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EN
This paper proposes the usage of the fuzzy rule-based Bayesian algorithm to determine which residential appliances can be considered for the Demand Response program. In contrast with other related studies, this research recognizes both randomness and fuzziness in appliance usage. Moreover, the input data for usage prediction consists of nodal price values (which represent the actual power system conditions), appliance operation time, and time of day. The case study of residential power consumer behavior modeling was implemented to show the functionality of the proposed methodology. The results of applying the suggested algorithm are presented as colored 3D control surfaces. In addition, the performance of the model was verified using R squared coefficient and root mean square error. The conducted studies show that the proposed approach can be used to predict when the selected appliances can be used under specific circumstances. Research of this type may be useful for evaluation of the demand response programs and support residential load forecasting.
EN
Load profiles of residential consumers are very diverse. This paper proposes the usage of a continuous wavelet transform and wavelet coherence to perform analysis of residential power consumer load profiles. The importance of load profiles in power engineering and common shapes of profiles along with the factors that cause them are described. The continuous wavelet transform and wavelet coherence has been presented. In contrast with other studies, this research has been conducted using detailed (not averaged) load profiles. Presented load profiles were measured separately on working day and weekend during winter in two urban households. Results of applying the continuous wavelet transform for load profiles analysis are presented as coloured scalograms. Moreover, the wavelet coherence was used to detect potential relationships between two consumers in power usage patterns. Results of coherence analysis are also presented in a colourful plots. The conducted studies show that the Morlet wavelet is slightly better suitable for load profiles analysis than the Meyer’s wavelet. Research of this type may be valuable for a power system operator and companies selling electricity in order to match their offer to customers better or for people managing electricity consumption in buildings.
PL
W artykule przedstawiono wielowariantowe prognozy długoterminowe liczby pojazdów elektrycznych w Polsce. Na podstawie opracowanych prognoz wykonano analizę wzrostu rocznego zapotrzebowania na energię elektryczną w Polsce do roku 2025 wynikająca z eksploatacji pojazdów elektrycznych. Sformułowano wnioski końcowe.
EN
The article presents long-term multi-variant forecasts of the number of electric vehicles in Poland. On the basis of the forecasts, an analysis of the growth of the annual electricity demand in Poland by 2030 resulting from the operation of electric vehicles was performed. Final conclusions were formulated.
EN
The article deals with minimizing the costs of electricity supply at the preliminary network planning stage. It presents selected information on costs in power engineering. The facility location problem and Mixed-Integer Linear Programming has been also described. A computational example of the application of this method is presented to solve the problem of minimizing the costs of electricity supply between high voltage / 110 kV power stations and 110 kV urban stations.
PL
Artykuł dotyczy minimalizacji kosztów dostaw energii elektrycznej na etapie wstępnego planowania sieci. Przedstawiono w nim wybrane informacje dotyczące kosztów w elektroenergetyce. Opisano zagadnienie lokalizacji obiektów oraz metodę optymalizacji mieszanej całkowitoliczbowej liniowej. Zaprezentowano przykład obliczeniowy zastosowania tych metod do rozwiązania problemu zminimalizowania kosztów dostaw energii elektrycznej pomiędzy stacjami NN / 110 kV a stacjami miejskimi 110 kV.
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