Compel (Vol. 23, 2004): Special Issue by Carpinelli G., Testa A.

By Carpinelli G., Testa A.

Specified factor: chosen papers from PMAPS 2002 -Conference on Probabilistic equipment utilized to energy structures, Naples 2002

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Compel (Vol. 23, 2004): Special Issue

Specified factor: chosen papers from PMAPS 2002 -Conference on Probabilistic equipment utilized to energy structures, Naples 2002

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In this case, a delayed exponential model has been suggested to simulate the aggregate demand, where the power consumption is initially constant, and then decreases exponentially to a stationary level – P0 (Agneholm and Daalder, 2000). In the following paragraphs, an enhanced aggregation method will be presented, mainly based on two premises: a detailed physically based load model and an improved stochastic aggregation technique. Elemental load models General description The first problem to be solved in physically-based modelling technologies (PBLM) is to model the load at the individual level.

And Pavella, M. (1993), “Advances in decision trees applied to power system security assessment”, IEE 2nd International Conference on Advances in Power System Control, Operation and Management, December 1993, Hong Kong. htm Probabilistic power system security analysis considering protection failures Probabilistic power system security analysis 35 Xingbin Yu and Chanan Singh Department of Electrical Engineering, Texas A&M University, Texas, USA Keywords Electric power systems, Reliability management Abstract This paper proposes a method of probabilistic security analysis of power systems including protection system failures.

The method described in this paragraph is called after the games of chance – the simplest random number generator. Sometimes, the term has been used synonymously with stochastic simulation, but the method applies to problems with no probabilistic content as well as those with a bright probabilistic structure (Ripley, 1987). In our case, the use of MC simulation arises to imitate or obtain the dynamic behaviour of a real aggregate system of perhaps a hundred of HVAC appliances with different but close parameters – a quasi-homogeneous load control group.

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