Power electronics for smart grids

Chapter 31 - Power Electronics Applications in Smart Grid

Climate change is one of the most pressing issues of our time and mitigating it requires a reduction of CO2 emissions. A big step towards achieving this goal is increasing the share of renewable energy sources, as the energy sector currently contributes 35% to all greenhouse gas emissions. However, integrating these renewable energy sources challenges the current power system in two major ways. Firstly, renewable generation consists of more spatially distributed and smaller power plants than conventional generation by nuclear or coal plants, questioning the established hierarchical structures and demanding a new grid design. Restructuring becomes necessary because wind and solar plants have to be placed at favorable sites, e.g., close to coasts in the case of wind. Secondly, renewables do not provide a deterministic and controllable power output but introduce power fluctuations that have to be controlled adequately. Many solutions to these challenges are build on the concept of smart grids, which require an extensive information technology (IT) infrastructure communicating between consumers and generators to coordinate efficient actions. However, an intertwined power and IT system raises great privacy and security concerns. Is it possible to forgo a large IT infrastructure in future power grids and instead operate them purely based on local information? How would such a decentrally organized system work? What is the impact of fluctuation on short time scales on the dynamical stability? Which grid topologies are robust against random failures or targeted attacks? This thesis aims to establish a framework of such a self-organized dynamics of a power grid, analyzing its benefits and limitations with respect to fluctuations and discrete events. Instead of a centrally monitored and controlled smart grid, we propose the concept of Decentral Smart Grid Control, translating local power grid frequency information into actions to stabilize the grid. This is not limited to power generators but applies equally to consumers, naturally introducing a demand response. We analyze the dynamical stability properties of this framework using linear stability methods as well as applying numerical simulations to determine the size of the basin of attraction. To do so, we investigate general stability effects and sample network motifs to find that this self-organized grid dynamics is stable for large parameter regimes. However, when the actors of the power grid react to a frequency signal, this reaction has to be sufficiently fast since reaction delays are shown to destabilize the grid. We derive expressions for a maximum delay, which always desynchronizes the system based on a rebound effect, and for destabilizing delays based on resonance effects. These resonance instabilities are cured when the frequency signal is averaged over a few seconds (low-pass filter). Overall, we propose an alternative smart grid model without any IT infrastructure and analyze its stable operating space. Furthermore, we analyze the impact of fluctuations on the power grid. First, we determine the escape time of the grid, i.e., the time until the grid desynchronizes when subject to stochastic perturbations. We simulate these events and derive an analytical expression using Kramer's method, obtaining the scaling of the escape time as a function of the grid inertia, transmitted power, damping etc. Thereby, we identify weak links in networks, which have to be enhanced to guarantee a stable operation. Second, we collect power grid frequency measurements from different regions across the world and evaluate their statistical properties. Distributions are found to be heavy-tailed so that large disturbances are more common than predicted by Gaussian statistics. We model the grid dynamics using a stochastic differential equation to derive the scaling of the fluctuations based on power grid parameters, identifying effective damping as essential in reducing fluctuation risks. This damping may be provided by increased demand control as proposed by Decentral Smart Grid Control. Finally, we investigate discrete events, in particular the failure of a single transmission line, as a complementary form of disturbances. An initial failure of a transmission line leads to additional load on other lines, potentially overloading them and thereby causing secondary outages. Hence, a cascade of failures is induced that propagated through the network, resulting in a large-scale blackout. We investigate these cascades in a combined dynamical and event-driven framework, which includes transient dynamics, in contrast to the often used steady state analysis that only solves static flows in the grid while neglecting any dynamics. Concluding, we identify critical lines, prone to cause cascades when failing, and observe a nearly constant speed of the propagation of the cascade in an appropriate metric. Overall, we investigate the self-organized dynamics of power grids, demonstrating its benefits and limitations. We provide tools to improve current grid operation and outline a smart grid solution that is not reliant on IT. Thereby, we support establishing a 100% renewable energy system.

