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Abstract
Primary frequency reserves in Northern Europe have traditionally been provided with hydro plants and fossil fuel-burning spinning reserves. Recently, smart distributed energy resources have been equipped with functionality needed to participate on frequency reserves. Key categories of such resources include photovoltaic systems, batteries, and smart loads. Most of these resources are small and cannot provide the minimum controllable power required to participate on frequency reserves. Thus, virtual power plants have been used to aggregate the resources and trade them on the frequency reserves markets. The information technology aspects of virtual power plants are proprietary and many of the details have not been made public. The first contribution of this article is to propose a generic data model and application programming interface for a virtual power plant with the above-mentioned capabilities. The second contribution is to use the application programming interface to cope with the unpredictability of the frequency reserve capacity that the photovoltaic systems and other distributed energy resources are able to provide to the frequency reserves markets in the upcoming bidding period. The contributions are demonstrated with an operational virtual power plant installation at a Northern European shopping center, aggregating photovoltaic Primary Frequency Reserves resources.
Original language | English |
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Article number | 1242 |
Number of pages | 23 |
Journal | Energies |
Volume | 14 |
Issue number | 5 |
DOIs | |
Publication status | Published - Mar 2021 |
MoE publication type | A1 Journal article-refereed |
Keywords
- solar power
- virtual power plant
- application programming interface
- primary frequency reserve
- frequency containment reserve
- demand response
- forecasting
- machine learning
- neural network
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Dive into the research topics of 'A Virtual Power Plant Solution for Aggregating Photovoltaic Systems and Other Distributed Energy Resources for Northern European Primary Frequency Reserves'. Together they form a unique fingerprint.Projects
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Predictricity
Sierla, S. (Principal investigator), Aaltonen, H. (Project Member), Karhula, N. (Project Member), Vyatkin, V. (Project Member), Subramanya, R. (Project Member) & Hölttä, T. (Project Member)
01/04/2019 → 31/03/2022
Project: Business Finland: Other research funding