2016 IEEE Region 10 Conference (TENCON) 2016
DOI: 10.1109/tencon.2016.7848086
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Dynamic economic dispatch of hybrid microgrid with energy storage using quadratic programming

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Cited by 29 publications
(15 citation statements)
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“…Content may change prior to final publication. 29, (30), and (37). 4: (c) Initialize the upper bound constraint in equation (31).…”
Section: Numerical Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Content may change prior to final publication. 29, (30), and (37). 4: (c) Initialize the upper bound constraint in equation (31).…”
Section: Numerical Resultsmentioning
confidence: 99%
“…SOCi,r(t) by considering an average ratio of the residual energy of the EVs where α 1 is the weight factor to consider the state of the EV user of the charge value into the dissatisfaction cost. In addition to this EV case, such a quadratic model has been widely used in other fields [28]- [30]. Correspondingly, for each i ∈ I, the utility function of the buyer i is defined as follows:…”
Section: B Utility Function Of the Buyersmentioning
confidence: 99%
“…The main objective was to formulate the economic dispatch considering hybrid system comprising of solar and energy storage system to ensure in meeting the daily load demand [25]. With the help of MATLAB based quadratic programming, dynamic economic dispatch was carried out on the hybrid system in direction to encounter the daily load demand.…”
Section: Literature Survey On Economic Dispatch Of Hybrid Systems / Mmentioning
confidence: 99%
“…Cost coefficients were set as a i ∼ U(0.01, 1), b i ∼ U (20, 20.5), c i ∼ U(600, 1530) [28]. The configuration data of the test systems such as load profiles, DGs' ramping rates, predicted outputs of PVs were obtained from [20,23,29] with proportional modifications. P G t0 and P ft0 were set as the average output of each DG and zero, respectively, and parameters λ 0 = 0.1, v 0 = 0.1, μ = 10, α = 0.1, β = 0.7, ε feas = 10 −4 , and ε = 10 −4 were applied.…”
Section: Simulationsmentioning
confidence: 99%