Management of Voltage Flexibility from Inverter-Based Distributed Generation Using Multi-Agent Reinforcement Learning

The increase in the use of converter-interfaced generators (CIGs) in today’s electrical grids will require these generators both to supply power and participate in voltage control and provision of grid stability. At the same time, new possibilities of secondary QU droop control in power grids with a large proportion of CIGs (PV panels, wind generators, micro-turbines, fuel cells, and others) open new ways for DSO to increase energy flexibility and maximize hosting capacity. This study extends the existing secondary QU droop control models to enhance the efficiency of CIG integration into electrical networks. The paper presents an approach to decentralized control of secondary voltage through converters based on a multi-agent reinforcement learning (MARL) algorithm. A procedure is also proposed for analyzing hosting capacity and voltage flexibility in a power grid in terms of secondary voltage control. The effectiveness of the proposed static MARL control is demonstrated by the example of a modified IEEE 34-bus test feeder containing CIGs. Experiments have shown that the decentralized approach at issue is effective in stabilizing nodal voltage and preventing overcurrent in lines under various heavy load conditions often caused by active power injections from CIGs themselves and power exchange processes within the TSO/DSO market interaction.

Metrological aspects of an automated method for measuring electrophysical parameters of soft magnetic materials

The structure of an automated system for measuring magnetic-hysteresis loops, normal magnetization curve, magnetic permeability with an error of no more than ± 1% is proposed. The measuring principle is based on the inferential measurements of the magnetic induction and the coercive force by integrating the secondary voltage and the excitation current. As a result of metrological analysis, an increase in the measurements accuracy is achieved both by improving the hardware implementation and calibrating the measuring channels, by introducing a correction for the systematic component of the error.

Modelling and Control Design for Full Bridge DC-DC Converter

In this paper, modeling and analysis of full bridge dc-dc converter is present using state space averaging technique. Isolated dc-dc converter is widely used in power applications. Mainly full bridge dc-dc converter is used where high power and high voltage required. The transformer is used here to produce a higher voltage in secondary voltage side. PI controller is used to stabilize the output of the converter. Simulation is done for getting different outputs by giving same input. To observe the stability and transient response results are obtained using matlab simulink. Keywords: Full Bridge, DC-DC converter, state space, isolated, transient response.

Distributed Secondary Voltage Control for DC Microgrids with Consideration of Asynchronous Sampling

This paper studies the distributed secondary control of DC microgrids (MGs) in the case of asynchronous sampling, including both the stability condition and accurate consensus algorithm. The asynchrony means that the update actions of each distributed generation (DG) based on the local information and information received from neighbors are independent of the actions of others at sampled discrete times, which would cause deviation from the accurate convergence and even lead to instability in the worst case. First, a small-signal model of MG installed with secondary voltage control is established to include the individual sampling periods. A stability criterion based on the periodic continuity of sampling instant offset is thus formulated to reveal a stability mapping of multiple sampling. By quantifying the accuracy deviations caused by the asynchrony, an improved ratio consensus strategy is proposed that allows the deviation to be estimated accurately via an auxiliary signal and compensated with respect to the eventual equilibrium to produce an exact solution. Our approach customizes the stability and accuracy for distributed secondary control considering asynchronous sampling in MG, which has been ignored in most existing literature. The effectiveness of the proposed methodology is verified by simulations.