Adela Bara

Electricity load profile calculation using self-organizing maps

Smart metering data management involves determining load profiles for households, buildings, retailers, industrial and other types of final electricity consumers. They are interesting for grid operators in order to perform electricity consumption forecast and better plan their resources, market operators in order to perform settlements on electricity markets, suppliers to set adequate advanced tariff schemas and consumers for electricity consumption optimization purposes, visualisation of trends, identifying load peaks and energy intensive appliances, etc. In this paper, we calculated load profiles based on artificial neural network such as self-organizing maps and compared these results with the results based on the same dataset when we previously applied clustering methods.

Protection relay settings management at Akdeniz DISCO through DIgSILENT StationWare

Number of setting values of relays has increased considerably with the replacement of electro-mechanical relays to digital relays recently. Moreover, increase in the number of distributed and renewable generators connected to distribution grids complicates the protection relay coordination process. Essentially, settings of protection devices should be managed more carefully than before in a systematical way. This paper presents the protection relay settings management at Akdeniz DISCO through DIgSILENT StationWare software platform. The platform is utilized to manage relay setting process beginning from the relay coordination analysis phase to final implementation phase on site. The software is configured to allow remote access to relay setting management platform by different level of users which have different level of permissions depending on their roles in the whole process.

Informatics Solutions for Smart Trading on Wholesale Electricity Markets Containing RES Bidders

This paper presents an informatics solution that aims to assist energy suppliers in setting up their bids on wholesale electricity markets. The solution is developed into a cloud computing platform as an online dashboard, including the following components: consumption optimization and forecasting, generation forecasting, advanced data analytics, and decision rules. These components require a complex data integration model that gathers data from different sources such as: smart meters and appliances, SCADA systems and wholesale electricity market.

Prosumers' renewable small-size generation forecasting analyses with ARIMA models

Renewable small-size generation is becoming more and more attractive for smart-cities. It replaces to some extend conventional power generation based on coal, oil, gas, etc. and can range between 30 W to 400 kW. This leads to less polluted cities and lower investment in onerous transmission and distribution grids since generation sources is closer to final electricity and thermal energy consumers. In this paper, we used input data from small-size generation renewable sources based on solar irradiance and wind speed. The input data have been undergone through the Extract-Transform-Load (ETL) process. After the ETL, we performed first and second order of autoregressive, moving average, combined autoregressive and moving average, and autoregressive integrated moving average that is a generalization of combined autoregressive and moving average. We considered two study cases for performing forecasting analyses: the wind power generators located in Tulcea city and photovoltaic panel that is located in Giurgiu city. These forecasts could be mainly used by prosumers to perform load profiles, improve their consumption optimization, electricity market related activities, etc. We applied several different forecasting methods (SVM, ANN), but the best results we obtained with ARIMA models.