Arash Nejadpak

A theoretical bilevel control scheme for power networks with large-scale penetration of distributed renewable resources

In this paper, we present a bilevel control framework to achieve a highly-reliable smart distribution network with large-scale penetration of distributed renewable resources (DRRs). We assume that the power distribution network consists of several residential/commercial communities. In the first level of the proposed control scheme, distributed community-level controllers are designed based on the stochastic model of demand and generation. These controllers utilize the local storage units and DRRs to maintain a certain level of reliability for the community. In order to formulate the residential demand and DRRs, we use the Gaussian white noise added to some periodic signals, formulated as a stochastic process. In the second level of the proposed control framework, we take the advantage of bulk generation units to improve the reliability by a global flow controller. In other words, we get help from a few number of bulk power plants in the grid to improve its reliability in the context of satisfying the residential demand with high probability. The global controller dispatches the available non-renewable power plants between communities to enhance the reliability of each community. Using our stochastic model, we obtain a theoretical low-threshold for the certainty of the demand satisfaction in the smart power distribution network.

A Novel Cloud-Based Platform for Implementation of Oblivious Power Routing for Clusters of Microgrids

There has been an increasing demand for connectivity of the clusters of microgrids to increase their flexibility and security. This paper presents a framework for implementation, simulation, and evaluation of a novel power routing algorithm for clusters of microgrids. The presumed cluster is composed of multiple direct current (dc) microgrids connected together through multi-terminal dc system in a meshed network. In this structure, the energy is redirected from the microgrid with excessive power generation capacity to the microgrid which has power shortage to supply its internal loads. The key contribution of this paper is that each microgrid in the cluster is unaware of the current state and other flows of the cluster. In this approach, the optimal power flow problem is solved for the system while managing congestion and mitigating power losses. The proposed methodology works for both radial and non-radial networks regardless of the network topology, scale, and number of microgrids involved in the cluster. Therefore, it is also well suited for large-scale optimal power routing problems that will emerge in the future clusters of microgrids. The effectiveness of the proposed algorithm is verified by MATLAB simulation. We also present a comprehensive cloud-based platform for further implementation of the proposed algorithm on the OPAL-RT real-time digital simulation system. The communication paths between the microgrids and the cloud environment can be emulated by OMNeT++.

A survey on smart grid metering infrastructures: Threats and solutions

Without a reliable metering and communication infrastructure, the smart grid could become a catastrophe to national security and economy. A true smart grid infrastructure should detect all existing and predict future threats through intrusion detection methods. Smart grids are susceptible to various physical and cyber-attack as a result of communication, control and computation vulnerabilities employed in the grid. The paper provides a comprehensive study on types of threats and solutions on smart grid communication and metering infrastructures. As a part of this survey, the smart grid metering infrastructures susceptibilities and recommended remedial actions are identified. In addition, the paper details types of known attacks on existing metering infrastructure and defensive methodologies.

A comprehensive cloud-based real-time simulation framework for oblivious power routing in clusters of DC microgrids

In this paper, we propose a novel cloud-based approach for solving the optimal power routing problem in clusters of DC microgrids. To this end, we deploy oblivious network routing design. Each cluster includes multiple microgrids which are connected via DC links in a multi-terminal DC system in a meshed network topology. In the proposed framework, the energy will be transmitted from the microgrid with additional power generation to the microgrid with power shortage to supply the loads internally. According to the nature of oblivious routing algorithm, all of the microgrids belonging to a specific cluster are unaware of the current cluster status. Furthermore, each microgrid does not need to have the access to the current flows through the multi-terminal DC system as well as the generation capacity and load demand of other microgrids. The optimal routing strategy considers two main objectives: 1)managing congestion through the DC lines, and 2) minimizing power loss through the network. The performance of our novel oblivious power routing method does not depend on the topology of network, i.e. it is applicable to both radial and non-radial power networks of different scales and arbitrary number of microgrids. The effectiveness of the proposed algorithm has been verified in MATLAB simulation. Furthermore, we propose a comprehensive simulation platform for further implementation of the proposed strategy on OPAL-RT real-time simulator system (RTDS). In our proposed platform, the communication path between the microgrids can be implemented on a cloud-based environment emulated by OMNeT++.

