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Battery Optimization in Microgrids Using Markov Decision Process Integrated with Load and Solar Forecasting
Başlık:
Battery Optimization in Microgrids Using Markov Decision Process Integrated with Load and Solar Forecasting
Yazar:
Jain, Prateek, author.
ISBN:
9780438114166
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (95 pages)
Genel Not:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Jonathan Kimball Committee members: Mehdi Ferdowsi; Robert Landers.
Özet:
Rising climatic concerns call for unconventional/renewable energy sources which reduce the carbon footprint. Microgrids that integrate a variety of renewable energy resources play a key role in utilizing these energy resources in a more efficient and environmentally friendly manner. Battery systems effectively help to utilize these energy resources more efficiently. This research work presents a framework based on Markov Decision Process (MDP) integrated with load and solar forecasting to derive an optimal charging/discharging action of Battery with rolling horizon implementation. The load forecasting regression models are discussed and developed. Also, various solar forecasting models like clear sky, multi-regression and Non-Linear Autoregressive Neural Network model with Exogenous time-series are discussed and compared. The control algorithm is developed to reduce the monthly billing cost by reducing the peak load demand while also maintaining the state of charge of the battery. The presented work simulates the control algorithm for one month based on historic load and solar data. The results indicate substantial cost savings are possible with the proposed algorithm.
Notlar:
School code: 0587
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(691021.1) | 691021-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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