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unscented-transformation
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Modification of unscented kalman filter using a set of scaling parameters
, Article IET Signal Processing ; Volume 12, Issue 4 , 2018 , Pages 471-480 ; 17519675 (ISSN) ; Malaek, M. B ; Sharif University of Technology
Institution of Engineering and Technology
2018
Abstract
This work, based on the standard unscented Kalman filter (UKF), proposes a modified UKF for highly non-linear stochastic systems, assuming that the associated probability distributions are normal. In the standard UKF with 2n + 1 sample points, the estimated mean and covariance match the true mean and covariance up to the third order, besides, there exists a scaling parameter that plays a crucial role in minimising the fourth-order errors. The proposed method consists of a computationally efficient formulation of the unscented transform that incorporates N - 1, N ≥ 2, constant parameters to scale 2n(N - 1) + 1 sample points such that the 2Nth order errors are minimised. The scaling parameters...
Unscented transformation-based probabilistic optimal power flow for modeling the effect of wind power generation
, Article Turkish Journal of Electrical Engineering and Computer Sciences ; Vol. 21, issue. 5 , 2013 , p. 1284-1301 ; ISSN: 13000632 ; Fotuhi-Firuzabad, M ; Aminifar, F ; Sharif University of Technology
Abstract
The unprecedented increasing penetration of distributed energy resources, mainly harvesting renewable energies, is a direct result of environmental concerns. These types of energy resources bring about more uncertainties in the power system and, consequently, necessitate probabilistic analyses of the system performance. This paper develops a new approach for probabilistic optimal power flow (P-OPF) by adapting the unscented transformation (UT) method. The heart of the proposed method lies in how to produce the sampling points. Appropriate sample points are chosen to perform the P-OPF with a high degree of accuracy and less computational burden in comparison with the features of other...
Unscented transformation-based probabilistic optimal power flow for modeling the effect of wind power generation
, Article Turkish Journal of Electrical Engineering and Computer Sciences ; Volume 21, Issue 5 , 2013 , Pages 1284-1301 ; 13000632 (ISSN) ; Fotuhi Firuzabad, M ; Aminifar, F ; Sharif University of Technology
2013
Abstract
The unprecedented increasing penetration of distributed energy resources, mainly harvesting renewable energies, is a direct result of environmental concerns. These types of energy resources bring about more uncertainties in the power system and, consequently, necessitate probabilistic analyses of the system performance. This paper develops a new approach for probabilistic optimal power flow (P-OPF) by adapting the unscented transformation (UT) method. The heart of the proposed method lies in how to produce the sampling points. Appropriate sample points are chosen to perform the P-OPF with a high degree of accuracy and less computational burden in comparison with the features of other...
Probabilistic load flow in correlated uncertain environment using unscented transformation
, Article IEEE Transactions on Power Systems ; Volume 27, Issue 4 , 2012 , Pages 2233-2241 ; 08858950 (ISSN) ; Fotuhi Firuzabad, M ; Aminifar, F ; Sharif University of Technology
2012
Abstract
As a matter of course, the unprecedented ascending penetration of distributed energy resources, mainly harvesting renewable energies, is a direct consequence of environmental concerns. This type of energy resource brings about more uncertainties in power system operation and planning; consequently, it necessitates probabilistic analyses of the system performance. This paper develops a new approach for probabilistic load flow (PLF) evaluation using the unscented transformation (UT) method. The UT method is recognized as a powerful approach in assessing stochastic problems with/without correlated uncertain variables. The capability of the UT method in modeling correlated uncertain variables is...
Stochastic Reconfiguration and Optimal Coordination of V2G Plug-in Electric Vehicles Considering Correlated Wind Power Generation
, Article IEEE Transactions on Sustainable Energy ; Volume 6, Issue 3 , 2015 , Pages 822-830 ; 19493029 (ISSN) ; Niknam, T ; Fotuhi Firuzabad, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
This paper investigates the optimal operation of distribution feeder reconfiguration (DFR) strategy in the smart grids with high penetration of plug-in electric vehicles (PEVs) and correlated wind power generation. The increased utilization of PEVs in the system with stochastic volatile behavior along with the high penetration of renewable power sources such as wind turbines (WTs) can create new challenges in the system that will affect the DFR strategy greatly. In order to reach the most efficiency from the PEVs, the idea of vehicle-to-grid (V2G) is employed in this paper to make a bidirectional power flow (either charging/discharging or idle mode) strategy when providing the main charging...
