Scalable open source smart grid simulator (SGSim)

In smart power grid, communication network is an integral fragment that communicate vital information to various stakeholders for efficient transmission of electricity. For autonomous functioning of power system, the sensor node connected to grid components enable information sharing for monitoring and control of the state of the grid. Also, the smart grid deployment scenarios require data communication to various grid nodes to be reliable, secure and standards compliant. In this paper, we have proposed a conceptual architecture for evaluating IoT deployment scenario and presenting power system simulation on real-time simulator and experimental evaluation of IPv6 based IETF 6TiSCH compliant grid nodes in smart grid scenario. The proposed architecture for simulation and experiments leverages Internet of Things (IoT) approach to address the smart grid requirement.

The promise of smart grids is very attractive. However, it is not yet clear what the future smart grid will look like. Although most researchers acknowledge that users will play a more prominent role in smart grids, there is a lot of uncertainty on this issue. To counter the strong technological bias in smart grid research and literature, we propose that research should focus more on the social and business dimension of smart grid developments. The main elements of such a research agenda are: Developing more socially embedded visions on smart grids and the services it will provide A shift in the focus on developing smart grids components and systems towards the services it will deliver Development and testing of innovative user-centered business models and ecosystems. More general, on the role of users in smart grids, the main lesson is that user roles should be taken more seriously in relation to smart grids: experts should no longer regard users exclusively and/or simply as potential barriers to smart grid innovation but also as important stakeholders and potential participants in the innovation process.

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.

Smart grid scenarios and their impact on strategic plan—A case study of Omani power sector

With the growth of photovoltaic power generation, the safe operation problems are becoming increasingly important. At the same time, the high uncertainty of load also brings great pressure to the power grid. It becomes necessary to improve the accuracy of distributed photovoltaic power generation and load prediction, and various emerging prediction methods are used based on smart grid, which provides support for accurate prediction of modern power system combined with big data analysis because of its high integration of information, and it has become an important research direction. This chapter will review the distributed photovoltaic power generation and load forecasting of smart grid from the perspective of technical methods. In addition, this chapter also sorts out the multi-objective optimization methods of smart grid, and introduces the optimization methods in the smart grid scenario with high proportion of distributed generation. At the same time, the distributed optimization methods with high efficiency and privacy reflected in power grid optimization is also analyzed in this article.

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.

A pervasive and extensive communication, obtainment and processing of the wireless communication network is evident as a significant development of the 5th generation network. The evolution, in reference to the current cellular technology is evolving the 5th generation to a novel smart grid. The 5th generation wireless network exhibits fundamental services for timely and crucial application for the smart grids. Currently, the electricity market is supplied with the 5th generation network as a new organization framework to enhance the manner in which the utility relates to the smart grids. This research work is purposed to present a thorough evaluation of the 5th generation network and its vision concerning the smart grids. The critical evaluation presented in this paper discusses the current wireless initiatives and the potential architectural transitions evident in the past few years. Moreover, to effectively comprehend the user-centered analyses of the smart grid systems, a thorough evaluation of the 5th generation architecture with the grids is vital. The present status of the 5th generation is the smart grid with various analyses for energy abundances as enumerated in this research paper. The focus presented in this paper focuses on future potential smart grids communication frameworks composed of future roadmaps and the problems that should be visional. The full research provides a thorough evaluation of the 5th generation network in accordance to future smart networks.

The future smart grid (SG) is envisioned as a very dynamic and decentralized energy network, where electricity is generated in distributed and dispersed ways, while the customers are not only consumers but also producers, playing an active role in energy generation. Bidirectional interactions between producers, consumers, and other entities are possible in the SG. Collaboration and near or real-time interactions are envisioned between all grid stakeholders, but these will depend upon timely communication, monitoring, and control capabilities. To realize the emerging SG infrastructure, several services are needed to empower all stakeholders and enable them to realize the expected interactions. The SG deployment and development have given rise to a strong interdisciplinary research. The SG is designed to integrate the most advanced communication, networking, and computing technologies into electrical power grids to make them smarter. The current status is that most of the blackouts and voltage disturbances could be prevented if we had better and faster communication devices and technologies to run the electrical grid. In order to make the current electrical power grid a smart grid, the design and implementation of a new communication and computing infrastructure for the grid are important research fields. These new technologies are seen as additional instruments that will be available to achieve targets for promoting competition, increasing the safety, reliability, and efficiency of electricity systems, and reducing the environmental impacts of energy generation. However, the boom in SGs also raises many economic and social questions.

