M. Hadi Amini

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.

Distributed security constrained economic dispatch

In this paper, we investigate two decomposition methods for their convergence rate which are used to solve security constrained economic dispatch (SCED): 1) Lagrangian Relaxation (LR), and 2) Augmented Lagrangian Relaxation (ALR). First, the centralized SCED problem is posed for a 6-bus test network and then it is decomposed into subproblems using both of the methods. In order to model the tie-line between decomposed areas of the test network, a novel method is proposed. The advantages and drawbacks of each method are discussed in terms of accuracy and information privacy. We show that there is a tradeoff between the information privacy and the convergence rate. It has been found that ALR converges faster compared to LR, due to the large amount of shared data.

A Decentralized Electricity Market Scheme Enabling Demand Response Deployment

In smart grid, demand response (DR) programs can be deployed to encourage electricity consumers towards scheduling their controllable demands to off-peak periods. Motivating the consumers to participate in a DR program is a challenging task, as they experience a confidential discomfort cost by modifying their load demand from the desirable pattern to the scheduled pattern. Meanwhile, to balance the load and generation, the independent system operator (ISO) requires to motivate the suppliers towards modifying their generation profiles to follow the changes in the load demands. Additionally, to protect the entities’ privacy, the ISO needs to apply an effective well-designed pricing scheme. In this paper, we focus on proposing a decentralized DR framework considering the operating constraints of the grid. In our proposed framework, each individual entity responds to the control signals called conjectured prices from the ISO to modify its demand or generation profile with the locally-available information. We formulate the centralized problem of the ISO that jointly minimizes the suppliers’ generation cost and the consumers’ discomfort cost. We also discuss how the ISO determines the conjectured prices to motivate the entities toward an operating point that coincides with the solution to the centralized problem. The performance of the proposed algorithm is evaluated on a modified IEEE 14-bus in reducing the suppliers’ and consumers’ cost, as well as the transmission lines congestion.

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++.

Overview of the Security and Privacy Issues in Smart Grids

In recent years, there is an increasing trend in the power systems from a centralized fossil fuel-based grid toward a distributed green-based network. This requirement compels a new way of designing smart grids for a more reliable and secure power system performance. Involving the demand side in the power system management requires large-scale utilization of distributed communication networks.

Smart Grids: Security and Privacy Issues

This book provides a thorough treatment of privacy and security issues for researchers in the fields of smart grids, engineering, and computer science. It presents comprehensive insight to understanding the big picture of privacy and security challenges in both physical and information aspects of smart grids. The authors utilize an advanced interdisciplinary approach to address the existing security and privacy issues and propose legitimate countermeasures for each of them in the standpoint of both computing and electrical engineering. The proposed methods are theoretically proofed by mathematical tools and illustrated by real-world examples.

Hopf Bifurcation Control of Power System Nonlinear Dynamics via a Dynamic State Feedback Controller–Part I: Theory and Modeling

This two-part paper introduces a dynamic state feedback control law that guarantees the elimination of Hopf bifurcations (HB) before reaching the saddle-node bifurcations (SNB). Part I is devoted to the mathematical representation of the detailed system dynamics, investigation of HB and SNB theorems, and state feedback controller design. For purposes of dynamical analysis, the stable equilibria of the system is obtained. Then the control system is designed with the objective of preventing the voltage collapse before the SNB, such that the structural stability of the system is preserved in the stationary branch of the solutions. The controller aims to relocate Hopf bifurcations to the stationary branch of solutions located after SNB, eliminating the HB from normal operating region of the system. In order to evaluate the performance of the proposed controller, bifurcation analysis has been performed in Part II using single-machine and multi-machine test systems.

A Panorama of Future Interdependent Networks: From Intelligent Infrastructures to Smart Cities

In this chapter, we briefly provide a big picture of emerging challenges in the interdependent networks. The introduced networks will collaborate together to achieve sustainability in terms of upgrading the infrastructures to more intelligent and efficient systems, providing more realistic models of interdependent networks, and modernizing the conventional urban areas to smart cities. Then, we provide the potential trends to address the challenges caused by integration of these networks. We also introduce smart cities as a prominent example of sustainable interdependent networks. We then provide the motivations for studying theory and applications of interdependent networks while capturing the requirements of the sustainable development. Finally, we explain the general structure of the book and provide a brief overview of the chapters. For more information please visit www.interdependentnetworks.com.

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++.

Smart Grid reliability assessment utilizing Boolean Driven Markov Process and variable weather conditions

The transition from conventional electric grid to a more environmentally-friendly, reliable and efficient grid necessitates the reliability improvement. This will play an indispensable role in the future power system called Smart Grid (SG) due to the digital power supply requirements. This distinctive study demonstrates a combined effect of weather conditions and distributed generations (DGs) on the availability of the power system in a region. The ability to model the dynamics of the SG including the variation of weather conditions at different locations for the large-scale system is formulated. In this effort a novel approach is proposed based on the Variable Weather Boolean Logic Driven Markov Process (VW-BDMP), which is utilized along with statistical data. The major contribution of this paper is to introduce a method for the SG reliability assessment (SGRA) considering variable weather conditions, which provides an advantageous tool for the future power system reliability studies.