Dynamic optimization of natural gas networks under customer demand uncertainties
, Article Energy ; Volume 134 , 2017 , Pages 968-983 ; 03605442 (ISSN) ; Bozorgmehry Boozarjomehry, R ; Sharif University of Technology
Abstract
In natural gas transmission networks, the efficiency of daily operation is strongly dependent on our knowledge about the customer future demands. Unavailability of accurate demand forecasts makes it more important to be able to characterize the loads and quantify the corresponding uncertainty. A planning strategy for natural gas transmission networks under future demand uncertainty is addressed, which involves coupling of a gas transmission network dynamic simulator with the stochastic optimization framework. Loads from a gas-fired power plant are studied where the loads are characterized by a number of uncertain parameters, and unscented transform is utilized for uncertainty propagation....
On possibilistic and probabilistic uncertainty assessment of power flow problem: A review and a new approach
, Article Renewable and Sustainable Energy Reviews ; Vol. 37 , 2014 , p. 883-895 ; ISSN: 13640321 ; Rashidinejad, M ; Fotuhi-Firuzabad, M ; Sharif University of Technology
Abstract
As energy resource planning associated with environmental consideration are getting more and more challenging all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascend with an unprecedented rate. This fact causes new uncertainties to the power system context; ergo, the uncertainty analysis of the system performance seems necessary. In general, uncertainties in any engineering system study can be represented probabilistically or possibilistically. When sufficient historical data of the system variables is not available, a probability density function (PDF) might not be defined, while they must be represented in another...
Probabilistic load flow in correlated uncertain environment using unscented transformation
, Article IEEE Transactions on Power Systems ; Vol. 27, issue. 4 , 2012 , p. 2233-2241 ; ISSN: 08858950 ; Fotuhi-Firuzabad, M ; Aminifar, F ; Sharif University of Technology
Abstract
As a matter of course, the unprecedented ascending penetration of distributed energy resources, mainly harvesting renewable energies, is a direct consequence of environmental concerns. This type of energy resource brings about more uncertainties in power system operation and planning; consequently, it necessitates probabilistic analyses of the system performance. This paper develops a new approach for probabilistic load flow (PLF) evaluation using the unscented transformation (UT) method. The UT method is recognized as a powerful approach in assessing stochastic problems with/without correlated uncertain variables. The capability of the UT method in modeling correlated uncertain variables is...
Probabilistic optimal power flow in correlated hybrid wind-PV power systems: A review and a new approach
, Article Renewable and Sustainable Energy Reviews ; Volume 41 , January , 2015 , Pages 1437-1446 ; 13640321 (ISSN) ; Rashidinejad, M ; Firuz Abad, M. F ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
Hastening the power industry reregulation juxtaposed with the unprecedented utilization of uncertain renewable energies (REs), faces power system operation with sever uncertainties. Consequently, uncertainty assessment of system performance is an obligation. This paper reviews the probabilistic techniques used for probabilistic optimal power flow (P-OPF) studies and proposes a novel and powerful approach using the unscented transformation (UT) method. The heart of the proposed method lies in how to produce the sampling points. Appropriate sampling points are chosen to perform the P-OPF with a high degree of accuracy and less computational burden compared with features of other existing...
Considering forecasting errors in flexibility-oriented distribution network expansion planning using the spherical simplex unscented transformation
, Article IET Generation, Transmission and Distribution ; Volume 14, Issue 24 , 2020 , Pages 5816-5822 ; Jooshaki, M ; Moein Aghtaie, M ; Fotuhi Firuzabad, M ; Lehtonen, M ; Sharif University of Technology
Institution of Engineering and Technology
2020
Abstract
The rapid rise in the grid integration of low-carbon technologies, e.g. renewable energy sources (RESs) and plug-in electric vehicles (PEVs), has led to several challenges in distribution networks (DNs). This is due to the intermittent generation of RESs and uncertain loads of PEVs, both of which necessitate enhancing the flexibility requirements at the distribution level so as to accommodate the high penetration of these clean technologies in the future. To address such issues, this study proposes a mixed-integer linear programming-based expansion planning model for DNs considering the impact of high RES and PEV penetration, the associated uncertainties, and providing flexibility...