Blockchain-Based Multi-Tier Double Auctions for Smart Energy Distribution Grids

The risk of electric power supply and demand is becoming more and more outstanding. So in order to avoid electric power supply and demand risks, we should set up the electric power supply and demand early warning management system. In this paper, the influencing factors of electric power supply and demand are analyzed, and then the principal component analysis method is used to reduce factors, then the support vector machine method is used to realize the early warning of the electric power supply and demand. At last, it is validated that the results by this method is feasible for early warning.

The "Smart Grid" refers to various efforts to modernize the power grid through the application of alternate sources of energy and intelligent devices. The present national interest in Smart Grid applications has generated many questions concerning the role of distribution engineering in the future. What features do utility engineers need in distribution system analysis tools to support the future Smart Grid? This paper will discuss some relevant EPRI research in this area that focuses on selected issues related to Smart Grid analysis relevant to rural utilities. The essential characteristics of distribution system analysis tools to support analysis of these issues are discussed.

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.

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.

Introduction The power grid controls their electric power supply by maintaining voltage, frequency, and transient stability, by predicting the electricity demand at any given time. However, recent large-scale implementation of photovoltaics (PV) makes it difficult to meet them because the gap between power supply and demand will be widening. The suppression of any power sources including solar power generation with sacrificing some electricity is sometimes adopted to avoid large-scale blackouts, and the situation is expected to be a common event at the 2030s. An effective solution to such situations is called as “leveling power”, which is the ability to maintain a balance between power supply and demand. Leveling power needs to be introduced not only into the centralized power grid but also into distributed energy systems. The major candidate of leveling power at distributed energy systems is electrochemical energy storage technology such as secondary batteries or hydrogen Power-to-Gas-to-Power (P2G2P). A smart energy system called Ene-swallow has been developed by our research group, and applied to Ookayama campus at the Tokyo Institute of Technology. This system manages 1400 kW-PV, 100 kW-FC, 70 kW gas engine and 100 kWh storage battery with a 10,000 kW-class electricity demand. Ene-Swallow also accumulates the power demand data in 1-sec intervals and PV power generation data in 1-min intervals. We previously carried out a techno-economic analysis of a hydrogen energy storage system to level the annual gap of power supply and demand [1]. Here we evaluated the potential of electrochemical energy storage as a leveling power with using the annual data from those data. Method We analyzed the current situation requirements for leveling power (analysis-1) and the applicability of a distributed energy storage system (analysis-2). For analysis-1, we analyzed 1-hour data of power generation and consumption published from power companies across Japan (Fig. 1a), and 1-min data of PV power generation (Fig. 1b) and 1-sec data of power demand (Fig. 1c) at Ookayama campus. For analysis-2, we set a tentative distributed grid with a 10,000 kW-class electricity demand, a given amount of primary power generation by PV and the power supply from the grid. In this work, we set no leveling power by the grid, which supplied constant power. Then, we determined the entire gap between power supply and demand during a single year based on the actual 1-minute data of PV power generation and power demand from April, 2017 to March, 2018. Then we estimated the required amount of energy storage, and thus determined the required number of P2G2P devices with alkaline electrolysis cell (AEC), solid oxide fuel cells (SOFC), H2 tanks and compressors, and lithium-ion batteries (LIB). In the system, the balance of power generation and consumption in a day is controlled as shown in Fig. 2. During the daytime, the surplus power from PV is leveled by an AEC. If AEC capacity is not sufficient, it is leveled by LIB. At night, the required power for demand is generated by an SOFC and/or an LIB. By optimizing the capacity of each component device in the distributed system, we evaluated the total system cost. We specified the expected technical parameters in the future (for the year 2030), such as unit price, efficiency and lifetime as shown in Table 1. Results From analysis-1, the 1-hour data showed that the supply fluctuation of PV power generation during the day strongly impacts the power grid when the energy mix ratio of PV to total annual demand reached about 10% when keeping nuclear power generation constant. The 1-minute data showed large fluctuations in PV generation within in a short time period (< 1 hr) during weather such as a cloudy day (Fig. 1b). Power fluctuations with different time scales have to be leveled by using electrochemical energy storage technologies. Analysis-2 showed that the total system cost could be reduced by using a combined system of P2G2P and LIB by utilizing their different characteristics. The combined system of P2G2P can reduce their total energy cost with dividing the role by power generation and the storage when the cost targets shown in Table 1 can be achieved. [Acknowledgements] A part of this study is supported by the New Energy and Industrial Technology Development Organization (NEDO) and MIRAI program of Japan Science and Technology Agency (JST). Reference [1] T.Okubo et al., 234th ECS Meeting AiMES 2018, (September 30-October 4, 2018) Figure 1

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.

