AI and digitalization as enablers of flexible power system

Abstract. The Paris climate agreement obligate energy and power sector to reduce greenhouse gasses even though at the same time the global power demand increases. This leads to need to increase emission-free power generation with renewable energy sources (RES). Wind- and solar power technologies have developed significantly and price of power generated by them has decreased clearly in recent years. These factors have led to large-scale installations globally. However transitioning towards RES, such as wind and solar power, poses a challenge, since supply and demand in the electric power system must be equal at all times, but wind- and solar power are non-adjustable. These factors leads to need of finding flexibility from elsewhere e.g. from demand side, but also from storage systems. Purpose of this thesis is to analyze electric power system’s flexibility and how it can be increased by employing digital technologies including artificial intelligence (AI). This research was done by using qualitative conceptual research method, where data is collected until saturation point is reached. Data was collected from scientific journals and relevant sources to form conceptual understanding of current state and future possibilities. With digital technologies and artificial intelligence, companies can create new types of products, services and business models, which create more value for the customer. At the same time, these new solutions can improve the electric power system and create needed flexibility. The thesis studied these novel solutions and discussed practical implementation of three example cases in more detail. Digital solutions are rising into more significant role and they act as enablers for greener electric power system.Tekoäly ja digitalisaatio joustavan sähköjärjestelmän mahdollistajana. Tiivistelmä. Pariisin ilmastosopimus velvoittaa energia- ja sähkösektorit rajoittamaan kasvihuonepäästöjä, vaikka samaan aikaan sähkön kysyntä globaalisti kasvaa. Tämä johtaa tarpeeseen lisätä päästötöntä sähköntuotantoa uusiutuvilla energialähteillä. Tuuli- ja aurinkovoimateknologiat ovat kehittyneet ja niillä tuotetun sähkön hinta on laskenut selvästi viime vuosina. Nämä seikat ovat johtaneet niiden laajamittaiseen käyttöönottoon maailmanlaajuisesti. Siirtyminen näihin energiamuotoihin tuottaa haasteita sähköjärjestelmälle, sillä sähköjärjestelmässä tuotannon ja kulutuksen tulee olla tasapainossa koko ajan, mutta tuuli- aurinkovoiman sähköntuotantoa ei pystytä säätämään. Nämä seikat ovat johtaneet tarpeeseen löytää joustavuutta sähköjärjestelmän muista osista mm. kysynnästä, mutta myös varastoinnista. Tämän tutkimuksen tavoitteena on tutkia ja analysoida, miten sähköjärjestelmän joustavuutta voidaan lisätä digitaalisten teknologioiden, erityisesti tekoälyn avulla. Tutkimus on tehty laadullisella konseptuaalisella tutkimusmenetelmällä, jossa datan keräystä on jatkettu saturaatiopisteen saavuttamiseen asti. Data on kerätty tiedejulkaisuista ja muista tutkimuksen kannalta merkityksellisistä lähteistä, joiden pohjalta on voitu muodostaa konseptuaalinen ymmärrys tämän hetken tilasta ja tulevaisuuden mahdollisuuksista. Digitaalisten teknologioiden ja tekoälyn avulla yritykset voivat luoda uudenlaisia tuotteita, palveluita ja liiketoimintamalleja, jotka tuottavat aikaisempaa enemmän arvoa asiakkaalle. Samalla nämä uudet ratkaisut pystyvät parantamaan sähköjärjestelmää ja luomaan tarvittavaa joustavuutta. Tässä työssä tutustuttiin näihin uusiin ratkaisuihin ja tutkittiin myös niiden käytännön toimivuutta analysoimalla kolmea esimerkkitapausta tarkemmin. Digitaaliset ratkaisut ovat nousemassa merkittävään osaan sähköjärjestelmää ja niillä, kuten monella muullakin digitaalisiin teknologioihin pohjautuvilla ratkaisuilla voidaan mahdollistaa ympäristöystävällisempi sähköjärjestelmä

The Next Generation Internet of Things Architecture Towards Distributed Intelligence: Reviews, Applications, and Research Challenges

Increasing the implication of growing data generated by the Internet of Things (IoT) brings the focus toward extracting knowledge from the raw data derived from sensors. In the current cloud computing architecture, all the IoT raw data are transmitted to the cloud for processing, storage, and controlling things. Nevertheless, the scenario of sending all raw data to the cloud is inefficient as it wastes the bandwidth and increases the network load. This problem can be solved by providing IoT Gateway at the edge layer with the required intelligence to gain the knowledge from raw data to decide whether to actuate or offload complicated tasks to the cloud. This collaboration between the cloud and the edge is called distributed intelligence. This work highlights the distributed intelligence concept in IoT. It presents a deep investigation of distributed intelligence between the cloud and the edge layers under IoT architecture, with an emphasis on its vision, applications, and research challenges. This work aims to bring the attention of IoT specialists to distributed intelligence and its role to deduce current IoT challenges such as availability, mobility, energy efficiency, security, scalability, interoperability, and reliability

