Solar Energy Forecasting and Optimization System for Efficient Renewable Energy Integration
| Autor: | Diana Manjarres, Sergio Gil-Lopez, Ricardo S. Alonso, Itziar Landa-Torres |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Energy management Computer science 020209 energy Photovoltaic system 02 engineering and technology 021001 nanoscience & nanotechnology Solar energy Automotive engineering Renewable energy 0202 electrical engineering electronic engineering information engineering Key (cryptography) Electricity 0210 nano-technology business Energy (signal processing) Voltage |
| Zdroj: | Data Analytics for Renewable Energy Integration: Informing the Generation and Distribution of Renewable Energy ISBN: 9783319716428 DARE@PKDD/ECML |
| DOI: | 10.1007/978-3-319-71643-5_1 |
| Popis: | Solar energy forecasting represents a key issue in order to efficiently manage the supply-demand balance and promote an effective renewable energy integration. In this regard, an accurate solar energy forecast is of utmoss importance for avoiding large voltage variations into the electricity network and providing the system with mechanisms for managing the produced energy in an optimal way. This paper presents a novel solar energy forecasting and optimization approach called SUNSET which efficiently determines the optimal energy management for the next 24 h in terms of: self-consumption, energy purchase and battery energy storage for later consumption. The proposed SUNSET approach has been tested in a real solar PV system plant installed in Zamudio (Spain) and compared towards a Real-Time (RT) strategy in terms of price and energy savings obtaining attractive results. |
| Databáze: | OpenAIRE |
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