To meet the increasing challenges on global warming and customer demands, the current hierarchical structure of electric power grid is undergoing a rapid change by focusing on high efficiency, reliability and flexibility. To address such challenges, the new concept of smart grid with a sophisticated communication infrastructure has emerged. While power grid systems are based on traditional information architectures at present, the evolving smart grid has a strong need on communication connections among a huge amount of distributed elements, such as generators, substations, monitoring sensors and customers. However, the power industry is facing dilemma that communication resources are limited due to the lack of wireless spectrum resources and the restrictions of wired applications. This paper firstly provides the architecture of the wide-area monitoring system for smart grid by applying a spectrum sensing and sharing technique of cognitive radio, based on an overview of the current communication technologies. Afterwards, the paper presents the feasible application of cognitive communication architecture on the existing power quality monitoring system by combining long-term and short-term monitoring approaches.

I am proudly presenting this special issue to the professional communities of the world. Power electronics is an extremely important element in modern smart grid and renewable energy systems. Basically, it uses high-efficiency switching power semiconductor devices to convert and control electrical power with the help of dc-to-dc, dc-to-ac, ac-to-dc, and ac-to-ac converters that are applied extensively in industrial, commercial, residential, transportation, aerospace, military, and utility systems. Power electronics plays significant role in modern industrial automation and high-efficiency energy systems that include renewable energy systems (such as wind and photovoltaic), bulk energy storage, electric and hybrid vehicles, and energy-efficiency improvement of electrical equipment. In modern electric power grid, power electronics is indispensable in high-voltage dc (HVDC) system, static VAR compensators (SVCs), flexible ac transmission system (FACTS)-based active and reactive power flow control, uninterruptible power system (UPS), fuel-cell-based energy system, etc. After a dynamic technology evolution for nearly five decades, power electronics has now grown possibly as the most important technology in the 21st century. Currently, most of our energy comes from fossil fuels and nuclear power plants. Fossil fuels cause environmental pollution that causes global warming or climate change problems. Nuclear energy is clean in that respect, but it has safety and radioactive waste disposal problems. For these reasons, the whole world is now turning toward renewable energy, where power electronics is an indispensable ingredient.

Synthetically analyze the power distribution communication network technology in the smart power grid link. It mainly includes the summary of the smart distribution network, electric power communication backbone network and then layer communication requirements, the network mode and the application mode of WLAN technology in the distribution network, EPON network technology, micropower wireless technology, PTN technology and power broadband wireless systems. State the demand of the smart power distribution business and put forward technical guidance for the smart power distribution communication network scheme. In view of the complex distribution network architecture, more nodes and scattered, complex business types data business needs, put forward the integrated solutions of optical fiber communication as the backbone access, wireless bandwidth, passive optical communication as the coverage, the short distance wireless communication as the main terminal access. It provides a reference for the communication plan of distribution side.

The rapid integration of distributed generation sources and power electronic converters in modern smart grids has introduced significant power quality (PQ) challenges, including increased harmonic distortion, voltage instability, and power losses. Existing optimization techniques struggle with slow convergence, suboptimal tuning of control parameters, and limited PQ enhancement. To deal with these problems, this research proposes a novel Lightning Search Optimization–Quantum Neural Network (LSO-QNN) approach for optimizing the Distribution Static Compensator (DSTATCOM)-based Proportional–Integral–Derivative (PID) controller to enhance PQ in grid-connected renewable energy systems. The novelty of this work lies in the hybridization of LSO with QNN, which enables adaptive and dynamic tuning of PID controller gains, ensuring faster convergence, enhanced harmonic suppression, and improved voltage stability compared to conventional methods. Simulation findings indicates that the proposed LSO-QNN approach achieves a voltage Total Harmonic Distortion (THD) of 0.38% and Current THD of 3.4%, significantly outperforming Particle Swarm Optimization (PSO) (6.4%), Heap-Based Optimizer (HBO) (4.5%), and Nomadic People Optimizer (NPO) (5.5%). Moreover, it improves voltage stability (1.1s) and reduces computation time (34 ms), achieving an overall efficiency of 99.3%. These findings establish the superiority of LSO-QNN over traditional optimization techniques, making it a highly effective and practical solution for real-world PQ enhancement in smart grids.