Energy Efficient Protocols for Active RFID

Radio frequency identification (RFID) systems come in different flavours; passive, active, semi-passive, or semi-active. Those different types of RFID are supported by different, internationally accepted protocol standards as well as by several accepted proprietary protocols. Even though the diversity is large between the flavours and between the standards, the RFID technology has evolved to be a mature technology, which is ready to be used in a large variety of applications. This thesis explores active RFID technology and how to develop and apply data communication protocols that are energy efficient and which comply with the different application constraints. The use of RFID technology is growing rapidly, and today mostly “passive” RFID systems are used because no onboard energy source is needed on the transponder (tag). However, the use of “active” RFID-tags with onboard power sources adds a range of opportunities not possible with passive tags. Besides that Active RFID offers increased working distance between the interrogator (RFID-reader) and tags, the onboard power source also enables the tags to do sensor measurements, calculations and storage even when no RFID-reader is in the vicinity of the tags. To obtain energy efficiency in an Active RFID system the communication protocol to be used should be carefully designed. This thesis describes how energy consumption can be calculated, to be used in protocol definition, and how evaluation of protocols in this respect can be made. The performance of such a new protocol, in terms of energy efficiency, aggregated throughput, delay, and number of collisions in the radio channel is evaluated and compared to an existing, commercially available protocol for Active RFID, as well as to the IEEE standard 802.15.4 (used, e.g., in the Zigbee medium-access layer). Simulations show that, by acknowledging the payload and using deep sleep mode on the tag, the lifetime of a tag is increased. For all types of protocols using a radio channel, when arbitrating information, it is obvious that the utilization of that channel is maximized when no collisions occur. To avoid and minimize collisions in the media it is possible to intercept channel interference by using carrier sense technology. The knowledge that the channel is occupied should result in a back-off and a later retry, instead of persistently listening to the channel which would require constant energy consumption. We study the effect on tag energy cost and packet delay incurred by some typical back-off algorithms (constant, linear, and exponential) used in a contention based CSMA/CA (Carrier Sense Multiple Access/ Collision Avoidance) protocol for Active RFID communication. The study shows that, by selecting the proper back-off algorithm coefficients (based on the number of tags and the application constraints), i.e., the initial contention window size and back-off interval coefficient, the tag energy consumption and read-out delays can be significantly lowered. The initial communication between reader and tag, on a control channel, establishes those important protocol parameters in the tag so that it tries to deliver its information according to the current application scenario in an energy efficient way. The decision making involved in calculating the protocol parameters is conducted in the local RFID-reader for highest efficiency. This can be done by using local statistics or based on knowledge provided by the logistic backbone databases. As the CMOS circuit technology evolves, new possibilities arise for mass production of low price and long life active tags. The use of wake-up radio technology makes it possible for active tags to react on an RFID-reader at any time, in contrast to tags with cyclic wake-up behaviour. The two main drawbacks with an additional wake-up circuit in a tag are the added die area and the added energy consumption. Within this project the solution is a complete wake-up radio transceiver consisting of only one hi-frequency very low power, and small area oscillator. To support this tag topology we propose and investigate a novel reader-tag communication protocol, the frequency binary tree protocol

A trust supportive framework for pervasive computing systems

Recent years have witnessed the emergence and rapid growth of pervasive comput- ing technologies such as mobile ad hoc networks, radio frequency identification (RFID), Wi-Fi etc. Many researches are proposed to provide services while hiding the comput- ing systems into the background environment. Trust is of critical importance to protect service integrity & availability as well as user privacies. In our research, we design a trust- supportive framework for heterogeneous pervasive devices to collaborate with high security confidence while vanishing the details to the background. We design the overall system ar- chitecture and investigate its components and their relations, then we jump into details of the critical components such as authentication and/or identification and trust management. With our trust-supportive framework, the pervasive computing system can have low-cost, privacy-friendly and secure environment for its vast amount of services

