Corrective Voltage Control Scheme Considering Demand Response and Stochastic Wind Power

Rabiee, Abbas; Soroudi, Alireza; Mohammadi‐Ivatloo, Behnam; Parniani, Mostafa

doi:10.1109/tpwrs.2014.2316018

Cited by 133 publications

(86 citation statements)

References 34 publications

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“…-Scenario based modeling [7], [8] • Fuzzy approach [9] • Robust optimization [10] Each technique has its own "pros and cons". For example, stochastic techniques require knowledge of the probability density function of uncertain parameter.…”

Section: B Literature Reviewmentioning

confidence: 99%

Information Gap Decision Theory Based OPF With HVDC Connected Wind Farms

Rabiee

Soroudi

Keane

2015

IEEE Trans. Power Syst.

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104

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Section: B Literature Reviewmentioning

confidence: 99%

Information Gap Decision Theory Based OPF With HVDC Connected Wind Farms

Rabiee

Soroudi

Keane

2015

IEEE Trans. Power Syst.

Self Cite

104

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“…From this perspective, smart technologies can be viewed as real options [3]. Examples of such technologies include the Coordinated Voltage Control (CVC) [4], [9] Soft-Open Points (SOP) [5] and Demand-side Response (DSR) [6] [7]. It is shown in this paper that since deterministic planning approaches cannot capture the managerial flexibility, these smart technologies are largely ignored; such an observation shows the importance of departing from current deterministic planning approaches in order to reduce spending on conventional assets and increase the integration of smart technologies.…”

Section: Input Parameters γmentioning

confidence: 99%

Stochastic optimisation-based valuation of smart grid options under firm DG contracts

Giannelos

Konstantelos

Štrbac

2016

2016 IEEE International Energy Conference (ENERGYCON)

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Abstract-Under the current EU legislation, Distribution Network Operators (DNOs) are expected to provide firm connections to new DG, whose penetration is set to increase worldwide creating the need for significant investments to enhance network capacity. However, the uncertainty around the magnitude, location and timing of future DG capacity renders planners unable to accurately determine in advance where network violations may occur. Hence, conventional network reinforcements run the risk of asset stranding, leading to increased integration costs. A novel stochastic planning model is proposed that includes generalized formulations for investment in conventional and smart grid assets such as Demand-Side Response (DSR), Coordinated Voltage Control (CVC) and Soft Open Point (SOP) allowing the quantification of their option value. We also show that deterministic planning approaches may underestimate or completely ignore smart technologies. Power drawn by SOP at terminal (pu) Index Terms-Firm DG contracts, Option Value of smart technologies, Planning under uncertainty, Real Options I. NOMENCLATURE Sets and indices

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“…It is worth mentioning that the content of sections IV-B, IV-C and IV-D are derived from well-established load flow and HVDC models which are given in [4], [15], [16], [25]- [28].…”

Section: Problem Formulationmentioning

confidence: 99%

“…It can be avoided by preventive voltage control (PVC) or by post-contingency corrective voltage control (CVC). The post-contingency CVC aims to restore voltage stability by directing the system into a new secure equilibrium point shortly after a severe contingency, such as the outage of a heavily loaded transmission line or transformer [4]. But, PVC is initiated in the condition that the system's loading margin (LM), is less than a desired value [5].…”

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confidence: 99%