2020
DOI: 10.1049/iet-rpg.2020.0215
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Linear network model for integrated power and gas distribution systems with bidirectional energy conversion

Abstract: With the advancement of emerging power-to-gas (P2G) technologies, the integrated power and gas distribution system (IPGDS) with bidirectional energy conversion is becoming a promising measure to promote the integration of renewablebased distributed generation. This study proposes the linear network model for the IPGDS and takes the reactive power consumption of P2G into account. The linear model considering the network constraints of the IPGDS is implemented combining the Wendroff difference for gas network eq… Show more

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Cited by 8 publications
(3 citation statements)
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References 42 publications
(49 reference statements)
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“…Therefore, this paper uses second‐order cone programming (SOCP) to transform the non‐convex equations in the established optimization model [26]. Compared with the original MINNP problem, the transformed equation is a mixed integer convex programming, which can be quickly and accurately solved by some commercial solvers [27].…”
Section: Model Solution Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Therefore, this paper uses second‐order cone programming (SOCP) to transform the non‐convex equations in the established optimization model [26]. Compared with the original MINNP problem, the transformed equation is a mixed integer convex programming, which can be quickly and accurately solved by some commercial solvers [27].…”
Section: Model Solution Methodsmentioning
confidence: 99%
“…Based on the second‐order cone transformation, the RO model in the TSR‐VVOC strategy is further processed, which can be expressed in the following compact matrix form: minxmaxμminyaTy\begin{equation}\mathop {\min }\limits_x \mathop {\max }\limits_\mu \mathop {\min }\limits_y {a^T}y\end{equation} normals.t.1emAxa\begin{equation}{\rm{s}}{\rm{.t}}{\rm{. }}\quad Ax \ge a\end{equation} Byf\begin{equation}By \le f\end{equation} Dy+Ex=d\begin{equation}Dy + Ex = d\end{equation} Fy=u\begin{equation}Fy = u\end{equation} Ciy2ciTy\begin{equation}{\left\| {{C_i}y} \right\|_2} \le c_i^Ty\end{equation} μW\begin{equation}\mu \in W\end{equation}where constraints () of the RO model are equivalent to constraints (27)–(). x , μ , y are equivalent variable sets, A , B , D , E , F , C i , a , f , d , u , cinormalT${c}_{i}^{\mathrm{T}}$ are equivalent coefficient matrices or vectors, W is an uncertain set.…”
Section: Model Solution Methodsmentioning
confidence: 99%
“…As shown in Figure 1, when DFIG participates in reactive power regulation of the power system, its regulation ability is mainly determined by the capacity of the stator side and grid side rectifier. The output power constraints on the stator side are (Zhou et al, 2020):…”
Section: Modeling Of Wind Turbinementioning
confidence: 99%