Managing uncertainty of wind energy with Wind Generators Cooperative

Opathella, C.; Venkatesh, Bala

doi:10.1109/pesgm.2015.7286028

Cited by 10 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where H k ∈ ℝ 1 × W is the kth row of H and h k ∈ ℝ is the kth entry of h; λ ∈ ℝ, s i ∈ ℝ, θ i, k ∈ ℝ and γ i, k ∈ ℝ 2W × 1 are decision variables; ∥ ⋅ ∥ * is the operator of dual norm that corresponds to the norm employed in (8). In this paper, the norm in (8) is chosen as 1-norm.…”

Section: Estimating Tap Without Exactly Known Pdtmentioning

confidence: 99%

“…Such uncertain feature can impose great challenges upon power system scheduling and operation [3][4][5]. In this regard, tremendous work has been conducted either by exploring the flexibility of current power system or by incorporating energy storage systems [6][7][8]. For the sake of improving operational flexibility, two key issues have been the central focus of existing literature: (i) how to make an immune dispatch strategy, and (ii) how to assess the capability of a given dispatch strategy to hedge against uncertainties.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Liu¹,

Liu

Wei

et al. 2019

IET Renewable Power Generation

View full text Add to dashboard Cite

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.

show abstract

Section: Estimating Tap Without Exactly Known Pdtmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Liu¹,

Liu

Wei

et al. 2019

IET Renewable Power Generation

View full text Add to dashboard Cite

show abstract

“…The results we provide collocate within the learning, control and optimisation research areas. This research direction finds applications in various problems such as wind energy (Opathella and Venkatesh , 2013;Bayens et al , 2013), and the inventory control problem Bauso et al (2008); Bauso et al (2010).…”

Section: Ams Subject Classifications 68q25 68r10 68u05mentioning

confidence: 99%

Game-Theoretic Learning and Allocations in Robust Dynamic Coalitional Games

Smyrnakis¹,

Bauso²,

Tembiné³

2019

SIAM J. Control Optim.

View full text Add to dashboard Cite

“…The resulted wind generation uncertainty has imposed great challenge on power system operation like unit commitment (UC) and economic dispatch (ED) [3,4,5]. To cope with this problem, tremendous work has been conducted either by exploring the flexibility of current power system or integrating other devices with quicker response like energy storage systems (EES) [6,7,8]. In terms of improving power system flexibility, improving the accuracy of modeling wind generation uncertainty, making immune operation strategies and evaluating power system's capability to accommodate wind generation are three topics that have been wildly concerned.…”

Section: Introductionmentioning

confidence: 99%

Estimating lower probability bound of power system's capability to fully accommodate variable wind generation

Liu

Zhai

Liu³

et al. 2018

J. eng.

View full text Add to dashboard Cite

As the penetration of wind generation increases, the uncertainty it brings has imposed great challenges to power system operation. To cope with the challenges, tremendous research work has been conducted, among which two aspects are of most importance, i.e. making immune operation strategies and accessing the power system's capability to accommodate the variable energy. Driven and inspired by the latter problem, this paper will discuss the power system's capability to accommodate variable wind generation in a probability sense. Wind generation, along with its uncertainty is illustrated by a polyhedron, which contains prediction, risk and uncertainty information. Then, a three-level optimization problem is presented to estimate the lower probability bound of power system's capability to fully accommodate wind generation. After reformulating the inner max-min problem, or feasibility check problem, into its equivalent mixed-integer linear program (MILP) form, the bisection algorithm is presented to solve this challenging problem. Modified IEEE systems are adopted to show the effectiveness of the proposed method.

show abstract

Managing uncertainty of wind energy with Wind Generators Cooperative

Cited by 10 publications

References 0 publications

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

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

Game-Theoretic Learning and Allocations in Robust Dynamic Coalitional Games

Estimating lower probability bound of power system's capability to fully accommodate variable wind generation

Contact Info

Product

Resources

About