Optimization of a multiple-scale renewable energy-based virtual power plant in the UK

Ahmed Hany Elgamal, Gudrun Kocher-Oberlehner, Valentin Robu, Merlinda Andoni

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Commercial Virtual Power Plants (CVPPs) have recently emerged as one of the most promising solutions for enabling intermittent renewable energy generation sources to efficiently trade the energy they generate in the electricity market. In this study, we develop several optimization and forecasting methods, and apply them to model the operation of multiple renewable generators across Scotland, trading energy as a single CVPP. The aim of the techniques developed is to optimize the scheduling of the CVPP, such as to maximize revenues and reduce the penalties resulting from forecasting errors, while considering operational and market constraints, such as variable costs, ramping rates, start-up costs, day-ahead and imbalance prices. The practical application is based on a case study of operational renewable energy plants in Scotland, and optimizes the CVPP operation for 3 months in winter and summer of 2017, respectively. Renewable generation output, day-ahead prices and imbalance prices are obtained from historical data for the same year. The numerical results show a profit increase of around 12% for the CVPP compared to standalone operation of renewable plants. This increase is observed for different market and imbalance settlement strategies.

Original languageEnglish
Article number113973
JournalApplied Energy
Volume256
Early online date17 Oct 2019
DOIs
Publication statusPublished - 15 Dec 2019

Keywords

  • Biomass energy
  • Electricity markets
  • Energy trading
  • Virtual power plant
  • Wind energy

ASJC Scopus subject areas

  • Building and Construction
  • Energy(all)
  • Mechanical Engineering
  • Management, Monitoring, Policy and Law

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