ENERGY MANAGEMENT AND ENERGY INFORMATICS

Energy informatics is a novel field in energy market and research, covering the use of information and communication technology (ICT) to address energy-related challenges in future cities. Energy management integrates and optimizes assets and infrastructure in the energy domain including energy sources, generation, distribution, monitoring systems, billing, and prosumers. Methodologies used for “smart” implementations often combine sensors with artificial intelligence and machine learning. It is originated on flow networks that are the major suppliers and consumers of energy where efficiency can be improved by collecting and analyzing information. In this way, intelligent software platforms will seamlessly match energy supply and demand without human interaction.

Projects

Research & Development

Training & Education

Solutions & Products

Projects

The continuing energy transition to more efficiency will push public and private end-users and stakeholders to take new roles in the changing energy systems.

To shape the market and effectively organizing the concept for different segments including residential, industrial, and commercial on a regional and national level, energy system integration (ESI) and demand side management (DSM) based on modern enablers such as information and communication technology (ICT) deployment would be inevitable. Taking the existing commercialized and/or innovative enabling technologies/systems and specific requirements of each energy hub (EH) into account, Energiring studies all the potentials as well as requirements and participates in both test-rig and real-world implementation for such development. Aside from technological solutions, economic, social, legal and/or political characteristics play a significant role in this energy transition and integration which should be taken into account and addressed in such projects.

Research & Development

There is a continuous increase in the global amount of urban population, and consequently, many global concerns, such as air and water pollution, energy access, environmental concerns, and consumption demand. One of the main challenges is to provide cities with affordable and reliable energy sources. To deal with this issue, it is proposed to promote smart city projects. In other words, it is projected to develop a new paradigm with the aim of optimizing energy generation and consumption in future cities. In a smart city, all of the components, such as smart factories and homes, are connected and the data about their energy consumption can be gathered continuously. If it is found that a section consumes the most energy in a special hour of the day, then the energy devoted to other sections can be minimized automatically to balance the whole system at a minimum cost.

To optimize energy generation/consumption, several types of information need to be available. For instance, in order to smooth the peak electricity, the energy profile as well as the user’s acceptable level need to be known. These requirements encourage the smart city to use Internet of Things (IoT) technology. IoT is an emerging technology that uses the Internet and aims to provide connectivity between physical devices or “things”. By introducing IoT, smart cities can manage the energy consumption efficiently by monitoring and transmitting the data to the utility control centers. Home appliances, environmental monitoring, education and healthcare, transportation, and the food industry are some examples in which the energy consumption can be reduced efficiently by using IoT technology. Specifically, home appliances are major sources of energy consumption. Here, the intelligent operation of activities facilitates energy consumption optimization. Moreover, demand management is a key for customizing the energy use by managing the lighting, cooling, and heating systems.

Generally speaking, it can be concluded that an IoT-based energy management system is a crucial component that enables new energy-related value-added services. Also, it intelligently facilitates automatic operation control.

Our main focus in energy informatics and IoT technology is on networking based on 5G, machine learning, blockchain technology and smart contracts which are categorized as below:

Training & Education

Solutions & Products

5G-based IoT technology

In IoT technology, a number of sensors are placed everywhere to collect data. The data collected by the sensors need to be communicated to affect the operations of the smart city. In such communications, 5G network which is inextricably linked with smart cities, plays a critical role. This network allows the collected information to be transmitted in real-time to central monitoring units. In 5G technology, the data-rate is high and the latency is low. These two characteristics will allow for many new applications to be deployed that were not possible before 5G.

Massive machine type communication (MMTC)

In 5G technology, MMTC is a machine communication that is suggested for a large number of IoT devices. This machine communication is effective for a large number of sensors and actuators exchanging a huge amount of data. Smart buildings and air and water quality monitoring are two examples of MMTC applications.

Critical machine type communication (CMTC)

CMTC is proposed for applications where the data is delay-intolerant, and the critical nature of the data requires guaranteed and accurate transmission to the destination. Autonomous vehicles and traffic safety control are two examples of CMTC applications.

Multi-access edge computing (MEC)

One of the enabling technologies in 5G that will greatly impact the smart city deployments is MEC; it is a cloud-based service environment that allows for real-time access to applications which are inherently intolerant of latencies. The architecture of MEC provides computing and storage capabilities for applications at the edge of its internal network. Self-driving cars that need machine learning techniques on large data sets, and video-monitoring that generates a huge amount of data during its records, are two examples of MEC application.

Network slicing

Considering a single set of standard network functions, it is impractical to implement a network that is capable of supporting a wide variety of use cases and demanding performance requirements simultaneously. Network slicing is key to meeting 5G’s diverse requirements. To meet a special requirement, network slicing enables the network elements and functions to be easily configured and reused in each network slice. In network slicing, each of the slices has its own network architecture, quality of service and network provisioning.

Blockchain technology and smart contracts

As a subversive technology, blockchain is leading a new round of technological change and industrial transformation in the world, and is expected to become the “source of policy” for global technological innovation and model innovation. This promotes the strategic cooperation of smart stakeholders in energy sector leading to the development of energy network sharing concept for sustainable development.

Artificial intelligence and machine learning

Machine learning (ML) generally is through spotting patterns in large data sets and by generating new knowledge from this experience in the form of data. In the learning phase, the large sets of data are statistically-mined and algorithms get trained. The algorithms then apply their training to predict and forecast in the respective areas. For the energy sector, this arrangement (AI+IoT+ML) or Internet of Energy (IoE) results in higher system efficiency, saving costs, reduced time, convenience, among other benefits. The areas that are directly impacted are industries, electric utilities, transport, buildings and residences.