Introduction To Smart Grid Quantum Pdf Download _VERIFIED

Modern electricity infrastructure faces various challenges, including the electrification of transport, and climate change. In response to these challenges, smart grids are being developed, which rely on Information and Communications Technology (ICT) for pervasive monitoring and automated control. These smart grids facilitate more efficient utilization of energy, reduce costs, and enable better integration of renewable energy sources, resulting in enhanced resilience and sustainability in electricity production and distribution (Farhangi 2010).

This chapter provides an overview of the key concepts and theories relevant to the research. First, a brief introduction to quantum computing is given; it forms the basis for the consequent section on the HHL algorithm, a quantum algorithm for solving systems of linear equations. Then, we cover how said algorithm is used to perform quantum DC power flow analysis. Finally, we explain co-simulation and its application in smart grid applications.

Introduction To Smart Grid Quantum Pdf Download

Download Zip 🔥 https://urllie.com/2y7XRD 🔥

The emergence of complex cyber-physical systems and systems of systems has brought with it an increased research interest in co-simulation. A broad state-of-the art analysis can be found in Hafner and Popper (2021) whereas Gomes et al. (2018) provide an in-depth technical discussion. The simulation paradigm has proven promising in various application domains, among them maritime and automotive engineering as well as robotics (Gomes et al. 2017). The most prominent domain for co-simulation seems to be power grids. Palensky et al. (2017) provide an extensive primer on co-simulation of power systems together with ICT. For an empirical analysis of smart grid co-simulation see (Schweiger et al. 2019) and for a literature review see Mihal et al. (2022).

For this study, we have chosen the smart grid co-simulation framework Mosaik (Version 3.0). It provides two programming interfaces: One is responsible for the interaction between the orchestrator and a simulator. The other specifies how a simulation scenario can be defined, including instantiating and connecting entities. A central aspect of co-simulation is the selection of participating simulators and the nature of their information exchange. Here, we briefly describe each simulator and Fig. 5 shows their connections. Please note that for all but one simulator, there is only one instance. For example, in our small-scale case-study scenario, there is only one solar farm even though the solar-farm simulator is capable of handling multiple instances. In contrast, the aggregate-load simulator handles three instances.

FIGURE 1. An example of the proposed cyberattack structure of a future hybrid quantum-classical smart grid. The cyberattack scenario occurs when an attacker compromises the real-time measurement device and causes it to output anomalous false data that cause the quantum device to malfunction, with the anomalies being classically difficult to differentiate from the regular noisy samples.

Citation: Nader A, Dubois M-A and Kundur D (2023) Exploring quantum learning in the smart grid through the evolution of noisy finite fourier series. Front. Energy Res. 11:1061602. doi: 10.3389/fenrg.2023.1061602

The electric grid is evolving from an electrical network composed primarily of large centralized fossil fuel plants to a more distributed infrastructure, which includes renewable and energy storage type plants. Wind, photovoltaic (PV), and energy storage system (ES) technologies have observed significant cost reductions as they have continued to mature and reach mass production1,2,3. These technologies are now being adopted more frequently into the emerging electric smart grid, both in large and small deployments.

In this paper, we achieve our objective by using QKD secret keys to authenticate communications of integrated power electronics energy resources in electric grid infrastructure. This work is the first time quantum secret keys have been used to authenticate smart grid communications. More specifically, (a) QKD secret keys have been applied over the IoT protocol MQTT for supporting DER communications, (b) the developed software design to utilize and manages secret keys established by a commercial Qubitekk quantum key distribution system to authenticate M2M communications, and (c) the platform has been applied in a real utility setting (at EPB in Chattanooga Tennessee, between a data center and an electrical substation connected via an optical fiber). We first lay the foundation of our developed approach in the next section and then provide a detailed description of our system and methods used to solve the challenges in the following sections.

In this work, the concept of operations is the communications between a single photovoltaic (PV) system and a SCADA system. In the following sections, a generalized architecture for supporting the authentication of smart grid communications using quantum key distribution demonstration is discussed.

