Analysis of Radial Distribution Systems With Embedded Series FACTS Devices Using a Fast Line Flow-Based Algorithm

Yan, Ping; Sekar, A.

doi:10.1109/tpwrs.2005.856986

Cited by 25 publications

(9 citation statements)

References 17 publications

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“…Power flow constraints : The AC power flow equations are non‐linear and non‐convex constraints. In order to have a convex optimisation model, line flow based (LFB) [25] AC power flow equations are considered as follows.

\begin{matrix} true \\ left \forall i \in Ω_{n}, \forall t \in Ω_{t}, \forall l \in Ω_{l} : \\ left \sum_{l \in Ω_{l}} A_{l i} P_{l, t}^{net} = P_{i, t}^{G} + P_{i, t}^{w} + P_{i, t}^{p v} - P_{i, t}^{D} - P_{i, t}^{c h} + P_{i, t}^{d c h} \end{matrix}

\begin{matrix} true \\ left - \sum_{l \in Ω_{l}} B_{l i} R_{l} J_{l, t} \\ left \sum_{l \in Ω_{l}} A_{l i} Q_{l, t}^{net} = Q_{i, t}^{G} + Q_{i, t}^{w} - Q_{i, t}^{D} - \sum_{l \in Ω_{l}} B_{l i} X_{l} J_{l, t} \end{matrix}

\begin{matrix} true \\ left - (() 1 - z_{l}^{r}) normalM \leq U_{j, t} - 2 \sum_{l \in Ω_{l}} B_{l j} (R_{l} P_{l, t}^{net} + X_{l}) \end{matrix}

…”

Section: Description Of the Proposed Oepmmentioning

confidence: 99%

Optimal flexibility coordination for energy procurement in distribution networks

Hooshmand

Rabiee

Jalilzadeh

et al. 2021

IET Renewable Power Gen

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The main goal of distribution network operator is to establish a balance between supply and demand at the lowest cost while considering the technical constraints. Nowadays, distribution network operators exploit various types of flexibilities to minimise operational costs. However, each flexibility resource has its own technical and economic characteristics. This paper proposes a day‐ahead energy dispatch model which allows the distribution network operator to minimise the energy procurement costs on an hourly basis. The developed model considers various flexibility resources such as renewable energy sources, energy storage systems, demand response, optimal distribution system reconfiguration, and on‐load tap changers optimal settings. The proposed model is formulated as a convex mixed‐integer second‐order conic programming model. It is implemented on the IEEE standard 33‐bus and 70‐bus radial systems to demonstrate its capabilities. The obtained numerical results substantiate the role of distributed energy resources in energy procurement cost reduction, while the impact of distribution system reconfiguration and on‐load tap changers on voltage profile improvement.

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\begin{matrix} true \\ left \forall i \in Ω_{n}, \forall t \in Ω_{t}, \forall l \in Ω_{l} : \\ left \sum_{l \in Ω_{l}} A_{l i} P_{l, t}^{net} = P_{i, t}^{G} + P_{i, t}^{w} + P_{i, t}^{p v} - P_{i, t}^{D} - P_{i, t}^{c h} + P_{i, t}^{d c h} \end{matrix}

\begin{matrix} true \\ left - \sum_{l \in Ω_{l}} B_{l i} R_{l} J_{l, t} \\ left \sum_{l \in Ω_{l}} A_{l i} Q_{l, t}^{net} = Q_{i, t}^{G} + Q_{i, t}^{w} - Q_{i, t}^{D} - \sum_{l \in Ω_{l}} B_{l i} X_{l} J_{l, t} \end{matrix}

\begin{matrix} true \\ left - (() 1 - z_{l}^{r}) normalM \leq U_{j, t} - 2 \sum_{l \in Ω_{l}} B_{l j} (R_{l} P_{l, t}^{net} + X_{l}) \end{matrix}

…”

Section: Description Of the Proposed Oepmmentioning

confidence: 99%

Optimal flexibility coordination for energy procurement in distribution networks

Hooshmand

Rabiee

Jalilzadeh

et al. 2021

IET Renewable Power Gen

View full text Add to dashboard Cite

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“…The algorithm implemented for accommodating all the above proposed models is based on the well known current injection algorithm [11]. This kind of algorithm, as well as the Backward/Forward Swept algorithms use a formulation based in the Current Kircchoff Law (KCL) and Voltage Kircchoff Law (KVL) [10], [31]- [33] instead of the traditional power injection formulation used for instance by the conventional Newton-Raphson methods [8], [34]. The latter are usually faster for solving unconstrained power flow problems with smooth characterstics devices, but the former are faster and more stable for solving constrained power flow problems containing devices with non-smooth characteristics as it will be demonstrated later in this paper.…”

Section: Current Injection Power Flow Algorithmmentioning

confidence: 99%

DC Railway Simulation Including Controllable Power Electronic and Energy Storage Devices

Arboleya

Belaid

El‐Sayed

2018

IEEE Trans. Power Syst.

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This work presents a comprehensive set of steady state models to be included in power flow simulation studies of DC railway networks. This simulation framework covers all important aspects and features of each element of modern DC railways. The proposed models are simplified to achieve the maximum simulation speed while keeping the required accuracy. Not only non-reversible, controlled and uncontrolled reversible substations are considered, but also on-board and off-board accumulation systems. The train model can consider the low network receptivity (overvoltage protection for trains equipped with regenerative braking) and overcurrent protection. It is also possible to include in the simulation DC/DC links between nodes of the railway network at the same or different voltage. To date, there is no other work able to conjugate all the mentioned models in a complex multi-train scenario.

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“…In the following, a short introduction of this method is described to make the problem clear. Note that the accuracy of the LFB power flow model has been investigated and approved in different applications [20][21][22]. Matrix representations of active and reactive power balance equations at all buses, save the slack bus, are expressed as (1) and (2), respectively.…”

Section: Nomenclaturementioning

confidence: 99%

A non-iterative approach for AC state estimation using line flow based model

Safdarian

Fotuhi‐Firuzabad

Aminifar

2012

International Journal of Electrical Power & Energy Systems

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Analysis of Radial Distribution Systems With Embedded Series FACTS Devices Using a Fast Line Flow-Based Algorithm

Cited by 25 publications

References 17 publications

Optimal flexibility coordination for energy procurement in distribution networks

Optimal flexibility coordination for energy procurement in distribution networks

DC Railway Simulation Including Controllable Power Electronic and Energy Storage Devices

A non-iterative approach for AC state estimation using line flow based model

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