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Rasolomampionona D.D.,Instytucie Elektroenergetyki Politechniki Warszawskiej | Robak S.,Instytucie Elektroenergetyki Politechniki Warszawskiej | Chmurski P.,Centrum Zastosowan Zaawansowanych Technology Sp. Z O.O. | Tomasik G.,Centrum Zastosowan Zaawansowanych Technology Sp. Z O.O.
Rynek Energii | Year: 2010

The submitted paper presents a short review of presently used DSR (Demand Side Response), enclosing characteristic models of different DSR programs installed and run by different power entities in different countries. This review also includes the concept of resource integrated management, the objective of which is the supply of electric power at minimal social costs. Moreover some subtle differences of defining me DSR actions by different worldwide power entities are presented. Also the legal aspect used for facilitating the DSR implementation in power system control is analysed.

In the paper two applications of particle swarm optimization (PSO) algorithm for weights values optimization of artificial neural network are presented. First application consists in optimization of weights values only with the PSO in such a way to minimize forecast error. Second application aids this process using classical back propagation algorithm. The main purpose of this hybrid system is forecasting of electric energy load for distribution company. For this task efficiency tests were done. Conclusions concerning properties of proposed method and ways of development are presented.

Parol M.,Instytucie Elektroenergetyki Politechniki Warszawskiej
Rynek Energii | Year: 2011

Market and regulatory issues of connection and operation of low voltage microgrids have been described in the paper. Benefits from microgrid operation to electricity utility have been characterized, i.e. avoided costs of electricity utility have been described. Then, system services, which can be provided by microgrid for distribution network operator have been characterized, both in normal operation states and in fault states. In further part of the paper, regulatory issues concerning connection of low voltage microgrids to distribution network of electricity utility have been presented. At the end of the paper summary of the described issues has been presented.

This paper deals with a new original method of spatial electric load forecasting for urban agglomerations. A bottom-up approach is proposed which does not take into account the global exogenous varieties. Only local exogenous varieties affecting the spatial electric load distribution in a forecasting model are identified. For this purpose a technique of fuzzy cellular automata is used. The forecasting model as well as identified model parameters have been presented. Additionally, a test prediction of spatial electric load forecasting has been carried out in order to verify the proposed forecasting method.

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