This work presents and discusses the application of power electronics for the integration of several distributed generation sources, as well as those related to it, the microgrids and the smart grids, to the power sector. Trends and challenges are addressed for the area of study and an embracing overview of the main technologies and techniques is presented for future investigation. As there are many power electronics devices available for employment, in each one of these crucial, modern, sustainable electrical systems, it is important for students, researchers and professionals to understand and compare the state of the art of them all, for the right choice in their respective uses. These apparatuses not only allow grid matching, but also provide new functions that enhance these artifacts’ operations, and of the entire power system. Thus, in this paper, the relationship between power electronics and distributed generation is detailed, with the role and classification of each static converter for the improved operation of wind power, photovoltaic systems, fuel cells, small hydro and microturbines exposed. While the first two are more widely covered in the literature, the last three are rarely discussed and differentiated, in terms of their power electronics interfaces. Then, the same is made for microgrids and smart grids, also scarcely approached in other works, with regard to the characteristics of the power converters applied, confirming their superior performances with the use of power electronics. Finally, conclusions are given.

It is my honor to present the proceedings of the 2024 3rd International Conference on Smart Grid and Green Energy (ICSGGE 2024). ICSGGE 2024 is an event that brings together the world’s leading experts and scholars in the fields of smart grid and green energy, and is also an excellent platform for sharing the latest research results and discussing the application of cutting-edge technologies in related research domains. With the increasing severity of global climate change and energy crisis, smart grid and green energy, as the key means to solve the energy problem, have received extensive attention from the international community. In order to further promote technological innovation, academic exchanges and cooperation in the fields of smart grid and green energy, ICSGGE 2024 was held from April 19th to 21st, 2024 in Chengdu, China (virtual conference). ICSGGE 2024 brought together top scholars and researchers from all over the world, who shared their latest research results and practical experiences in the fields of smart grid and green energy in this conference. Such topics as The Role of Smart Grids to Drive Cities Towards Carbon Neutrality (by Prof. Steivan Defilla, Tianjin University, China), Role of Energy Conservation & Management in Energy Transition (by Prof. Muhammad Asif, King Fahd University of Petroleum & Minerals, Saudi Arabia), among others were discussed during the keynote speech part. Through exchanges and discussions, we have jointly explored the development trends and future research direction of smart grid and green energy, stimulated innovative thinking, and promoted academic exchanges and cooperation. This proceedings of ICSGGE 2024 contains excellent academic papers from all around the world, which not only cover the basic theories, teaching methods, and evaluation systems of smart grid and green energy, but also discuss in depth the applications and innovations in many fields. Topics include but are not limited to Smart Grid Security, Energy Transfer and Interactive Technology, Communication-Based Control and Protection, Photovoltaic Systems and Solar Energy Engineering, Power Electronics and Drives, Wind Energy Generation, etc. Each paper has been strictly reviewed and screened to ensure its academic value and practical application value. We would like to express my heartfelt thanks to all the experts and scholars, organizers, sponsors and participants who have contributed to and supported this conference. And we believe that all the experts and scholars have harvested fruitful results and inspired new inspirations in this event. Through our joint efforts and wisdom, the ICSGGE 2024 has become a grand event in the fields of smart grid and green energy, and made a new contribution to the promotion of electronic and energy engineering. The Committee of ICSGGE 2024 List of Committee Member is available in this Pdf.

