Abstract:With a higher penetration of distributed generation in the power system, the application of microgrids is expected to increase dramatically in the future. This paper proposes a novel method to design optimal droop coefficients of dispatchable distributed energy resources for a microgrid in the Energy Internet considering the volatility of renewable energy generation, such as wind and photovoltaics. The uncertainties of renewable energy generation are modeled by a limited number of scenarios with high probabilities. In order to achieve stable and economical operation of a microgrid that is also suitable for plug-and-play distributed renewable energy and distributed energy storage devices, a multi-objective optimization model of droop coefficients compromising between operational cost and the integral of time-weighted absolute error criterion is developed. The optimization is solved by using a differential evolution algorithm. Case studies demonstrate that the economy and transient behavior of microgrids in the Energy Internet can both be improved significantly using the proposed method.
The contradiction between the unbalanced geographical distribution and the electricity consumption of energy distribution determines the long-distance; high-capacity transmission will be an important feature in the future development of the electric power industry. Based on GPS technology, WAN synchronized phases measurement technology has provide real-time dynamic information to the system. However, continuous improvement of the PMU distribution and the real-time monitoring of the grid by WAMS system increasingly comprehensive, massive measurement data have been brought about. Studying the measured data from various trips; it meets the 3V (volume, variety, velocity) characteristics of big data. This paper presents big massive data processing methods to solve the problem with various angles, and its feasibility and necessity.
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