Meshed distribution network vs reinforcement to increase the distributed generation connection

Alvarez‐Hérault, Marie‐Cécile; N’Doye, N.; Gandioli, Camille; Hadjsaïd, Nourédine; Tixador, Pascal

doi:10.1016/j.segan.2014.11.001

Cited by 46 publications

(33 citation statements)

References 18 publications

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“…It is usually subjected to same issues and more or less same requirements as LDN. It has advantages of comparatively higher reliability, DG penetration, better voltage response (for DG critical voltage mode) and comparatively fewer power losses compared to LDN from objective viewpoint [74,75]. However, complex fault traceability makes is more susceptible to faults and early recovery from reliability viewpoint in traditional planning methods [76].…”

Section: Mesh Distribution Network (Mdn)mentioning

confidence: 99%

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Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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Smart grids (SGs), as an emerging grid modernization concept, is spreading across diverse research areas for revolutionizing power systems. SGs realize new key concepts with intelligent technologies, maximizing achieved objectives and addressing critical issues that are limited in conventional grids. The SG modernization is more noticeable at the distribution grid level. Thus, the transformation of the traditional distribution network (DN) into an intelligent one, is a vital dimension of SG research. Since future DNs are expected to be interconnected in nature and operation, hence traditional planning methods and tools may no longer be applicable. In this paper, the smart distribution network (SDN) concept under the SG paradigm, has presented and reviewed from the planning perspective. Also, developments in the SDN planning process have been surveyed on the basis of SG package (SGP). The package presents a SDN planning foundation via major SG-enabling technologies (SGTF), anticipated functionalities (SGAF), new consumption models (MDC) as potential SDN candidates, associated policies and pilot projects and multi-objective planning (MOP) as a real-world optimization problem. In addition, the need for an aggregated SDN planning model has also been highlighted. The paper discusses recent notable related works, implementation activities, various issues/challenges and potential future research directions; all aiming at SDN planning.

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Section: Mesh Distribution Network (Mdn)mentioning

confidence: 99%

“…The normal topologies in MDN include weakly mesh or all mesh [77,78]. The former mode is realized with topologies attain by closing a selective number of TS, whereas the later mode works under normal operation by closing all TS [12,14,26,75].…”

Section: Mesh Distribution Network (Mdn)mentioning

confidence: 99%

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

et al. 2017

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“…On the one hand, this is the most straightforward and robust optimisation technique available as it is simple to understand (and easy to explain to DNOs, regulators and other actors) and guarantees finding the optimal solution under all conditions (even for complex mixed integer, nonlinear and nonconvex problems). On the other hand, this approach tends to be overlooked (particularly for academic applications) due to its simple nature and because it can be computationally expensive or even infeasible in most applications [41] [42]. In this light, the recursive function has been designed to significantly reduce the computational costs of the search by systematically terminating all instances that face an infeasible investment strategy (e.g., in this work, whenever the network fails to meet P2/6 recommendations), which also prevents them from spreading.…”

Section: "Optimisation" Recursive Algorithmmentioning

confidence: 99%

Practical recursive algorithms and flexible open-source applications for planning of smart distribution networks with Demand Response

Ceseña

Mancarella

2016

Sustainable Energy, Grids and Networks

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-Distribution networks are currently undergoing fundamental changes due to the rise of smart solutions such as for instance Demand Response (DR), which increases network complexity and challenges the adequacy of traditional planning practices. This calls for the use of suitable planning methodologies. However, the planning problem may be too cumbersome for most commercial software tools, or may lead to complex bespoke optimisation models that may not be easy to use by network planners. In this light, this work proposes a recursive function that can be used in practical algorithms for planning of smart distribution networks. The recursive function can emulate business-as-usual planning practices and further optimise them, including DR options as potential substitutes for network reinforcement. Several case studies based on real UK networks highlight the robustness and flexibility of the proposed algorithms to address different problems, including uncertainty analysis and risk management. The results clearly show that the proposed tool leads to increased economic and social benefits, particularly when optimising investment strategies considering smart DR solutions. The model is herein distributed open-source as accompanying material to this paper with the aim of encouraging new practices required for smart distribution network planning beyond the traditional academic applications.

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“…Several works have been developed to investigate reinforcement issues in radial and meshed distribution level and to provide adequate simulation tools and methods. Alvarez-Herault et al [3] demonstrated the benefits of meshing the network instead of reinforcing it. Novoselnik et al [4] provided a procedure to improve networks' performance taking into consideration the advantage of its meshed development.…”

Section: Introductionmentioning

confidence: 99%

On the Determination of Meshed Distribution Networks Operational Points after Reinforcement

2019

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This paper proposes a calculation algorithm that creates operational points and evaluates the performance of distribution lines after reinforcement. The operational points of the line are probabilistically determined using Monte Carlo simulation for several objective functions for a given line. It is assumed that minimum voltage at all nodes has to be balanced to the maximum load served under variable distributed generation production, and to the energy produced from the intermittent renewables. The calculated maximum load, which is higher than the current load, is expected to cover the expected needs for electric vehicles charging. Following the proposed operational patterns, it is possible to have always maximum line capacity. This method is able to offer several benefits. It facilitates of network planning and the estimation of network robustness. It can be used as a tool for network planners, operators and large users. It applies to any type of network including radial and meshed.

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Meshed distribution network vs reinforcement to increase the distributed generation connection

Cited by 46 publications

References 18 publications

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective

Practical recursive algorithms and flexible open-source applications for planning of smart distribution networks with Demand Response

On the Determination of Meshed Distribution Networks Operational Points after Reinforcement

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