A new approach of point estimate method for probabilistic load flow

Mohammadi, Mohammad; Shayegani, A.; Adaminejad, H.

doi:10.1016/j.ijepes.2013.02.019

Cited by 72 publications

(39 citation statements)

References 15 publications

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“…In that study, to improve calculation performance, a combined kernel density estimation with Nataf transformation is utilized. In addition, in [20], an analysis of PLF using the novel point estimate approach is demonstrated.…”

Section: Introductionmentioning

confidence: 99%

Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering

et al. 2018

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Abstract:The ongoing study aims to establish a direct probabilistic load flow (PLF) for the analysis of wind integrated radial distribution systems. Because of the stochastic output power of wind farms, it is very important to find a method which can reduce the calculation burden significantly, without having compromising the accuracy of results. In the proposed approach, a K-means based data clustering algorithm is employed, in which all data points are bunched into desired clusters. In this regard, probable agents are selected to run the PLF algorithm. The clustered data are used to employ the Monte Carlo simulation (MCS) method. In this paper, the analysis is performed in terms of simulation run-time. Also, this research follows a two-fold aim. In the first stage, the superiority of data clustering-based MCS over the unsorted data MCS is demonstrated properly. Moreover, the impact of data clustering-based MCS and unsorted data-based MCS is investigated using an indirect probabilistic forward/backward sweep (PFBS) method. Thus, in the second stage, the simulation run-time comparison is carried out rigorously between the proposed direct PLF and the indirect PFBS method to examine the computational burden effects. Simulation results are exhibited on the IEEE 33-bus and 69-bus radial distribution systems.Keywords: direct probabilistic load flow; wind-integrated radial distribution systems; K-means based data clustering; Monte Carlo simulation; indirect probabilistic forward/backward sweep load flow

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Section: Introductionmentioning

confidence: 99%

Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering

et al. 2018

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“…Its accuracy mostly depends on the number of samples. Conversely, point estimate methods [4][5][6] use an approximation technique, in which input variables are decomposed into a series of pairs of values and weights, and then the moments of the output variables are calculated as a function of the inputs. In a different way, the analytical approach applies an arithmetic algorithm (e.g., using a convolution technique [7] or cumulant method [8][9][10][11]) with probability density functions (PDFs) and/or cumulative distribution functions (CDFs) of input random variables so that PDFs and CDFs of output random variables can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Advanced probabilistic power flow methodology for power systems with renewable resources

Le¹,

Nguyen²,

Ngo³

et al. 2017

Turk J Elec Eng & Comp Sci

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Abstract:Renewable resources have added additional uncertainty to power grids. Deterministic power flow does not provide sufficient information for power system calculation and analysis, since all sources of uncertainty are not taken into account. To handle uncertainties PPF has been introduced and used as an efficient tool. In this paper, we present a cumulant-based PPF approach that can account for various sources of uncertainty in power systems with renewable resources such as wind and photovoltaic energy. We also propose the use of a new methodology to estimate probability distribution for wind power output based on measured data. The proposed approach is carried out on a modified IEEE-14 bus test system. Simulation results of the proposed method are then compared with the result obtained by Monte Carlo simulation.

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“…Due to the randomness of the wind, the wind farm when connected to the network has a great impact on the power system. And the power flow calculation is the main way to carry out quantitative analysis of the impact [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Research on the Optimal Reactive Power Control of the Wind Farm by Flow Calculation

Tang¹,

Qin²,

Xian³

et al. 2017

Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

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Abstract. Wind energy is clean and renewable, with the progress of the wind power technology, the accumulation of operation and maintenance experience, reduced generation cost, large capacity of wind farms connected to grid have been built. It is urgent to study the reactive power optimization control of the wind farm, so as to realize the wind farm and power system stability, reliable, good and economic operation. This paper established a wind farm containing 33 sets of 1.5MW double-fed wind turbines in power system analysis software package (PSASP). Through the 18 kinds of different operating types of the power flow calculation by PSASP simulation, the optimal reactive power control scheme is presented by comprehensive analysis on power flow calculation results to finish the wind farm reactive power optimization control aim. Accordingly, this paper makes a detailed analysis of the reactive power optimization control scheme, such as the choice of the compensation device, the position of the compensation and the compensation capacity, by comparing the power flow calculation results before and after the installation of reactive power compensation equipment in the wind farm, the effectiveness of the reactive power optimized control scheme is verified.

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A new approach of point estimate method for probabilistic load flow

Cited by 72 publications

References 15 publications

Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering

Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering

Advanced probabilistic power flow methodology for power systems with renewable resources

Research on the Optimal Reactive Power Control of the Wind Farm by Flow Calculation

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