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Optimal Configuration of Energy Storage in Distributed Generation System

Author: TianJun
Tutor: XiaRuiHua
School: North China Electric Power University (Beijing)
Course: Proceedings of the
Keywords: Distributed Power Power prediction Least squares support vector machine Energy storage capacity optimization Hybrid energy storage control
CLC: TM61
Type: Master's thesis
Year: 2011
Downloads: 1006
Quote: 3
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Abstract


Distributed power grid to generate a lot of problems, the root cause lies in its effortless intermittent and randomness. Energy storage device has a fast throughput of power and flexibility of four-quadrant operation capacity in a distributed system, the introduction of energy storage aspects, not only to promote the application of renewable energy, but also improve the stability of distributed power run, to maintain system frequency and voltage stability, compensation random load fluctuations. Currently, most of the configuration of distributed generation storage system capacity and power selection starting from the economical point of view, or is determined by the cumulative error of the prediction, with little From the relationship between the predicted power and the output power of distributed power supply smoothing, to configure energy storage capacity and control storage charge and discharge is not perfect, and the coordination of the different types of energy storage systems controlled study. Firstly, on the basis of in-depth analysis of the main factors of the prediction accuracy of the impact of wind turbines, solar photovoltaic cells, Distributed Power established a predictive model of distributed power generation based on least squares support vector machine theory, and distributed power output randomness power and smooth power difference between the actual output of the distributed power storage compensation, instead of the traditional energy storage capacity configured to maintain fat balance electricity supply and demand compensation program, to improve the power of prediction accuracy, reduced energy storage installation capacity. Secondly, on the one hand, the proposed storage compensation actual PV output power and predicted power error, the local distribution network with distributed power trend curve in strict accordance with the plans to promote the coordination of power system daily generating capacity plan; On the other hand, storage compensation actual PV output power and smoothing power difference of the smoothing method of the skies photovoltaic power output variation rate constraints can get ahead of the accumulator charge-discharge control amount, reducing the impact on the power system of the photovoltaic output randomness. Once again, the combination of the complementary characteristics of the high power density of the super-capacitors and battery of high energy density, design a prediction based on the storage compensation power, and considering that the battery state of charge and super capacitor charge and discharge the voltage limits of the active control strategy. Prepared in MATLAB Distributed Power prediction algorithm to achieve the energy storage to improve the distributed power output prediction accuracy, the idea of ??reducing their own capacity; established in PSCAD hybrid energy storage system simulation model, validated storage capacity optimization configuration as well as the effectiveness of the hybrid storage controller design

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