The intermittent characteristics of microgrids (MGs) have motivated the development of energy management systems (EMSs) in order to optimize the use of distributed energy resources. In current studies, the implementation of an EMS followed by experimental-based analyses for both grid-tied and stand-alone MG operation modes is often neglected. Additionally, the design of a management strategy that is capable of preserving the storage device lifetime in battery-based MGs using a power gradient approach is hardly seen in the literature. In this context, this work presents the application of an EMS for battery-based MGs which is suitable for both grid-tied and stand-alone operation modes. The proposed EMS is formulated as an optimal power flow (OPF) problem using the-constraint method which is responsible for computing the current references used by the EMS to control the MG sources. In the optimization problem, the total generation cost is minimized such that the active power losses are kept within pre-established boundaries, and a battery management strategy based on power gradient limitation is included. Finally, the effectiveness of the proposed EMS is evaluated by two scenarios which enable detailed analyses and validation. The first considers a dispatchable and a non-dispatchable source, whereas the second a dispatchable source and a storage device. The experimental results showed that the proposed EMS is efficient in both operation modes and is also capable of smoothing the state of charge (SoC) behavior of the storage device. INDEX TERMS Battery power gradient, distributed generation, energy management system, microgrid, optimal power flow, storage device.
This study proposes a method for islanding detection in distributed generation systems, namely, hybrid fuzzy positive feedback (PF). The aim is to reduce the injection of disturbances during the grid-connected operation from the anti-islanding methods, particularly at the instant of load connection and, do not require adjustment of the PF gain and frequency filters. This method is designed from fuzzy inference rules and the frequency and voltage inputs are also taken into account in the design procedure. Since the classical active methods do not identify if the voltage variation arises from the islanding condition or from a power quality issue in the grid, the fuzzy PF enables the proposed methods to differentiate the islanding condition from other grid events. In contrast to classical methods that have a fixed PF gain, a dynamic fuzzy PF gain is obtained by means of the fuzzy inference rules. The classical active technique is compared with the proposed approach in terms of detection time and injected disturbances during the grid-connected operation. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed approach.
In this study, the authors propose a method to implement a low-cost hardware-in-the-loop (HIL) system for power converters and microgrids design, test and analysis. This approach uses a digital signal processor (DSP) Texas Instruments as the HIL core. All the differential equations of the power converters are solved in real-time by the DSP and displayed in the digital-to-analogue outputs. Three different converters are modelled in this study: boost converter, single-phase inverter connected to the grid and three-phase inverter connected to the grid. Experimental results are obtained and compared to the HIL response. These results were made triggering the real converter and the HIL with the same open-loop pulse width modulation signal, showing high fidelity between the digital models over the real systems. In a second moment, a microgrid is modelled in the proposed HIL and tested with a closed-loop controller. The experiments show that the proposed hardware supports time steps as low as 1 μs or 1 MHz update rate, depending on the model. The proposed technique has the potential to reduce testing time and cost, once commercial HIL devices such as Typhoon, dSPACE and RTDS have a significant cost, not affordable or available to all the research community
This study proposes an islanding detection method for distributed generation systems, namely frequency fuzzy positive feedback (FFPF).The goal is to reduce the injection of disturbances, from the anti-islanding methods, during the grid-connected operation, as well as standardise the PF gain, with no adjustments needed according to the type of loads. This method is designed from fuzzy inference rules and two inputs are also considered in the design procedure. Since the classical active methods do not identify whether the frequency variation arises from the islanding condition or from a power quality issue in the grid, the fuzzy PF enables the proposed method to differentiate the islanding condition from other grid events. In contrast to classical methods that have a fixed PF gain, a dynamic fuzzy gain that adapts to any type of load is obtained by means of the fuzzy inference rules. The classical active technique is compared with the proposed approach in terms of detection time and injected disturbances during the grid-connected operation. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed approach.
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