Synchrophasor technology: Applications and benefits over conventional measurement

Synchrophasor technology is a growing area of interest for the electric power system. The technology is capable of fast, time-synchronized data that includes phase angles of the electrical measurements. When the energy management system (EMS) has access to the phasor representations of different electrical measurements, it opens the possibilities of more precise system monitoring. In the conventional measurement schemes, state estimation is dependent on magnitude measurements, power metering, low-resolution data, and physical estimates of grid facilities, such as transmission lines. It is not difficult to see that physical estimates of this expansive system can dramatically impact the accuracy of system monitoring. In this paper, data analysis and mathematical concepts are the primary methods of analysis. Measures for the evaluation involve frequency response, error measurements, and interference identification. In the analysis performed, it has been found that frequency can be directly linked to fault events. Also, the total vector error (TVE) of the synchrophasor data with respect to the conventional state estimations is near the compliant level of 1% for sufficient error tolerance. Although this is not a complete success, it does suggest that a synchrophasor-based state estimator scheme may very well support the compliance of the data. If the state estimator were supported by the high-resolution phasor measurements, this would conceivably satisfy the goals set forth by industry standards. Lastly, interference from storm conditions has also been analyzed, and some significant voltage disturbances were observed. These quick, detailed grid measurements could alleviate issues that have resulted from growing power system complexity. Synchrophasor technology has real potential for wide-area monitoring and system awareness.

A literature survey of wireless power transfer

Over 115 years ago Tesla invented the concept of wireless power transfer. Many industrial applications based on this technology have been developed ever since. This technology is of interest especially where the interconnecting wires are inconvenient, or even impossible. This paper provides a survey that describes the history of wireless power technology. Specifically two types of wireless power transfer, radiative and non- radiative, are studied. Additionally the formation of the first standard (Qi) and other standards are mentioned. Finally, the main challenges and future prediction of this technology are presented too.

Best practices for online marketing in Twitter: An experimental study

In this paper, we develop a guideline for advertisers to make the best marketing practices by visualizing and studying the evolution of popular Twitter hashtags. We monitor specific quantitative attributes like the numbers of initiators and commentators. This information allows us to identify the patterns for best practices. This practices are not noticeable to advertisers who aim to utilize Twitter to do online marketing. The result of the study indicates four patterns for successful hashtags, as well as findings about the use of commercial hashtags. Practical implications of these findings are discussed, as well as suggestions for future research.

An optimization based method for design of the adaptive mechanism parameters in a model adaptive reference system estimator in a sensorless motor drive system

This paper presents an optimization based technique to design the proportional and integral coefficients of the adaptive mechanism of a Model Reference Adaptive System (MRAS) based estimator in a Permanent Magnet Synchronous Motor (PMSM) drive system. In this paper, first the MRAS based drive system is modeled linearly. Then the idea of the paper is explained based on the linear model. Finally, the proposed method is used to design the proportional and integral coefficients for a sample PMSM drive system to demonstrate its effectiveness. Preliminary simulation results are provided to verify the design method.

Cooperative load sharing in V2G application

In this paper, a state-of-charge (SoC) based distributed cooperative control (DCC) strategy has been proposed for minimizing the voltage regulation and proportional power sharing (in per unit) among Plug-in-Electric Vehicles (PEVs) and distributed generations (DGs) connected in DC μGrid. The proposed method can control the charging and discharging rates of PEVs depending on the available generation capacity of the DC μGrid. Using the information from neighboring PEVs and DGs only, the global μGrid voltage is estimated and proportional load sharing among the converters is achieved by cooperative control methodology. A distributed Energy Management System (EMS) for PEV has also been proposed which has low computational burden. The system operation and performance has been verified through simulation.

Smart load distribution in AC µGrid: Operation and control

This paper presents a droop-based control methodology for a cluster of distributed generation systems and loads, accumulated together to form an AC μGrid. It is very important to operate and control μGrid in a way to achieve more reliability, cost benefit and enhanced performance. The main control objective in the proposed control methodology is to provide a plug-and-play functionality to the clusters of μGrids. Therefore, not only they will maintain the terminal voltage constant, but also, there will be an equal load sharing among the energy resources in per unit. This method will offer a high stability to these systems during the interconnection with other μGrids. The proposed methodology has been described analytically and has been verified through simulation.