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BD4NRG Open call winners


Production forecast for renewable energy sources - Pro4RES

Company/Organization: Inden, Information solution, d.o.o.

Inden was established in 2016 with the purpose of advanced information solution development in the field of industry and energy. Today, Inden is fast growing company that employs engineers, doctoral-level engineers and masters of science from the fields of electrotechnics, information sciences and logistics which allows for an interdisciplinary approach to problem-solving. Inden is specialized in development, implementation and maintenance of information solutions in industry and energy with the main of focus of increased control, traceability, transparency and digitization of paper processes, with significant focus on using the latest stack of technologies.

Project Description

Accurate forecasting is extremely important as energy traders and stakeholders require reliable information on the production of energy. Various stakeholders in the industry and academia that use renewable energy sources for electricity production use data to predict electricity production and analyze supply/consumption trends to better manage and predict trading trends requiring accurate and timely forecasts.

The Pro4RES project addresses the second topic of the open call i.e. Optimization of the grid and distributed assets (namely RES generation prediction and demand forecasting for efficient operational planning).

The main idea behind the project proposal is development of models and their optimization for forecasting hydro and solar energy prediction and offering them as services as a part of BD4NRG platform. Renewable energy sources are one of the major smart grid enablers and can supplement power sources, however they must be monitored carefully.

One of the main challenges in incorporating renewables to power system operation is their weather-dependent energy generation. The Pro4RES project addresses this challenge as the proposal’s purpose is the development of a tool and models that could predict energy generation from renewable energy sources (namely solar and hydro).

Because of the need for renewable energy forecasts from energy market participants and power system operators, the proposal’s ambition is to offer reliable forecasting services. Reliable information are vital to ensure a reliable energy supply. The integration of the proposed service in BD4RNG platform would allow different stakeholders to get access to such models through the BD4RNG platform.

The expected results of the proposal Pro4RES are expected to affect decision-making in energy communities and markets as it is expected that companies could use it in day-to-day operational decision-making. In the time of energy crisis and market uncertainties the momentum is in favor of accelerating energy efficiency and renewable energy sources. More accurate forecasts could help policy makers set realistic goals toward RES production targets which is important for development of new strategies and policies.

Based on the discussion with our mentor and alignment with the BD4RNG project scope the objectives are:

  • Analysis of the input data to determine the quality of the data.
  • Selection of most suitable models for solar energy generation forecast.
  • Selection of most suitable models for hydro energy generation forecast.
  • Optimization of models for different types of forecasts which are necessary for operational planning

As one of the challenges of BD4RNG is the inability to integrate all the models through available libraries, the project proposal addresses this key challenge as the proposal’s objective is to develop and provide models which can be integrated into DB4RNG platform.