Traditional electric generation based on fossil fuel consumption threatens the humanity with global warming, climate change, and increased carbon emission. Renewable resources such as wind or solar power are the solution to these problems. The smart grid is the only choice to integrate green power resources into the energy distribution system, control power usage, and balance energy load. Smart grids employ smart meters which are responsible for two-way flows of electricity information to monitor and manage the electricity consumption. In a large smart grid, smart meters produce tremendous amount of data that are hard to process, analyze and store even with cloud computing. Fog computing is an environment that offers a place for collecting, computing and storing smart meter data before transmitting them to the cloud. This environment acts as a bridge in the middle of the smart grid and the cloud. It is geographically distributed and overhauls cloud computing via additional capabilities including reduced latency, increased privacy and locality for smart grids. This study overviews fog computing in smart grids by analyzing its capabilities and issues. It presents the state-of-the-art in area, defines a fog computing based smart grid and, gives a use case scenario for the proposed model.

Future Smart Grids will need to integrate thousands of independently operated intelligent energy devices into one organizational unit. Distributed ledger technologies can provide the means for a business-driven consensus between supply and demand of electrical power. This approach is limited by the computing power of the participating devices. We describe a way to increase the scalability of this approach by a) aggregating power consumption and generation, thus reducing the computational load on the blockchain and by b) applying the concept of edge computing to increase reliability and reaction time. We propose a hierarchical clustering approach for smart grid power balancing, which aims to advance our understanding of architectures for future real-world smart grids.

The traditional power grid is considered no longer viable because it is old, overstretched, unreliable hence the reason for the transformation into the smart grid (SG). The Future SG will have monitoring, automation and communication capabilities which is the main focus of this paper. The SG can also provide two-way communication, real-time pricing and demand-side management. It will have self-healing capability in the case of any fault in the system, unlike the conventional power grid. Furthermore, the SG will have renewable energy resources (RER), advanced metering infrastructure(AMI), supervisory control and data acquisition (SCADA) and plug-in electric vehicles (PEVs) as the essential blocks of SG. The reliability of the SG can be guaranteed by intelligent monitoring and control system with robust information and communication technology. This paper provides a survey of the SG system, a basic overview of the SG, a summary of the various types of communication technologies that can be used in the SG, the requirements for smart grid communication in other to have an effective and efficient communication system and finally, the future trends of SG communication.

In the future, communications networks are expected to become less an end itself than a means to an end by exploiting them not only for telecommunications per se but also across other relevant economic sectors in order to reap larger benefits from interdisciplinary research across traditional borders, e.g., an increased overall reduction of greenhouse gas emissions across multiple sectors such as energy and transportation, as envisioned by the future Smart Grid. The two main quality attributes of a Smart Grid communications infrastructure are reliability and latency, as defined in IEEE P2030. This paper proposes to aggregate triple-play and Smart Grid services into a converged fiber-wireless (FiWi) broadband access network based on low cost Ethernet passive optical network (EPON) and wireless mesh networks. We first show that, as the load of the FiWi network increases, performance degradation in terms of packet drop and latency of Smart Grid applications occurs due to the lack of quality-of-service (QoS) protection. To mitigate this problem, we propose an adaptive admission control algorithm to provide QoS support for FiWi Smart Grid communications networks. Simulation results show that the proposed admission control enables QoS guarantees for triple-play applications as well as future Smart Grid applications over the same FiWi infrastructure.

One of the main characteristics of a smart grid is the availability of large volumes of data, for example, gained from sensors. This data can be utilized as a tool to estimate the state of the system as a whole or any component within the system. In order to achieve actionable information from the variety of data that is available from smart grids, it is important to use the correct mathematical and signal processing tools. Furthermore, the future smart grid is expected to have high levels of reliability. This can be achieved by integrating the condition monitoring systems with maintenance management, wherein the focus is shifted from corrective maintenance to predictive condition‐based maintenance.This chapter introduces the concept of reliability‐centered asset management (RCAM). The RCAM approach provides the possibility of both qualitative and quantitative analysis toward optimal maintenance strategy. Furthermore, various issues with condition monitoring in smart grids have been discussed along with some literature that suggest possible solutions for these issues. Finally, a detailed case study of a data‐based condition monitoring method based on artificial neural network is presented to demonstrate one of the many possibilities to use data from various measurement systems to reach actionable decisions.

From old to new: Assessing cybersecurity risks for an evolving smart grid

Demand-side management is an effective means to optimize resource utilization in the electricity grid. The smart grid can enable the utility company to shape the users consumption by adopting appropriate pricing strategies. Having received the price information, each user may independently schedule its appliances to minimize its electricity payment. In this paper, we consider a smart grid scenario with a single utility company and multiple users where the utility company adopts day-ahead pricing strategy. We formulate the problem as a binary linear programming problem. The simulation results show that users can reduce their bills by 25% using the proposed technique.