نتایج جستجو برای: probabilistic harmonic power flow
تعداد نتایج: 1045274 فیلتر نتایج به سال:
The enhancement in the penetration of intermittent generation necessitates the need to include uncertain behaviour in the conventional power flow programs. In this paper, four different wind generation models have been incorporated in probabilistic load flow for calculating the probability distribution of the reactive power consumed by the wind generators for three different scenarios; i) uncor...
Exploitation of renewable energy sources in power networks, especially wind energy, is considered an alternative for power generation as a non-polluting source with a low environmental impact and low operational cost. Hence, renewable energy has motivated the increment of penetration of Distributed Generation (DG) in distribution networks and the development of methodologies to evaluate their e...
A multiphase harmonic load flow algorithm is developed based on backward/forward sweep to examine the effects of various factors on the neutral to earth voltage (NEV), including unsymmetrical system configuration, load unbalance and harmonic injection. The proposed algorithm composes fundamental frequency and harmonic frequencies power flows. The algorithm and the associated models are tested o...
In this paper a procedure is established for solving the Probabilistic Load Flow in an electrical power network, considering correlation between power generated by power plants, loads demanded on each bus and power injected by wind farms. The method proposed is based on the generation of correlated series of power values, which can be used in a MonteCarlo simulation, to obtain the probability d...
The non-dispatchable nature of wind generation implies that system operation depends on wind power prediction programs that forecast wind farms production with high levels of uncertainty. This means that probabilistic power analysis tools become more and more necessary in systems with high wind penetration. Probabilistic load flow becomes especially difficult when wind generation is considered....
A probabilistic power flow (PPF) study is an essential tool for the analysis and planning of a power system when specific variables are considered as random variables with particular probability distributions. The most widely used method for solving the PPF problem is Monte Carlo simulation (MCS). Although MCS is accurate for obtaining the uncertainty of the state variables, it is also computat...
Power decoupling of pulsating grid side power from constant source side power is one of the paramount issues in single phase-phase grid-connected renewable systems. The principal aim of such systems is the decrease of the capacitance of the decoupled capacitor. However, this causes some problems such as an increase in the total harmonic distortion (THD) of injected current to the grid and bus v...
This paper proposes a probabilistic power flow (PPF) method considering continuous and discrete variables (continuous and discrete power flow, CDPF) for power systems. The proposed method—based on the cumulant method (CM) and multiple deterministic power flow (MDPF) calculations—can deal with continuous variables such as wind power generation (WPG) and loads, and discrete variables such as fuel...
This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active man...
This paper presents a probabilistic power flow model subject to connection temperature constraints. Renewable power generation is included and modelled stochastically in order to reflect its intermittent nature. In contrast to conventional models that enforce connection current constraints, short-term current overloading is allowed. Temperature constraints are weaker than current constraints, a...
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