Contributed Session Mon.2.MA 550

Monday, 13:15 - 14:45 h, Room: MA 550

Cluster 18: Optimization in energy systems [...]

Network operation under failures and losses


Chair: Maicon Coelho Evaldt



Monday, 13:15 - 13:40 h, Room: MA 550, Talk 1

Richard L. Chen
Survivability-constrained generation unit commitment with post-contingency corrective recourse

Coauthors: Amy Cohn, Neng Fan, Ali Pinar, Jean-Paul Watson


We consider the problem of optimizing generation unit commitment under load uncertainty while ensuring N-k-ε survivability criterion. This survivability criterion is a generalization of the well-known N-k criterion, and it requires that at least (1-εk) fraction of the total demand is met even after failures of any k system components, for all k=0,1,·s,k\textmd{max}. We present a mixed-integer formulation of this problem that takes into account both transmission and generation component failures. We propose a cutting plane algorithm that can avoid combinatorial explosion in the number of contingencies that needs to be considered, by seeking vulnerabilities in intermediary solutions and constraining the search space accordingly. Our empirical studies on modified instances from the IEEE test systems showed the effectiveness of our proposed techniques.



Monday, 13:45 - 14:10 h, Room: MA 550, Talk 2

Jose Vicente Canto dos Santos
New genetic algorithms for contingencies selection in electric power systems

Coauthor: Iverson F. Costa


The importance of a reliable supply of electricity to the industrial society is unquestionable. In a control center of an electrical utility, an important computational task is the security analysis. In this task, contingency is the output of operation of an equipment and contingencies selection is the determination of the most severe contingencies for the system. Even with the current technological advances, an analysis in real time of all possible failures in a large grid is impractical. In this work we present a method to perform efficiently the selection of multiple contingencies. The problem is modeled as a combinatorial optimization problem, and solved by genetic algorithms that make efficient the screenings of the associated non-convex and non-linear search spaces. We developed a robust method, which considers aspects of power flow and voltage that was tested with an IEEE test system and with a large real network, considering double outages of branches. Excellent results with levels of accuracy close to 100,%, when compared with an exact method, obtained with scans of reduced portions of search spaces are presented.



Monday, 14:15 - 14:40 h, Room: MA 550, Talk 3

Maicon Coelho Evaldt
Optimal allocation of equipment for monitoring and identification of commercial losses in distribution networks

Coauthors: Luis Basilio, Rodrigo M. de Figueiredo, José Vicente C. dos Santos, Márcio Refael Stracke


In 2011, the Brazilian National Agency of Electrical Energy estimated that economic losses due to fraud in distribution networks are around US. 4.6 billion a year in Brazil. This paper focuses on this problem and presents a system for monitoring and identification of commercial losses. The proposed solution is based on low cost power meters installed at strategic points of the network, communicating by wireless with a control central. Inconsistences in billing are identified based on the network model and data received from power meters. A linear programming method is employed to define the areas of installation that produce the best coverage results, considering distance, number of consumers and power demand. Graphic and mathematic tools PSL DMS, GEPath and Google Earth are employed to represent the grid under test. The methodology is applied in a real network of 4 km of extension. Economic viability and payback analysis for the proposed solution are also presented. The main contribution of this work, for electrical utilities, is a reliable indication of commercial losses in each monitored segment of the distribution network.


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