A Generic Convex Model for a Chance-Constrained Look-Ahead Economic Dispatch Problem Incorporating an Efficient Wind Power Distribution Modeling

Khorramdel, Benyamin; Zare, Alireza; Chung, C. Y.; Gavriliadis, P. N.

doi:10.1109/tpwrs.2019.2940288

Cited by 26 publications

(16 citation statements)

References 34 publications

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“…However, KDE may suffer from the boundary effect for bounded variables. Boundary effect has been addressed in several power system analyses [31–33]. The authors recent study examined a Bernstein‐smoothed density forecasting method [24], which can tackle the boundary effect.…”

Section: Problem Statement and Supporting Mathematical Methodsmentioning

confidence: 99%

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Data‐driven look‐ahead voltage stability assessment of power system with correlated variables

Nejadfard-jahromi

Mohammadi

2022

IET Generation Trans & Dist

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Probabilistic voltage stability assessment (VSA) of distribution systems has recently gained significant research attention due to the proliferation of renewable energy sources (RESs). This study presents a nonparametric data-driven VSA in a look-ahead framework by considering correlated variables. First, an accurate but relatively fast correlation model is developed by considering stochastic interdependency with unknown dependency structure. Then, the probabilistic density function (PDF) of the voltage stability index is estimated for near-future minutes. The proposed method employs Bernstein vine copula (BVC) for estimating the unknown underlying dependence structure among different variables. This non-parametric method imposes no assumption on the dependence structure and can handle the problems where no information is available for judging about dependence structure and its belongingness to a specific type of copula function. Additionally, global sensitivity analysis (GSA), with an embedded surrogate model based on the extreme learning machine (ELM), is utilized to rank the loads and RESs according to their contribution to voltage stability margin. Furthermore, a parallel implementation of vine copula construction and dimension reduction is developed based on the GSA to speed up the proposed VSA. The efficiency of the proposed method is examined by simulating the results of modified IEEE 33-node and 123-node systems.

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Section: Problem Statement and Supporting Mathematical Methodsmentioning

confidence: 99%

“…However, KDE may suffer from the boundary effect for bounded variables. Boundary effect has been addressed in several power system analyses [31][32][33].…”

Section: Short Term Forecastingmentioning

confidence: 99%

Data‐driven look‐ahead voltage stability assessment of power system with correlated variables

Nejadfard-jahromi

Mohammadi

2022

IET Generation Trans & Dist

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“…The raw probability distribution of available renewable generation can be obtained from empirical analysis on historical operation data and/or short-term numerical weather forecasting in form of probability histograms, which can be further fitted with parametric distributions such as Gaussian, Cauchy, Weibull, and beta distributions. Recently, mixture models are employed to describe the probability density of renewable generation in a more flexible and accurate approach, including Gaussian mixture model [19], versatile mixture distribution [20], and beta kernel density representation [21]. Therefore, we assume that the PDF of available re- 3) can be calculated numerically for specific values of r ub i r lb i .…”

Section: A Linearization Of Objective Functionmentioning

confidence: 99%

Optimal Decomposition of Stochastic Dispatch Schedule for Renewable Energy Cluster

Yang

Wang

et al. 2021

Journal of Modern Power Systems and Clean Energy

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The correlated renewable energy farms are usually aggregated as a cluster in economic dispatch to relieve computational burden. This strategy can also achieve better performance since the precision of predicting the power generation of a cluster can be higher than those of individual farms. This paper proposes an optimal decomposition method to allocate dispatch schedules among renewable energy farms (REFs) in the cluster under existing stochastic optimization framework. The proposed model takes advantage of probabilistic characteristics of renewable generation to minimize the curtailment and ensure the feasibility of dispatch schedule of the clusters. Approximated tractable formulation and efficient solution method are the proposed to solve the proposed model. Numerical tests show that the proposed method achieves the optimal decomposition of dispatch schedule among REFs and facilitates the utilization of renewable generation.

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“…In non-smooth problems, the impact of the valve system is considered in the power generation cost function. Both smooth and non-smooth problems have been successfully solved using heuristic techniques, as respectively reported in [ 5 , 6 ] and [ 7 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

A Non-Convex Economic Dispatch Problem with Point-Valve Effect Using a Wind-Driven Optimisation Approach

Ramli

Kamari

Halim

et al. 2021

J. Electr. Eng. Technol.

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This study presents the efficiency of the wind-driven optimisation (WDO) approach in solving non-convex economic dispatch problems with point-valve effect. The best economic dispatch for a power system is one wherein the system can generate energy at a low cost. The calculation of the generating cost is subject to a number of constraints, such as the power demand for the entire system and the generation limit for each generator unit in the system. In addition, the system should also produce low power loss. The WDO optimisation technique is developed based on the concept of natural wind movement, which serves as a stabiliser to equalise the inequality of air pressure in the atmosphere. One major advantage of WDO over other techniques is its search accuracy. The proposed algorithm has been implemented in two systems, namely, the 10-generator and 40-generator systems. Both systems were tested in a Matlab environment. To highlight the capabilities of WDO, the results using this proposed technique are compared with the results obtained using flower pollination algorithm, moth flame optimisation, particle swarm optimisation and evolutionary programming techniques to determine the efficiency of the proposed approach in solving economic dispatch. The simulation results show the capability of WDO in determining the optimal power generation value with minimum generation cost and low rate of power loss.

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A Generic Convex Model for a Chance-Constrained Look-Ahead Economic Dispatch Problem Incorporating an Efficient Wind Power Distribution Modeling

Cited by 26 publications

References 34 publications

Data‐driven look‐ahead voltage stability assessment of power system with correlated variables

Data‐driven look‐ahead voltage stability assessment of power system with correlated variables

Optimal Decomposition of Stochastic Dispatch Schedule for Renewable Energy Cluster

A Non-Convex Economic Dispatch Problem with Point-Valve Effect Using a Wind-Driven Optimisation Approach

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