An efficient starting process for calculating interval power flow solutions at maximum loading point under load and line data uncertainties

Pereira, L.E.S.; Costa, Vander Menengoy da

doi:10.1016/j.ijepes.2016.01.040

Cited by 7 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The current uncertain harmonic power flow algorithms are mainly divided into probabilistic algorithm [5] , fuzzy algorithm [6] , and interval algorithm [7] . The fuzzy algorithm uses membership density function to describe the uncertainty, mainly uses fuzzy mathematics theory to solve the voltage state quantity; The probabilistic algorithms adopt random values to represent indeterminacy, and uses multiple sampling, semi-invariant method to solve the distribution characteristics of voltage state quantity.…”

Section: Introductionmentioning

confidence: 99%

Interval Harmonic Power Flow Algorithm Based on Relative Distance Measure

Fang

Lan

Lin

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

In the harmonic power flow calculation of the power grid, the indeterminacy of new energy generation, the volatility and intermittency of nonlinear load will lead to the uncertainty of the injected harmonic current. In order to deal with the uncertainty information in the power grid, relative distance measurement (RDM) is used instead of point values to describe the uncertainty of distributed generations(DGs) output and state variables. In this paper, the RDM harmonic source model is built to solve the interval harmonic power flow. Through a typical 33-node distribution network calculation example, it is testified that the RDM Power flow algorithm has sufficient completeness and low conservatism compared with the traditional interval algorithm and Monte Carlo method.

show abstract

Section: Introductionmentioning

confidence: 99%

Interval Harmonic Power Flow Algorithm Based on Relative Distance Measure

Fang

Lan

Lin

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…The authors of [17] propose a continuation PF-based method to compute all Type 1 solutions. The authors of [18] present an efficient starting process for calculating interval PF solutions at maximum loading point while considering both load and line data uncertainties.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [12] presents an efficient starting process for calculating interval power flow solutions at maximum loading point while considering both load and line data uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Locating all real solutions of power flow equations: a convex optimisation‐based method

Liu

Wei

Liu

2018

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

This paper proposes a convex optimization based method that either locates all real roots of a set of power flow equations or declares no real solution exists in the given area. In the proposed method, solving the power flow equations is reformulated as a global optimization problem (GPF for short) that minimizes the sum of slack variables. All the global minima of GPF with a zero objective value have a one-to-one correspondence to the real roots of power flow equations. By solving a relaxed version of GPF over a hypercube, if the optimal value is strictly positive, there is no solution in this area and the hypercube is discarded. Otherwise the hypercube is further divided into smaller ones. This procedure repeats recursively until all the real roots are located in small enough hypercubes through the successive refinement of the feasible region embedded in a bisection paradigm. This method is desired in a number of power system security assessment applications, for instance, the transient stability analysis as well as voltage stability analysis, where the closest unstable equilibrium and all Type-I unstable equilibrium is required, respectively. The effectiveness of the proposed method is verified by analyzing several test systems.

show abstract