The awareness capability of output power for renewable resources is essential for enhancing the resilience of power systems. Photovoltaic (PV) forecasting technology is an essential technology for increasing the operation efficiency and controllable resources for power systems after extreme natural events. Conventional Markov chain (MC) methods often ignore the time characteristics and the actual distribution of the PV output power sequence when making PV forecasts. This article proposes improved MC methods of equal quantity and clustering-based division methods. The methods can consider the interval distributions of the PV output power time series and select an hour as the time interval. As a sequence, the predicted power at the next moment can be closer to the expectation of the output power distributions. Such a method is combined with a similar day algorithm to calculate the forecast result. Case studies were conducted with one-year operation data from a 25-MW PV station. The results indicate that the proposed methods can effectively improve the accuracy of prediction results compared with traditional methods. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
With increasing levels of renewable energy in power systems, the coordination of different types of dispatchable resources, such as coal-fired power plants, hydropower plants, energy storage systems, and electric vehicles, has become more important than before. To optimally dispatch these operating units, the quality of the forecasting results becomes increasingly important for the operation of power systems. In this study, an ultra-short forecasting method was proposed for photovoltaic (PV) systems. It provided a forecast of the power output for the following 5 min using sky images obtained photographically in real time. The brightness of the key area was an important factor in determining the output power of the PV system. The output power was calculated using several different features extracted from the sky images. The brightness and other key features were then processed by a bidirectional long short-term memory network. The accuracy of the proposed PV forecasting method improved the accuracy of the forecast for the total power system. A testbed system was established to capture sky images in real time and verify the effectiveness of the proposed method.
Compared with AC systems, HVDC systems are more flexible and potentially contribute to enhancing system resilience. Currently, three types of HVDC technologies, LCC-HVDC (Line-commutated Current-sourced Converters, LCC), VSC-HVDC (Voltage Sourced Converter, VSC), and MMC-HVDC (Modular-Multilevel-Converter, MMC), are applied in practical projects. All types of HVDC systems can be applied to stabilize the system frequency of AC power systems and facilitate system recovery after extreme natural events. The operation characteristics, methods, and control strategies of different HVDC technologies for facilitating system operation are reviewed herein; it is indicated that HVDC technology is an effective solution for enhancing system resilience. Renewable resources, energy storage systems, and demand response devices can be coordinated well with HVDC systems. The frequency and voltage regulation ability of power systems and the black start ability can be enhanced by introducing HVDC systems into power systems. Several isolated AC power systems can be connected to HVDC systems. These AC systems can interact with other AC systems through HVDC systems by conforming to their operational characteristics and constraints. The resilience of these AC systems can be enhanced by these interactions. Additionally, related operation methods and control strategies will also be reviewed. JEL CLASSIFICATION Power electronics, electric power applicationsThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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