Thesis deals with the design of intelligent electrical socket. At the beginning of the thesis, there are described the characteristics of the distribution network in the Czech Republic and the ways of measuring these properties. The selected integrated circuit that realizes the measurement is described in detail. The third chapter deals with the current possibilities of power management, especially from the perspective of the distribution company and the concept of smart networks. The fourth chapter deals with the selection of communication interface suitable for smart socket as an element of smart home. The selected IEEE 802.15.4 standard and the microcontroller implementing the communication itself are described in more detail. The following part of the work is about design of the intelligent socket development board, on which the concept is tested and the design of the final hardware is described in this chapter. The last chapter describes the measurement results realized by the created device.

The aim of this master´s thesis is to find a suitable means of communication to provide supervisory control for the distribution network of the utility company E.ON. Comparison of a digital radio system, which would be in the property of the company and of the radio systems of mobile operators is done. In this work the reader gets familiar with the structure of the distribution network of the utility company E.ON and with the scope of activities of the grid controller. The reader also gets acquainted with the current state of the radio system of the E. ON, and with the requirements, which should be fulfilled by them. An important part of this work is formed by the description of the possibilities of the private radio systems and mobile operators. At the end, the possibility of the private radio systems and systems of mobile operator usage in the Smart Grid system is given.

The thesis deals with the design of wireless communication system using Wireless M- Bus, which works in the 169 MHz band. This system is designed to collect data from meters that are not equipped with a radio and have pulse outputs. The thesis describes the Wireless M-Bus standard and the current components of the communication system used by ModemTec. It also describes the selection and design of a suitable hardware implementing the receiver and transmitter modules and the firmware design for these modules. The thesis deals with the parameterization of the transmitter module in order to specify the parameters of the transmitted measured quantity.

<div>The accelerated urbanization of countries has led the adoption of the smart power grid with an explosion in high power usage. The emergence of Non-intrusive load monitoring (NILM), also referred to as Energy Disaggregation has followed the recent worldwide adoption of smart meters in smart grids. NILM is a convenient process to analyze composite electrical energy load and determine electrical energy consumption.</div><div><br></div><div>A number of state-of-the-art NILM (energy disaggregation) algorithms have been proposed recently to detect various individual appliances from one aggregated signal observation. Different kinds of classification methods such as Hidden Markov Model (HMM), Support Vector Method (SVM), neural networks, fuzzy logic, Naive Bayes, k-Nearest Neighbors (kNN), and many other hybrid approaches have been used to classify the estimated power consumption of electrical appliances from extracted appliances signatures. This study proposes an end-to-end edge computing system with an NILM algorithm, which especially focuses on recognizing Electric Vehicle (EV) charging. This system consists of three main components: (1) Data acquisition and Preprocessing, (2) Extraction of EV charging load via an NILM algorithm (Load identification) on the NILMTK Framework, (3) and Result report to the cloud server platform.</div><div><br></div><div>The monitoring of energy consumption through the proposed system is remarkably beneficial for demand response and energy efficiency. It helps to improve the understanding and prediction of power grid stress as well as enhance grid system reliability and resilience of the power grid. Furthermore, it is highly advantageous for the integration of more renewable energies that are under rapid development. As a result, countless potential NILM use-cases are expected from monitoring and identifying energy consumption in a power grid. It would enable smarter power consumption plans for residents as well as more flexible power grid management for electric utility companies, such as Duke Energy and ComEd.</div>

The way its future power systems are designed will have significant impact on sub-Saharan Africa's (SSA) aspirations to move from low electricity consumption rates to enhance life quality and further increase economic opportunity. At present, Africa is experiencing higher economic growth rates than other continents (including Asia). And so is its need for electric power. However, all too often the options that are chosen are the ones with lowest risk and that require little coordination. In part, this is because region-wide planning, coordination and institutions are in their infancy. “Low risk” power plants typically include oil generators that can be sited close to loads, other fossil fuel power plants, and hydro plants that can easily be connected to the continent’s grid. However, hydropower production has been limited due to changes in weather and climate and socio-economic impacts. Additionally, its potential has also not been reached as large sites are far from adequate grids. A restructuring of the energy system that considers both the potential for increased geographical integration while moving gradually towards more sustainable electricity generation may hold significant promise. This work considers the potential of another renewable technology namely concentrating solar power (CSP) and connecting supply and demand centers via high voltage direct current (HVDC) power lines. Specifically, the focus is on utility-scale solar power generation to supply the needs of growing urban centers of demand. It develops a Geographic Information System-based (GIS) model with a spatial resolution of 30 arc-seconds to calculate the cost evolution of the electricity produced by different technologies of CSP plants and the costs of grid development to selected centers of demand. The results show that major SSA metropolis can benefit from distant CSP economically attractive to compete with inlaid coal-based generation. In 2010, total imports of coal exceeded 1.4 million short tons with consequent economic and environmental costs. Solar towers plants endowed with thermal storage may become a leading technology for smoothing purposes with zero fuel costs. Furthermore, Africa’s vast solar resources are far from urban centers of demand and a transmission system capable to integrate high levels of renewable energy while improving reliability of supply is required. The results of this study point to the importance of SSA centers to rely on a Super Grid approach to take advantage from CSP least-cost potential and to discontinue expensive traditional sources. Overall, solar corridors can integrate with geographically-wide wind and hydro potentials to create clean energy corridors and encourage a transition towards more sustainable energy systems.

