Decentralized control and fair load-shedding compensations to prevent cascading failures in a smart grid

Shi, Benyun; Liu, Jiming

doi:10.1016/j.ijepes.2014.12.041

Cited by 43 publications

(35 citation statements)

References 33 publications

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“…This representation (sometimes with weighted links) is adequate for both high-voltage transmission grids (the vast majority of the reviewed contributions focus on high-voltage transmission power grids) and medium-and low-voltage distribution grids [117], as well as smart grids [10,64,114,115,118,119] (these two later classes of grids having being studied at a lesser extent).…”

Section: Complex Network Conceptsmentioning

confidence: 99%

“…The two metrics that have been found to work best are the "electrical degree centrality" and the "electrical betweenness centrality"; the "electrical degree centrality" C E D (i) of a node i hinges on the degree centrality given by Equation (10), and is given by…”

Section: Novel Electrical Metrics Inspired By Topological Metricsmentioning

confidence: 99%

“…This is the reason why the study of cascading failures in power grids (both in power transmission grids [2,8], distributed generation [9] and smart grids [10]) is currently a vibrant topic which is being profusely investigated [2][3][4][8][9][10][11][12][13][14][15]. Some historic blackouts-such as the recently one occurred in India on end July 2012 [15], those in the north-east area of US and Canada (August 14, 2003) [16][17][18], the one affecting a large portion of Italy (September 28,2003) and other countries in the European Union [19,20]-have been widely studied using both Complex Networks (CN) and Electrical Engineering (EE) tools [2,7,8,[12][13][14][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]<...>…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

et al. 2015

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This paper reviews the most relevant works that have investigated robustness in power grids using Complex Networks (CN) concepts. In this broad field there are two different approaches. The first one is based solely on topological concepts, and uses metrics such as mean path length, clustering coefficient, efficiency and betweenness centrality, among many others. The second, hybrid approach consists of introducing (into the CN framework) some concepts from Electrical Engineering (EE) in the effort of enhancing the topological approach, and uses novel, more efficient electrical metrics such as electrical betweenness, net-ability, and others. There is however a controversy about whether these approaches are able to provide insights into all aspects of real power grids. The CN community argues that the topological approach does not aim to focus on the detailed operation, but to discover the unexpected emergence of collective behavior, while part of the EE community asserts that this leads to an excessive simplification. Beyond this open debate it seems to be no predominant structure (scale-free, small-world) in high-voltage transmission power grids, the vast majority of power grids studied so far. Most of them have in common that they are vulnerable to targeted attacks on the most connected nodes and robust to random failure. In this respect there are only a few works that propose strategies to improve robustness such as intentional islanding, restricted link addition, microgrids and Energies 2015, 8 9212 smart grids, for which novel studies suggest that small-world networks seem to be the best topology.

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Section: Complex Network Conceptsmentioning

confidence: 99%

Section: Novel Electrical Metrics Inspired By Topological Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

et al. 2015

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“…In a broader approach, a "hybrid" grid is understood as the coexistence of largely interconnected grids with central control and smaller, decentralized areas that could be operated as micro-grids, in the case of emergency. In this context, small, distributed, smart grids as complex networks are on the rise [16,31,48,50], towards an electric grid characterized by a very considerable influence of prosumers, which will have a considerable influence on the electricity distribution infrastructure in the near future.…”

Section: The Benefits Of Adding Linksmentioning

confidence: 99%

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

et al. 2017

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Abstract:In this work, we describe an approach that allows for optimizing the structure of a smart grid (SG) with renewable energy (RE) generation against abnormal conditions (imbalances between generation and consumption, overloads or failures arising from the inherent SG complexity) by combining the complex network (CN) and evolutionary algorithm (EA) concepts. We propose a novel objective function (to be minimized) that combines cost elements, related to the number of electric cables, and several metrics that quantify properties that are beneficial for SGs (energy exchange at the local scale and high robustness and resilience). The optimized SG structure is obtained by applying an EA in which the chromosome that encodes each potential network (or individual) is the upper triangular matrix of its adjacency matrix. This allows for fully tailoring the crossover and mutation operators. We also propose a domain-specific initial population that includes both small-world and random networks, helping the EA converge quickly. The experimental work points out that the proposed method works well and generates the optimum, synthetic, small-world structure that leads to beneficial properties such as improving both the local energy exchange and the robustness. The optimum structure fulfills a balance between moderate cost and robustness against abnormal conditions. Our approach should be considered as an analysis, planning and decision-making tool to gain insight into smart grid structures so that the low level detailed design is carried out by using electrical engineering techniques.

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“…Removing the need for a leader agent may be preferable since it removes the central point of failure. Examples of leaderless MAS are presented in [13,14] where voltages are regulated by distributed generators acting as cooperative agents, in [15,16] where decentralized methods of optimal reactive power control are presented, in [17] where a distributed fair load shedding algorithm is presented, and in [18] where consumer agents cooperate to perform optimal load scheduling.…”

Section: Introductionmentioning

confidence: 99%

Asynchronous consensus for optimal power flow control in smart grid with zero power mismatch

Millar

Jiang

2018

J. Mod. Power Syst. Clean Energy

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The heterogeneous nature of smart grid components and the desire for smart grids to be scalable, stable and respect customer privacy have led to the need for more distributed control paradigms. In this paper we provide a distributed optimal power flow solution for a smart distribution network with separable global costs, separable non-convex constraints, and inseparable linear constraints, while considering important aspects of network operation such as distributed generation and load mismatch, and nodal voltage constraints. An asynchronous averaging consensus protocol is developed to estimate the values of inseparable global information. The consensus protocol is then combined with a fully distributed primal dual optimization utilizing an augmented Lagrange function to ensure convergence to a feasible solution with respect to power flow and power mismatch constraints. The presented algorithm uses only local and neighbourhood communication to simultaneously find the mismatch between power generation, line loss and loads, to calculate nodal voltages, and to minimize distributed costs, leading to a completely distributed solution of the global problem. An IEEE test feeder system with a reasonable number of nodes is used to illustrate the proposed method and efficiency.

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Decentralized control and fair load-shedding compensations to prevent cascading failures in a smart grid

Cited by 43 publications

References 33 publications

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

Asynchronous consensus for optimal power flow control in smart grid with zero power mismatch

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