Voltage Quality Assessment in a Distribution System With Distributed Generation—A Probabilistic Load Flow Approach

Sexauer, Jason M.; Mohagheghi, Salman

doi:10.1109/tpwrd.2013.2259599

Cited by 59 publications

(19 citation statements)

References 16 publications

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“…In deterministic load flow (DLF) study, certain load and generation are used to investigate the state variable of the network. To handle these uncertainties probabilistic load flow (PLF) study are taken into consideration [3]. In PLF, future condition of the power system is investigated by using different input parameters.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Load Flow Analysis of Power System Network Considering Uncertainty with Generation and Correlated Loads

Shahzad

et al. 2019

International Journal of Simulation: Systems, Science &Amp; Technology

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Probabilistic load flow has gain attractive attention in electric power system planning, operation, and control. Probabilistic load flow is an efficient tool to access the performance of the power system considering the uncertainties of the load demand and generation. However, future operating condition and operating criteria could not be predicted without considering uncertainty. Due to integration of renewable energy sources into power system network brought uncertainty and dependence factor. Most of the uncertainties in power system are load increment, generation scheduling, and network topology in which engineers are dealing with them. In this paper, Box-Muller sampling algorithm is proposed to solve the probabilistic load flow problems considering uncertainty with generation and correlated loads. The main advantage of the proposed approach is that accurate solution can be obtain with less computation time and can address the dependence between variables. Also, it is almost unconstrained for the probability distributions of the input random variables. The proposed method is compared with correlated simple random sampling Monte Carlo simulation. For the demonstration purpose, the proposed method is investigated using IEEE 14-bus and IEEE 118-bus test systems. The simulation results indicate that Box-Muller sampling method is a promising approach in probabilistic load flow evaluation.

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Section: Introductionmentioning

confidence: 99%

Probabilistic Load Flow Analysis of Power System Network Considering Uncertainty with Generation and Correlated Loads

Shahzad

et al. 2019

International Journal of Simulation: Systems, Science &Amp; Technology

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“…With the technologies related to new energy generation being maturing day by day and the construction of the energy internet being pushed forward constantly [1][2][3], penetrations of distributed generations (DGs) in the distribution network are increasing gradually [4,5]. Before the electric power grid and other energy networks connecting with each other and forming an energy internet, building a green smart grid with the core of energy routers to accept large-scale renewable energy sources widely is one way to construct the energy internet [6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Transient Voltage Stability in a Low Voltage Distribution Network Using SST for the Integration of Distributed Generations

Zhou

Shan

et al. 2018

Journal of Electrical and Computer Engineering

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Models of a low voltage distribution network using a typical tertiary-structure solid state transformer (SST) for the integration of distributed generations (DGs) and a conventional low voltage distribution network integrated with DGs were established to study the transient voltage stability issue, using the power system simulation software PSCAD. Effects on the transient voltage stability of the load bus and DC bus in the SST system are analyzed when grid-side cable line faults (such as short circuit and line disconnection) occur or the total output of DGs drops greatly. The results show that, comparing with the conventional system, the SST has apparent advantages on enhancing the transient voltage stability of load bus while facing different disturbances, even though SST has to regulate the voltage passively. Short circuit faults at different location of the grid-side line have different effects on the transient voltage stability, while the effect of disconnection fault is not related to fault location. Moreover, the DC bus voltage is easy to keep climbing continually when short circuit fault of the line occurs that is close to the SST input stage or disconnection fault occurs at any location of the line. If a battery energy storage station is installed, the transient voltage stability of DC bus and load bus will be improved effectively because of the regulation function of battery storage.

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“…Probabilistic load flow using Monte Carlo Simulation was used in [6] to assess the voltage quality of a distribution system with distributed generation. Stochastic approaches were used in [7] to investigate network constraints in a power system with distributed generation.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic analysis of radial distribution network performance with varying wind speed levels

Narayan

Kumar

2014

2014 6th IEEE Power India International Conference (PIICON)

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This paper presents an analysis of radial distribution network considering the probabilistic modeling of loads, substation voltage and integrated wind energy source. The impacts on the distribution network for varying wind speed levels are studied. The wind power source is placed on the most optimum buses obtained from stability index calculations. A total of five scenarios for different wind speed levels are studied in this paper. The impact of wind power output on power loss reduction and voltage profile improvement are observed. The results are analyzed for various wind speed levels on an IEEE 33 bus radial distribution system.

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Voltage Quality Assessment in a Distribution System With Distributed Generation—A Probabilistic Load Flow Approach

Cited by 59 publications

References 16 publications

Probabilistic Load Flow Analysis of Power System Network Considering Uncertainty with Generation and Correlated Loads

Probabilistic Load Flow Analysis of Power System Network Considering Uncertainty with Generation and Correlated Loads

Analysis of Transient Voltage Stability in a Low Voltage Distribution Network Using SST for the Integration of Distributed Generations

Probabilistic analysis of radial distribution network performance with varying wind speed levels

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