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In optimizing the vibrodiagnostics of thermal power plants, a mathematical model was developed and used to increase the power plants' safety and operational characteristics. The choice of diagnostic condition parameters of the components was made based on optimization characteristics that affect the accuracy of the solution and operational readiness of the thermal power plant. The research aimed to develop a universal model by analyzing more optimized vibrodiagnostics of the turbogenerator, which achieves high operational reliability, high safety, an extension of service life, an extension of working life, a reduction of overhaul time, etc. The application of the model represents the concept of optimization with the checking of condition parameters, which is applied to turbogenerator assemblies that have a continuous change of condition parameters as a function of the monitoring time, for which the functional dependence between the intensity of the parameter change and the operating time can be determined. [ABSTRACT FROM AUTHOR]

The support of prosumers in the countries of the European Union has registered significant growth, especially regarding the energy produced from photovoltaic panels in households or in commercial spaces after 2020. Romania will promote the distributed generation from renewable sources with installed power between 3 kW and 100 kW, the on-grid installations being subsidized through the financial support of the Environmental Fund Administration (3 kW for residential prosumers) with,,photovoltaic green house,, program and Ministry of Economy, Energy and Business Environment with the,,Electric Up,, program (between 27 kW - 100 kW power with recharging stations of at least 22 kWp for electric and hybrid electric vehicles for commercial prosumers). This paper proposes an analysis of a commercial prosumer with a specific case study in north Dobrogea in Romania, comprise of a comparative analysis for an integrated 30 kW comercial user with 44 kW charghing station for electric and hybrid electric vehicles installed on the ground, in order to reduce the energy consumption with a management system for the optimal coordination of the energy to the owner's need, also to see the rentability of the system when it's a comercial user and the own consumption is higher during the day. The project applies to Romanian legislation and can be used for similar projects considering that in coming years these types of systems will appear. [ABSTRACT FROM AUTHOR]

Summary: The integration of intermittent renewable energy sources coupled with the increasing demand of electric vehicles (EVs) poses new challenges to the electrical grid. To address this, many solutions based on demand response have been presented. These solutions are typically tested only in software‐based simulations. In this paper, we present the application in hardware‐in‐the‐loop (HIL) of a recently proposed algorithm for decentralised EV charging, prediction‐based multi‐agent reinforcement learning (P‐MARL), to the problem of optimal EV residential charging under intermittent wind power and variable household baseload demands. P‐MARL is an approach that can address EV charging objectives in a demand response aware manner, to avoid peak power usage while maximising the exploitation of renewable energy sources. We first train and test our algorithm in a residential neighbourhood scenario using GridLAB‐D, a software power network simulator. Once agents learn optimal behaviour for EV charging while avoiding peak power demand in the software simulator, we port our solution to HIL while emulating the same scenario, in order to decrease the effects of agent learning on power networks. Experimental results carried out in a laboratory microgrid show that our approach makes full use of the available wind power, and smooths grid demand while charging EVs for their next day's trip, achieving a peak‐to‐average ration of 1.67, down from 2.24 in the baseline case. We also provide an analysis of the additional demand response effects observed in HIL, such as voltage drops and transients, which can impact the grid and are not observable in the GridLAB‐D software simulation. [ABSTRACT FROM AUTHOR]

An active method for double-frequency power ripple decoupling in single-phase inverters is presented in this paper, exhibiting the main advantage of not using additional power semiconductors besides the H-bridge. The proposed method requires only two capacitors placed between the midpoint and one end of each inverter leg. An original control solution of the inverter ensures the power ripple transfer toward the two decoupling capacitors without affecting the inverter output voltage. The simple design makes the proposed solution easy to adapt for single-phase inverters in H-bridge configuration. This paper focuses on the autonomous operation mode of the inverter, detailing its operating principle and the control analysis. The system performances, including the impact of the decoupling circuit on the inverter efficiency, are assessed by means of experimental results. [ABSTRACT FROM PUBLISHER]

Frequency control in autonomous microgrids (MG) with high penetration of renewable energy sources represents a great concern to ensure the system stability. In this regard, this paper presents an enhanced control method for battery energy storage systems (BESS) to support the frequency of MG and with the ability of disconnecting from the MG to supplying in the island mode a local consumer. A frequency controller, combining a conventional droop control with an inertia emulation function, governs the BESS active power transfer during the primary frequency control level. The BESS may also provide voltage support in the point of common coupling with the MG. Moreover, the proposed BESS may compensate, partially or totally, the power absorbed by the local loads in order to improve the MG frequency response. When the MG power quality worsens below a certain level, in terms of voltage and frequency, the BESS detaches from the MG and continues to operate islanded. The reconnection is accomplished following a smoothly resynchronization of the local voltage with the MG, without disturbing the local loads supply. Additionally, this paper also discusses about the aspects related to the BESS management and its integration within the proposed system. The simulation and experimental results assess the feasibility of the proposed control solutions. [ABSTRACT FROM AUTHOR]

This study analyses the integration impact of battery energy storage systems (BESSs) on the short‐term frequency control in autonomous microgrids (MGs). Short‐term frequency stability relates with the primary or speed control level, as defined in the regulations of the classical grids. The focus is on autonomous MGs that dynamically behave similarly to the classical power systems. This is the systems case with classical distributed generators (DGs), but which can also contain renewable energy sources (RESs) in a certain penetration level. During MG islanded operation, the local generators take over most of the frequency control process, by means of their automatic generation control, which include inertia response and primary control. However, RES‐based DGs are rarely able to provide grid frequency support, as they lack controllability and usually the power conversion chain does not have the possibility of storing and releasing energy when required by the system. Therefore the need of boosting the MG power reserves by adding energy storage systems is often a requirement. The study highlights the improvement in the MG short‐term frequency stability brought by an original BESS control structure enhanced with both inertial response and an adaptive droop characteristic during battery state‐of‐charge limitations. The conducted analysis is accomplished by adopting aggregated models for the involved control mechanisms. The developed model is analysed in frequency domain, whereas an experimental test bench including a real‐time digital simulator with BESS controller in a hardware‐in‐the‐loop structure is used for assessing the system performances. [ABSTRACT FROM AUTHOR]

A control strategy for an autonomous induction generator (IG) system synchronization and seamless transfer to an inverter-based microgrid (MG) is presented in the current paper. The IG system control in autonomous mode is performed by a combination between a Voltage Source Inverter (VSI) and a Dump Load (DL). The MG consists of an MG leading inverter having on its DC side a supercapacitor-based energy storage system, two MG supporting inverters, and local loads. The paper presents the IG control part for the VSI-DL system, as well as the synchronisation algorithm that enables the smooth interconnection with the MG. An analysis of the IG impact on an islanded MG is also provided. Experimental validations accomplished on a complex laboratory test-bench have focused on the dynamic events associated with the IG system connection/disconnection to/from the MG and also on the MG response to a load being turned on and off when the IG operates connected to the MG. The obtained results have shown that the proposed synchronization algorithm ensures a seamless transfer for the IG system from autonomous to MG connected mode and vice-versa. Moreover, when a significant load transient occurs within the MG operation, the IG presence does not alter the MG stability. [ABSTRACT FROM AUTHOR]