Abstract
Fractional order proportional-integral-derivative(FOPID) controllers have attracted increasing attentions recently due to their better control performance than the traditional integer-order proportional-integral-derivative (PID) controllers. However, there are only few studies concerning the fractional order control of microgrids based on evolutionary algorithms. From the perspective of multi-objective optimization, this paper presents an effective FOPID based frequency controller design method called MOEO-FOPID for an islanded microgrid by using a Multi-objective extremal optimization (MOEO) algorithm to minimize frequency deviation and controller output signal simultaneously in order to improve finally the efficient operation of distributed generations and energy storage devices. Its superiority to nondominated sorting genetic algorithm-II (NSGA-II) based FOPID/PID controllers and other recently reported single-objective evolutionary algorithms such as Kriging-based surrogate modeling and real-coded population extremal optimization-based FOPID controllers is demonstrated by the simulation studies on a typical islanded microgrid in terms of the control performance including frequency deviation, deficit grid power, controller output signal and robustness.
Highlights
Microgrids have been widely considered as a building block of future smart grid [1], so there have been many real islanded microgrid systems developed for rural and distant areas [2,3,4,5]
This paper proposes a multi-objective extremal optimization (MOEO)-based fractional order proportional-integral-derivative (FOPID) method called Multi-objective extremal optimization (MOEO)-FOPID for the fractional order frequency control of an islanded microgrid in order to improve the efficient operation of distributed generations and energy storage devices
MOEO-FOPID was proposed for an islanded microgrid, by using a multi-objective extremal optimization algorithm to improve the efficient operation of distributed generations and energy storage devices
Summary
Microgrids have been widely considered as a building block of future smart grid [1], so there have been many real islanded microgrid systems developed for rural and distant areas [2,3,4,5]. How to control the voltage and frequency of a microgrid in an islanded model has been one of the major challenges for researchers recently [6], because it is often more difficult than—in grid-connected mode. When the microgrids operate in the grid-connected mode, the control of voltage and frequency depends on the regulation of the main utility grid. While the microgrids are in the islanded mode, the distributed components should regulate the stochastic and determinate fluctuation caused by some distributed generations, e.g., wind turbine generator and solar photovoltaics, and demand-side loads. Some frequency control methods for microgrids or hybrid power systems have been proposed by using traditional proportional-integral-derivative (PID) controllers or robust. A hybrid method by combining particle swarm optimization (PSO)
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