Grid Integration of DC Buildings: Standards, Requirements and Power Converter Topologies

Residential dc microgrids and nanogrids are the emerging technology that is aimed to promote the transition to energy-efficient buildings and provide simple, highly flexible integration of renewables, storages, and loads. At the same time, the mass acceptance of dc buildings is slowed down by the relative immaturity of the dc technology, lack of standardization and general awareness about its potential. Additional efforts from multiple directions are necessary to promote this technology and increase its market attractiveness. In the near-term, it is highly likely that the dc buildings will be connected to the conventional ac distribution grid by a front-end ac-dc converter that provides all the necessary protection and desired functionality. At the same time, the corresponding requirements for this converter have not been yet consolidated. To address this, present paper focuses on various aspects of the integration of dc buildings and includes analysis of related standards, directives, operational and compatibility requirements as well as classification of voltage levels. In addition, power converter configurations and modulation methods are analyzed and compared. A classification of topologies that can provide the required functionality for the application is proposed. Finally, future trends and remaining challenges pointed out to motivate new contributions to this topic

Harmonic and Supraharmonic Emissions of Plug-In Electric Vehicle Chargers

open1noElectric vehicle (EV) charging represents a relevant electric load with a rapid evolution in terms of number, power rating and distortion, in particular, considering the connection to the low-voltage public grid: available short-circuit power may be limited and particularly susceptible loads may co-exist in the same grid portion. Standards can partially address the problem cover-ing only the harmonic interval, but they necessitate significant extension and improvement in the supraharmonic range. In addition, EV chargers have been observed to violate in some scenarios the applicable harmonic limits, so that the mechanisms of emission and distortion should be better understood and evaluated, including phenomena of mutual influence between EV chargers and with pre-existing grid distortion. Although models can help simulate large-scale scenarios in terms of fundamental frequency phenomena, such as power flow, voltage fluctuation and imbalance, sub-stantial and reliable information can come from experimental results, providing measured harmonic and supraharmonic emissions, accompanied by details on loads mix, grid characteristics and EV charger operating conditions. This work thus defines the applicable constraints in terms of limits and compatibility levels for public and light industrial low-voltage grids, discusses the available experimental results and datasets, analyzing the typical distortion behavior and providing indication of sources of information for further studies.openMariscotti, AndreaMariscotti, Andre

Smart home power management system for electric vehicle battery charger and electrical appliance control

This paper presents a power management system (PMS) designed for smart homes aiming to deal with the new challenges imposed by the proliferation of plug-in electric vehicles (EVs) and their coexistence with other residential electrical appliances. The PMS is based on a hybrid wireless network architecture composed by a local hub/gateway and several Bluetooth Low Energy (BLE) and Wi-Fi sensor/actuator devices. These wireless devices are used to transfer information inside the smart home using the MQTT (Message Queuing Telemetry Transport) protocol. Based on the proposed solution, the current consumption of the EV battery charger and other residential electrical appliances are dynamically monitored and controlled by using a configurable algorithm, ensuring that the total current consumption does not cause the tripping of the home circuit breaker. An Android client application allows the user to monitor and configure the system operation in real-time, a developed Wi Fi smart plug permits to measure the RMS values of current of the connected electrical appliance and change its state of operation remotely, and an EV battery charger may be controlled in terms of operating power according to set-points received from the Android client application. Experimental tests are used to evaluate the quality of service provided by the developed smart home platform in terms of communication delay and reliability. An experimental validation for different conditions of operation of the proposed smart home PMS concerning the power operation of the EV battery charger with the proposed control algorithm is also presented.info:eu-repo/semantics/acceptedVersio

Smart electric vehicle charging strategy in direct current microgrid

This thesis proposes novel electric vehicle (EV) charging strategies in DC microgrid (DCMG) for integrating network loads, EV charging/discharging and dispatchable generators (DGs) using droop control within DCMG. A novel two-stage optimization framework is deployed, which optimizes power flow in the network using droop control within DCMG and solves charging tasks with a modified Djistra algorithm. Charging tasks here are modeled as the shortest path problem considering system losses and battery degradation from the distribution system operator (DSO) and electric vehicles aggregator (EVA) respectively. Furthermore, a probabilistic distribution model is proposed to investigate the EV stochastic behaviours for a charging station including time-of-arrival (TOA), time-of-departure(TOD) and energy-to-be-charged (ETC) as well as the coupling characteristic between these parameters. Markov Chain Monte Carlo (MCMC) method is employed to establish a multi-dimension probability distribution for those load profiles and further tests show the scheme is suitable for decentralized computing of its low burn-in request, fast convergent and good parallel acceleration performance. Following this, a three-stage stochastic EV charging strategy is designed to plug the probabilistic distribution model into the optimization framework, which becomes the first stage of the framework. Subsequently, an optimal power flow (OPF) model in the DCMG is deployed where the previous deterministic model is deployed in the second stage which stage one and stage two are combined as a chance-constrained problem in stage three and solved as a random walk problem. Finally, this thesis investigates the value of EV integration in the DCMG. The results obtained show that with smart control of EV charging/discharging, not only EV charging requests can be satisfied, but also network performance like peak valley difference can be improved by ancillary services. Meanwhile, both system loss and battery degradation from DSO and EVA can be minimized.Open Acces