Probabilistic evaluation of a power system's capability to accommodate uncertain wind power generation

Abstract

With the rapidly growing integration of wind power generation (WPG), it is of great importance for an operator to grasp the ability of the power system to accommodate uncertain WPG. This study proposes two probabilistic methods to assess such capability of a power system based on the level of data availability. If the probability distribution type (PDT) of wind power prediction error (WPPE) is known, the total accommodation probability is calculated as the sum of a fully guaranteed probability and a partially guaranteed probability. The former one leads to a tri-level max-max-min optimisation problem which is solved via a dichotomy procedure, and the latter one can be obtained based on the geometrical analysis of the dispatchable region of WPG. If the PDT of WPPE is not exactly known, the authors tackle the problem via a data-driven uncertainty quantification method. More precisely, they consider a family of ambiguous probability distributions around the empirical distribution described by historical data in the sense of Wasserstein metric. The probability of failure in the worst-case distribution is calculated from a linear programming. The proposed method is tested on modified PJM-5 and IEEE-118 bus systems. Comparison with the traditional Monte Carlo Simulation method demonstrates its efficacy and efficiency.

Sensitivity and Robustness Issues of Operating Envelopes in Unbalanced Distribution Networks

“…Under the assumptions that: (i) the upper limit of nodal voltage is V max i for a bus i and voltage compliance is the only factor to be considered in calculating DOEs, and (ii) all customers are subject to the same DOE, say P DOE , then P DOE can be calculated using a bisection algorithm initialised from reasonable DOE bounds, as shown in Algorithm 1. The bisection algorithm is a simple numerical approach commonly used in power system operation assessments (e.g., [33], [34]), and it can naturally be applied in PF-based approaches to calculate DOEs with guaranteed convergence. The UTPF can be formulated and solved with off-the-shelf solvers, e.g.…”

Multi-scenario flexibility assessment of power systems considering renewable energy output uncertainty

“…In the study of the flexibility assessment of systems containing renewable energy, by studying the power output characteristics of wind power and photovoltaic, a mathematical morphology algorithm is used to obtain the flexibility evaluation index system for different time scales and climbing directions by Tong et al (2023). For the problem of flexibility assessment of power systems containing a high proportion of wind power access, based on the Monte Carlo simulation method and economic dispatch model for the calculation of flexibility metrics, Li et al (2015) and Liu et al (2019) proposed a flexibility evaluation index system based on the fluctuation of wind power and load, as well as the inherent flexibility supply capacity of various generation resources in the system. Li et al (2017) conducted a quantitative analysis from the perspective of the regulation range of system flexibility resources, and a practical system flexibility adequacy calculation method was proposed based on the power balance constraint to realize the evaluation of system renewable energy consumption capacity.…”

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