Affine arithmetic for efficient and reliable resolution of weather-based uncertainties in optimal power flow problems

Abstract

The massive diffusion of renewable power generators in existing power grids introduces large uncertainties in power system operation, hindering their hosting capacity, and introducing several critical issues in network management. To address these challenging issues, weather-based optimal power flow has been recognized as one of the most promising enabling methodology for increasing the system flexibility by exploiting the real power components loadability. Anyway, the deployment of this technique in a real operation scenario could be seriously compromised due to the effects of data uncertainty, which could sensibly affect both the generated/demanded power profiles, and the components thermal modeling. In this context, the research for reliable techniques aimed at representing and managing these uncertainties represents one of the most relevant problem to solve. Armed with such a vision, this paper advocates the role of Affine Arithmetic in reliable solving weather-based OPF problems in the presence of multiple and correlated uncertainties. Experimental results obtained on a real case study, which is based on a congested portion of a transmission system characterized by a massive pervasion of wind generators, will be presented and discussed in order to assess the benefits deriving by the application of the proposed method.

Handling uncertainties with affine arithmetic and probabilistic OPF for increased utilisation of overhead transmission lines

“…The STR and DTR limits are implemented on all lines, which are assumed to be ACSR 'Fox' conductor type, [35]. Detailed network information can be obtained from [34].…”

“…For a given wind speed profiles, power outputs of wind turbines (WTs) in WF can be estimated through many approaches [34]. Most common approach is the use of manufacturer power curve, which specifies the relationship between the input wind speed and WT output power.…”

SFOA: Sun Flower Optimization Algorithm to Solve Optimal Power Flow

“…In 2019, Guido Coletta et al [4], addressed a problem in weather-based method, which was identified as a major potential facilitating technique in order to increase the system suppleness using the components of real power loadability. Nevertheless, in real operation circumstances, the consumption of this method could be acutely cooperation because of the uncertainty data effects.…”

“…Earlier, numerous researchers examined on several optimization algorithms that exhibit the different issues and how it obtain and resolved with assist for the solution of the OPF [4]. Generally, two kinds of algorithms are exploited namely traditional and intelligent algorithms in order to resolve the OPF problems.…”

Solution proposal to the unit commitment problem incorporating manifold uncertainties

“…Furthermore, some progress has already been made in treating multiple uncertainties in power system analysis. A kind of affine arithmetic (AA) method was developed to model uncertain renewable generations in optimal power flow (OPF) problem [22, 23], and a weather‐based OPF was subsequently proposed based on the AA method [24]. As for the case where the probability, possibility, and interval measures were considered simultaneously, Luo et al .…”