The Swedish electrical power system faces many challenges. Stricter environmental and economic demands require a more efficient use of both the transmission and distribution grids as well as the production capabilities. Since the Swedish national demand of electricity is fluctuating, the system has always been dimensioned to meet the periods of high demand, resulting in a low utilization of the system. To meet these challenges, the concept of a “Smart Grid” has been phrased. One of the most important goals of a Smart Grid is to enable end-consumers to participate more actively in the energy market. One way to do this is through “load-shifting” where consumption (or loads) are moved from hours of high demand (peak hours) to hours of low demand (off-peak hours). Load-shifting is a part of a set of intentional consumption modifications denoted “Demand Response” (DR) and is deemed to be one of the most important tools of the Smart Grid. In Sweden, a Smart Grid project called the Stockholm Royal Seaport (SRS) project is currently taking place. The project have phrased a hypotheses regarding load-shifting called the “Active customer” scenario, in which a customer load-shifts 5-15 % of his electricity consumption. To facilitate this scenario, the SRS project uses an end-consumer price model for electricity, called the SRS price model, as well as technological and market solutions not yet available on a national scale.   This study investigates what impact the results from the SRS pilot project might have if implemented for private apartment end-consumers on a Swedish national scale. The study is divided into three parts. The first part investigates the challenges of a national scale implementation of private apartment end-consumer DR and the SRS price model. The second part investigates what the impact would be if the entire Swedish private apartment end-consumer sector where to act in accordance with the Active customer scenario. The third part consists of a sensitivity analysis. Four challenges for a national private apartment end-consumer load-shift implementation have been elicited. They are; the lack of easily moveable loads in a foreseeable future, the heterogeneous cost of distribution, the suggested price models low peak to off-peak price ratio and the comparatively small cost of electricity of the private apartment end-consumers. The SRS price model is deemed to give a clear economic incentive for load-shift of private apartment end-consumer without electric heating. However, the incentive might be considered too weak with yearly savings of 48-165 SEK for a 15 % load-shift, depending on apartment consumption. This corresponds to yearly savings of 124 to 429 million SEK for the entire customer segment. These challenges are deemed to be of a non-technical character, but rather of a marketing and communication nature. The impact of a fully implemented national private apartment end-consumer load-shift in accordance with the Active customer scenario and the SRS price model is deemed to be beneficial from an overall power system point of view. However, the impact on the private apartment end-consumer national demand is small in comparison with other plausible system developments, such as energy demand reductions due to more efficient lighting solutions. The sensitivity analysis of private apartment end-consumer cost savings when acting in accordance with the Active customer scenario indicates that the percentage savings may increase in the future when considering more volatile prices for electric energy or the implementation of a time differentiated energy tax.

The intelligent handling of waste is a pressing issue today. Up until the 19th century it had been however an integral part of societies especially when it comes to the waste generated by construction and demolition (Bahamon and Sanjines, 2010). After industrial revolution (1750-1850) which opened the gates of mass production and mass consumption followed and supported by two major forces of capitalism and the dramatic increase in world population, the generation of waste accelerated correspondingly and in a global scale. The mass extraction of natural resources on one hand (limited amount of natural resources), and the problems caused by waste landfilling and incineration such as pollution and diseases on the other hand, made us stop this linear extraction-to-waste trend and recognize recycling as a solution. Recycling chiefly addresses a sustainable approach to reduce the negative effects of waste and at the same time involves processing used materials (waste) into new products to prevent waste of potentially useful materials (Eco Cloud), however through recycling not only some energy has to be consumed to make this process run but also some portion of pollution would be generated as a side effect. What is more is that up until today recycling has been neither in many cases economically profitable nor has it been possible to recycle all the amount of waste. For instance In US- as the most consuming society on the planet Earth- only 34% of the municipal solid waste can be recycled and the rest ends up in either landfills or incinerators (EPA,2010). This project is to mainly focus on the definition of a rather comprehensive network (Network of Reuse) which sits right before recycling through which as much as possible of the total amount of waste could be directly absorbed back into the society (with minor changes in some cases) in different scales, the resultants of which would be claimed not to be only less energy consumption and less pollution caused through processing waste (as in recycling) but also avoiding a considerable amount of unrecycled materials from ending up in landfills and incineration. In fact the assumed network-which is simulated by the smart grid model- could be said to be a complementary section added to the existing trend today and is on no account against recycling. Like any other network, the network of reuse is based upon strategies, tools, and policies. The rhizomic growing structure of this network-that is in contrast to the tree structure of recycling- suggests a bottom up movement in handling waste and empowering people while the proposed time-line strategy is assumed to be moving from entertainment towards a coherent business network. In fact the project itself suggests the necessity of more bottom up structures to happen in our future planning. The entire project is highly founded upon research and could be applied in a variety of actual designs and concrete cases. Therefore, in this project no specific site is being addressed directly but the actual need for adding the supposed network is explored.

