Suppression of Second-Order Harmonic Current for Droop-Controlled Distributed Energy Resource Converters in DC Microgrids

Droop-controlled distributed energy resource converters in dc microgrids usually show low output impedances. When coupled with ac systems, second-order harmonics typically appear on the dc-bus voltage, causing significant harmonic currents at the converters resource side. This paper shows how to reduce such undesired currents by means of notch filters and resonant regulators included in the converters control loops. The main characteristics of these techniques in terms of harmonic attenuation and stability are systematically investigated. In particular, it is shown that the voltage control-loop bandwidth is limited to be below twice the line frequency to avoid instability. Then, a modified notch filter and a modified resonant regulator are proposed, allowing to remove the constraint on the voltage loop bandwidth. The resulting methods (i.e., the notch filter, the resonant regulator, and their corresponding modified versions) are evaluated in terms of output impedance and stability. Experimental results from a dc microgrid prototype composed of three dc-dc converters and one dc-ac converter, all with a rated power of 5kW, are reported

Plug and Play DC-DC Converters for Smart DC Nanogrids with Advanced Control Ancillary Services

This paper gives a general view of the control possibilities for dc-dc converters in dc nanogrids. A widely adopted control method is the droop control, which is able to achieve proportional load sharing among multiple sources and to stabilize the voltage of the dc distribution bus. Based on the droop control, several advanced control functions can be implemented. For example, power-based droop controllers allow dc-dc converters to operate with power flow control or droop control, whether the hosting nanogrid is operating connected to a strong upstream grid or it is operating autonomously (i.e., islanded). Converters can also be equipped with various supporting functions. Functions that are expected to play a crucial role in nanogrids that fully embrace the plug-and-play paradigm are those aiming at the monitoring and tuning of the key performance indices of the control loops. On-line stability monitoring tools respond to this need, by continuously providing estimates of the stability margins of the loops of interest; self- tuning can be eventually achieved on the basis of the obtained estimates. These control solutions can significantly enhance the operation and the plug-and-play feature of dc nanogrids, even with a variable number of hosted converters. Experimental results are reported to show the performance of the control approaches

Analysis of an On-Line Stability Monitoring Approach for DC Microgrid Power Converters

An online approach to evaluate and monitor the stability margins of dc microgrid power converters is presented in this paper. The discussed online stability monitoring technique is based on the Middlebrook's loop-gain measurement technique, adapted to the digitally controlled power converters. In this approach, a perturbation is injected into a specific digital control loop of the converter and after measuring the loop gain, its crossover frequency and phase margin are continuously evaluated and monitored. The complete analytical derivation of the model, as well as detailed design aspects, are reported. In addition, the presence of multiple power converters connected to the same dc bus, all having the stability monitoring unit, is also investigated. An experimental microgrid prototype is implemented and considered to validate the theoretical analysis and simulation results, and to evaluate the effectiveness of the digital implementation of the technique for different control loops. The obtained results confirm the expected performance of the stability monitoring tool in steady-state and transient operating conditions. The proposed method can be extended to generic control loops in power converters operating in dc microgrids

Making Multimodal Generation Easier: When Diffusion Models Meet LLMs

We present EasyGen, an efficient model designed to enhance multimodal understanding and generation by harnessing the capabilities of diffusion models and large language models (LLMs). Unlike existing multimodal models that predominately depend on encoders like CLIP or ImageBind and need ample amounts of training data to bridge the gap between modalities, EasyGen is built upon a bidirectional conditional diffusion model named BiDiffuser, which promotes more efficient interactions between modalities. EasyGen handles image-to-text generation by integrating BiDiffuser and an LLM via a simple projection layer. Unlike most existing multimodal models that are limited to generating text responses, EasyGen can also facilitate text-to-image generation by leveraging the LLM to create textual descriptions, which can be interpreted by BiDiffuser to generate appropriate visual responses. Extensive quantitative and qualitative experiments demonstrate the effectiveness of EasyGen, whose training can be easily achieved in a lab setting. The source code is available at https://github.com/zxy556677/EasyGen

Robust Localization Algorithm Based on Best Length Optimization for Wireless Sensor Networks

In this paper, a robust range-free localization algorithm by realizing best hop length optimization is proposed for node localization problem in wireless sensor networks (WSNs). This algorithm is derived from classic DV-Hop method but the critical hop length between any relay nodes is accurately computed and refined in space WSNs with arbitrary network connectivity. In case of network parameters hop length between nodes can be derived without complicated computation and further optimized using Kalman filtering in which guarantees robustness even in complicated environment with random node communication range. Especially sensor fusion techniques used has well gained robustness, accuracy, scalability, and power efficiency even without accurate distance or angle measurement which is more suitable in nonlinear conditions and power limited WSNs environment. Simulation results indicate it gained high accuracy compared with DV-Hop and Centroid methods in random communication range conditions which proves it gives characteristic of high robustness. Also it needs relatively little computation time which possesses high efficiency. It can well solve localization problem with many unknown nosed in the network and results prove the theoretical analysis