Primary Frequency Regulation Based on Deloaded Control, ANN, and 3D-Fuzzy Logic Controller for Hybrid Autonomous Microgrid

Abstract

This study proposes an original approach to improve the Primary Frequency Regulation (PFR) of an Autonomous Microgrid (A-μG). The Wind Turbine Generator (WTG) is considered to be a principal resource. Due to the wind variability and intermittency, Diesel Generator (DG) is incorporated to meet the load peak. However, to reduce the system maintenance and fuel consumption and to increase the microgrid efficiency, Battery Energy Storage System (BESS) is added. Hence, to meet the load demand, the A-μG relies on the strengths of each technology. Among these various system components, an Intelligent Energy Management System (IEMS) is built in two stages to manage the μG. First, the deloaded method is adopted to use the rotational kinetic energy, as a reserve, when the wind speed is low or the power consumption is high. Second, aiming at enhancing the dynamic of deloaded WTG and the DG participation, two intelligent-based control strategies, Artificial Neural Network (ANN) and three-dimensional Fuzzy Logic-Frequency Regulation (3D-FL-FR), are designed and compared. Different case studies and circumstances have been performed to test the efficiency of the adopted IEMS. The performances of both approaches have been proven in terms of guaranteeing the power balance of the A-μG and improving the primary frequency regulation. Indeed, with 3D-FL-FR combined with the DC, the frequency deviation is −2.8%, while the ANN control with DC records a frequency deviation of −3.6%. Therefore, both intelligent based controllers comply with the IEEE Std 1547-2003, even under large load demand and wind power fluctuation. However, the comparison results reveal the supremacy of the 3D-FL-FR against the ANN-based IEMS.

De-Loaded Technique Enhanced by Fuzzy Logic Controller to Improve the Resilience of Microgrids Based on Wind Energy and Energy Storage Systems

“…By regulating the ARS, the WT is able to generate an optimal mechanical power, P m , as given in [13,14]:…”

“…According to [13,21], for each ARS, the reference of the de-loaded WTG-power, P ref , is calculated as indicated in (11):…”

Analysis of inertia, damping, and synchronization characteristics in grid-connected photovoltaic systems with fuzzy logic control

“…Future plans involve experimental validation and integrating energy optimization into the system. The study [9] suggested a new way to improve a small self-sufficient power grid using wind and diesel generators, along with batteries for efficiency. An intelligent energy management system (IEMS) was made in two steps: first, using extra energy when wind is low or demand is high, and second, using smart controls to boost performance.…”

Frequency control of the islanded microgrid including energy storage using soft computing

“…In other words, a controller with a linear model operates in a linear range, but due to the capabilities of ANN in solving problems with high mathematical complexity and the high power of these networks in estimating functions, designers are encouraged to use these networks in the design of self-tuning controllers to control nonlinear processes 23 . In [24][25][26][27] , a PI-controller with a hybrid ANN form is used as a direct adaptive controller to control the microgrid frequency, in which PSO and fuzzy algorithms are used to optimize ANN coefficients and their rapid training.…”