This paper presents the first demonstration of quantum key-based authentication of smart grid communications across an energy delivery infrastructure environment. The developed system utilizes a flexible and scalable smart grid communications protocol: a publish-subscribe method. Further, keys from a commercial Qubitekk quantum key distribution system along with the Carter-Wegman authentication protocol are used, which in principle offer information-theoretic security. With this demonstration, quantum and classical security technologies have been shown to work in the energy infrastructure to authenticate data and control communications, providing long-term security, capable of exceeding the expected infrastructure service life. Future development of the reported techniques could include full hardware integration via smart grid manufacturers. In addition, hardware platforms with fully integrated power electronics systems are in development today in a new facility called the Grid Research Integration and Deployment Center (GridC). This facility provides an avenue to fully scale the presented implementation into multiple power electronics systems and integration demonstrations. On the other hand, in terms of cybersecurity, previous work demonstrated the trusted relay on the power grid but stopped short of showing how to use the distributed secret keys45, which is the focus of this work. Future work could concentrate on developing scalable secure communications including a wider range of power infrastructure devices.

Authentication of data and control messages is crucial for reliable, safe, and secure grid operations. Using an authentication protocol and secret keys known only to the sender and the receiver enable bi-directional message authentication. Moreover, an information-theoretic (meaning security is not based upon computing resource assumptions) authentication protocol based on private-key encryption comes without the latency penalty of public-key cryptosystems23,24. For example, using the Carter-Wegman68 authentication protocol requires fewer computational resources and thus provides a long-lasting and more resource-efficient authentication compared to the asymmetric public-key-based authentication protocols25. Thus, Demonstrating QKD technology in a real-world environment to verify the feasibility of quantum-based cybersecurity for power grid communications is a crucial way point towards wider adoption. A controlled laboratory setup dramatically reduces environmental impacts compared to field deployments. For example, environmental variables such as temperature and humidity, in addition to the electromagnetic emanations of specialized power equipment, can affect the quantum hardware, including optics, electronics, and electro-optics. Further, the fiber optic deployment mechanism in a real-world environment is another vital element to consider. The QKD key rate of an underground and aerial fiber will likely be affected in some QKD implementations and may require additional equipment/engineering compared to lab-based demonstrations.

Meanwhile, formal analysis, machine learning, and quantum computing are all cutting-edge techniques not only applicable to power grids, but also usable for broad applications. Therefore, working on these projects can also provide students with multi-discipline knowledge in those directions as well as their engineering applications.

Uttley said smart grids, electrical grids, and water grids are part of the critical infrastructure that can become the target of attacks, especially because those systems stay in the field for many years or even decades. Other industries that can take advantage of the increased robustness provided by quantum random-number generators include the financial industry and health care.

As research has shown, data will be at the core of this transformation. Significant investments in smart grid technology over the past two decades have resulted in advanced grid monitoring and measurement, resulting in the continual collection of myriads of data from various parts of the grid. Computing tools have accordingly resurfaced as enabling means that can convert data to information and ultimately to actions. Traditional computing relies on large operating margins to ensure a secure and resilient grid operation. Today, these extensive operating margins cause an estimated US$5-US$15B in additional energy delivery costs, which will further increase as renewable energy grows over the next several decades.

Grid analytics signifies a set of Software-as-a-Service (SaaS) tools to support accurate modeling appropriate for various time scales of decision making at different layers of such complex interconnected grid. Given this growing complexity, the traditional computing methods may become ineffective to address the new set of challenges or offer innovative solutions. A viable and emerging solution is Quantum Computing technology. Quantum Computing is developed based on quantum mechanical phenomena that describe the nature and conduct of energy and matter at the level of fundamental subatomic particles. A quantum computer operates by controlling the behavior of these particles to achieve desired computation. Quantum computers mark a step forward in computing capacity, which is potentially superior to a modern supercomputer by offering extensive efficiency growth. Based on the laws of quantum physics, a quantum computer can achieve enormous processing power over multi-state capacity and can execute multiple functions simultaneously by using possible permutations. 006ab0faaa