybrid energy ship power system is developed in this paper. Firstly, a novel hybrid energy ship power system model including the diesel generator, energy storage system, propulsion system, dynamic load and photovoltaic power generation device is constructed under the constraint of energy efficiency and greenhouse gases emissions. Considering the various navigation situations that the ship may encounter, such as photovoltaic power generation limit in extreme weather and diesel generator power change in load shedding, the corresponding scheduling optimization problems for the hybrid energy ship power system are established. Under the cost and gas emission constraints, an improved genetic algorithm-based scheduling optimization algorithm is proposed. By introducing the nonlinear parameter change model in crossover and mutation operator, the performance of improved genetic algorithm can be enhanced, such as convergence speed and global optimization ability. Compared with current works, the proposed scheduling optimization strategy can achieve the lowest cost while reducing environmental impacts. Finally, simulation results under the given navigation cases demonstrate the superiority of the proposed improved genetic algorithm-based scheduling optimization strategy.

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Dynamic State Estimation of Medium-voltage DC Integrated Power System with Pulse Load

Cited by 10 publications

References 18 publications

Time-domain Dynamic State Estimation for Unbalanced Three-phase Power Systems

Time-domain Dynamic State Estimation for Unbalanced Three-phase Power Systems

Dynamic state estimation of power systems considering maximum correlation entropy and quadratic function

An energy dispatch optimization for hybrid power ship system based on improved genetic algorithm

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