Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.Comment: To be published in IEEE Communications Surveys and Tutorial

Home Energy Management System and Internet of Things: Current Trends and Way Forward

Managing energy in the residential areas has becoming essential with the aim of cost saving, to realize a practical approach of home energy management system (HEMS) in the area of heterogeneous Internet-of-Thing (IoT) devices. The devices are currently developed in different standards and protocols. Integration of these devices in the same HEMS is an issue, and many systems were proposed to integrate them efficiently. However, implementing new systems will incur high capital cost. This work aims to conduct a review on recent HEMS studies towards achieving the same objectives: energy efficiency, energy saving, reduce energy cost, reduce peak to average ratio, and maximizing user's comfort. Potential research directions and discussion on current issues and challenges in HEMS implementation are also provided

Meter Scoping Study

This report presents a summary of metering technology and cost information from past studies in an attempt to identify key barriers to more widespread implementation

On possibilities of smart meters switching at low voltage level for emergency grid management

Smart Meter (SM) is an advanced remotely readable energy meter with two-way communication capability which measures the electrical energy in real-time or near-real-time and securely sends data to Distribution System Operator (DSO). A smart metering system is an application of SMs on a larger scale, i.e. the application of a general principle on a system rather than on individual appliance. The European Commission (EC) has included ten common minimum functional requirements for electricity smart metering systems. One functionality requirement among these functional requirements is that the SM should allow remote ON/OFF switch to control the supply. Some DSOs who have installed remote ON/OFF switch are currently applying this technique for customers typically one by one when customers are changing addresses, or when contracts are terminated, or have defaulted on their payments. The switching functionalities of the SMs could be used for multiple customers, thereby opening up new possibilities for emergency electrical grid management by excluding prioritized customers. There is an interest to investigate if the multiple SMs switching might have some impacts on the Power Quality (PQ) of the electrical grid and also the challenges in implementing this technique on the existing smart metering system during emergency situation. In this thesis work, three field tests have been performed on multiple SMs switching focusing on the impact of the SMs switching on the PQ of the grid. A risk analysis was carried out before conducting the field tests. The PQ measurements were done by Power Quality Meters (PQMs) during the multiple SMs switching. Voltage variations and PQ events were recorded in the PQMs. Waveform data of the PQ events were recorded at 12.8 kHz sampling frequency. The test results are then evaluated based on PQ standards. Moreover, performance of the existing smart metering system was investigated during the multiple SMs switching to identify the challenges and possibilities of using multiple SMs switching. The analysis of the test results show that there were no other PQ events or voltage variations except some transient events which were recorded at some customer level during the reconnection of the SMs. However, the duration of the transient events was only fractions of a millisecond and deviation of the voltage transients were below +/-50% except for few transient events which have deviations of more than +/- 50% but less than +/-60%. This type of transient events may not be able to create damage to sensitive customers’ loads. The multiple SMs switching may not have impact on the PQ if the number of customers is low. However, SMs switching for large number of customers might have impact on the PQ which needs to be investigated. Moreover, the performance of the existing smart metering system during multiple SMs switching shows some limitations on implementing the switching technique for large scale of customers. The identified limitations are e.g., long time requirement for SMs switching and errors in the real-time status update report during SMs switching. Furthermore, the findings show that more research is needed to identify required functions for future smart metering system to implement multiple SMs switching during emergency grid management

