5 resultados para distributed control and estimation

em Instituto Politécnico do Porto, Portugal


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In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

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The purpose of the present work is to determine the antioxidant capacity (AC) of 27 commercial beers. The AC indicates the degree of protection of a certain organism against oxidative damage provoked by reactive oxygen and nitrogen species. Assays were carried out by the following methods: (i) total radical trapping antioxidant parameter (TRAP); (ii) trolox equivalent antioxidant capacity (TEAC); (iii) trolox equivalent antioxidant capacity (DPPH); (iv) ferric-ion reducing antioxidant parameter (FRAP); (v) cupric reducing antioxidant capacity (CUPRAC); (vi) oxygen radical absorbance capacity (ORAC). Ascorbic acid (AA), gallic acid (GA) and trolox (TR) were used as standards. All beers showed antioxidant power, but a wide range of ACs was observed. The effect of several factors upon these differences was studied. Statistical differences were found between ACs of beers of different colours. ORAC method provided always higher experimental ACs, of significant statistical differences to other assays.

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Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

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Underwater acoustic networks can be quite effective to establish communication links between autonomous underwater vehicles (AUVs) and other vehicles or control units, enabling complex vehicle applications and control scenarios. A communications and control framework to support the use of underwater acoustic networks and sample application scenarios are described for single and multi-AUV operation.

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It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation.