5 research outputs found
Online Static Security Assessment of Power Systems Based on Lasso Algorithm
As one important means of ensuring secure operation in a power system, the
contingency selection and ranking methods need to be more rapid and accurate. A
novel method-based least absolute shrinkage and selection operator (Lasso)
algorithm is proposed in this paper to apply to online static security
assessment (OSSA). The assessment is based on a security index, which is
applied to select and screen contingencies. Firstly, the multi-step adaptive
Lasso (MSA-Lasso) regression algorithm is introduced based on the regression
algorithm, whose predictive performance has an advantage. Then, an OSSA module
is proposed to evaluate and select contingencies in different load conditions.
In addition, the Lasso algorithm is employed to predict the security index of
each power system operation state with the consideration of bus voltages and
power flows, according to Newton-Raphson load flow (NRLF) analysis in
post-contingency states. Finally, the numerical results of applying the
proposed approach to the IEEE 14-bus, 118-bus, and 300-bus test systems
demonstrate the accuracy and rapidity of OSSA.Comment: Accepted by Applied Science
Special issue on developing and implementing smart grids : novel technologies, techniques and models
fi=vertaisarvioimaton|en=nonPeerReviewed
Two-Step Many-Objective Optimal Power Flow Based on Knee Point-Driven Evolutionary Algorithm
To coordinate the economy, security and environment protection in the power
system operation, a two-step many-objective optimal power flow (MaOPF) solution
method is proposed. In step 1, it is the first time that knee point-driven
evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and
thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated
decision analysis technique is utilized to provide decision makers with
decision supports by combining fuzzy c-means (FCM) clustering and grey
relational projection (GRP) method together. In this way, the best compromise
solutions (BCSs) that represent decision makers' different, even conflicting,
preferences can be automatically determined from the set of Pareto-optimal
solutions. The primary contribution of the proposal is the innovative
application of many-objective optimization together with decision analysis for
addressing MaOPF problems. Through examining the two-step method via the IEEE
118-bus system and the real-world Hebei provincial power system, it is verified
that our approach is suitable for addressing the MaOPF problem of power
systems.Comment: Accepted by Journal Processe