Developing a forecast and monitoring system for solar parks

OData support
Supervisor:
Kövesdán Gábor
Department of Automation and Applied Informatics

Small photovoltaic power stations will soon have to provide next day prediction of the produced energy. This justifies the design and the implementation of a web application which corresponds to the purpose.This thesis expands upon the backend implementation of the task, which provides an access point to the thin clients.

My program receives weather data from different external sources and stores it. Then it makes a next day prediction on the basis of this data and the base information of the current PV plant. Furthermore, my application supports the function in which it sends the data to the responsible organizations, then receives and processes the answer, finally makes decisions based on the response.

The aim of my thesis is to create the software that fits these requirements and to test the implementation with different techniques. Moreover, it expands to the examination and analysis of the relevant techniques (Kotlin, Elasticsearch) and to showing the advantages of these in relation to other techniques.

As a result, I examined the Kotlin programming language and the possible utility of the Elasticsearch database in Java EE environment.

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