ANALYSIS OF INDUSTRIAL MICROGRID POWER CURVES BASED ON THE THEORY OF STOCHASTIC VARIABLES FOR CONTROL SYSTEM DEVELOPMENT AND COMPONENT SIZING

Design and control of microgrids require a wide range of considerations and information. One main issue is the sizing and operation strategy of storage units with respect to the huge variation in several system conditions. In addition to grid coupling conditions, the power profile is a key feature that has to be included in these considerations. Particularly in the industrial environment the consumption of loads fluctuates greatly and the application of standard load profiles (which use average values) is impracticable. This paper presents a stochastic approach for analyzing the power curves. Common methods for modeling stochastic variables are compared and assessed based on pros and cons related to the presented field of application. The focus of this paper is not prediction but visualization and stochastics-based statements that aid in assessing power curves and dimension components of microgrids.


​​​​​​Content

  1. Introduction
  2. Preliminary Considerations
  3. Comparison of Modeling Methods
    1. Parameter Estimation of an Assumed Density Function
    2. Determination of Frequency Distribution with Quantization
    3. Kernel Density Estimation
    4. Assessment of the Methods
  4. Stochastic Power Profile
  5. Statistical Statements
  6. Conclusion
  7. Acknowledgement

White Paper Analysis of Industrial Microgrid Power Curves Based on the Theory of Stochastic Variables for Control System Development and Component Sizing

Authors


S. Kempen
AEG Power Solutions GmbH Emil-Siepmann-Str. 32 D-59581 Warstein-Belecke, Germany

T. Vogt, A. Peters, N. Fröhleke, J. Böcker
Power Electronics and Electrical Drives University of Paderborn, D-33095 Paderborn, Germany, vogt@lea.upb.de