Smart grid

Tese de mestrado integrado em Engenharia da Energia e do Ambiente, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016The SG concept arises from the fact that there is an increase in global energy consumption. One of the factors delaying an energetic paradigm change worldwide is the electric grids. Even though there is no specific definition for the SG concept there are several characteristics that describe it. Those features represent several advantages relating to reliability and efficiency. The most important one is the two way flow of energy and information between utilities and consumers. The infrastructures in standard grids and the SG can classified the same way but the second one has several components contributing for monitoring and management improvement. The SG’s management system allows peak reduction, using several techniques underlining many advantages like controlling costs and emissions. Furthermore, it presents a new concept called demand response that allows consumers to play an important role in the electric systems. This factor brings benefits for utilities, consumers and the whole grid but it increases problems in security and that is why the SG relies in a good protection system. There are many schemes and components to create it. The MG can be considered has an electric grid in small scale which can connect to the whole grid. To implement a MG it is necessary economic and technical studies. For that, software like HOMER can be used. However, the economic study can be complex because there are factors that are difficult to evaluate beyond energy selling. On top of that, there are legislation and incentive programs that should be considered. Two case studies prove that MG can be profitable. In the first study, recurring to HOMER, and a scenario with energy selling only, it was obtained a 106% reduction on production cost and 32% in emissions. The installer would have an $8 000 000 profit in the MG’s lifetime. In the second case, it was considered economic services related to peak load reduction, reliability, emission reduction and power quality. The DNO had a profit of$41,386, the MG owner had $29,319 profit and the consumers had a$196,125 profit. We can conclude that the MG with SG concepts can be profitable in many cases

Smart Metering Communication Protocols and Performance Under Cyber Security Vulnerabilities

The communication process is the key that characterizes the modern concept of smart grid, a new technology that introduced a “two-way communication” in energy measurement systems and can be best represented through the smart meters. Hence, the goal of smart metering communication is to ensure a secure and reliable transmission of information that can only be accessed by end users and energy supplying companies. With the goal of improving the information security in smart energy grids, the research presented in this work focused on studying different advanced metering infrastructure communication protocols and, it showcases a series of experiments performed on smart meters to evaluate their defenses against a set of cybersecurity attacks. A small-scale simulation of a smart metering system was performed in the cybersecurity laboratory in the department of Electrical and Computer Engineering at the University of Texas - Rio Grande Valley; and specialized software applications were developed to retrieve data in real time. Our experimental results demonstrated that security attacks have a considerable impact on the communication aspect of smart meters. This could help making smart meter manufacturing companies aware of the dangers caused by cyber-attacks and develop robust defenses against security attacks and enhance overall efficiency and reliability of the smart grid power delivery

The design and application of power line carrier communication and remote meter reading for use in integrated services and broadband - integrated services digital networks

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN009939 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Internet of things (IoT) based adaptive energy management system for smart homes

PhD ThesisInternet of things enhances the flexibility of measurements under different environments, the development of advanced wireless sensors and communication networks on the smart grid infrastructure would be essential for energy efficiency systems. It makes deployment of a smart home concept easy and realistic. The smart home concept allows residents to control, monitor and manage their energy consumption with minimal wastage. The scheduling of energy usage enables forecasting techniques to be essential for smart homes. This thesis presents a self-learning home management system based on machine learning techniques and energy management system for smart homes. Home energy management system, demand side management system, supply side management system, and power notification system are the major components of the proposed self-learning home management system. The proposed system has various functions including price forecasting, price clustering, power forecasting alert, power consumption alert, and smart energy theft system to enhance the capabilities of the self-learning home management system. These functions were developed and implemented through the use of computational and machine learning technologies. In order to validate the proposed system, real-time power consumption data were collected from a Singapore smart home and a realistic experimental case study was carried out. The case study had proven that the developed system performing well and increased energy awareness to the residents. This proposed system also showcases its customizable ability according to different types of environments as compared to traditional smart home models. Forecasting systems for the electricity market generation have become one of the foremost research topics in the power industry. It is essential to have a forecasting system that can accurately predict electricity generation for planning and operation in the electricity market. This thesis also proposed a novel system called multi prediction system and it is developed based on long short term memory and gated recurrent unit models. This proposed system is able to predict the electricity market generation with high accuracy. Multi Prediction System is based on four stages which include a data collecting and pre-processing module, a multi-input feature model, multi forecast model and mean absolute percentage error. The data collecting and pre-processing module preprocess the real-time data using a window method. Multi-input feature model uses single input feeding method, double input feeding method and multiple feeding method for features input to the multi forecast model. Multi forecast model integrates long short term memory and gated recurrent unit variations such as regression model, regression with time steps model, memory between batches model and stacked model to predict the future generation of electricity. The mean absolute percentage error calculation was utilized to evaluate the accuracy of the prediction. The proposed system achieved high accuracy results to demonstrate its performance