Probabilistic power flow calculation based on importance-Hammersley sampling with Eigen-decomposition

Li, Quan; Zhao, Nan

doi:10.1016/j.ijepes.2021.106947

Cited by 10 publications

(6 citation statements)

References 39 publications

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“…This section demonstrates the P‐OPF simulations and validation performed by the proposed methods discussed in the literature [34–69]. The P‐OPF problem in electric power systems considers the integration of RE sources such as WT and PV.…”

Section: Discussionmentioning

confidence: 99%

“…Modified IEEE 118-bus test system, integrating WT [34] The presented comprehensive survey of advanced methods used for the solution of P-OPF in RE-DG integrated power systems shows the problem, optimization objectives, and validation systems. It can be seen from the survey table that most of the applied methods are focused on fuel cost minimization, as the renewable energy sources integration minimizes the utilization of conventional generations such as thermal units, which consequently results in fuel cost minimization.…”

Section: Figure 12mentioning

confidence: 99%

“…Hence, various advanced methods using optimization techniques have been recently developed to solve the probabilistic OPF problem in the DG‐integrated power system. For instance, in reference [34], the probabilistic OPF was addressed in the presence of WT integration, and metaheuristic optimization method Importance‐Hammersley Sampling (IHSE) with Eigen‐decomposition was opted to solve the OPF problem.…”

Section: Systematic Literature On Advanced Studies For P‐opfmentioning

confidence: 99%

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Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Ullah

Wang

et al. 2022

IET Generation Trans & Dist

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In the active distribution networks (ADNs), the emerging trend of high penetration of sustainable energy sources such as wind turbines, photovoltaics, and the forthcoming integration of energy storage devices and additional dynamic loads like plug-in-electric vehicles (PEVs) influences to change the nature of electric distribution networks. Consequently, it deteriorates power quality and reliability in terms of unacceptable voltage rise-drop, harmonic distortion, voltage unbalance, and excessive power loss. In this context of transition into the active distribution network, the probabilistic optimal power flow (P-OPF) in the ADN is considered an important tool that helps the distribution grid operators for defining the optimal settings of the system's control variables. However, the optimal solution of P-OPF becomes highly complex while considering the multiple variables, timevarying characteristics and operational uncertainties associated with sustainable resources, consumer behaviour and electricity market prices. This review aims at promoting the research and discussion of P-OPF studies in the context of ADNs characteristics and challenges. First, we perform a data-driven and visualized scientometric analysis of 1988 quality documents retrieved from the Scopus during the last ten years using VOSviewer software. Second, an in-depth investigation of the recent and emerging techniques for solving the P-OPF problem is presented. Third, a set of recommendations and highlights of future challenges for P-OPF in ADNs are offered. The review findings showed high interest among the scientific community in sustainable energy source integration, given the recent rise in publications and citations. Also, there is still a lack of innovative optimization techniques that can adequately handle the current issues associated with P-OPF and objectives with fair computational efficiency and accuracy. Finally, this paper offers a guide for P-OPF researchers to navigate the recent studies considering the sustainable sources, spot the new research frontiers, and identify the most impactful countries and publishers.

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Section: Discussionmentioning

confidence: 99%

Section: Figure 12mentioning

confidence: 99%

Section: Systematic Literature On Advanced Studies For P‐opfmentioning

confidence: 99%

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Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Ullah

Wang

et al. 2022

IET Generation Trans & Dist

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“…Elsewhere, the authors of [26] provide a novel POPF model that copes with uncertainties, considering electrical power generation from a wind turbine. Another study [27] introduces a new POPF problem solution approach for electrical power networks, including wind energy sources, using an approach that adopts sampling to determine the probability density functions (PDF). The authors of [28] provide a new method for the POPF solution of large power networks, including Pearson correlated uncertainty sources, using a technique that enhances the efficiency from each aspect.…”

Section: Introductionmentioning

confidence: 99%

Solution of Probabilistic Optimal Power Flow Incorporating Renewable Energy Uncertainty Using a Novel Circle Search Algorithm

Shaheen

Ullah

Qais³

et al. 2022

Energies

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Integrating renewable energy sources (RESs) into modern electric power systems offers various techno-economic benefits. However, the inconsistent power profile of RES influences the power flow of the entire distribution network, so it is crucial to optimize the power flow in order to achieve stable and reliable operation. Therefore, this paper proposes a newly developed circle search algorithm (CSA) for the optimal solution of the probabilistic optimal power flow (OPF). Our research began with the development and evaluation of the proposed CSA. Firstly, we solved the OPF problem to achieve minimum generation fuel costs; this used the classical OPF. Then, the newly developed CSA method was used to deal with the probabilistic power flow problem effectively. The impact of the intermittency of solar and wind energy sources on the total generation costs was investigated. Variations in the system’s demands are also considered in the probabilistic OPF problem scenarios. The proposed method was verified by applying it to the IEEE 57-bus and the 118-bus test systems. This study’s main contributions are to test the newly developed CSA on the OPF problem to consider stochastic models of the RESs, providing probabilistic modes to represent the RESs. The robustness and efficiency of the proposed CSA in solving the probabilistic OPF problem are evaluated by comparing it with other methods, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and the hybrid machine learning and transient search algorithm (ML-TSO) under the same parameters. The comparative results showed that the proposed CSA is robust and applicable; as evidence, an observable decrease was obtained in the costs of the conventional generators’ operation, due to the penetration of renewable energy sources into the studied networks.

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“…When the PPF problem is considered in the independent standard uniform space, this task is equivalent to generating samples uniformly distributed in a hypercube space. Several studies have reported that Sobol sequence [4], Hammersley sequence [4], Latin hypercube sampling method [5,6] and Latin supercube sampling method [7] behave better than pseudo-random sequences.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic power flow computation using nested point estimate method

Xiao

Chen

2021

IET Generation Trans & Dist

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The probabilistic power flow (PPF) computation involves quantifying and propagating uncertainty over hundreds of variables. Zhao's point estimate method (PEM) has been widely used for PPF computation, and the computational burden increases linearly with respect to the number of PPF inputs. In this paper, Zhao's PEM is reformulated as the Kronecker product of Gauss-Hermite quadrature and an identity matrix. Following this formulation, a new PEM termed Nested PEM is developed based on Hadamard matrix, which can reduce the computational burden nearly by half relative to Zhao's PEM. In order to consider the dependence among PPF inputs, the extended generalized lambda distribution (EGLD) is employed to model marginal distributions of correlated PPF inputs, and the t -copula is introduced to map PPF problem to the independent standard normal space. Finally, case studies are conducted on a modified IEEE 118-bus system to illustrate the proposed PEM.

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Probabilistic power flow calculation based on importance-Hammersley sampling with Eigen-decomposition

Cited by 10 publications

References 39 publications

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Solution of Probabilistic Optimal Power Flow Incorporating Renewable Energy Uncertainty Using a Novel Circle Search Algorithm

Probabilistic power flow computation using nested point estimate method

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