"Smart grid" generally refers to a class of technology bringing electricity delivery systems into the 21st century, using computer-based remote control and automation. With the growing energy demand, efficient usage of the available energy resources is increasingly becoming a major issue around the world. Smart grid is a step in that direction. Research in the European Union and the United States are currently underway to modernize the existing and aging transmission grid and to streamline the usage of electricity. A typical electricity grid consists of two major entities - the utility company and the distribution control system (DCS). Electricity is generated at the utility company and the DCS is responsible for the distribution of electricity to individual homes/consumers. A smart meter (SM) is an electronic device that measures the electricity consumed at the consumer's premises and provides added information to the utility company. The data concentration unit (DCU) is a device acting as a communication hub collecting and encoding data from multiple smart meters in a neighborhood and forwarding the data to the utility company. The aim of this project is to design a network for securing the communication between the SM and the DCU in a smart metering network environment. The meter data communicated from the SM to the DCU is very sensitive and in the hands of an attacker, can reveal significant personal information about an individual. Hence it is of at most importance to protect the meter data transmitted from the SM. On the other hand the control signals transmitted from the DCU to the SM, need protection in order to thwart off unauthorized signals (i.e., an intruder can impersonate the DC and send out control signals to the SMs). Hence the SM and the DCU should be authenticated by each other and authorized and the data and/or control signals exchanged between them should be encrypted. / "Smart grid" avser i allmänhet en klass av teknik föra system elleverans till 21: a århundradet, med hjälp av datorbaserade fjärrkontroll och automation. Med den ökande efterfrågan på energi, är effektiv användning av de tillgängliga energiresurser blir alltmer en viktig fråga över hela världen. Smart grid är ett steg i den riktningen. Forskning i Europeiska unionen och USA för närvarande pågår för att modernisera befintliga och åldrande transmissionsnätet och effektivisera användningen av el. En typisk elnätet består av två större enheter - de allmännyttiga företaget och \distribution control system"(DCS). El genereras vid verktyget företaget och DCS ansvarar för distributionen av el till enskilda hem / konsumenter. En smart meter (SM) är en elektronisk apparat som mäter elförbrukning på konsumentens lokaler och ger ökad information till elbolaget. \Data concentration unit"(DCU) är en enhet fungerar som ett kommunikationsnav insamling och kodning av data från flera smarta mätare i ett område och vidarebefordra data till elbolaget. Syftet med detta projekt är att utforma ett nätverk för att säkra kommunikationen mellan SM och DCU i ett smart mätning nätverksmiljö. Mätaren uppgifter som lämnas från SM till DCU är mycket känslig och i händerna på en angripare, kan avslöja viktig personlig information om en individ. Följaktligen är det av som mest betydelse för att skydda de mätdata som sänds från SM: en. å andra sidan styrsignaler överförs från DCU till SM och behöver skydd för att hindra av obehöriga signaler (dvs en inkräktare kan personifiera DC och skicka ut styrsignaler till SM). Därför SM och DCU ska bestyrkas av varandra och godkänts och data och / eller styrsignaler utväxlas mellan dem ska vara krypterad.

Accurate and timely diagnosis of faults is essential for the reliability and security of power grid operation and maintenance. The emergence of big data has enabled the incorporation of a vast amount of information in order to create custom fault datasets and improve the diagnostic capabilities of existing frameworks. Intelligent systems have been successful in incorporating big data to improve diagnostic performance using computational intelligence and machine learning based on fault datasets. Among these systems are fuzzy inference systems with the ability to tackle the ambiguities and uncertainties of a variety of input data such as climate data. This makes these systems a good choice for extracting knowledge from energy big data. In this thesis, qualitative climate information is used to construct a fault dataset. A fuzzy inference system is designed whose parameters are optimized using a single layer artificial neural network. This fault diagnosis framework maps the relationship between fault variables in the fault dataset and fault types in real-time to improve the accuracy and cost efficiency of the framework. / Graduate

Electric Vehicles (EVs) reduce dependency on oil and carbon emissions. An upsurge in demand for EVs could lead to negative impacts on the grid. However, charging strategies, such as supporting the grid using vehicle-to-grid (V2G) and smart charging technology, can go a long way to reducing the impacts on the electrical load curve. The thesis presents a number of aspects which relate to the interconnection between EVs and the electric grid for achieving an optimized integration. An adaptive algorithm has been developed to perform load peak shaving by V2G and smart charging, while a hypothetical case study containing several types of EVs in a local grid has been conducted. The aim is to examine the developed algorithm. In conclusion, by using the adaptive algorithm, written in C++, an optimum status has been achieved concerning the electric grid and EV batteries.