This study proposes a collaborative optimization configuration scheme of wind-solar ratio and energy storage based on the complementary characteristics of wind and light. On the premise of maintaining the stability of...
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The power oscillation induced by the large-scale integration of wind power into the power grid has become one of the important issues affecting the safe and stable operation of the power grid. Aiming at the dynamic in...
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Aiming at the problem of getting low resolution image and blurred image during unmanned aerial vehicle (UAV) inspection, a super-resolution reconstruction algorithm based on very deep network super resolution (VDSR) i...
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The ice disaster has brought many adverse effects on the power transmission system, which is mainly studied from the transmission line failure rate perspective. Strong winds often accompany the ice disaster weather, t...
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This paper proposes a new disturbance localization method for powersystem based on group sparse representation of compressed sensing. Based on the analysis of disturbance characteristics of powersystem, the sparse d...
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As errors in point forecasts of wind power are unavoidable, interval forecasts can adequately describe the uncertainty in wind power and thus provide further guidance to dispatchers in their decision making. Current i...
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As errors in point forecasts of wind power are unavoidable, interval forecasts can adequately describe the uncertainty in wind power and thus provide further guidance to dispatchers in their decision making. Current interval prediction methods are still incomplete in terms of tapping into the physical variability of wind power, especially for the specific time scale of the ultra-short term. This paper therefore proposes a new framework for interval forecasting of ultra-short-term wind power that incorporates the power fluctuation process. Firstly, a fluctuating process of wind power series is defined and a Kalman-SOM method for clustering the fluctuating processes of wind power is constructed. Secondly, a quantile regression forest interval prediction model is constructed for multiple fluctuation processes for ultra-short-term time scales. Finally, the effectiveness of the overall framework is validated at a wind farm in Jilin Province, China. Compared with the traditional interval prediction method. The interval bandwidth is reduced by 0.86% on average, and the interval coverage is increased by 1.4% on average. The results demonstrate the effectiveness and feasibility of the method in this paper.
Aiming at the problem of heavy overload in the distribution station area during the peak period of energy consumption caused by intermittent loads such as agricultural motor wells, the mobile energy storage technology...
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Against the backdrop of the increasing proportion of new energy generation, pumped storage, as the main energy storage method, face problems of low utilization and poor economic benefits. To improve the enthusiasm and...
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With the incorporation of more renewableenergy sources, distribution networks are shifting from passive to active. The enhanced coupling of transmission and distribution networks is enhanced and bidirectional tides a...
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High percentage of photovoltaic gain connect to the wire line, so that the electricity grid from power distribution of the receiving end of the network into a set of production, storage, distribution of multi-source c...
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