Security region of natural gas pipeline network system: Concept, method and application

Song, Chenhui; Xiao, Jun; Zu, Guoqiang; Hao, Ziyuan; Zhang, Xinsong

doi:10.1016/j.energy.2020.119283

Cited by 27 publications

(5 citation statements)

References 29 publications

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“…Nevertheless, the inherently unpredictable characteristics of wind and PV power generation may lead to substantial resource wastage (Joseph and Balachandra, 2020). Digital technologies are being used effectively to accurately model and optimize various processes (Li et al, 2020;Song et al, 2021;Yang et al, 2023). Thus, to enhance the utilization of RE resources and encourage efficient energy consumption, establishing a coordination mechanism for multi-energy complementation through digital technologies is imperative.…”

Section: Introductionmentioning

confidence: 99%

A capacity optimization and scheduling scheme of a multi-energy complementary power station considering energy trading

Zou¹,

Zhang

Wei

2023

Front. Energy Res.

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Digital technology is rapidly advancing, and the resulting digitization of energy is becoming an inevitable trend. Integrating digital technology with energy planning can enable efficient utilization of renewable energy (RE); the fluctuation of RE generation, such as wind and photovoltaic (PV), can be reduced, and the reliability of the power grid can be ensured. A better solution for RE utilization and planning based on digital technology is proposed in this paper. First, an operation mechanism of a multi-energy complementary power station is proposed based on the complementary characteristics of multiple energy sources in the power generation process. The current status and related issues of multi-energy complementary power stations are studied in this paper. Second, a two-layer model of optimization that integrates the complementary features of multiple energy sources and system planning requirements is developed in this paper based on the aforementioned power station operation mechanism. The two layers of the model are nested with each other to realize the operation of the power station. The upper model includes the RE utilization rate and the benefits of the energy storage (ES) system. The lower model includes the operating cost of the power station. The solution model includes the highest utilization rate of RE and the lowest operation cost. Finally, the simulation operation is performed based on the data on a provincial power grid. The model and operation strategy of the multi-energy complementary power station based on digital technology proposed by this paper are verified.

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Section: Introductionmentioning

confidence: 99%

A capacity optimization and scheduling scheme of a multi-energy complementary power station considering energy trading

Zou¹,

Zhang

Wei

2023

Front. Energy Res.

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“…Numerical experiments on such problems are developed in this paper. Other applications of quadratic projections emerge in the context of the security region of gas networks [26], or in local learning methods [9].…”

Section: Introductionmentioning

confidence: 99%

Projection onto quadratic hypersurfaces

Loïc¹,

Absil²,

Papavasiliou³

2022

Preprint

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We address the problem of projecting a point onto a quadratic hypersurface, more specifically a central quadric. We show how this problem reduces to finding a given root of a scalar-valued nonlinear function. We completely characterize one of the optimal solutions of the projection as either the unique root of this nonlinear function on a given interval, or as a point that belongs to a finite set of computable solutions. We then leverage this projection and the recent advancements in splitting methods to compute the projection onto the intersection of a box and a quadratic hypersurface with alternating projections and Douglas-Rachford splitting methods. We test these methods on a practical problem from the power systems literature, and show that they outperform IPOPT and Gurobi in terms of objective, execution time and feasibility of the solution.

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“…Being able to easily project onto a quadratic hypersurface, or quadric, would remove the need of this trade-off. Second, the projection onto a quadratic hypersurface is a direct requirement of some applications: either in 2D and 3D spaces (mostly in image processing and computer-aided design) [14,24,10], or in larger dimensional spaces such as the nonconvex economic dispatch [22], the security of the gas network [20], and local learning methods [6]. Finally, being able to project onto a quadratic hypersurface can be seen as the first step to project onto the intersection of quadratic hypersurfaces.…”

Section: Introductionmentioning

confidence: 99%

Quadproj: a Python package for projecting onto quadratic hypersurfaces

Loïc¹,

Absil²

2022

Preprint

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Quadratic hypersurfaces are a natural generalization of affine subspaces, and projections are elementary blocks of algorithms in optimization and machine learning. It is therefore intriguing that no proper studies and tools have been developed to tackle this nonconvex optimization problem. The quadproj package is a user-friendly and documented software that is dedicated to project a point onto a non-cylindrical central quadratic hypersurface.

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Security region of natural gas pipeline network system: Concept, method and application

Cited by 27 publications

References 29 publications

A capacity optimization and scheduling scheme of a multi-energy complementary power station considering energy trading

A capacity optimization and scheduling scheme of a multi-energy complementary power station considering energy trading

Projection onto quadratic hypersurfaces

Quadproj: a Python package for projecting onto quadratic hypersurfaces

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