This paper concerns very-short-term (5-Minute) forecasting of photovoltaic power generation. Developing the methods useful for this type of forecast is the main aim of this study. We prepared a comprehensive study based on fragmentary time series, including 4 full days, of 5 min power generation. This problem is particularly important to microgrids’ operation control, i.e., for the proper operation of small energy micro-systems. The forecasting of power generation by renewable energy sources on a very-short-term horizon, including PV systems, is very important, especially in the island mode of microgrids’ operation. Inaccurate forecasts can lead to the improper operation of microgrids or increasing costs/decreasing profits for microgrid operators. This paper presents a short description of the performance of photovoltaic systems, particularly the main environmental parameters, and a very detailed statistical analysis of data collected from four sample time series of power generation in an existing PV system, which was located on the roof of a building. Different forecasting methods, which can be employed for this type of forecast, and the choice of proper input data in these methods were the subject of special attention in this paper. Ten various prognostic methods (including hybrid and team methods) were tested. A new, proprietary forecasting method—a hybrid method using three independent MLP-type neural networks—was a unique technique devised by the authors of this paper. The forecasts achieved with the use of various methods are presented and discussed in detail. Additionally, a qualitative analysis of the forecasts, achieved using different measures of quality, was performed. Some of the presented prognostic models are, in our opinion, promising tools for practical use, e.g., for operation control in low-voltage microgrids. The most favorable forecasting methods for various sets of input variables were indicated, and practical conclusions regarding the problem under study were formulated. Thanks to the analysis of the utility of different forecasting methods for four analyzed, separate time series, the reliability of conclusions related to the recommended methods was significantly increased.

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.

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.

Artykuł proponuje wykorzystanie koherencji falkowej do analizy zjawiska utraty synchronizmu przez generator synchroniczny na skutek wystąpienia zwarcia w sieci przesyłowej. Na podstawie badań symulacyjnych oraz użycia koherencji falkowej zbadano związki pomiędzy różnymi wielkościami elektrycznymi i mechanicznymi

This paper proposes the use of wavelet coherence to conduct a study on the im-pact of renewable energy sources' generation on voltage losses in lines. The case study of the low-voltage distribution grid equipped with seven photovoltaic panels and one wind turbine was examined to demonstrate the functionality of the proposed methodology. Based on the simulation studies, the concept of how time-varying generation from the wind turbine or photovoltaic panels can affect the voltage losses in the selected power lines over one month was discussed. The analysis results were visualized using wavelet coherence delay plots. In contrast to other related studies, this research also includes additional plots like scale-averaged coherence, scale-averaged phase shift, time-averaged phase shift, and time-averaged coherence. The conducted studies extend and enrich the current view on the im-pact of renewable energy sources' generation on the power grid. The use of wavelet coher-ence can also help highlight additional information that may be ignored or overlooked, es-pecially in fast-paced systems. This kind of research may be useful for supplementing the results of load flow calculations with additional information on the voltage losses for dis-tribution grid operators. It can be considered a general tool for conducting a more in-depth analysis of the influence of renewable energy sources on the power grid.