Περίληψη
Η παρούσα διατριβή έχει ως αντικείμενο τη διερεύνηση, ανάπτυξη και υλοποίηση αποδοτικών μεθοδολογιών πρόβλεψης της παραγωγής και ζήτησης ηλεκτρικής ενέργειας σε ευφυή δίκτυα, ώστε να αντιμετωπιστεί η αυξημένη μεταβλητότητα που έχει προκύψει τα τελευταία χρόνια από την αύξηση της διεσπαρμένης παραγωγής από ανανεώσιμες πήγες ενέργειας (ΑΠΕ), της έλευσης μονάδων αποθήκευσης και της απελευθέρωσης των αγορών ηλεκτρικής ενέργειας. Οι μεθοδολογίες πρόβλεψης υλοποιήθηκαν σε υπολογιστική πλατφόρμα με χρήση συγχρόνων τεχνολογιών της πληροφορικής, ώστε να εντοπίζονται κρίσιμες καταστάσεις του ηλεκτρικού συστήματος και να δίνεται η δυνατότητα ενεργοποίησης υπηρεσιών ευελιξίας για την αντιμετώπιση τους.Αρχικά, πραγματοποιείται μια σύντομη εισαγωγή στα ηλεκτρικά δίκτυα και στη σημασία των ευφυών δικτύωνand common services for transmission and distribution systems. This is done to address the increased variability resulting from the growth of distributed energy generation from renewable sources (RES), the appearance of energy storage units, and the liberalization of electricity markets in recent years. The prediction methodologies are implemented on a computational platform using contemporary information technology to identify critical states of the electrical system and enable the activation of flexibility services by grid operators and distribution system operators (DSOs).Initially, a brief introduction to electrical networks and the importance of smart energy grids is provided. Additionally, the significance of developing and implementing efficient forecasting methodologies for electricity production and demand in smart grids is emphasized, given the increased variability caused by the growth of distributed RES, the introduction of energy storage units, and the liberalization of electricity markets. Subsequently, the current 'target' model is analyzed, which establishes four energy markets (balancing, intraday, day-ahead, and forward markets), delineating the roles of market participants and the importance of forecasting for the smooth operation of these markets. To meet the need for efficient forecasting, the forecasting model for the OneNet research project is presented, along with the forecasting methodology and scenarios for active power management and the mitigation of adverse weather conditions through coordinated actions by transmission and distribution system operators. The proposed methodology and computational application developed within the framework of OneNet provide guidelines for designing a specialized architecture that fully supports all services and data exchange with other project entities and partners. The aim is to achieve highly efficient forecasting and reducing the need for backup resources and flexibility. To ensure the effective, efficient, and high-quality operation of future distribution networks, investors will be provided with tools that allow them to monitor the operation of the distribution network in real-time and automatically coordinate flexible resources within the network. The dissertation includes examples from the use of the computational application, forecasting results, corresponding performance metrics (KPIs), graphical representations of critical situations, and the procedures for addressing them. Various work scenarios and related flowcharts of actions, with the selection and activation of flexibility services by energy market participants, are also presented in detail.
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