14 - Privacy-preserving in smart grids using Ethereum and Hyperledger blockchain

Integration of industrial consumers into the smart grid concept can be facilitated by optimizing short and very short-term forecasts of load curves for industrial consumers. Minimizing forecast errors can improve the supplier-consumer relationship by reducing supplier balancing costs, which can lower the energy bill, and anticipate possible network faults or network congestion which means improved operation across the entire power system. The present paper aims at demonstrating the usefulness of energy forecasting by using machine learning methods. In the context of installing monitoring systems with load curve recording data at short intervals of time, huge amounts of data are obtained that need to be capitalized in real time (automated), otherwise the investments necessary to modernize the way in which the energy is used are not justified, consequently disfavouring the development and digitization of electrical networks. Integration of the industrial consumer into the smart grid concept can be applied in detail at large industrial consumers where forecasts can be made on certain areas inside factories or electric equipment with high installed electric capacity. The use of smart grid technologies removes the current limits for monitoring, processing and communication between consumption and production. To be able to capitalize on the forecasts, a very important aspect is the automation of their realization and quick access to the decision makers who may be human or other smart grid integrated systems. That is why the present paper proposes the use of machine learning methods in the short and very short forecast, and the results will be compared with the classical forecasting methods. Hourly load curves from the industrial consumers will be used for forecasts.

Review on smart grid control and reliability in presence of renewable energies: Challenges and prospects

The smart grid concept is being fostered due to required evolution of the power network to incorporate distributed energy sources (DES), renewable energy sources (RES), and electric vehicles (EVs). The inclusion of these components on the smart grid requires an information and communication technology (ICT) layer in order to exchange information, control, and monitor the electrical components of the smart grid. The two-way communication flows brings cyber security issues to the smart grid. Different cyber security countermeasures need to be applied to the heterogeneous smart grid according to the computational resources availability, time communication constraints, and sensitive information data. This paper presents the main security issues and challenges of a cyber secure smart grid, whose main objectives are confidentiality, integrity, authorization, and authentication of the exchanged data.

Electric vehicles may be an alternative to the use of petroleum, by allowing to reduce the pollution problems and mitigate the safety questions involved on extraction, importation and combustion of fossil fuels. Thus, the inclusion of this vehicles as one of the decisive factors on planning distribution systems represents a big opportunity for developing new technologies and systems. Moved by challenges, the concept of Smart Grids was created to define the evolution of traditional electrical networks, combining the infrastructure of electrical energy with moderns installations of distributed computation, communications networks and new paradigms of generation and energy consumption. In this context, the present work provides an evolution analysis of technologies for electric vehicles promoting the smart grids, mapping the disponible mechanical configurations, technological rotes in course and the behavior of recent market for electrical vehicles. Through the outline traced at work, it is considered that electrical vehicles incorporates a range of technologies that are substantially different in relation to conventional vehicles and networks, since energetic input until more sophisticated elements. Ultimately, is possible to affirm that Brazil still lacks a public policy to the progress of this sector ant that this area is configured as a possible front of research and innovation of high impact for society.

The concept of smart grid has emerged as a convergence of traditional power system engineering and information and communication technology. It is vital to the success of next generation of power grid, which is expected to be featuring reliable, efficient, flexible, clean, friendly, and secure characteristics. In this paper, we propose an efficient and privacy-preserving aggregation scheme, named EPPA, for smart grid communications. EPPA uses a superincreasing sequence to structure multidimensional data and encrypt the structured data by the homomorphic Paillier cryptosystem technique. For data communications from user to smart grid operation center, data aggregation is performed directly on ciphertext at local gateways without decryption, and the aggregation result of the original data can be obtained at the operation center. EPPA also adopts the batch verification technique to reduce authentication cost. Through extensive analysis, we demonstrate that EPPA resists various security threats and preserve user privacy, and has significantly less computation and communication overhead than existing competing approaches.

A Solid-State Transformer as Enabling Technology for Microgrids for Integration into the Power Distribution System: An Overview