| Περίληψη: | The use of renewable energy sources across Europe and many other parts of the world has been largely supported by government and economic incentives in recent years. Taking into account European Union climate change legislation requiring EU Member States to produce 20% of their electricity from renewable sources by the year 2020, it is clear that few European countries will be able to achieve this objective. The only way in which the majority of EU countries can get closer to the goal is to make use of excess capacity from domestic Renewable Energy Sources (RES). This thesis examined the need to involve small and medium-sized producers and consumers in the energy market with the aim both of economic benefit and of changing their energy behavior. Initially, the current techniques / algorithms were studied regarding the grouping of producers and consumers as well as the pricing process. It was proposed to create a new smart grid architecture with the contribution of a new aggregator that organizes all small and medium-sized producer-consumers in clusters that act on the same policy. Studies have been made using already known algorithms (spectral, genetic, and adaptive) to find the appropriate producer-consumer cluster that will reduce their energy costs.
The study was enriched with the use of prediction techniques, offering even greater accuracy in the end result. Clustering methods based on correlation were then proposed to find the appropriate producer / consumer groups to serve current demand for both real-time and post-day markets. The pricing of the energy supply on the market was an important part of this dissertation, for which purpose the following algorithms were proposed.
Initially, a pricing algorithm was developed and implemented in flexible markets for the economic benefits and smooth operation of the market. An algorithm of producer-consumer grouping in smart power networks was then studied and implemented with the aim of reducing consumption and changing energy behavior. All of the above-mentioned technical algorithms were evaluated using experiments from anonymous user data over the last five years. The integration of the algorithms into two platforms VIMSEN Decision Support System (VIMSEN-DSS) platform and the Researchers Algorithm Toolkit (RAT) platform has demonstrated both the correct operation of the outputs and the smooth operation of the proposed techniques within an integrated information system.
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