Market participation of large-scale Hybrid power plant
Author
Satheesh, Sharan
Term
4. term
Education
Publication year
2020
Pages
59
Abstract
Dette speciale undersøger, hvordan et storskala hybridkraftværk, der kombinerer vind, solceller og batterilagring, effektivt kan deltage i day-ahead- og intradag-elmarkeder. Arbejdet adresserer behovet for at opfylde markedsforpligtelser og maksimere indtægter under variabel vedvarende produktion og med hensyn til batterislitage. Der udvikles en markedsdeltagelsesalgoritme og en anlægscontroller (Hy-PPC), og anlægget modelleres i MATLAB/Simulink og DIgSILENT PowerFactory. Prognoser for produktion og priser anvendes til budgivning i day-ahead-markedet og til korrigerende handlinger i intradag-/balancemarkedet. Med det australske elmarked som casestudie viser simuleringer, at algoritmen sammen med det foreslåede kontrolsystem kan opfylde forpligtelser i hvert handelsinterval, afbøde overforpligtelser fra day-ahead via intradagshandel og sælge overskydende energi, når den er tilgængelig. Studiet gennemgår markedsrammer, modellering og kontroltilgang og diskuterer forventede økonomiske effekter; detaljerede resultattal er ikke inkluderet i dette uddrag.
This thesis investigates how a large-scale hybrid power plant combining wind, solar PV, and battery storage can participate effectively in day-ahead and intraday electricity markets. It addresses the challenge of meeting market commitments and maximizing revenues under variable renewable generation while considering battery wear. A market participation algorithm and a plant-level controller (Hy-PPC) are developed, and the plant is modeled in MATLAB/Simulink and DIgSILENT PowerFactory. Forecasts of generation and prices inform bidding in the day-ahead market and corrective actions in the intraday/balancing market. Using the Australian electricity market as a case study, simulations show that the algorithm, together with the proposed control system, can fulfill commitments for each trading interval, mitigate day-ahead over-commitments via intraday trading, and sell excess energy when available. The study outlines market context, plant modeling, and control approach, and discusses expected economic impacts; detailed numerical results are not included in this excerpt.
[This summary has been generated with the help of AI directly from the project (PDF)]
Keywords
Documents