Gestão de energia em carregador eléctrico

Electric Vehicles have been gradually gaining more traction, appearing as a possible measure to reduce the environment impact caused by the transportation sector. To increase the quality of the electric charging infrastructure, this dissertation addresses the development of a charging station with a focus on modularity and updatability. The charging station should implement a service-oriented architecture with a distributed environment of multiple chargers in grid capable of balancing loads in real time. The charging station communicates with a central system by using the most recent version of the OCPP protocol (OCPP 2.0.1), used to control a charger network.Veículos Elétricos têm vindo gradualmente a ganhar mais tração, aparecendo como uma possível medida para reduzir o impacto ambiental causado pelo setor dos transportes. De modo a melhorar a qualidade da infraestrutura de carregamento elétrico, esta dissertação aborda o desenvolvimento de uma estação de carregamento com foco na modularidade e facilidade de atualização. A estação de carregamento deverá implementar uma arquitetura orientada a serviços com um ambiente distribuído de múltiplos carregadores em rede capazes de balancear cargas em tempo real. A estação de carregamento comunica com um sistema central utilizando o protocolo OCPP na versão mais recente (OCPP 2.0.1), utilizado para controlar uma rede de carregadores.Mestrado em Engenharia de Computadores e Telemátic

Kestrel: Job Distribution and Scheduling using XMPP

A new distributed computing framework, named Kestrel, for Many-Task Computing (MTC) applications and implementing Virtual Organization Clusters (VOCs) is proposed. Kestrel is a lightweight, highly available system based on the Extensible Messaging and Presence Protocol (XMPP), and has been developed to explore XMPP-based techniques for improving MTC and VOC tolerance to faults due to scaling and intermittently connected heterogeneous resources. Kestrel provides a VOC with a special purpose scheduler for VOCs which can provide better scalability under certain workload assumptions, namely CPU bound processes and bag-of-task applications. Experimental results have shown that Kestrel is capable of operating a VOC of at least 1600 worker nodes with all nodes visible to the scheduler at once. When using multiple sites located in both North America and Europe, the latencies introduced to the round trip time of messages were on the order of 0.3 seconds. To offset the overhead of XMPP processing, a task execution time of 2 seconds is sufficient for a pool of 900 workers on a single site to operate at near 100% use. Requiring tasks that take on the order of 30 seconds to a minute to execute would compensate for increased latency during job dispatch across multiple sites. Kestrel\u27s architecture is rooted in pilot job frameworks heavily used in Grid computing, it is also modeled after the use of IRC by botnets to communicate between compromised machines and command and control servers. For Kestrel, the extensibility of XMPP has allowed development of protocols for identifying manager nodes, discovering the capabilities of worker agents, and for distributing tasks. The presence notifications provided by XMPP allow Kestrel to monitor the global state of the pool and to perform task dispatching based on worker availability. In this work it is argued that XMPP is by design a very good fit for cloud computing frameworks. It offers scalability, federation between servers and some autonomicity of the agents. During the summer of 2010, Kestrel was used and modified based on feedback from the STAR group at Brookhaven National Laboratories. STAR provided a virtual machine image with applications for simulating proton collisions using PYTHIA and GEANT3. A Kestrel-based virtual organization cluster, created on top of Clemson University\u27s Palmetto cluster, was able to provide over 400,000 CPU hours of computation over the course of a month using an average of 800 virtual machine instances every day, generating nearly seven terabytes of data and the largest PYTHIA production run that STAR ever achieved. Several architectural issues were encountered during the course of the experiment and were resolved by moving from the original JSON protocols used by Kestrel to native XMPP equivalents that offered better message delivery confirmation and integration with existing tools

Security in Internet of Things: networked smart objects.

Internet of Things (IoT) is an innovative paradigm approaching both industries and humans every-day life. It refers to the networked interconnection of every-day objects, which are equipped with ubiquitous intelligence. It not only aims at increasing the ubiquity of the Internet, but also at leading towards a highly distributed network of devices communicating with human beings as well as with other devices. Thanks to rapid advances in underlying technologies, IoT is opening valuable opportunities for a large number of novel applications, that promise to improve the quality of humans lives, facilitating the exchange of services. In this scenario, security represents a crucial aspect to be addressed, due to the high level of heterogeneity of the involved devices and to the sensibility of the managed information. Moreover, a system architecture should be established, before the IoT is fully operable in an efficient, scalable and interoperable manner. The main goal of this PhD thesis concerns the design and the implementation of a secure and distributed middleware platform tailored to IoT application domains. The effectiveness of the proposed solution is evaluated by means of a prototype and real case studies

Predicting software performance in symmetric multi-core and multiprocessor Environments

With today\u27s rise of multi-core processors, concurrency becomes a ubiquitous challenge in software development.Performance prediction methods have to reflect the influence of multiprocessing environments on software performance in order to help software architects to find potential performance problems during early development phases. In this thesis, we address the influence of the operating system scheduler on software performance in symmetric multiprocessing environments