This paper focuses on the firm real-time requirements of Time-Critical Wide Area Measurement and Control systems for future Smart Grids. It outlines the findings from the first stage in an ongoing body of work aimed at developing models and techniques that will enable the performance evaluation of these systems to take place prior to their implementation. It then discusses the first phase in the second stage of this project that addresses the problem of evaluation in cases where the output from system's devices is variable. It then presents some preliminary findings and outlines the direction for future work.

As a part of the vision of the future's smart grids, this article intends to provide an integrated protective algorithm that employs a specially driven index for the detection of faults in different layers of the grid (transmission, distribution, and/or microgrids). The proposed algorithm evaluates the difference between the positive sequence powers measured by phasor measurement units (PMUs) located at the terminals of the line/feeder/zone required to be protected. An index named as a periodic change of positive sequence power index (PC‐PSPI) is evaluated as the periodic change of the previous power difference per one cycle. The PC‐PSPI is always zero during no‐fault conditions as the power difference per one cycle is relatively constant during normal daily operations. However, the previous condition is disrupted during the presence of faults leading to fault detection. To ensure the proper functionality of PC‐PSPI for different layers of the grid, various testing systems were used including the WSCC 9‐bus transmission system, IEEE 34‐bus distribution system, and a modified microgrid version of the IEEE 34‐bus equipped with distributed generation (DG) units. All systems were simulated using MATLAB/Simulink software packages. The proposed algorithm proved its reliability in operation even for severe fault and islanding cases.

Interest in electrical energy storage systems is increasing as the opportunities for their application become more compelling in an industry with a back-drop of ageing assets, increasing distributed generation and a desire to transform networks into Smart Grids. A field trial of an energy storage system designed and built by ABB is taking place on a section of 11 kV distribution network operated by EDF Energy Networks in Great Britain. This paper reports on the findings from simulation software developed at Durham University that evaluates the benefits brought by operating an energy storage system in response to multiple events on multiple networks. The tool manages the allocation of a finite energy resource to achieve the most beneficial shared operation across two adjacent areas of distribution network. Simulations account for the key energy storage system parameters of capacity and power rating. Results for events requiring voltage control and power flow management show how the choice of operating strategy influences the benefits achieved. The wider implications of these results are discussed to provide an assessment of the role of electrical energy storage systems in future Smart Grids.

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

In light of the increasing cost of electricity and the Global Warming campaigns to reduce general electricity usage, there is a growing interest in analysing power consumption in households[6]. By analyzing the electricity usage of appliances more accurate conclusions can be drawn on their efficiency and need for replacement . Furthermore , this can also determine whether an appliance is drawing unusually high amounts of power when turned off and whether it should rather be unplugged. In this way electricity consumption and cost can be reduced[1] . The smart meter project is one of the most important needs these days, In Smart Grid ; the smart meters are versatile role with intelligent capabilities in order to meet the consumer's demands and each objective[5]. Smart meter can measure and communicate detailed real-time electricity usage, facilitate remote real-time monitoring and control power consumptions and consumers are providedwith real time pricing and analysed usage information, which is a technical data to be transmitted to the grid, who are utility providers. More detailed feedback on each appliance to the user[5]. Future smart grids will likely to be more tightly integrated with the cyber infrastructure for sensing, control , scheduling , dispatch, billing and cyber attacks can be detected by using smart meters and also ordering the power demand through online[6]. Every home uses electricity with different consumption and different amounts of watts according to the different types and numbers of the appliances they have[1]. Our proposed system offers a real tine feedback on the entire electricity usage and the consumption of many appliance at device level as a result, This allow the user to monitor measure and compare their energy consumption and electricity level on house hold and on device level[5].

Grid inefficiency, grid instability, projected world energy consumption, decreasing use of fossil resources and reduction of the CO2 footprint, were the motivations to develop the distributed generation system (DGS) and the Smart grid. The future DGS and Smart grid worker will need a solid background at several disciplines such as engineering math and physics, electrical, electronic, power, control, information technology, and business & management. Motivated by the last facts several attempts have been proposed in colleges and universities to satisfy the current and future work force. Following this trend in this paper a new course in DG and Smart grid for an Electrical Engineering Technology Program at Mohawk College is presented. Fundamentals and practical recommendations based on inquiry-based model are also covered.

A closed-loop energy price controlling method for real-time energy balancing in a smart grid energy market