In the modern generation, Electric Power has become one of the fundamental needs for humans to survive. This is due to the dependence of continuous availability of power. However, for electric power to be available to the society, it has to pass through a number of complex stages. Through each stage power quality problems are experienced on the grid. Under-voltages and over-voltages are the most common electric problems experienced on the grid, causing industries and business firms losses of Billions of dollars each year. Researchers from different regions are attracted by an idea that will overcome all the electrical issues experienced in the traditional grid using Artificial Intelligence (AI). The idea is said to provide electric power that is sustainable, economical, reliable and efficient to the society based on Evolutionary Algorithms (EAs). The idea is Smart Grid. The research focused on Power Quality Optimization in Smart Grid based on improved Differential Evolution (DE), with the objective functions to minimize voltage swells, counterbalance voltage sags and eliminate voltage surges or spikes, while maximizing the power quality. During Differential Evolution improvement research, elimination of stagnation, better and fast convergence speed were achieved based on modification of DE’s mutation schemes and parameter control selection. DE/Modi/2 and DE/Modi/3 modified mutation schemes proved to be the excellent improvement for DE algorithm by achieving excellent optimization results with regards to convergence speed and elimination of stagnation during simulations. The improved DE was used to optimize Power Quality in smart grid in combination with the reconfigured and modified Dynamic Voltage Restorer (DVR). Excellent convergence results of voltage swells and voltage sags minimization were achieved based on application of multi-objective parallel operation strategy during simulations. MATLAB was used to model the proposed solution and experimental simulations. / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)

SCADA-system (Supervisory Control and Data Acquisition) har under de senaste decennierna använts i stor utsträckning, med utmärkta resultat för nätverksdrift och -förvaltning. Kunder ställer emellertid krav på att SCADA-system ska kunna integrera externa komponenter för att möjliggöra utveckling av befintliga och nya affärsprocesser. Det innebär att dessa system utvecklas från en monolitisk infrastruktur till en löst kopplad och flexibel arkitektur. Således har nya behov uppstått för att förbättra systemets interoperabilitet, minska komplexiteten och förbättra underhållet. Föreliggande masterprojekt presenterar ett ramverk för att förutsäga systems interoperabilitetet (IPF); ett ramverk som stöder arkitekturprocessen under de tidiga stadierna av produktutveckling. Vidare har arbetet undersökt några alternativa arkitekturer, vilka har modellerats och verifierats med hjälp av ovannämnda ramverk. En första konceptuell arkitektur har utvecklats för att förbättra interoperabiliteten hos interna system, för att reducera kopplingen mellan det grundläggande SCADA-systemet och Energy Management-systemet (EMS). Därefter genererades en andra arkitektur som möjliggör integration av externa komponenter för att främja den externa interoperabiliteten. Resultat visar att de föreslagna arkitekturerna är korrekta (enligt IPF) och systemets driftskompatibilitet förbättras. Vidare förefaller den slutligt föreslagna lösningen vara mindre komplex än den nuvarande arkitekturen på lång sikt, men det skulle behövas en större insats och väsentliga förändringar för att uppgradera systemarkitekturen. / SCADA (Supervisory Control and Data Acquisition) systems have been widely used during the last decades delivering excellent results for the power network operation and management. However, some current customer requirements are for SCADA systems to integrate external components in order to perform advanced power network studies and develop both existing and new business processes. This novel viewpoint will make these systems evolve from a monolithic infrastructure towards a loosely coupled and flexible architecture. Hence, new needs have arisen with the aim of improving the system interoperability, reducing the complexity and enhancing the maintainability. This master´s thesis project presents an Interoperability Prediction Framework (IPF), that supports the architecture design process during the early stages of product development. In addition, this work has also investigated some alternative architectures, which have been modelled and verified using the previously mentioned framework. A first conceptual architecture has been designed to improve the internal system interoperability, reducing the coupling between the basic SCADA and the Energy Management System (EMS). Later, a second architecture that allows the integration of external components has been introduced to promote the external interoperability. Results show that the proposed architectures are correct (according to the IPF) and the interoperability of the system is improved. Furthermore, initial conclusions suggest that the final proposed solution would be less complex than the current architecture in the long term, although a large effort and substantial changes would be needed to upgrade the system architecture.